Calibration Parameters Research Articles

Minimal cellular automaton model with heterogeneous cell sizes predicts epithelial colony growth

Regulation of cell proliferation is a crucial aspect of tissue development and homeostasis and plays a major role in morphogenesis, wound healing, and tumor invasion. A phenomenon of such regulation is contact inhibition, which describes the dramatic slowing of proliferation, cell migration and individual cell growth when multiple cells are in contact with each other. While many physiological, molecular and genetic factors are known, the mechanism of contact inhibition is still not fully understood. In particular, the relevance of cellular signaling due to interfacial contact for contact inhibition is still debated. Cellular automata (CA) have been employed in the past as numerically efficient mathematical models to study the dynamics of cell ensembles, but they are not suitable to explore the origins of contact inhibition as such agent-based models assume fixed cell sizes. We develop a minimal, data-driven model to simulate the dynamics of planar cell cultures by extending a probabilistic CA to incorporate size changes of individual cells during growth and cell division. We successfully apply this model to previous in-vitro experiments on contact inhibition in epithelial tissue: After a systematic calibration of the model parameters to measurements of single-cell dynamics, our CA model quantitatively reproduces independent measurements of emergent, culture-wide features, like colony size, cell density and collective cell migration. In particular, the dynamics of the CA model also exhibit the transition from a low-density confluent regime to a stationary postconfluent regime with a rapid decrease in cell size and motion. This implies that the volume exclusion principle, a mechanical constraint which is the only inter-cellular interaction incorporated in the model, paired with a size-dependent proliferation rate is sufficient to generate the observed contact inhibition. We discuss how our approach enables the introduction of effective bio-mechanical interactions in a CA framework for future studies.

Three-dimensional rainbow refractometry.

We propose a new, to the best of our knowledge, rainbow technique called three-dimensional rainbow refractometry (TDRR), with a cylindrical lens in the signal collecting system. With a TDRR model based on the ray transfer matrix developed, it is proved that the tilt angle of the rainbow signal is related to the axial position of the droplet, which helps to obtain the 3D position. By converting rainbow scattering angle calibration into the system parameter calibration, a new rainbow data processing program is written in combination with the model to obtain the refractive index and the particle size. With TDRR, we measured a monodisperse droplet stream of deionized water at room temperature for experimental validation and obtained the refractive index with an absolute error of less than 0.0015, the droplet size with an error within ±5%, and the axial position with an error within ±3%, which demonstrated a high accuracy of TDRR.

Determination and parameters calibration of the soybean-bonded particle model based on discrete element method

Determination and parameters calibration of the soybean-bonded particle model based on discrete element method

Improved understanding of calibration efficiency, difficulty and parameter uniqueness of conceptual rainfall runoff models using fitness landscape metrics

The ease and efficiency with which conceptual rainfall runoff (CRR) models can be calibrated, as well as issues related to the uniqueness of their parameters, has received significant attention in literature. While several studies have tried to gain a better understanding of the underlying factors affecting these issues by examining the features of model error surfaces, this has generally been done in an ad-hoc fashion using lower-dimensional representations of higher-dimensional surfaces. In this paper, it is suggested that exploratory landscape analysis (ELA) metrics can be used to quantify key features of the error surfaces of CRR models, including their roughness and flatness, as well as their degree of optima dispersion throughout the surface. This enables key error surface features of CRR models to be compared in a consistent, efficient and easily communicable fashion for models with different combinations of attributes (e.g. model structure, catchment climate conditions, error metrics, and calibration data set lengths). Results from the application of ELA metrics to the error surfaces of 420 CRR models with different combinations of the above attributes indicate that increasing model complexity results in an increase in relative error surface roughness and relative optima dispersion and that, while increasing catchment wetness increases the relative roughness of error surfaces, it also decreases optima dispersion. This suggests that for the models considered in this study, optimisation efficiency is likely to decrease with increasing model complexity and catchment wetness, while optimisation difficulty is likely to increase and parameter uniqueness likely to decrease with model complexity and catchment dryness. While implications for choice of model complexity will need further work, this study highlights the potential value of the proposed approach to understanding the calibration efficiency, difficulty and parameter uniqueness of conceptual rainfall runoff models.

