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Euryale ferox was chosen for this study to examine its mechanical properties during chewing. Experiments and the discrete element method were used to conduct the study. Initially, the intrinsic and contact parameters of E. ferox were established through physical tests. The maximum compressive force of breakage and chewing mechanical properties (hardness, springiness, and chewiness) were measured using a texture profile analyzer (TPA). A Hertz–Mindlin with bonding model of the E. ferox was constructed. Optimal values for significant factors, including the normal stiffness per unit area, shear stiffness per unit area, and bonding radius, were obtained through single‐factor, Plackett–Burman, steepest ascent, and Box–Behnken response surface tests, with the maximum compressive force as the index. Under optimal parameter combination conditions, the relative error between the simulated and experimental values of the maximum compressive force was 0.79%, and the relative errors between the simulated and TPA test values of all indicators were less than 5.65%. This study provides a valuable reference for simulating the textural characteristics of agricultural products. [ABSTRACT FROM AUTHOR]

The lack of discrete element method (DEM) models and calibration parameters for Cucurbita ficifolia seeds, as well as low accuracy and efficiency of common parameters calibration methods, hinder the application of DEM for computer simulation in air-suction directional seeding equipment. In this study, the DEM parameters of the seeds were calibrated. The angle of repose (AOR), intrinsic parameters, and partial contact parameters of the seeds were experimentally measured. The seed 3D models were reconstructed based on the three-view profile information. The parameters and their value ranges were filtered through the Plackett–Burman design and steepest ascent test. The response surface method (RSM) and machine learning were utilised for optimisation inversion of the parameters. The experiments showed that the geometric relative error of the seed model was 0.69–6.54%, which meets the modelling requirements for DEM. The seed–seed static friction coefficient, the seed–seed and the seed–PVC rolling friction coefficient were 0.341, 0.026, and 0.059, respectively, which were obtained by inverting the GA-BP regression model via the Genetic Algorithm. The simulated AOR was 26.64°, with a relative error compared to the actual AOR of 1.64%, which was better than the simulated AOR obtained by RSM optimisation. The greater the smoothing value setting in EDEM software, the less the particle filling, resulting in improved simulation efficiency but reduced model accuracy. The CPU + GPU(CUDA) solver showed high DEM solution efficiency. The results reveal that the method can be used to quickly and accurately construct a 3D model of the seed, and the parameter optimisation accuracy of GA-BP-GA is better than that of RSM. [Display omitted] • A fast and precise method for parameters calibration based on DEM was present. • The ficifolia seed parameters were calibrated and used to develop planters. • The CAD-based 3D modelling method was used to reconstruct the ficifolia seed model. • Machine learning was used to invert the optimal parameters, which was better than RSM. • The effect of solver and particle count on simulation error and runtime was studied. [ABSTRACT FROM AUTHOR]

The effective representation of land surface hydrological models strongly relies on spatially varying parameters that require calibration. Well-calibrated physical models can effectively propagate observed information to unobserved variables, but traditional calibration methods often result in nonunique solutions. In this paper, we propose a hydrological parameter calibration training framework consisting of a transformer-based parameter learning model (ParaFormer) and a surrogate model based on LSTM. On the one hand, ParaFormer utilizes self-attention mechanisms to learn a global mapping from observed data to the parameters to be calibrated, which captures spatial correlations. On the other hand, the surrogate model takes the calibrated parameters as inputs and simulates the observable variables, such as soil moisture, overcoming the challenges of directly combining complex hydrological models with a deep learning (DL) platform in a hybrid training scheme. Using the variable infiltration capacity model as the reference, we test the performance of ParaFormer on datasets of different resolutions. The results demonstrate that, in predicting soil moisture and transferring calibrated parameters in the task of evapotranspiration prediction, ParaFormer learns more effective and robust parameter mapping patterns compared to traditional and state-of-the-art DL-based parameter calibration methods. [ABSTRACT FROM AUTHOR]

The compacted straw cube (CSC) is the structural unit of a rectangular straw bale. A rectangular straw bale can be regarded as an ordered assembly of several CSCs constrained by strings. Straw bale is the object of mechanical operation in the straw collection, storage, management, and terminal utilisation. As a basis for studying the mechanics of rectangular straw bales, it remains a challenge to establish the CSC discrete element model incorporating the elastic, plastic, and viscous mechanical characteristics of the flexible straw and calibrate its simulation parameters. An original method of CSC discrete element modelling and simulation parameters calibration based on EDEM software was proposed. The CSC model was developed by performing virtual uniaxial compression tests with thousands of flexible straw stems using Edinburgh elasto-plastic adhesion (EEPA) as the contact model between straw stems. With compressive stress σ 10 as the response value, the discrete element parameters of the CSC model were determined by the Plackett-Burman design test, the steepest climb test, and the Box-Behnken design test. The results showed that the relative error of the simulated compressive stresses σ 10 was 1.04% for the 120 mm thickness of CSC. The relative errors of the CSC with 180 and 240 mm thicknesses were 3.89% and 2.6%, respectively, which validated that the model and parameters were reliable. The proposed method provides a new perspective for analysing the interaction mechanism between straw bales and mechanical components, which is significant for the development of straw management and utilisation equipment. [Display omitted] • A novel discrete element modelling method for compacted straw cubes was proposed. • A novel method for calibrating DEM parameters of compacted straw was proposed. • The modelling and parameter calibration methods were validated with small errors. • This study facilitated the analysis of micromechanics of straw bales with DEM. [ABSTRACT FROM AUTHOR]

The viscoelastic-plastic damage model has been widely used to predict the long-term performance of asphalt mixtures. However, it is challenging for obtaining model parameters to separate the total strain and determine the yield function. This study proposed an improved multistage creep-recovery test to simplify the acquisition of constitutive model parameters. The method was designed to identify the viscoplastic parameters by the equilibrium condition when the specimen was fully hardened and calibrate the damage parameters through the changes of modulus in the process of plastic development. The results indicated the proposed test is an effective method to calibrate the parameters of the viscoplastic damage model, as well as the nonlinearity between the stiffness and strength. In addition, it was found that the sigmoid function may be the more satisfactory choice to fit the cohesion excluding the damage compared with the negative exponential function. [ABSTRACT FROM AUTHOR]

