The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The bas...The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.展开更多
Machine learning-based surrogate models have significant advantages in terms of computing efficiency. In this paper, we present a pilot study on fast calibration using machine learning techniques. Technology computer-...Machine learning-based surrogate models have significant advantages in terms of computing efficiency. In this paper, we present a pilot study on fast calibration using machine learning techniques. Technology computer-aided design(TCAD) is a powerful simulation tool for electronic devices. This simulation tool has been widely used in the research of radiation effects.However, calibration of TCAD models is time-consuming. In this study, we introduce a fast calibration approach for TCAD model calibration of metal–oxide–semiconductor field-effect transistors(MOSFETs). This approach utilized a machine learning-based surrogate model that was several orders of magnitude faster than the original TCAD simulation. The desired calibration results were obtained within several seconds. In this study, a fundamental model containing 26 parameters is introduced to represent the typical structure of a MOSFET. Classifications were developed to improve the efficiency of the training sample generation. Feature selection techniques were employed to identify important parameters. A surrogate model consisting of a classifier and a regressor was built. A calibration procedure based on the surrogate model was proposed and tested with three calibration goals. Our work demonstrates the feasibility of machine learning-based fast model calibrations for MOSFET. In addition, this study shows that these machine learning techniques learn patterns and correlations from data instead of employing domain expertise. This indicates that machine learning could be an alternative research approach to complement classical physics-based research.展开更多
Kinematic calibration is a reliable way to improve the accuracy of parallel manipulators, while the error model dramatically afects the accuracy, reliability, and stability of identifcation results. In this paper, a c...Kinematic calibration is a reliable way to improve the accuracy of parallel manipulators, while the error model dramatically afects the accuracy, reliability, and stability of identifcation results. In this paper, a comparison study on kinematic calibration for a 3-DOF parallel manipulator with three error models is presented to investigate the relative merits of diferent error modeling methods. The study takes into consideration the inverse-kinematic error model, which ignores all passive joint errors, the geometric-constraint error model, which is derived by special geometric constraints of the studied RPR-equivalent parallel manipulator, and the complete-minimal error model, which meets the complete, minimal, and continuous criteria. This comparison focuses on aspects such as modeling complexity, identifcation accuracy, the impact of noise uncertainty, and parameter identifability. To facilitate a more intuitive comparison, simulations are conducted to draw conclusions in certain aspects, including accuracy, the infuence of the S joint, identifcation with noises, and sensitivity indices. The simulations indicate that the complete-minimal error model exhibits the lowest residual values, and all error models demonstrate stability considering noises. Hereafter, an experiment is conducted on a prototype using a laser tracker, providing further insights into the diferences among the three error models. The results show that the residual errors of this machine tool are signifcantly improved according to the identifed parameters, and the complete-minimal error model can approach the measurements by nearly 90% compared to the inverse-kinematic error model. The fndings pertaining to the model process, complexity, and limitations are also instructive for other parallel manipulators.展开更多
Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SM...Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.展开更多
Concrete slabs are widely used in modern railways to increase the inherent resilient quality of the tracks,provide safe and smooth rides,and reduce the maintenance frequency.In this paper,the elastic performance of a ...Concrete slabs are widely used in modern railways to increase the inherent resilient quality of the tracks,provide safe and smooth rides,and reduce the maintenance frequency.In this paper,the elastic performance of a novel slab trackform for high-speed railways is investigated using three-dimensional finite element modelling in Abaqus.It is then compared to the performance of a ballasted track.First,slab and ballasted track models are developed to replicate the full-scale testing of track sections.Once the models are calibrated with the experimental results,the novel slab model is developed and compared against the calibrated slab track results.The slab and ballasted track models are then extended to create linear dynamic models,considering the track geodynamics,and simulating train passages at various speeds,for which the Ledsgard documented case was used to validate the models.Trains travelling at low and high speeds are analysed to investigate the track deflections and the wave propagation in the soil,considering the issues associated with critical speeds.Various train loading methods are discussed,and the most practical approach is retained and described.Moreover,correlations are made between the geotechnical parameters of modern high-speed rail and conventional standards.It is found that considering the same ground condition,the slab track deflections are considerably smaller than those of the ballasted track at high speeds,while they show similar behaviour at low speeds.展开更多