A multi-stage spatial queueing model with logistic arrivals and departures consistent with the microscopic fundamental diagram and hysteresis

This paper introduces a spatial queueing model for a single bottleneck during morning peak hours. Utilizing the logistic function and after appropriate calibration, it articulates the arrival and departure flows in continuous, differentiable terms. By validating the model across different peak periods and locations, the demand model’s robustness is superior to other commonly used functions. This model also incorporates constant or varying capacity scenarios. It effectively captures key aspects of morning peak traffic, including the emergence of hysteresis loops in fundamental diagrams (FDs) of density and flow. The model’s multi-stage approach recognizes three distinct phases in traffic flow: freeflow, transition, and queued segments, ensuring spatial consistency in flow and density across these stages. It accounts for the growth of the queued segment and vehicle spillback under various bottleneck intensities, with the resulting FDs for speed and density also displaying hysteresis loops. The calibration of model parameters utilizes time-series data of traffic flow and density space–time maps derived from real-world data. The validation results accurately reflect real traffic scenarios, emulating the counterclockwise hysteresis loops observed in density and its heterogeneity, and provide both planar and three-dimensional FDs at different points along the traffic link, each mirroring real-life traffic patterns. Additionally, a comparison with the cell transmission model (CTM) reveals that the proposed model exhibits superior generalization and robustness.

Multivariate Validation at Multistation of Distributed Watershed Hydrological Modeling Based on Multisource Data on Chinese Loess Plateau

Earlier, hydrological simulation calibration and validation relied on flow observations at hydrological stations, but multisource observations changed the basin hydrological simulation from single-flow validation to multivariate validation, including evaporation, soil water, and runoff. This study used the Soil and Water Assessment Tool (SWAT) distributed hydrological model to simulate and investigate hydrological processes in the Jinghe River Basin in China. After a single-station, single-variable calibration using flow observation data at the Zhangjiashan Hydrological Station, multisource data were used to validate actual evaporation, soil water, and runoff. Using the flow station data from Zhangjiashan station for parameter calibration and validation, the simulated values of R2, NSE, and KGE were all above 0.64, the PBIAS was within 20%, and the values of all the metrics in the calibration period were better than those in the validation period. The results show that the model performed satisfactorily, proving its regional applicability. Qingyang, Yangjiaping, and Zhangjiazhan stations had R2, NSE, and KGE values above 0.57 and PBIAS within 25% during regional calibration, considering spatial variability. Additionally, simulation accuracy downstream increased. R2, NSE, and KGE were above 0.50, and PBIAS was within 25% throughout validation, except for Qingyang, where the validation period was better than the calibration period. The Zhangjiashan station monthly runoff simulation improved after regional calibration. Runoff validation performed highest in the multivariate validation of evaporation–soil water–runoff, followed by actual evaporation and soil water content in China. The evaluation results for each hydrological variable improved after additional manual calibration. Multivariate verification based on multisource data improved the hydrological simulation at the basin scale.

Analysis of Power-to-gas-to-X systems with metal hydride storage based on coupled electrochemical and thermodynamic simulation

Power-to-gas-to-X systems consisting of photovoltaic cells, proton-exchange membrane electrolysis, hydrogen storage based on metal hydrides, proton-exchange membrane fuel cells and buffer batteries could be used to meet heat and electricity demands of homes, businesses, or small districts. The actual size of the individual components and their interplay have to be optimized for the technical and economic feasibility of the overall system. A simulation-based optimization workflow would be a suitable way to accomplish this task, but there are hardly any tools that can simultaneously simulate power, fluid and heat flows of such systems and efficiently perform their optimization. In this paper, a multiphysical energy system simulation and optimization tool is introduced which models electrochemical and thermodynamic processes simultaneously, including modern equations of state and an own numerical solver for the arising differential–algebraic system of equations, and provides new methods for the calibration of parameters of the metal hydride storage, proton-exchange membrane electrolyzer and fuel cell as well as a metamodel-based approach for sizing optimization. As a demonstrator for the novel tool, a simulation model of a hydrogen lab is successfully set up based on experimental results. The novel tool is able to extract polarization and jump curves of the fuel cell, determine a first temperature and pressure dependency of the efficiency of the electrolysis coupled with the metal hydride storage and speed up sizing optimization through metamodeling by a factor 262.1 at 4.9% and 32.7 at 3.3% accuracy.

NUMERICAL MODELING OF COASTAL TIDES AND CURRENT PATTERN AT NORTHERN PEAT COAST OF BENGKALIS ISLAND

Riau Province experiences a loss of coastline every year due to erosion. The northern coast of Bengkalis Island is prone to coastal setback. Apart from land collapse, erosion is also caused by the flow of water along the coast. To be able to carry out good disaster management, accurate coastal hydrodynamic modelling is important. Some important components of hydrodynamics are tidal characteristics and current patterns. These important components are identified using numerical models. Manning parameter calibration is used to improve the model's accuracy. The tidal characteristic obtained was mixed, predominantly semidiurnal. Meanwhile, the pattern of tidal currents is known from the direction of movement. At spring tide, water moves towards the south and southwest with an average speed of 0.210 m/s and at neap tide, it moves towards the northeast with an average speed of -0.232 m/s.