Discrete element method (DEM) simulation is widely used to calculate the flow characteristics of particles under certain conditions. DEM input parameters are the prerequisite for the accurate modeling and simulation of particles. In order to explore the mechanical properties and breaking behavior of gluten pellets, the pellet material property, the interaction parameters of pellet–stainless steel and pellet–pellet (multi-spheres autofill model), and the bonding parameters (bonded particle model) were calibrated by experiments and simulations. The relative error of the angle of repose, the breaking displacement, and the breaking force between simulated and experimental values were 0.28%, 0.66%, and 1.09%, respectively. Based on the regression analysis in the Design-Expert 12.0 software, the relationships among evaluating indicators (angle of repose, breaking displacement, and breaking force) and their corresponding influencing factors were established, respectively. Meanwhile, the feasibility of applying the interaction parameters of the multi-spheres autofill model to the bonded particle model was verified through the free fall test, the inclined plane sliding test, and the inclined plane tumbling time test. This work can provide a reference for the design of pellet feed processing and transportation machinery. [ABSTRACT FROM AUTHOR]

In this paper, a novel method based on edge spread information fitting (ESIF) is proposed to accurately calibrate the geometric parameters of a focused light field camera. A focused light field camera with flexible adjustment of spatial resolution and angular resolution is designed and built to capture the four-dimensional light field information of the scenes, and the geometric relationship between the focus plane of the camera and its internal parameters is derived to establish and simplify the calibration model. After that, a new algorithm based on sub-pixel edge fitting is designed to accurately detect corners, and the minimum corner size can be calculated to confirm the focus plane. In the simulation experiments, the error is 0.083% between the ground truth and the calibration result. The physical experiments show that our method is effective and reliable for the geometric calibration of a focused light field camera. Our method cleverly utilizes the special imaging geometric relationship of the focused light field camera to ensure the better calibration accuracy, which makes the calibration process more reliable. [ABSTRACT FROM AUTHOR]

This paper aims to propose a generalizable parameter calibration framework for discrete element method (DEM) and to develop the refined dynamic compaction DEM (RDCD) model for red-bed soft rocks (RBSR), which is used to investigate the contribution of tamping weight (W) and drop distance (H) to dynamic compaction quality control. Firstly, the linear model (LM) and the linear parallel bond model (LPBM) were selected to accurately represent the dynamic behavior of RBSR based on dynamic compaction characteristics. A generalizable calibration framework for LM and LPBM contact models was further proposed. Secondly, based on the calibration framework, a series of DEM simulations, parameters significance analysis, and physical tests were conducted to accurately calibrate the contact parameters of RBSR. Finally, the RDCD model for RBSR was developed, which was used to investigate the contribution of W and H to dynamic compaction quality control from a micro perspective. All results indicated that the proposed generalizable calibration framework could provide an accurate determination of RBSR contact parameters for dynamic compaction simulation. Specially, the lightweight inversion model for LPBM parameters was developed, enabling the rapid acquisition of contact parameters for RBSR. The LM parameters of RBSR were determined directly and indirectly, which could be directly applied to various RBSR. Moreover, the shockwaves generated by a heavier tamper with a lower drop distance had longer durations and larger propagation, enhancing the compactness of the overall specimen and generating larger and more uniformly distributed strong force chains. The dynamic compaction simulation results indicated that increasing the W could enhance dynamic compaction quality control. This paper contributes to the theoretical refinement of the contribution of W and H on-site dynamic compaction quality control. • A generalizable parameter calibration framework for discrete element method. • The refined dynamic compaction DEM model for red-bed soft rocks is developed. • The contribution of W and drop distance H to dynamic compaction is investigated. • The shockwaves generated by a heavier W have longer durations and propagation. [ABSTRACT FROM AUTHOR]

Accurate and reliable calibration of power plant models in the power system is crucial for maintaining grid stability and preventing power outages. This becomes even more crucial as the power grids become more dynamic and stochastic with the ever-increasing penetration of renewable energy sources, mid-size generators, smart loads, and energy storage. Current practice such as staged-test is costly and time-consuming. Alternatively, recent PMU-based approaches using online measurements without interfering with generators operation have been introduced to provide a scalable and low-cost to meet North American Electric Reliability Corporation (NERC) standards. This research paper proposes a PMU-based framework to validate and calibrate model parameters by a new iterative deep learning approach. The results show that the proposed approach can accurately calibrate power plantmodels from a single disturbance event without the urgent need of prior knowledge of the model’s initial parameters. The proposed method has been validated on real-world and simulated scenarios on a relatively large number of calibrated parameters with an average error of 1.43%.

Various carbon fiber–reinforced polymer (CFRP) strengthening systems have been developed to increase the fatigue lifetime of existing aging steel structures. According to the literature, the results of fatigue tests on CFRP-strengthened steel plates showed a significant increase in the fatigue lifetime of the specimens, compared with the bare ones. In particular, the fatigue lifetime extension was more pronounced for short initial crack sizes (i.e., low initial damage level). In this study, the fatigue-crack growth curves in bonded CFRP-strengthened single edge notched tension (SENT) specimens were numerically investigated. The proposed numerical approach adopted a cyclic cohesive-zone model (CCZM), which enabled the simulation of crack growth in steel plates, through the definition of a scalar damage variable (k). The selected model contained some parameters that did not possess a precise physical meaning and therefore were not amenable to direct measurement. Therefore, a robust identification procedure was proposed to calibrate the model parameters that governed fatigue behavior, which was based on the response of unstrengthened specimens in the crack propagation curves. The successful identification was then validated by comparison with the measured response of the strengthened SENT specimens, which were modeled by adopting the same identified model parameters. The adhesive between the CFRP laminate and steel substrate was simulated by defining an elasto–brittle surface-to-surface contact model, whose properties were selected based on well known approaches that were proposed in the literature. [ABSTRACT FROM AUTHOR]

The effective representation of land surface hydrological models strongly relies on spatially varying parameters that require calibration. Well-calibrated physical models can effectively propagate observed information to unobserved variables, but traditional calibration methods often result in nonunique solutions. In this paper, we propose a hydrological parameter calibration training framework consisting of a transformer-based parameter learning model (ParaFormer) and a surrogate model based on LSTM. On the one hand, ParaFormer utilizes self-attention mechanisms to learn a global mapping from observed data to the parameters to be calibrated, which captures spatial correlations. On the other hand, the surrogate model takes the calibrated parameters as inputs and simulates the observable variables, such as soil moisture, overcoming the challenges of directly combining complex hydrological models with a deep learning (DL) platform in a hybrid training scheme. Using the variable infiltration capacity model as the reference, we test the performance of ParaFormer on datasets of different resolutions. The results demonstrate that, in predicting soil moisture and transferring calibrated parameters in the task of evapotranspiration prediction, ParaFormer learns more effective and robust parameter mapping patterns compared to traditional and state-of-the-art DL-based parameter calibration methods.