It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and a...It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and adaptation actions to adapt societies to Climate Change, to limit losses and damages [1] [2]. As far as adaptation actions are concerned, numerical simulation, due to its results, its costs which require less investment than tests carried out on complex mechanical structures, and its implementation facilities, appears to be a major step in the design and prediction of complex mechanical systems. However, despite the quality of the results obtained, biases and inaccuracies related to the structure of the models do exist. Therefore, there is a need to validate the results of this SARIMA-LSTM-digital learning model adjusted by a matching approach, “calculating-test”, in order to assess the quality of the results and the performance of the model. The methodology consists of exploiting two climatic databases (temperature and precipitation), one of which is in-situ and the other spatial, all derived from grid points. Data from the dot grids are processed and stored in specific formats and, through machine learning approaches, complex mathematical equations are worked out and interconnections within the climate system established. Through this mathematical approach, it is possible to predict the future climate of the Sudano-Sahelian zone of Cameroon and to propose adaptation strategies.展开更多
The objective of this paper is to develop a methodology for calibration of a discrete element grain-based model(GBM)to replicate the hydro-mechanical properties of a brittle rock measured in the laboratory,and to appl...The objective of this paper is to develop a methodology for calibration of a discrete element grain-based model(GBM)to replicate the hydro-mechanical properties of a brittle rock measured in the laboratory,and to apply the calibrated model to simulating the formation of excavation damage zone(EDZ)around underground excavations.Firstly,a new cohesive crack model is implemented into the universal distinct element code(UDEC)to control the fracturing behaviour of materials under various loading modes.Next,a methodology for calibration of the components of the UDEC-Voronoi model is discussed.The role of connectivity of induced microcracks on increasing the permeability of laboratory-scale samples is investigated.The calibrated samples are used to investigate the influence of pore fluid pressure on weakening the drained strength of the laboratory-scale rock.The validity of the Terzaghi’s effective stress law for the drained peak strength of low-porosity rock is tested by performing a series of biaxial compression test simulations.Finally,the evolution of damage and pore pressure around two unsupported circular tunnels in crystalline granitic rock is studied.展开更多
In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental ...In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental in some catchments）, we used non-continuous calibration periods for more independent streamflow data for SIMHYD （simple hydrology） model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization （PSO） method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.展开更多
Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model ba...Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver's hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.展开更多
Channel roughness is a sensitive parameter in development of hydraulic model for flood forecasting and flood inundation mapping. The requirement of multiple channel roughness coefficient Mannnig’s ‘n’ values along ...Channel roughness is a sensitive parameter in development of hydraulic model for flood forecasting and flood inundation mapping. The requirement of multiple channel roughness coefficient Mannnig’s ‘n’ values along the river has been spelled out through simulation of floods, using HEC-RAS, for years 1998 and 2003, supported with the photographs of river reaches collected during the field visit of the lower Tapi River. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year 2006 in the river. The performance of the calibrated HEC-RAS based model has been accessed by capturing the flood peaks of observed and simulated floods;and computation of root mean squared error (RMSE) for the intermediated gauging stations on the lower Tapi River.展开更多
Mathematical models of the quantity and quality of water in hydrographic basins enable simulation of a wide variety of processes, including the production of water and sediments, and the dynamics of point and nonpoint...Mathematical models of the quantity and quality of water in hydrographic basins enable simulation of a wide variety of processes, including the production of water and sediments, and the dynamics of point and nonpoint sources of pollution. These models have become increasingly complex, requiring large amounts of input data, which can increase the uncertainty of the results of simulations. For this reason, it is essential to perform calibration and validation procedures. The objective of this work was to conduct sensitivity analysis and calibration of a distributed hydrological model (SWAT) applied to the flows of water in the watershed of the Poxim River. Satisfactory performance of the model was indicated by the values obtained for the Nash-Sutcliffe efficiency coefficient (0.77), the percent bias (5.05), the root mean square error (0.48), and the ratio of the RMSE to the standard deviation of the observations (RSR) (0.49). The set of parameters identified here could be used for the simulation and evaluation of other scenarios.展开更多