Application of geospatial multi-agent system for simulation of different aspects of tuberculosis transmission

BACKGROUND. The paper presents epidemiological process modeling, with a focus on tuberculosis utilizing multi-agent system. MATERIALS AND METHODS. This study involves the development of an algorithm that uses the potential of artificial intelligence to create a geospatial model that highlights the different routes of tuberculosis transmission. The simulation process itself is characterized by a number of key stages, including initialization of the city, calibration of health parameters, simulation of the working day, spread of infection, evolution of disease trajectories, rigorous statistical calculations and transition to the next day. A comprehensive description of the course of active tuberculosis according to official data of the World Health Organization is given. Each agent is provided with an appropriate and consistent model that includes relevant health attributes and necessary rules for their dynamic evolution. CONCLUSIONS. The model’s results exhibit stability and lack of significant fluctuations. The statistical values obtained for infected, latent, and recovered individuals align well with known medical data, confirming the model’s adequacy. The proposed model allows for tracking and analyzing the life and behavior of each individual agent, enabling a thorough assessment of tuberculosis infection spread and the development of prevention strategies.

Study on Parallel Bond and Smooth Joint Dual Model Parameter Calibration of Mechanical Properties of Shale Under Pressure

Study on Parallel Bond and Smooth Joint Dual Model Parameter Calibration of Mechanical Properties of Shale Under Pressure

Hydrogeological parameterisation of the Daruvar thermal aquifer: integration of fracture network analysis and well testing

Highly fractured Mesozoic carbonate rocks are the main reservoir of many geothermal resources in northern Croatia, being of environmental, cultural, and economic value for the local and regional communities. The Daruvar thermal springs (temperatures < 50°C) represent the outflow area of an intermediate scale, tectonically controlled, hydrothermal system hosted in Triassic carbonate rocks. Several investigations have been conducted in the Daruvar area detailing the architecture of regional and local fracture networks and quantifying the hydrogeological parameters of the thermal aquifer. In this work, an integrated approach based on structural and hydrogeological investigations was employed to model the network of fractures in the reservoir and quantify its impact on the hydraulic properties. Structural investigations were conducted in the Batinjska Rijeka quarry, considered as an outcrop analogue of the thermal aquifer, employing both a classical field approach and the virtual quantitative analysis of a 3D digital outcrop model. Structural analysis of the digital outcrop model allowed identification of two sub-vertical systems of discontinuities, dipping to the NW and the WSW respectively, in accordance with the data collected through direct field measurements. The main geometric features of the discontinuity network and their statistical distributions were employed to construct discrete fracture network models at both the outcrop scale (approximately 100 m) and the aquifer scale in Daruvar (approximately 700 m). Calibration of the input parameters allowed modelling of porosity and permeability values that reproduce the field values assessed through pumping tests, well tests, and well logging. This work highlights the importance of integrating geological and hydrogeological investigations to obtain a more reliable reconstruction and quantification of the processes driving the fluid flow in fractured aquifers and affecting the spatial distribution of their hydraulic properties.

Mirror-assisted 360° panoramic 3D measurement system based on rotary laser profilometer

Abstract The full surface digitization of real samples plays a crucial role in fields such as object recognition, industrial quality control, and reverse modeling. To achieve panoramic three-dimensional (3D) reconstruction of samples in complex scenes, we propose an advanced panoramic laser scanning system, consisting of a laser rotation scanning system and a pair of plane mirrors. With the assistance of mirrors, the projected line laser beam can illuminate the sample from full angles in a single scanning sequence, and the camera can capture the 3D information of the sample from several specific viewpoints. The scanning method of rotating allows us to achieve more efficient and larger-scale 3D scanning. After obtaining the sample’s 3D information from different viewpoints using the same calibration parameters, the sample’s full-surface 3D data in the global coordinate can be obtained using mirror reflections. We conducted precision and effectiveness tests on samples with different sizes, materials, shapes, and textures to demonstrate the ability of the proposed method to perform full-surface 3D reconstruction under different scenarios. The experimental results of accuracy evaluation demonstrate that the proposed system can achieve a measurement accuracy at the level of 100 μm. Additionally, the robust experimental results in different scenarios also indicate that the proposed panoramic laser scanning system is capable of accurately obtaining full-surface 3D data of various types of samples, providing a cost-effective, easy-to-use, efficient, high-resolution, and effective approach for achieving panoramic 3D reconstruction.