Discrete element method (DEM) simulation is widely used to calculate the flow characteristics of particles under certain conditions. DEM input parameters are the prerequisite for the accurate modeling and simulation of particles. In order to explore the mechanical properties and breaking behavior of gluten pellets, the pellet material property, the interaction parameters of pellet–stainless steel and pellet–pellet (multi-spheres autofill model), and the bonding parameters (bonded particle model) were calibrated by experiments and simulations. The relative error of the angle of repose, the breaking displacement, and the breaking force between simulated and experimental values were 0.28%, 0.66%, and 1.09%, respectively. Based on the regression analysis in the Design-Expert 12.0 software, the relationships among evaluating indicators (angle of repose, breaking displacement, and breaking force) and their corresponding influencing factors were established, respectively. Meanwhile, the feasibility of applying the interaction parameters of the multi-spheres autofill model to the bonded particle model was verified through the free fall test, the inclined plane sliding test, and the inclined plane tumbling time test. This work can provide a reference for the design of pellet feed processing and transportation machinery.

Clarifying the maize kernel movement during the crushing process is critical for improving the design and optimization of the impact mill. Rather than through experiments, maize kernel movement can be quantitatively analyzed through the discrete element method (DEM), and this could contribute more to the study of the crushing mechanism and equipment optimization. However, having an accurate particle model and contact parameters are prerequisites to ensure the accuracy of the DEM simulation. In this study, we proposed a maize kernel model construction method for the Rocky DEM simulation and a calibration method to calibrate contact parameters. The three-axis size, volume, and shape information of real maize kernels were obtained by 3D scanning, and then the maize kernel model was constructed by the section method. The particle–low-carbon-plate (p–w) and particle–particle (p–p) restitution coefficients were calibrated by using the improved inclined surface drop method. In addition, the angle of repose (AoR) and discharging time were considered together to calibrate the dynamical friction coefficients of p–w and p–p through the funnel method. Additionally, the maize kernel model and calibrated parameter values were used in a DEM simulation of the inclined surface drop test and the funnel test. The maximum relative errors between the simulation values and the measured values of the inclined surface drop test and the funnel test were 4.38% and 6.98%, respectively, which further verified that the proposed maize kernel model construction and contact parameter calibration methods are feasible and accurate. The research method used in this study is a novel idea that can be applied for the construction of the particle model and calibration of the contact parameters of granular materials with complex geometric structures, as well as the maize kernel model, and shows that calibrated contact parameters can provide a reference for the maize kernel crushing simulation to optimize the impact mill. [ABSTRACT FROM AUTHOR]

In this paper, a novel method based on edge spread information fitting (ESIF) is proposed to accurately calibrate the geometric parameters of a focused light field camera. A focused light field camera with flexible adjustment of spatial resolution and angular resolution is designed and built to capture the four-dimensional light field information of the scenes, and the geometric relationship between the focus plane of the camera and its internal parameters is derived to establish and simplify the calibration model. After that, a new algorithm based on sub-pixel edge fitting is designed to accurately detect corners, and the minimum corner size can be calculated to confirm the focus plane. In the simulation experiments, the error is 0.083% between the ground truth and the calibration result. The physical experiments show that our method is effective and reliable for the geometric calibration of a focused light field camera. Our method cleverly utilizes the special imaging geometric relationship of the focused light field camera to ensure the better calibration accuracy, which makes the calibration process more reliable.

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• Novel algorithm for internal and external parameters calibration of mecanum wheel omnidirectional mobile platform. • Parameter calibration based on principal component analysis and nonlinear optimization. • The calibration method is theoretically applicable to all types of holonomic robot mobile platforms. Mobile robot positioning, mapping, and navigation systems generally employ an inertial measurement unit to obtain the acceleration and angular velocity of the robot. However, errors in the internal and external parameters of an inertial measurement unit arising from defective calibration directly affect the accuracy of robot positioning and pose estimation. While this issue has been addressed by the mature internal parameters calibration method available for inertial measurement unit, external reference calibration method between the inertial measurement unit and the chassis of a mobile robot are lacking. This study addresses this issue by proposing a novel algorithm for internal parameter calibration of mecanum wheel omnidirectional mobile platform and external parameter calibration of mecanum chassis- inertial measurement unit based on principal component analysis and nonlinear optimization, which is designed for robots equipped with cameras, inertial measurement unit, mecanum wheels, and wheel speed odometers, and functions under the premise of accurate calibrations for the internal parameters of the inertial measurement unit and the internal and external parameters of the camera. All of the internal and external parameters calibrations are conducted using the robot's existing equipment without the need for additional calibration aids. The feasibility of the method is verified by its application to a mecanum wheel omnidirectional mobile platform. The proposed calibration method is thereby demonstrated to guarantee the accuracy of robot pose estimation. [ABSTRACT FROM AUTHOR]

Clarifying the maize kernel movement during the crushing process is critical for improving the design and optimization of the impact mill. Rather than through experiments, maize kernel movement can be quantitatively analyzed through the discrete element method (DEM), and this could contribute more to the study of the crushing mechanism and equipment optimization. However, having an accurate particle model and contact parameters are prerequisites to ensure the accuracy of the DEM simulation. In this study, we proposed a maize kernel model construction method for the Rocky DEM simulation and a calibration method to calibrate contact parameters. The three-axis size, volume, and shape information of real maize kernels were obtained by 3D scanning, and then the maize kernel model was constructed by the section method. The particle–low-carbon-plate (p–w) and particle–particle (p–p) restitution coefficients were calibrated by using the improved inclined surface drop method. In addition, the angle of repose (AoR) and discharging time were considered together to calibrate the dynamical friction coefficients of p–w and p–p through the funnel method. Additionally, the maize kernel model and calibrated parameter values were used in a DEM simulation of the inclined surface drop test and the funnel test. The maximum relative errors between the simulation values and the measured values of the inclined surface drop test and the funnel test were 4.38% and 6.98%, respectively, which further verified that the proposed maize kernel model construction and contact parameter calibration methods are feasible and accurate. The research method used in this study is a novel idea that can be applied for the construction of the particle model and calibration of the contact parameters of granular materials with complex geometric structures, as well as the maize kernel model, and shows that calibrated contact parameters can provide a reference for the maize kernel crushing simulation to optimize the impact mill.