The application of the Soil and Water Assessment Tool (SWAT) to the Olifants Basin in South Africa was the focus of our study with emphasis on calibration, validation and uncertainty analysis. The Basin was discretize...The application of the Soil and Water Assessment Tool (SWAT) to the Olifants Basin in South Africa was the focus of our study with emphasis on calibration, validation and uncertainty analysis. The Basin was discretized into 23 sub-basins and 226 Hydrologic Response Units (HRUs) using 3 arc second (90 m × 90 m) pixel resolution SRTM DEM with stream gauge B7H015 as the Basin outlet. Observed stream flow data at B7H015 were used for model calibration (1988-2001) and validation (2002-2013) using the split sample approach. Relative global sensitivity analysis using SUFI-2 algorithm was used to determine sensitive parameters to stream flow for calibration of the model. Performance efficiency of the Olifants SWAT model was assessed using Nash-Sutcliffe (NSE), coefficient of determination (R<sup>2</sup>), Percent Bias (PBIAS) and Root Mean Square Error-Observation Standard deviation Ratio (RSR). Sensitivity analysis revealed in decreasing order of significance, runoff curve number (CN2), alpha bank factor (ALPHA_BNK), soil evaporation compensation factor (ESCO), soil available water capacity (SOIL_AWC, mm H<sub>2</sub>O/mm soil), groundwater delay (GW_ DELAY, days) and groundwater “revap” coefficient (GW_REVAP) to be the most sensitive parameters to stream flow. Analysis of the model during the calibration period gave the following statistics;NSE = 0.88;R<sup>2</sup> = 0.89;PBIAS = -11.49%;RSR = 0.34. On the other hand, statistics during the validation period were NSE = 0.67;R<sup>2 </sup>= 0.79;PBIAS = -20.69%;RSR = 0.57. The observed statistics indicate the applicability of the SWAT model in simulating the hydrology of the Olifants Basin and therefore can be used as a Decision Support Tool (DST) by water managers and other relevant decisions making bodies to influence policy directions on the management of watershed processes especially water resources.展开更多
The paper describes an analysis of thermo-mechanical （TM） processes appearing during the Aspo Pillar Stability Experiment （APSE）. This analysis is based on finite elements with elasticity, plasticity and dam- age ...The paper describes an analysis of thermo-mechanical （TM） processes appearing during the Aspo Pillar Stability Experiment （APSE）. This analysis is based on finite elements with elasticity, plasticity and dam- age mechanics models of rock behaviour and some least squares calibration techniques. The main aim is to examine the capability of continuous mechanics models to predict brittle damage behaviour of gran- ite rocks. The performed simulations use an in-house finite element software GEM and self-developed experimental continuum damage MATLAB code. The main contributions are twofold. First, it is an inverse analysis, which is used for （1） verification of an initial stress measurement by back analysis of conver- gence measurement during construction of the access tunnel and （2） identification of heat transfer rock mass properties by an inverse method based on the known heat sources and temperature measurements. Second, three different hierarchically built models are used to estimate the pillar damage zones, i.e. elas- tic model with Drucker-Prager strength criterion, elasto-plastic model with the same yield limit and a combination of elasto-plasticity with continuum damage mechanics. The damage mechanics model is also used to simulate uniaxial and triaxial compressive strength tests on the ,Aspo granite.展开更多
In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single-or multi-objective functions when utilizing automatic calibration approaches.In most previous studies,...In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single-or multi-objective functions when utilizing automatic calibration approaches.In most previous studies, there is a general opinion that no single-objective function can represent all important characteristics of even one specific hydrological variable(e.g., streamflow).Thus hydrologists must turn to multi-objective calibration.In this study, we demonstrated that an optimized single-objective function can compromise multi-response modes(i.e., multi-objective functions) of the hydrograph, which is defined as summation of a power function of the absolute error between observed and simulated streamflow with the exponent of power function optimized for specific watersheds.The new objective function was applied to 196 model parameter estimation experiment(MOPEX) watersheds across the eastern United States using the semi-distributed Xinanjiang hydrological model.The optimized exponent value for each watershed was obtained by targeting four popular objective functions focusing on peak flows, low flows, water balance, and flashiness, respectively.Results showed that the optimized single-objective function can achieve a better hydrograph simulation compared to the traditional single-objective function Nash-Sutcliffe efficiency coefficient for most watersheds, and balance high flow part and low flow part of the hydrograph without substantial differences compared to multi-objective calibration.The proposed optimal single-objective function can be practically adopted in the hydrological modeling if the optimal exponent value could be determined a priori according to hydrological/climatic/landscape characteristics in a specific watershed.展开更多
The mechanical characteristics of crystalline rocks are affected by the heterogeneity of the spatial distribution of minerals.In this paper,a novel three-dimensional(3D)grain-based model(GBM)based on particle flow cod...The mechanical characteristics of crystalline rocks are affected by the heterogeneity of the spatial distribution of minerals.In this paper,a novel three-dimensional(3D)grain-based model(GBM)based on particle flow code(PFC),i.e.PFC3D-GBM,is proposed.This model can accomplish the grouping of mineral grains at the 3D scale and then filling them.Then,the effect of the position distribution,geometric size,and volume composite of mineral grains on the cracking behaviour and macroscopic properties of granite are examined by conducting Brazilian splitting tests.The numerical results show that when an external load is applied to a sample,force chains will form around each contact,and the orientation distribution of the force chains is uniform,which is independent of the external load level.Furthermore,the number of high-strength force chains is proportional to the external load level,and the main orientation distribution is consistent with the external loading direction.The main orientation of the cracks is vertical to that of the high-strength force chains.The geometric size of the mineral grains controls the mechanical behaviours.As the average grain size increases,the number of transgranular contacts with higher bonding strength in the region connecting both loading points increases.The number of high-strength force chains increases,leading to an increase in the stress concentration value required for the macroscopic failure of the sample.Due to the highest bonding strength,the generation of transgranular cracks in quartz requires a higher concentrated stress value.With increasing volume composition of quartz,the number of transgranular cracks in quartz distributed in the region connecting both loading points increases,which requires many high-strength force chains.The load level rises,leading to an increase in the tensile strength of the numerical sample.展开更多