Physically Motivated Model of a Painting Brush for Robotic Painting and Calligraphy

Robot artistic painting and robot calligraphy do require brush models for brushstroke simulation and painting robot control. One of the main features of the brush is its compliance, which describes the relationship between the brush footprint shape and the pressure applied to the brush. In addition, during motion, the brush footprint position lags from the brush handle position in a complicated manner. To date, the question of creating a physically correct model of these effects and choosing the best method for the model parameter calibration has not been presented in the literature. In the current paper, we derive equations of the brush contact patch motion, give their closed-form solutions, and investigate three methods for the brush model calibration: capturing brush footprints on a matte glass with a camera, painting calibration brushstrokes, and capturing a brush shape side projection with a camera. As we show, calibration brushstrokes give us primary information on brush contact patch displacement during painting, and capturing the brush side projection allows the accurate estimation of the gap from the brush tip to the center of the contact patch. Capturing brush footprints is useful for creating a brushstroke executable model. As an example, a model for a round artistic brush was created and verified in three tests, including measuring the coordinates of an angular brushstroke center line, simulating an angular brushstroke, and writing a signature using a robotic setup.

Parameter Calibration of Discrete Element Model of Wine Lees Particles

In order to investigate the contact characteristics of the mechanical parts of the brewing robot with wine lees particles, it is essential to calibrate the parameters of the discrete elemental model of wine lees particles. This paper proposes a method based on tests of the angle of repose. The simulation test is conducted to establish a regression model and combined with physical tests to find optimization. The contact model used in simulation modeling is Hertz-Mindlin with Johnson-Kendall-Roberts. Not all discrete element model parameters of wine lees particles have a significant impact on the angle of repose, so screening through Plackett-Burman Design is performed. The results indicate that the restitution coefficient between wine lees particles and restitution coefficient between wine lees particle and steel plate have a significant impact on angle of repose. Additionally, another parameter that is difficult to obtain, namely surface energy (JKR), also plays a crucial role. The optimal value interval for these three parameters is determined by the steepest ascent test, and a linear regression model for angle of repose is built through Box-Behnken Design. The optimal values obtained are as follows: restitution coefficient between wine lees particles—0.603; restitution coefficient between wine lees particle and steel plate—0.595; JKR—0.083. Finally, in order to verify the accuracy of calibrated parameters, simulation verification tests are carried out which show that there is only a relative error rate at 0.18% between simulated angle of repose and actual angle of repose, indicating that accurate calibration parameters were achieved. This study can provide reference for selecting discrete element model parameters for wine lees particles in future research endeavors.

A state-dependent dilatancy model for cemented sand

A modified stress–dilatancy model for cemented (or bonded) sand is developed to account for the effects of stress, density, bonding and debonding. The model is developed based on the critical state theory and state-dependent dilatancy theory. The critical state locus of the cemented sand corresponds to its initial cement content. Most importantly, a newly established bonding-state stress ratio is proposed to incorporate the effects of the bonding and debonding mechanical properties. The bonding-state stress ratio was determined using the initial bonding strength, initial confining stress, and current deviator strain. The initial bonding strength, which corresponds to the initial cement content reflects the strength enhancement caused by the bonded intergranular contacts after sample preparation. The current deviator strain reflects the gradual bonding breakage caused by the development of deviator shear deformation; the initial confining stress is adopted for normalization. Detailed processes of model development and parameter calibration are reported. The reliability of the model is analyzed by simulating a series of experimental datasets for cemented sand. This indicates that the proposed model can capture the strength–dilatancy of cemented sand under different values of stress, density, and bonding states.

A Moving Horizon Estimation for a Class of Soft Continuum Manipulators

Abstract This work proposes a formulation for the moving horizon estimation technique considering both states and parameters obtained simultaneously with reduced estimation issues. The parameters can be either constant or time-varying, while states are related to complex output trajectories related to underactuated systems. Particularly, the proposed formulation considers additional equality constraints as a counterpart of the dynamics tube-model predictive control. Thus, it becomes less dependent on probabilistic information, such as probability density function and covariance of the process noise. In addition, the calibration of the method parameters has less sensitivity and driven by the tube constraints. The proposed approach can be applied in different systems; however, here it is detailed for a class of soft continuum manipulators with fluidic actuation through a variable flowrate and demonstrated with numerical simulations in planar motion. Results indicate robustness of the algorithm estimation in a challenging scenario arising from underactuation as well as in the presence of uncertainty and external disturbance, while simultaneously states and a vector of structural parameters are coherently estimated.

Multiscale structure of LaAlO3 from single-crystal X-ray diffraction.