The complete and unique of DEM-FEM model parameters can be determined by a single-factor numerical calibration experiment. • A novel method based on experimental design is proposed for parameters calibration. • The proposed method enables to perform a single-factor numerical calibration test. • A complete and unique set of the DEM-FEM model parameters is determined. • The effectiveness of the calibration method is verified by tire-sand interaction. The real sand is usually idealized by using upscaled particles, due to the large number of particles of tire-sand interaction. This study aims to determine a unique and complete set of DEM-FEM model parameters to improve numerical accuracy of tire-sand interaction after particles idealization. To achieve this aim, a novel method based on experimental design is proposed to calibrate the DEM-FEM model parameters by a series of single-factor numerical calibration tests. Initially, the interaction properties such as equivalent friction coefficients of particle-particle, particle-soil bin and particle-tire are determined successively by comparing experimental test with numerical simulation using the angle of repose as a bulk response. The material parameters of particles are then obtained by modified iteratively to match the stress-strain behavior of the granular assembly in triaxial test. After that, the calibrated parameter set is used to investigate the interaction mechanisms between the off-road tire and the granular terrain. Finally, the simulation results are qualitatively in agreement with the soil bin experiments, which verifies the effectiveness of the calibrated parameter set for the tractive performance analysis of tire-sand interaction. [ABSTRACT FROM AUTHOR]

In this study, a soil–tunnel model for clay under earthquake loading is analyzed, using finite element methods and a kinematic hardening model with the Von Mises failure criterion. The results are compared with those from the linear elastic–perfectly plastic Mohr–Coulomb model. The latter model does not consider the stiffness degradation caused by imposing cyclic loading and unloading to the soil, whereas the kinematic hardening model can simulate this stiffness degradation. The parameters of the kinematic hardening model are calibrated based on the results of experimental cyclic tests and finite element simulation. Here, two methods—one using data from cyclic shear tests, and the other a new method using undrained cyclic triaxial tests—are used to calibrate the parameters. The parameters investigated are the peak ground acceleration (PGA), tunnel lining thickness, tunnel shape, and tunnel embedment depth, all of which have an effect on the resistance of the shallow tunnel to the stresses and deformations caused by the surrounding clay soils. The results show that unlike traditional models, the nonlinear kinematic hardening model can predict the response reasonably well, and it is able to create the hysteresis loops and consider the soil stiffness degradation under the seismic loads. [ABSTRACT FROM AUTHOR]

This work aims to determine a complete set of input parameters of the DEM-FEM coupling model, which ensures us obtain more realistic simulation results of the tire-terrain interactions. Firstly, we investigate the macroscopic responses of the gravel sample, the stress-strain curves and deformations, which is finished by the triaxial tests at different confining pressures of 25 kPa, 50 kPa and 100 kPa. Then, the microscopic input parameters of the numerical simulations are obtained by iteratively adjusting the coupling model parameters, which are employed to meet the macroscopic responses of the triaxial tests. Finally, the traction behavior researches of an off-road tire on gravel terrain are carried out by the DEM-FEM coupling model with the calibrated microscopic input parameters mentioned above. The predicted traction performance parameters such as the vertical reaction force, tractive force and tire sinkage are qualitatively in agreements with the corresponding experimental results. The effectiveness of the calibration method using numerical triaxial tests is validated in traction behavior of tire-terrain interactions. Unlabelled Image • Triaxial tests are performed to measure bulk behavior of the gravel assembly. • Numerical triaxial tests with flexible boundary are simulated by the DEM-FEM. • A complete set of model parameters is determined by bulk calibration approach. • The validity of parameter set is verified by analysis of tire-terrain interaction. [ABSTRACT FROM AUTHOR]

Grapevine in seasonally frozen regions needs to be warm-insulated by soil in winter with the antifreezing soil removed in spring most mechanically by a soil removal machine. The purpose of this paper is to simulate the interaction between the insulating soil (with sandy loam texture) and the soil-cleaning materials (Q235 steel, rubber) commonly used in the soil removal machine, based on the discrete element method. The simulation model was constructed based on properties of the soil by integrating the hysteretic spring contact model (HSCM) and the linear cohesion model (LCM) as the contact model between soil particles. We took soil-soil restitution coefficient, soil-soil frictional coefficient, soil-soil rolling coefficient and soil cohesion energy density as the determinants and the soil accumulation angle as an evaluation index. The 4-factor universal rotation center combination simulation test, based on the EDEM, was used to regress the relationship between the determinants and the index using the Design-Expert software. The results showed that the soil-soil frictional coefficient was the only parameter that did not have significant effects on the soil accumulation angle. The best contact-parameter combination between soil particles was obtained by taking the physically measured soil accumulation angle as the optimization objective, which gave 0.51 for the soil-soil restitution coefficient, 0.65 for the soil-soil frictional coefficient, 0.06 for the soil-soil rolling frictional coefficient, and 10 495 J/m³ for the soil cohesion energy density. The associated soil accumulation angle was 31.74°, with a relative error of 0.83% compared with the physically measured results. The universal testing machine for soil yield test was used to obtain the HSCM model parameters based on the change in penetration stress with the displacement, and the resultant soil yield strength was 0.38 MPa. The static frictional coefficient between soil and Q235 steel as well as the rubber measured by the inclination test bench was 0.38 and 0.48 respectively. These data and the EDEM were used to conduct the simulation test of the soil slip, with the restitution coefficient and the rolling frictional coefficient between soil and the materials taken as the determinants and the sliding frictional angle as evaluating index. Regressing the test date with the two-factor universal rotation center combination test showed that the rolling frictional coefficient between soil and the materials had a significant effect on the sliding frictional angle between soil and the steel plate and rubber. In contrast, the restitution coefficient between the soil and the materials impacted significantly on the sliding frictional angle between the soil and the rubber but not on the soil and the steel plate. The restitution coefficient and the rolling frictional coefficient between the soil and the Q235 steel as well as the rubber were optimized by using the measured sliding frictional angle as the optimization objective. The resultant restitution coefficient and the rolling frictional coefficient were 0.60 and 0.37 respectively for the soil and the Q235 steel, and 0.61 and 0.23 respectively for the soil and the rubber. Soil bin test and simulation test of the scraper were conducted to verify the calibrated discrete element model parameters. The horizontal forward resistance of the scraper in the soil bin test and simulation test was 228.36 and 213.79 N respectively, with a relative error of 6.38%. The results presented in this paper have important implications for using discrete element method to analyze the removal of grapevine-insulating soil. [ABSTRACT FROM AUTHOR]