This study aimed to investigate the effects of temporal variability on the optimization of the Hydrologiska ByrS.ns Vattenbalansavedlning （HBV） model, as well as the calibration performance using manual optimization...This study aimed to investigate the effects of temporal variability on the optimization of the Hydrologiska ByrS.ns Vattenbalansavedlning （HBV） model, as well as the calibration performance using manual optimization and average parameter values. By applying the HBV model to the Jiangwan Catchment, whose geological features include lots of cracks and gaps, simulations under various schemes were developed： short, medium-length, and long temporal calibrations. The results show that, with long temporal calibration, the objective function values of the Nash- Sutcliffe efficiency coefficient （NSE）, relative error （RE）, root mean square error （RMSE）, and high flow ratio generally deliver a preferable simulation. Although NSE and RMSE are relatively stable with different temporal scales, significant improvements to RE and the high flow ratio are seen with longer temporal calibration. It is also noted that use of average parameter values does not lead to better simulation results compared with manual optimization. With medium-length temporal calibration, manual optimization delivers the best simulation results, with NSE, RE, RMSE, and the high flow ratio being 0.563 6, 0.122 3, 0.978 8, and 0.854 7, respectively; and calibration using average parameter values delivers NSE, RE, RMSE, and the high flow ratio of 0.481 1, 0.467 6, 1.021 0, and 2.784 0, respectively. Similar behavior is found with long temporal calibration, when NSE, RE, RMSE, and the high flow ratio using manual optimization are 0.525 3, -0.069 2, 1.058 0, and 0.980 0, respectively, as compared with 0.490 3, 0.224 8, 1.096 2, and 0.547 9, respectively, using average parameter values. This study shows that selection of longer periods of temooral calibration in hvdrolouical analysis delivers better simulation in general for water balance analysis.展开更多
Maize is an emerging important crop in Bangladesh because of its high yield potential and economic profitability compared to rice and wheat crops. There is a need to understand the growth and yield behavior of this cr...Maize is an emerging important crop in Bangladesh because of its high yield potential and economic profitability compared to rice and wheat crops. There is a need to understand the growth and yield behavior of this crop in varying production environments of Bangladesh. Crop model such as Decision Support System For Agro-technology Transfer (DSSAT) version 4.6 (DSSAT hereafter) can be utilized cost effectively to study the performances of maize under different production environments. It needs to calibrate and validate DSSAT model for commonly cultivated maize cultivars in Bangladesh and subsequently take the model to various applications, including inputs and agronomic management options and climate change that impacts analyses. So, the present study was undertaken to firstly calibrate DSSAT model for popular four hybrid maize cultivars (BARI Hybrid Maize-7, BARI Hybrid Maize-9, Pioneer 30B07 and NK-40). Subsequently, it proceeded with the validation with independent field data sets for evaluating their growth performances. The genetic coefficients for these cultivars were evaluated by using Genotype coefficient calculator (GENCALC) and Generalized likelihood uncertainty estimation (GLUE) module of DSSAT on the basis of first season experiment. The performance of the model was satisfactory and within the significant limits. After calibration, the model was tested for its performance through validation procedure by using second season data. The model performed satisfactorily through phenology, biomass, leaf area index (LAI) and grain yield. Phenology, as estimated through days to flower initiation and maturity, was in good agreement, although simulated results were slightly over predicted compared to observed values but within the statistical significance limit...when compared with observed values at specific growth stages of the crop. The final yield values (10.12 to 10.59 t·ha-1) were in close agreement with the observed values (10.16 to 10.94 t·ha-1), as the percentage error was within tolerable limit (0.39% to 6.81%). The model has been successfully calibrated and validated for Gazipur environment and now can be used for climate change impact studies for similar environments in Bangladesh.展开更多
Channel roughness is the most sensitive parameter in development of hydraulic model for flood forecasting and flood plane mapping. Hence, in the present study it is attempted to calibrate the channel roughness coeffic...Channel roughness is the most sensitive parameter in development of hydraulic model for flood forecasting and flood plane mapping. Hence, in the present study it is attempted to calibrate the channel roughness coefficient (Manning’s “n” value) along the river Mahanadi, Odisha through simulation of floods using HEC-RAS. For calibration of Manning’s “n” value the flood of year 2003 has been considered. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year 2006 in the same river reach. The performance of the calibrated and validated HEC-RAS based model is tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that Mannnig’s “n” value of 0.032 gives best result for Khairmal to Munduli reach of Mahanadi River.展开更多
基金funded by the National Natural Science Foundation of China(Grant No.12272247)National Key Project(Grant No.GJXM92579)Major Research and Development Project of Metallurgical Corporation of China Ltd.in the Non-Steel Field(Grant No.2021-5).