A domain-resolved synchrotron single-crystal X-ray diffraction study of a LaAlO3 pseudo-merohedral twin crystal was successfully carried out in combination with powder diffraction data from the same sample. Multiscale structure information ranging from micro- to nano- to atomic scale was determined from one single crystal. There is almost no change of domain ratios at temperatures of less than 400 K indicating no movement of the domain wall. The changes in domain ratio indicating domain-wall movement were observed in the temperature range of 450 to 700 K, which is consistent with the result of the previous mechanical measurement. It is also found that the ratio of four twin components becomes equal (25%), just below phase transition temperature. These findings are important for domain engineering and theoretical studies related to LaAlO3. The temperature dependence of domain ratio was preserved in the heating and cooling cycle except for the first heating process to 840 K. Therefore, the domain structure after heating to 840 K is intrinsic to the crystal. Accurate structure parameters were determined through unit-cell parameter calibration and domain-resolved structure analysis. The method for calibration of unit-cell parameters from twin crystal data was derived and used to solve the inconsistent unit-cell parameters between single crystal and powder data in the present and previous studies.

Revealling pore microstructure impacts on the compressive strength of porous proppant based on finite and discrete element method

Ceramic spheres, typically with a particle diameter of less than 0.8 mm, are frequently utilized as a critical proppant material in hydraulic fracturing for petroleum and natural gas extraction. Porous ceramic spheres with artificial inherent pores are an important type of lightweight proppant, enabling their transport to distant fracture extremities and enhancing fracture conductivity. However, the focus frequently gravitates towards the low-density advantage, often overlooking the pore geometry impacts on compressive strength by traditional strength evaluation. This paper numerically bypasses such limitations by using a combined finite and discrete element method (FDEM) considering experimental results. The mesh size of the model undergoes validation, followed by the calibration of cohesive element parameters via the single particle compression test. The stimulation elucidates that proppants with a smaller pore size (40 µm) manifest crack propagation evolution at a more rapid pace in comparison to their larger-pore counterparts, though the influence of pore diameter on overall strength is subtle. The inception of pores not only alters the trajectory of crack progression but also, with an increase in porosity, leads to a discernible decline in proppant compressive strength. Intriguingly, upon crossing a porosity threshold of 10 %, the decrement in strength becomes more gradual. A denser congregation of pores accelerates crack propagation, undermining proppant robustness, suggesting that under analogous conditions, hollow proppants might not match the strength of their porous counterparts. This exploration elucidates the underlying mechanisms of proppant failure from a microstructural perspective, furnishing pivotal insights that may guide future refinements in the architectural design of porous proppant.

Stability analysis of layered circular rock tunnels considering anchor reinforcement based on an enhanced mesh-free method

The impact of geotechnical structure and support construction on the stability of a layered circular rock tunnel was investigated based on an improved mesh-free method. The Smoothed Particle Hydrodynamics (SPH) was improved by incorporating a total bridge broken strategy into the kernel function and was validated through analysis of the mechanical behavior in circular opening problem and uniaxial compression tests. The Particle Domain Search (PDS) method is utilized to create crack pathways and implement anchor reinforcement in specific areas without the requirement for grid division. An SPH model of the Muzhailing tunnel was established to investigate the stability of the surrounding rock considering different anchor lengths and spacing. The result indicated that the enhanced SPH method provides a feasible approach for the rapid assessment of tunnel convergence displacement and damage coefficients. Furthermore, this method was validated through laboratory experiments and analytical solutions. For layered tunnels with other different dip angles, this approach offers a general optimization strategy for anchor reinforcing surrounding rock. These findings suggest that the enhanced mesh-free method, owing to its characteristics of efficient parameter calibration and computation, can be further expanded to the rapid assessment of the stability of layered slopes and foundations considering anchor reinforcement.

Calibration of contact parameters of sandy soil for planting tiger nut based on non-linear tools

A methodology combining physical experiments with simulation was employed to acquire contact parameters of sandy soil precisely for planting tiger nuts in the desert area of Xinjiang. The stacking angle under different parameter combinations was applied as a response value. Through the Plackett–Burman test, several factors that have a significant influence were determined. The steepest ascent test was conducted to establish the finest scope of values for these parameters. The stacking angle was considered the response variable, and non-linear tools were used to optimize these parameters for simulation. The findings showed that applying response surface methodology (RSM) resulted in a relative error of 1.24%. In the case of BP-GA, the relative error compared to the physical test value was 0.34%, while for BP, it was 2.18%. After optimization using Wavelet Neural Network (WNN), the relative error was reduced to only 0.15%. Results suggest that WNN outperforms the RSM model, and the sandy soil model and parameters generated using WNN can be effectively utilized for discrete element simulation research.