Seed-fertilizer drill machines with fluted rollers generally utilize a calibrated relationship between the fluted-roller rotation speed and mass flow rate to control the application rate. However, this relationship model gradually deteriorates with operating time and is easily affected by working conditions. To maintain the initial operating accuracy, a self-calibrating system for adjusting the control model parameters was designed. It utilizes the application-rate information and fluted-rollers rotation speed data during the operation process to dynamically establish the calibrated relationship. During the field tests performed 18 times, the self-calibrating system could dynamically re-calibrate the relationship model. After the model parameters were updated, the application rate control system maintained a high accuracy level, though the relative deviation of control parameters was relatively higher. The average relative deviations between actual and theoretical cumulative application rates were 0.97% and 1.22% for seeding and fertilizing, respectively, and the standard deviations were 0.69% and 0.62%. Correspondingly, the average relative deviations of control parameters were 7.29% and 7.86%, and the standard deviations were 1.16% and 3.06%. These results indicate that the proposed method with closed-looped control can maintain high-quality control performance and improve the productivity of the drill machine, which will benefit the agricultural production. [ABSTRACT FROM AUTHOR]

Highlights • Effect caused by m and σ 0 hardly change with λ under different temperatures. • Calibrated failure probability is close to the experimental result when taking λ = 1.5. • A simple approach to calibrate the local approach has been proposed. Abstract This work presents a simplified method for parameters calibration of the new local approach model (NLAM) for cleavage fracture in a ferritic steel. Based on the Beremin model, a NLAM was recently proposed by Lei (2016) to calculate the Weibull parameters. Although the above NLAM proves to be mathematically and physically self-consistent, yet there are still no reliable and convenient methods to calibrate the model parameters. Considering the plastic volume is determined by the threshold coefficient of fracture process zone λ , we adopt four different values of λ in this work to calculate the plastic volume so as to obtain four groups of calibrated Weibull parameters. The material used in this study is the pressure vessel steel 20MnMoNi55 with some published strength data under two subzero temperatures. And the finite element analysis FEA) software ABAQUS is employed to obtain the stress distributions, then the calibration results for four different values of λ are compared and analyzed. These efforts show that taking λ = 1.5 is a more reasonable and reliable choice. [ABSTRACT FROM AUTHOR]

When a shield tunneling machine based on earth pressure balance (EPB) bores through the sandy pebble stratum, the conditioned sandy pebble inside the soil cabin of shield machine is an aggregation of numerous granules with pebble grains as skeleton. It is essential to construct a reasonable particle element model of the conditioned sandy pebble before carrying out discrete element simulation of the soil cabin system. Sandy pebble belongs to a kind of frictional material, the friction behavior of which is highly sensitive to the angularity of the grains. In order to take the shape effect into account, two particle element models—single sphere with rolling resistance and cluster of particles—were attempted in this paper. The undetermined contact parameters in two models were calibrated by virtue of least squares support vector regression machine (LS-SVR). With the purpose of making both the flow behavior and mechanical properties of the modeled soil consistent with reality, the calibration targets the result of laboratory test of slump test and large-scale triaxial test as goals. The presented comparative analysis indicates that the two established particle models both can well describe the strength property and fluidity of the actual soil due to properly calibrated parameters. So, the rolling resistance and cluster models are two effective ways to incorporate the shape effect. Besides, because of the angularity of the nonspherical grains, there exists strong interlocking between clusters. So, in the cluster model, relatively smaller rolling friction coefficient and surface energy are required. It is also concluded that the single sphere model is more computationally efficient than the cluster model. [ABSTRACT FROM AUTHOR]

Soil-rubber mixtures underneath foundations are an eco-sustainable and low-cost Geotechnical Seismic Isolation (GSI) solution. Using rubber grains from end-of-life tyres in the mixtures can provide a modern recycling system that reduces the stockpile of scrap tyres worldwide. In recent years, gravel-rubber mixtures (GRMs) properties have been investigated, finding good behaviour in static and dynamic conditions. Laboratory tests on GRMs advantages as GSI in the form of a layer underlying the foundation of a structure are available in the literature. Nevertheless, only one experimental campaign on a full-scale prototype structure resting on GRMs with 0% and 30% rubber content per weight was performed (SOFIA-SERA Research Programme). This paper presents 3D advanced nonlinear FEM analyses to reproduce and furnish new results about the above-mentioned full-scale test. The calibration of the parameters of the different constitutive models used for modelling the foundation soil and the GRMs was supported by an extensive geotechnical characterization. The developed FEM model was validated by the results from the above-mentioned full-scale test in terms of accelerations and velocities. Then, the dynamic behaviour of the GRMs was studied, also considering the shear strains versus the shear stresses and the horizontal and vertical displacements, quantities not investigated experimentally. Finally, the GRMs static behaviour was also investigated, considering the GRMs axial strains and the GRMs and foundation vertical displacements. The paper highlights the fundamental role of both experimental tests and numerical modelling, as invaluable tools for coupled analyses of the seismic behaviour of soil-structure systems, including innovative materials, such as GRMs, and the main advantages of using GRMs as GSI. • Gravel-rubber mixtures (GRMs) are an eco-sustainable and low-cost geotechnical seismic isolation system. • Using end-of-life tyres as rubber grains in GRMs provides a modern recycling system. • 3D numerical analyses reproduce and furnish new results about recent tests performed on a full-scale structure on GRMs. • The Authors performed a fine calibration of the advanced HSsmall constitutive model parameters for the investigated GRMs. • GRMs with 30% rubber content per weight significantly mitigate the ground motion. [ABSTRACT FROM AUTHOR]

In this study, a soil–tunnel model for clay under earthquake loading is analyzed, using finite element methods and a kinematic hardening model with the Von Mises failure criterion. The results are compared with those from the linear elastic–perfectly plastic Mohr–Coulomb model. The latter model does not consider the stiffness degradation caused by imposing cyclic loading and unloading to the soil, whereas the kinematic hardening model can simulate this stiffness degradation. The parameters of the kinematic hardening model are calibrated based on the results of experimental cyclic tests and finite element simulation. Here, two methods—one using data from cyclic shear tests, and the other a new method using undrained cyclic triaxial tests—are used to calibrate the parameters. The parameters investigated are the peak ground acceleration (PGA), tunnel lining thickness, tunnel shape, and tunnel embedment depth, all of which have an effect on the resistance of the shallow tunnel to the stresses and deformations caused by the surrounding clay soils. The results show that unlike traditional models, the nonlinear kinematic hardening model can predict the response reasonably well, and it is able to create the hysteresis loops and consider the soil stiffness degradation under the seismic loads.