文摘The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.
基金supported by the National Natural Science Foundation of China (Nos. 11690040 and 11690043)。
文摘Machine learning-based surrogate models have significant advantages in terms of computing efficiency. In this paper, we present a pilot study on fast calibration using machine learning techniques. Technology computer-aided design(TCAD) is a powerful simulation tool for electronic devices. This simulation tool has been widely used in the research of radiation effects.However, calibration of TCAD models is time-consuming. In this study, we introduce a fast calibration approach for TCAD model calibration of metal–oxide–semiconductor field-effect transistors(MOSFETs). This approach utilized a machine learning-based surrogate model that was several orders of magnitude faster than the original TCAD simulation. The desired calibration results were obtained within several seconds. In this study, a fundamental model containing 26 parameters is introduced to represent the typical structure of a MOSFET. Classifications were developed to improve the efficiency of the training sample generation. Feature selection techniques were employed to identify important parameters. A surrogate model consisting of a classifier and a regressor was built. A calibration procedure based on the surrogate model was proposed and tested with three calibration goals. Our work demonstrates the feasibility of machine learning-based fast model calibrations for MOSFET. In addition, this study shows that these machine learning techniques learn patterns and correlations from data instead of employing domain expertise. This indicates that machine learning could be an alternative research approach to complement classical physics-based research.
基金Supported by National Key Research and Development Program of China(Grant No.2019YFA0709001)National Natural Science Foundation of China(Grant Nos.52022056,51875334,52205031 and 52205034)National Key Research and Development Program of China(Grant No.2017YFE0111300).
文摘Kinematic calibration is a reliable way to improve the accuracy of parallel manipulators, while the error model dramatically afects the accuracy, reliability, and stability of identifcation results. In this paper, a comparison study on kinematic calibration for a 3-DOF parallel manipulator with three error models is presented to investigate the relative merits of diferent error modeling methods. The study takes into consideration the inverse-kinematic error model, which ignores all passive joint errors, the geometric-constraint error model, which is derived by special geometric constraints of the studied RPR-equivalent parallel manipulator, and the complete-minimal error model, which meets the complete, minimal, and continuous criteria. This comparison focuses on aspects such as modeling complexity, identifcation accuracy, the impact of noise uncertainty, and parameter identifability. To facilitate a more intuitive comparison, simulations are conducted to draw conclusions in certain aspects, including accuracy, the infuence of the S joint, identifcation with noises, and sensitivity indices. The simulations indicate that the complete-minimal error model exhibits the lowest residual values, and all error models demonstrate stability considering noises. Hereafter, an experiment is conducted on a prototype using a laser tracker, providing further insights into the diferences among the three error models. The results show that the residual errors of this machine tool are signifcantly improved according to the identifed parameters, and the complete-minimal error model can approach the measurements by nearly 90% compared to the inverse-kinematic error model. The fndings pertaining to the model process, complexity, and limitations are also instructive for other parallel manipulators.
基金supported by the National Natural Science Foundation of China(No.U2142206).
文摘Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.
基金Engineering and Physical Sciences Research Council (EPSRC) is also acknowledged for funding this work under Grant Number EP/N009207/1.
文摘Concrete slabs are widely used in modern railways to increase the inherent resilient quality of the tracks,provide safe and smooth rides,and reduce the maintenance frequency.In this paper,the elastic performance of a novel slab trackform for high-speed railways is investigated using three-dimensional finite element modelling in Abaqus.It is then compared to the performance of a ballasted track.First,slab and ballasted track models are developed to replicate the full-scale testing of track sections.Once the models are calibrated with the experimental results,the novel slab model is developed and compared against the calibrated slab track results.The slab and ballasted track models are then extended to create linear dynamic models,considering the track geodynamics,and simulating train passages at various speeds,for which the Ledsgard documented case was used to validate the models.Trains travelling at low and high speeds are analysed to investigate the track deflections and the wave propagation in the soil,considering the issues associated with critical speeds.Various train loading methods are discussed,and the most practical approach is retained and described.Moreover,correlations are made between the geotechnical parameters of modern high-speed rail and conventional standards.It is found that considering the same ground condition,the slab track deflections are considerably smaller than those of the ballasted track at high speeds,while they show similar behaviour at low speeds.