It is generally accepted that the model parameters calibration is an essential step before application. However, the traditional methods of obtaining a set of “optional parameters” based on a certain number of observations, fail to represent the uncertainties and get reliable estimates. To overcome this problem, we introduced the DE-MC (differential evolution Markov chain) algorithm with snooker update into the WOFOST (world food studies) model parameters calibration. The main objectives were: 1) to calibrate the WOFOST model by DE-MC algorithm with snooker update; 2) to evaluate the uncertainty of the model parameters after calibration; 3) to evaluate the uncertainty of the model outputs after calibration. Observational data including LAI (leaf area index) in different growth stages and the final yield of winter wheat in Zhengzhou Agrometeorological Experimental Station, were used to calibrate WOFOST model at potential mode with this algorithm. The crop parameters related to accumulated temperature were calculated directly from the crop phenological development date and near-surface temperature. The remaining crop parameters were analyzed by Sobol method. Taking Sobol global sensitivity index greater than 0.05 as the threshold for sensitive parameters, 14 parameters were then selected. The calibrated parameters were defined as the uniform distribution over their value interval. The likelihood function represented the mismatch of the model output with the measured observations, by which the parameters’ priori distribution converted to posterior distribution. The likelihood function for yield was set as a Gaussian distribution with the observational data as expected value and 10% of the observational data as standard deviation. Similarly, the likelihood function for LAI was set as a multidimensional Gaussian distribution with observational LAI as the expected vector and a diagonal matrix as the covariance matrix. At last, we found that: 1) Compared with the simulation results with model default parameters, the LAI simulation accuracy could be increased by 51.40%-53.07% after the parameter calibration, and the yield simulation accuracy is improved by 8.25%-8.88%; 2) The posterior distribution of life span of leaves growing at 35 Celsius (SPAN), specific leaf area at development stage of 0.7 (SLATB070), specific leaf area at development stage of 0.4 (SLATB040), maximum CO2 assimilation rate at development stage of 1.3 (AMAXTB130), and specific leaf area at development stage of 0 (SLATB00) could be approximated as a Gaussian distribution with SPAN having the minimum uncertainty; 3) Running model with the posterior parameters set, the uncertainty of simulated LAI from the three-leaf stage to the re-greening stage and from the jointing stage to the heading stage is larger; the uncertainty of the simulated yield increases with time before the milky ripe stage, stayed unchanged until maturity. It was concluded that DE-MC with snooker update was an effective algorithm for parameters estimation of WOFOST model, the calibration had the potential to reduce the uncertainty of the model parameters and the calibrated model was able to model the observational data with some degree of skill. The calibration data used in this study was the observation data from the agrometeorological site. Although the crop varieties were consistent, the inter-annual cultivation management measures were not strictly controlled (eg.: seeding density), and the accuracy of the calibration results might be affected. Subsequent experiments can be carried out in more areas using experimental data with quantitative control to further verify the effectiveness of this algorithm. [ABSTRACT FROM AUTHOR]

To simulate the bending behavior of wheat straw, a flexible straw model was developed based on the Hertz-Mindlin with bonding model using discrete element method. The proposed model was constructed by bonding straw units (filled by multi-spherical method) through parallel bonding keys. By means of a three-point bending test, single-factor sensitivity analysis and calibration of bonding parameters were performed. Results showed that elastic modulus of the flexible straw enhanced with the increase of bonded disk radius, normal stiffness per unit area and shear stiffness per unit area. The three bonding parameters were respectively calibrated to be 2.11 mm, 9.48×109 N/m³ and 4.67×109 N/m³ by solving the regression equation developed from Box-Behnken design. The simulated elastic modulus (in terms of those three calibrated parameters) exhibited 4.20% difference with the measured one. It proved that the flexible straw could accurately demonstrate bending property of the wheat straw. This would not only help to improve accuracy in simulating wheat straw, but also provide references for flexible straw modeling and parameters calibration of other crops. [ABSTRACT FROM AUTHOR]

This study investigated the mechanical properties and constitutive models of duplex stainless steel S22053 under cyclic large plastic strain loading. To this end, smooth round bar specimens of the base metal, deposited metal, and heat-affected mixing zone material were tested under monotonic tensile loading and cyclic loading. Furthermore, the failure modes and stress–strain curves of the specimens were analysed. Based on the test results of the smooth round bar specimens under cyclic symmetric constant amplitude and monotonic tensile loading, the N3L1 and S10 parameters of the Chaboche model for duplex stainless steel S22053 were calibrated, respectively. Then, the accuracy of the calibrated Chaboche model was verified against the test results of the smooth round bar and circular notched bar specimens. The results showed that the base metal and heat-affected mixing zone material have higher ductility, and the strength of the deposited metal is the highest. Furthermore, the N3L1 parameters can accurately simulate the behavior of smooth round bar specimens under cyclic medium plastic strain loading, while the S10 parameters are more suitable for simulating the mechanical response of circular notched bar specimens under cyclic large plastic strain loading. The accuracy of the Chaboche model depends on the matching of the loading strain range of the test data for calibrating the model with that of the simulation cases. The results of this study provide fundamental data for analysing the seismic and ductile fracture performance of duplex stainless steel and its welded structures. [Display omitted] • Mechanical properties of the S22053 base metal, deposited metal, and heat-affected mixing zone material are analysed. • Methods to calibrate the cyclic constitutive model parameters using cyclic and monotonic test data are proposed. • ULCF tests of circular notched bar specimens are simulated and compared. • Constitutive parameters suitable for large plastic strain cyclic loading are proposed and assessed. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the time evolution of floc size distribution of activated sludge flocculation through population balance model and calibration method for simulation.

Electromagnetic measurement technology is an important method for instrument parameters calibration, detection performance evaluation and complex system theory verification. In this paper, self-adaptive finite element method has been used to compute and analyze the weak electromagnetic wave signal, which is produced by changing electrode structure, transmitting frequency and antenna spacing of the through casing electromagnetic measurement tool. Numerical simulation results show that the detection depth of the tool can be influenced by the electrode structure can have the influence on, the resolution of high-resistivity and low-resistivity formation can be improved by transmitting frequency, the detection accuracy and detection depth of the through casing electromagnetic measurement tool can be influenced by the change of antenna spacing. [ABSTRACT FROM AUTHOR]

Since the drifts of Inertial Navigation System (INS) solutions are inevitable and also grow over time, a Doppler Velocity Log (DVL) is used to aid the INS to restrain its error growth. Therefore, INS/DVL integration is a common approach for Autonomous Underwater Vehicle (AUV) navigation. The parameters including the scale factor of DVL and misalignments between INS and DVL are key factors which limit the accuracy of the INS/DVL integration. In this paper, a novel parameter calibration method is proposed. An iterative implementation of the method is designed to reduce the error caused by INS initial alignment. Furthermore, a simplified INS/DVL integration scheme is employed. The proposed method is evaluated with both river trial and sea trial data sets. Using 0.03°/h(1σ) ring laser gyroscopes, 5 × 10−5 g(1σ) quartz accelerometers and DVL with accuracy 0.5% V ± 0.5 cm/s, INS/DVL integrated navigation can reach an accuracy of about 1‰ of distance travelled (CEP) in a river trial and 2‰ of distance travelled (CEP) in a sea trial.

The nervous system is today recognized to play an important role in the development of cancer. Indeed, neurons extend long processes (axons) that grow and infiltrate tumors in order to regulate the progression of the disease in a positive or negative way, depending on the type of neuron considered. Mathematical modeling of this biological process allows to formalize the nerve–tumor interactions and to test hypotheses in silico to better understand this phenomenon. In this work, we introduce a system of differential equations modeling the progression of pancreatic ductal adenocarcinoma (PDAC) coupled with associated changes in axonal innervation. The study of the asymptotic behavior of the model confirms the experimental observations that PDAC development is correlated with the type and densities of axons in the tissue. We study then the identifiability and the sensitivity of the model parameters. The identifiability analysis informs on the adequacy between the parameters of the model and the experimental data and the sensitivity analysis on the most contributing factors on the development of cancer. It leads to significant insights on the main neural checkpoints and mechanisms controlling the progression of pancreatic cancer. Finally, we give an example of a simulation of the effects of partial or complete denervation that sheds lights on complex correlation between the healthy, pre-cancerous and cancerous cell densities and axons with opposite functions. • Dynamical system modeling the pancreatic cancer progression and the axons regulation • The in silico denervations are consistent with the in vivo observations • The autonomic axons slow the PDAC progression at early stages • The sensory axons have a pro-tumoral effect especially on the proliferation process [ABSTRACT FROM AUTHOR]

Summary The quantification of the main water balance components becomes necessary to diminish the pollutants load from drainage, and its harmful effect on the environment, aggravated within a context of increasing water scarcity. As a first approach to the hydrological study of the 15,000 ha B-XII Irrigation District in Spain, a conceptual lumped model entitled WATEN has been developed, aiming to calculate the monthly flow rate discharge to the Guadalquivir River over the period 2002–2012. The model requires as inputs, irrigation, precipitation and potential crop evapotranspiration. Main model parameters are the total and readily available moisture in the soil, the effective rainfall and the irrigation efficiency. Energy consumption for drainage discharge was used for calibration. Both classical optimization and a robust approach based on Monte Carlo were performed. In order to diminish computational requirements, Monte Carlo was not haphazardly applied, but conducted on a similar manner to genetic algorithms, entitled Parameters Estimation on Driven Trials (PEDT). The model attained an average Nash–Sutcliffe coefficient e 2 ≅ 0.90 between observed and estimated drainage discharge. It was detected a significant crop evapotranspiration reduction compared to potential values. The volume of water discharged to the river might be sufficient for leaching irrigation water salts. [ABSTRACT FROM AUTHOR]

The economies of the sub-Saharan countries are based mainly their on rainfed agriculture. Medium- and long-term demographic projections show that population pressure will increase dramatically. In the future, greater emphasis will need to be given to the development of agricultural strategies, which, in turn, will require a better understanding of future water resources. To this end, climate and hydrological scenarios need to be developed involving different actors skilled in a range of activities, not only scientists in various fields (climatologists, hydrologists, sociologists, …), but also financial, political and social actors and decision makers. The process of developing scenarios is accompanied by many uncertainties, more or less understood, to which project managers and regional development planners must adapt. Illustrated by the example of the Bani River basin, a tributary of the Niger River, this study discusses the setting of “hydrological scenarios” and the predetermination of parameters of a hydrological model in a non-stationary global context. The choice of parameters has many impacts on the results of different scenarios, for instance for water resource assessment and the variability of water resources. These two factors are fundamental in determining who should lead the decision-making process in response to a request for a management or a development strategy. A methodology is proposed for determining parameter sets based on mixing several sets of parameters derived by moving calibration, and is in line with recommendations of an increasing number of managers: not to try to predict the future, but to envisage several possible futures that force impact models, thus providing managers with decision elements either to adapt to, or to use for adapting new infrastructure solutions to future conditions. [ABSTRACT FROM PUBLISHER]

Abstract: This research is intended for a super-size 3 dimensional scaling events sensing and positioning system based on binocular stereo vision. A model for computing the coordinates of targets in the physical world coordinate system is proposed and simulated. Constitution of a reference point for remote coordinate measurement is made for this purpose on condition that coordinates of both digital photogrammetric workstations are given, with the knowledge of the distance between the two workstations and the angles between optical axes of cameras and the base line connecting the workstations. A calibration method is presented. Applications of the results could be found in airport surface surveillance and runway incursion monitoring. Position data obtained in real time for aircraft and vehicles on the airport surface could be presented to an Advanced Surface Movement Guidance and Control System (A-SMGCS). [Copyright &y& Elsevier]

For calibrating the conceptual hydrological models (CHM), the traditional calibration method with a single objective cannot properly measure all the behaviors of the hydrological system. To obtain a successful parameters calibration, in this paper, we propose a multi-objective cultural self-adaptive electromagnetism-like mechanism (MOCSEM) algorithm, which is first implemented in solving the parameters calibration problem of CHM. In this algorithm, a self-adaptive parameter is applied in local search operation for adjusting the values of parameters dynamically. Meanwhile, cultural algorithm (CA) is adopted to keep a good diversity and uniformity of Pareto-optimal solutions (POS). MOCSEM is tested, firstly, by several benchmark test problems. After achieving satisfactory performance on the test problems, a case study is implemented for parameter calibration of a CHM by comparing the properties of POS obtained by the MOCSEM and other methods. Finally, when the optimization problem quickly becomes a decision-making problem because of the multiple objectives in CHM, fuzzy technique for order preference by similarity to an ideal solution method has been used to rank the POS and select the optimal scheme. The results show that the MOCSEM algorithm can provide high-accuracy parameters of CHM on various decision-making scenarios. [ABSTRACT FROM AUTHOR]