文摘It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and adaptation actions to adapt societies to Climate Change, to limit losses and damages [1] [2]. As far as adaptation actions are concerned, numerical simulation, due to its results, its costs which require less investment than tests carried out on complex mechanical structures, and its implementation facilities, appears to be a major step in the design and prediction of complex mechanical systems. However, despite the quality of the results obtained, biases and inaccuracies related to the structure of the models do exist. Therefore, there is a need to validate the results of this SARIMA-LSTM-digital learning model adjusted by a matching approach, “calculating-test”, in order to assess the quality of the results and the performance of the model. The methodology consists of exploiting two climatic databases (temperature and precipitation), one of which is in-situ and the other spatial, all derived from grid points. Data from the dot grids are processed and stored in specific formats and, through machine learning approaches, complex mathematical equations are worked out and interconnections within the climate system established. Through this mathematical approach, it is possible to predict the future climate of the Sudano-Sahelian zone of Cameroon and to propose adaptation strategies.
文摘The objective of this paper is to develop a methodology for calibration of a discrete element grain-based model(GBM)to replicate the hydro-mechanical properties of a brittle rock measured in the laboratory,and to apply the calibrated model to simulating the formation of excavation damage zone(EDZ)around underground excavations.Firstly,a new cohesive crack model is implemented into the universal distinct element code(UDEC)to control the fracturing behaviour of materials under various loading modes.Next,a methodology for calibration of the components of the UDEC-Voronoi model is discussed.The role of connectivity of induced microcracks on increasing the permeability of laboratory-scale samples is investigated.The calibrated samples are used to investigate the influence of pore fluid pressure on weakening the drained strength of the laboratory-scale rock.The validity of the Terzaghi’s effective stress law for the drained peak strength of low-porosity rock is tested by performing a series of biaxial compression test simulations.Finally,the evolution of damage and pore pressure around two unsupported circular tunnels in crystalline granitic rock is studied.
基金supported by the National Basic Research Program of China (the 973 Program,Grant No.2010CB951102)the National Supporting Plan Program of China (Grants No.2007BAB28B01 and 2008BAB42B03)the National Natural Science Foundation of China (Grant No. 50709042),and the Regional Water Theme in the Water for a Healthy Country Flagship
文摘In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental in some catchments）, we used non-continuous calibration periods for more independent streamflow data for SIMHYD （simple hydrology） model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization （PSO） method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.
基金Projects(51475254,51625503)supported by the National Natural Science Foundation of ChinaProject(MCM20150302)supported by the Joint Project of Tsinghua and China Mobile,ChinaProject supported by the joint Project of Tsinghua and Daimler Greater China Ltd.,Beijing,China
文摘Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver's hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.
文摘Channel roughness is a sensitive parameter in development of hydraulic model for flood forecasting and flood inundation mapping. The requirement of multiple channel roughness coefficient Mannnig’s ‘n’ values along the river has been spelled out through simulation of floods, using HEC-RAS, for years 1998 and 2003, supported with the photographs of river reaches collected during the field visit of the lower Tapi River. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year 2006 in the river. The performance of the calibrated HEC-RAS based model has been accessed by capturing the flood peaks of observed and simulated floods;and computation of root mean squared error (RMSE) for the intermediated gauging stations on the lower Tapi River.
文摘Mathematical models of the quantity and quality of water in hydrographic basins enable simulation of a wide variety of processes, including the production of water and sediments, and the dynamics of point and nonpoint sources of pollution. These models have become increasingly complex, requiring large amounts of input data, which can increase the uncertainty of the results of simulations. For this reason, it is essential to perform calibration and validation procedures. The objective of this work was to conduct sensitivity analysis and calibration of a distributed hydrological model (SWAT) applied to the flows of water in the watershed of the Poxim River. Satisfactory performance of the model was indicated by the values obtained for the Nash-Sutcliffe efficiency coefficient (0.77), the percent bias (5.05), the root mean square error (0.48), and the ratio of the RMSE to the standard deviation of the observations (RSR) (0.49). The set of parameters identified here could be used for the simulation and evaluation of other scenarios.
文摘The application of the Soil and Water Assessment Tool (SWAT) to the Olifants Basin in South Africa was the focus of our study with emphasis on calibration, validation and uncertainty analysis. The Basin was discretized into 23 sub-basins and 226 Hydrologic Response Units (HRUs) using 3 arc second (90 m × 90 m) pixel resolution SRTM DEM with stream gauge B7H015 as the Basin outlet. Observed stream flow data at B7H015 were used for model calibration (1988-2001) and validation (2002-2013) using the split sample approach. Relative global sensitivity analysis using SUFI-2 algorithm was used to determine sensitive parameters to stream flow for calibration of the model. Performance efficiency of the Olifants SWAT model was assessed using Nash-Sutcliffe (NSE), coefficient of determination (R<sup>2</sup>), Percent Bias (PBIAS) and Root Mean Square Error-Observation Standard deviation Ratio (RSR). Sensitivity analysis revealed in decreasing order of significance, runoff curve number (CN2), alpha bank factor (ALPHA_BNK), soil evaporation compensation factor (ESCO), soil available water capacity (SOIL_AWC, mm H<sub>2</sub>O/mm soil), groundwater delay (GW_ DELAY, days) and groundwater “revap” coefficient (GW_REVAP) to be the most sensitive parameters to stream flow. Analysis of the model during the calibration period gave the following statistics;NSE = 0.88;R<sup>2</sup> = 0.89;PBIAS = -11.49%;RSR = 0.34. On the other hand, statistics during the validation period were NSE = 0.67;R<sup>2 </sup>= 0.79;PBIAS = -20.69%;RSR = 0.57. The observed statistics indicate the applicability of the SWAT model in simulating the hydrology of the Olifants Basin and therefore can be used as a Decision Support Tool (DST) by water managers and other relevant decisions making bodies to influence policy directions on the management of watershed processes especially water resources.
基金the context of the international DECOVALEX Project (DEmonstration of COupled models and their VALidation against EXperiments)financed by Radioactive Waste Repository Authority (RAWRA),through Technical University of Liberec (TUL), Czech RepublicSKB through its sp Pillar Stability Experiment project
文摘The paper describes an analysis of thermo-mechanical （TM） processes appearing during the Aspo Pillar Stability Experiment （APSE）. This analysis is based on finite elements with elasticity, plasticity and dam- age mechanics models of rock behaviour and some least squares calibration techniques. The main aim is to examine the capability of continuous mechanics models to predict brittle damage behaviour of gran- ite rocks. The performed simulations use an in-house finite element software GEM and self-developed experimental continuum damage MATLAB code. The main contributions are twofold. First, it is an inverse analysis, which is used for （1） verification of an initial stress measurement by back analysis of conver- gence measurement during construction of the access tunnel and （2） identification of heat transfer rock mass properties by an inverse method based on the known heat sources and temperature measurements. Second, three different hierarchically built models are used to estimate the pillar damage zones, i.e. elas- tic model with Drucker-Prager strength criterion, elasto-plastic model with the same yield limit and a combination of elasto-plasticity with continuum damage mechanics. The damage mechanics model is also used to simulate uniaxial and triaxial compressive strength tests on the ,Aspo granite.
基金Under the auspices of National Key Research and Development Program of China(No.2016YFC0402701)National Natural Science Foundation of China(No.51825902)
文摘In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single-or multi-objective functions when utilizing automatic calibration approaches.In most previous studies, there is a general opinion that no single-objective function can represent all important characteristics of even one specific hydrological variable(e.g., streamflow).Thus hydrologists must turn to multi-objective calibration.In this study, we demonstrated that an optimized single-objective function can compromise multi-response modes(i.e., multi-objective functions) of the hydrograph, which is defined as summation of a power function of the absolute error between observed and simulated streamflow with the exponent of power function optimized for specific watersheds.The new objective function was applied to 196 model parameter estimation experiment(MOPEX) watersheds across the eastern United States using the semi-distributed Xinanjiang hydrological model.The optimized exponent value for each watershed was obtained by targeting four popular objective functions focusing on peak flows, low flows, water balance, and flashiness, respectively.Results showed that the optimized single-objective function can achieve a better hydrograph simulation compared to the traditional single-objective function Nash-Sutcliffe efficiency coefficient for most watersheds, and balance high flow part and low flow part of the hydrograph without substantial differences compared to multi-objective calibration.The proposed optimal single-objective function can be practically adopted in the hydrological modeling if the optimal exponent value could be determined a priori according to hydrological/climatic/landscape characteristics in a specific watershed.
基金the financial support of the National Natural Science Foundation of China(Grant No.52179118)the Graduate Innovation Program of China University of Mining and Technology(Grant No.2022WLKXJ032)the Postgraduate Research and Practice Innovation Program of Jiangsu Province,China(Grant No.KYCX22_2581).
文摘The mechanical characteristics of crystalline rocks are affected by the heterogeneity of the spatial distribution of minerals.In this paper,a novel three-dimensional(3D)grain-based model(GBM)based on particle flow code(PFC),i.e.PFC3D-GBM,is proposed.This model can accomplish the grouping of mineral grains at the 3D scale and then filling them.Then,the effect of the position distribution,geometric size,and volume composite of mineral grains on the cracking behaviour and macroscopic properties of granite are examined by conducting Brazilian splitting tests.The numerical results show that when an external load is applied to a sample,force chains will form around each contact,and the orientation distribution of the force chains is uniform,which is independent of the external load level.Furthermore,the number of high-strength force chains is proportional to the external load level,and the main orientation distribution is consistent with the external loading direction.The main orientation of the cracks is vertical to that of the high-strength force chains.The geometric size of the mineral grains controls the mechanical behaviours.As the average grain size increases,the number of transgranular contacts with higher bonding strength in the region connecting both loading points increases.The number of high-strength force chains increases,leading to an increase in the stress concentration value required for the macroscopic failure of the sample.Due to the highest bonding strength,the generation of transgranular cracks in quartz requires a higher concentrated stress value.With increasing volume composition of quartz,the number of transgranular cracks in quartz distributed in the region connecting both loading points increases,which requires many high-strength force chains.The load level rises,leading to an increase in the tensile strength of the numerical sample.