Since the drifts of Inertial Navigation System (INS) solutions are inevitable and also grow over time, a Doppler Velocity Log (DVL) is used to aid the INS to restrain its error growth. Therefore, INS/DVL integration is a common approach for Autonomous Underwater Vehicle (AUV) navigation. The parameters including the scale factor of DVL and misalignments between INS and DVL are key factors which limit the accuracy of the INS/DVL integration. In this paper, a novel parameter calibration method is proposed. An iterative implementation of the method is designed to reduce the error caused by INS initial alignment. Furthermore, a simplified INS/DVL integration scheme is employed. The proposed method is evaluated with both river trial and sea trial data sets. Using 0.03°/h(1σ) ring laser gyroscopes, 5 x 10-5 g(1σ) quartz accelerometers and DVL with accuracy 0.5% V ± 0.5 cm/s, INS/DVL integrated navigation can reach an accuracy of about 1‰ of distance travelled (CEP) in a river trial and 2‰ of distance travelled (CEP) in a sea trial. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a new method for selecting parameter values in elasto-plastic models for unsaturated soils under isotropic stress states. The proposed method is an improvement over more traditional calibration approaches as it explicitly takes into account experimental yielding behavior when defining the unsaturated normal compression surface. This is achieved by “enriching” measured yield stresses with corresponding values of specific volume (estimated from the observed elastic and virgin responses), which generates experimental points that can be interpolated together with virgin compression data. The proposed methodology is general and independent of the chosen mathematical forms of normal compression surface, elastic law and constitutive variables. The validity of the method is demonstrated by calibrating a reference model from a set of constant suction isotropic compression tests. Both improved and traditional calibration approaches are employed to select model parameter values which are then used to predict yield curves in the mean net stress–suction plane. Because of the incorporation of yielding data in the interpolation of the normal compression surface, the improved calibration method produces a more accurate prediction of yield stresses at different suctions compared with the standard method. Due to its generality and limited subjectivity, the proposed method provides an unbiased tool to compare strengths and weaknesses of different constitutive models. [Copyright &y& Elsevier]

This paper shows in detail the modelling of anisotropic polymeric foam under compression and tension loadings, including discussions on isotropic material models and the entire procedure to calibrate the parameters involved. First, specimens of poly(vinyl chloride) (PVC) foam were investigated through experimental analyses in order to understand the mechanical behavior of this anisotropic material. Then, isotropic material models available in the commercial software Abaqus™ were investigated in order to verify their ability to model anisotropic foams and how the parameters involved can influence the results. Due to anisotropy, it is possible to obtain different values for the same parameter in the calibration process. The obtained set of parameters are used to calibrate the model according to the application of the structure. The models investigated showed minor and major limitations to simulate the mechanical behavior of anisotropic PVC foams under compression, tension and multi-axial loadings. Results show that the calibration process and the choice of the material model applied to the polymeric foam can provide good quantitative results and save project time. Results also indicate what kind and order of error one will get if certain choices are made throughout the modelling process. Finally, even though the developed calibration procedure is applied to specific PVC foam, it still outlines a very broad drill to analyze other anisotropic cellular materials. [ABSTRACT FROM AUTHOR]

This article presents results concerning the local calibration of the transport parameters (longitudinal and transversal diffusions and decay coefficient) for a two-dimensional problem of water quality at Igapó I Lake, located in Londrina, Paraná, Brazil, using fecal coliforms as an indicator of water quality. The simulation of fecal coliforms concentrations all over the water body is conducted by means of a structured discretization of the geometry of Igapó I Lake, together with the finite difference and finite element methods. By using the velocity field, modeled by the Navier–Stokes and Poisson equations, the flow of fecal coliforms is described by means of a transport model, which considers advective and diffusive processes, as well as a process of fecal coliforms decay. In the checkpoint, the longitudinal and transversal diffusion coefficients and the coliforms decay coefficient that best fitted the value of the fecal coliforms concentration were D x = D y =0.001m2/h and k =0.5d−1 =0.02083h−1. A qualitative and quantitative analysis of the numerical simulations conducted in function of the diffusion coefficients and of the coliforms decay parameter provided a better understanding of the local water quality at Igapó I Lake. [Copyright &y& Elsevier]

In this paper, a novel macro traffic flow model is proposed integrating time delay and anticipation effect on the headway and velocity, which are indispensable factors in the course of driving. The stability condition of the novel model is derived by linear stability analysis method. The corresponding stability diagrams show that time delay deteriorates the stability of traffic flow, while anticipation effect is conducive to traffic flow stability. The existence and stability of Hopf bifurcations are discussed through bifurcation theory. Numerical results demonstrate that the improved continuum model presented can well describe the local cluster effect, fuel consumption and exhaust emissions. Considering the factor of anticipation and time delay has positive and negative impact on dynamic characteristic of macroscopic flow, respectively. In Hopf bifurcation simulation, partial data from Portable Emissions Measurement System (PeMS) is adopted to calibrate the parameters of the novel model. Meanwhile, the simulation results verify the existence of Hopf bifurcation. The occurrence of bifurcations brings a significant impact on the stability of traffic flow, in which the density wave of traffic flow arises equal-amplitude oscillations. • A novel macro traffic flow model considering time delay and anticipation is proposed. • The bifurcation analysis and nonlinear analysis for the novel proposed model is conducted. • The conditions and stability of the Hopf bifurcation for the modified model are proved. [ABSTRACT FROM AUTHOR]

Abstract: An improved particle swarm optimization (IPSO) is proposed in this paper. In the new algorithm, a population of points sampled randomly from the feasible space. Then the population is partitioned into several sub-swarms, each of which is made to evolve based on particle swarm optimization (PSO) algorithm. At periodic stages in the evolution, the entire population is shuffled, and then points are reassigned to sub-swarms to ensure information sharing. This method greatly elevates the ability of exploration and exploitation. Simulations for three benchmark test functions show that IPSO possesses better ability to find the global optimum than that of the standard PSO algorithm. Compared with PSO, IPSO is also applied to identify the hydrologic model. The results show that IPSO remarkably improves the calculation accuracy and is an effective global optimization to calibrate hydrologic model. [Copyright &y& Elsevier]

Abstract: Objective: To develop and validate a model of a clinical trial that evaluates the changes in cholesterol level as a surrogate marker for lipodystrophy in HIV subjects under alternative antiretroviral regimes, i.e., treatment with Protease Inhibitors vs. a combination of nevirapine and other antiretroviral drugs. Methods: Five simulation models were developed based on different assumptions, on treatment variability and pattern of cholesterol reduction over time. The last recorded cholesterol level, the difference from the baseline, the average difference from the baseline and level evolution, are the considered endpoints. Specific validation criteria based on a 10% minus or plus standardized distance in means and variances were used to compare the real and the simulated data. Results: The validity criterion was met by all models for considered endpoints. However, only two models met the validity criterion when all endpoints were considered. The model based on the assumption that within-subjects variability of cholesterol levels changes over time is the one that minimizes the validity criterion, standardized distance equal to or less than 1% minus or plus. Conclusion: Simulation is a useful technique for calibration, estimation, and evaluation of models, which allows us to relax the often overly restrictive assumptions regarding parameters required by analytical approaches. The validity criterion can also be used to select the preferred model for design optimization, until additional data are obtained allowing an external validation of the model. [Copyright &y& Elsevier]