基金supported by the National Natural Science Foundation of China(Grant No.41271040)the Special Fund of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering(Grant No.20145028012)
文摘This study aimed to investigate the effects of temporal variability on the optimization of the Hydrologiska ByrS.ns Vattenbalansavedlning （HBV） model, as well as the calibration performance using manual optimization and average parameter values. By applying the HBV model to the Jiangwan Catchment, whose geological features include lots of cracks and gaps, simulations under various schemes were developed： short, medium-length, and long temporal calibrations. The results show that, with long temporal calibration, the objective function values of the Nash- Sutcliffe efficiency coefficient （NSE）, relative error （RE）, root mean square error （RMSE）, and high flow ratio generally deliver a preferable simulation. Although NSE and RMSE are relatively stable with different temporal scales, significant improvements to RE and the high flow ratio are seen with longer temporal calibration. It is also noted that use of average parameter values does not lead to better simulation results compared with manual optimization. With medium-length temporal calibration, manual optimization delivers the best simulation results, with NSE, RE, RMSE, and the high flow ratio being 0.563 6, 0.122 3, 0.978 8, and 0.854 7, respectively; and calibration using average parameter values delivers NSE, RE, RMSE, and the high flow ratio of 0.481 1, 0.467 6, 1.021 0, and 2.784 0, respectively. Similar behavior is found with long temporal calibration, when NSE, RE, RMSE, and the high flow ratio using manual optimization are 0.525 3, -0.069 2, 1.058 0, and 0.980 0, respectively, as compared with 0.490 3, 0.224 8, 1.096 2, and 0.547 9, respectively, using average parameter values. This study shows that selection of longer periods of temooral calibration in hvdrolouical analysis delivers better simulation in general for water balance analysis.
文摘Maize is an emerging important crop in Bangladesh because of its high yield potential and economic profitability compared to rice and wheat crops. There is a need to understand the growth and yield behavior of this crop in varying production environments of Bangladesh. Crop model such as Decision Support System For Agro-technology Transfer (DSSAT) version 4.6 (DSSAT hereafter) can be utilized cost effectively to study the performances of maize under different production environments. It needs to calibrate and validate DSSAT model for commonly cultivated maize cultivars in Bangladesh and subsequently take the model to various applications, including inputs and agronomic management options and climate change that impacts analyses. So, the present study was undertaken to firstly calibrate DSSAT model for popular four hybrid maize cultivars (BARI Hybrid Maize-7, BARI Hybrid Maize-9, Pioneer 30B07 and NK-40). Subsequently, it proceeded with the validation with independent field data sets for evaluating their growth performances. The genetic coefficients for these cultivars were evaluated by using Genotype coefficient calculator (GENCALC) and Generalized likelihood uncertainty estimation (GLUE) module of DSSAT on the basis of first season experiment. The performance of the model was satisfactory and within the significant limits. After calibration, the model was tested for its performance through validation procedure by using second season data. The model performed satisfactorily through phenology, biomass, leaf area index (LAI) and grain yield. Phenology, as estimated through days to flower initiation and maturity, was in good agreement, although simulated results were slightly over predicted compared to observed values but within the statistical significance limit...when compared with observed values at specific growth stages of the crop. The final yield values (10.12 to 10.59 t·ha-1) were in close agreement with the observed values (10.16 to 10.94 t·ha-1), as the percentage error was within tolerable limit (0.39% to 6.81%). The model has been successfully calibrated and validated for Gazipur environment and now can be used for climate change impact studies for similar environments in Bangladesh.
文摘Channel roughness is the most sensitive parameter in development of hydraulic model for flood forecasting and flood plane mapping. Hence, in the present study it is attempted to calibrate the channel roughness coefficient (Manning’s “n” value) along the river Mahanadi, Odisha through simulation of floods using HEC-RAS. For calibration of Manning’s “n” value the flood of year 2003 has been considered. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year 2006 in the same river reach. The performance of the calibrated and validated HEC-RAS based model is tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that Mannnig’s “n” value of 0.032 gives best result for Khairmal to Munduli reach of Mahanadi River.
