Статті в журналах з теми "Modeling and parametric calibration"
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1
Mauro, Francisco, Andrew T. Hudak, Patrick A. Fekety, Bryce Frank, Hailemariam Temesgen, David M. Bell, Matthew J. Gregory, and T. Ryan McCarley. "Regional Modeling of Forest Fuels and Structural Attributes Using Airborne Laser Scanning Data in Oregon." Remote Sensing 13, no. 2 (January 13, 2021): 261. http://dx.doi.org/10.3390/rs13020261.
Анотація:
Airborne laser scanning (ALS) acquisitions provide piecemeal coverage across the western US, as collections are organized by local managers of individual project areas. In this study, we analyze different factors that can contribute to developing a regional strategy to use information from completed ALS data acquisitions and develop maps of multiple forest attributes in new ALS project areas in a rapid manner. This study is located in Oregon, USA, and analyzes six forest structural attributes for differences between: (1) synthetic (i.e., not-calibrated), and calibrated predictions, (2) parametric linear and semiparametric models, and (3) models developed with predictors computed for point clouds enclosed in the areas where field measurements were taken, i.e., “point-cloud predictors”, and models developed using predictors extracted from pre-rasterized layers, i.e., “rasterized predictors”. Forest structural attributes under consideration are aboveground biomass, downed woody biomass, canopy bulk density, canopy height, canopy base height, and canopy fuel load. Results from our study indicate that semiparametric models perform better than parametric models if no calibration is performed. However, the effect of the calibration is substantial in reducing the bias of parametric models but minimal for the semiparametric models and, once calibrations are performed, differences between parametric and semiparametric models become negligible for all responses. In addition, minimal differences between models using point-cloud predictors and models using rasterized predictors were found. We conclude that the approach that applies semiparametric models and rasterized predictors, which represents the easiest workflow and leads to the most rapid results, is justified with little loss in accuracy or precision even if no calibration is performed.
2
Lucor, Didier, and Olivier P. Le Maître. "Cardiovascular Modeling With Adapted Parametric Inference." ESAIM: Proceedings and Surveys 62 (2018): 91–107. http://dx.doi.org/10.1051/proc/201862091.
Анотація:
Computational modeling of the cardiovascular system, promoted by the advance of fluid-structure interaction numerical methods, has made great progress towards the development of patient-specific numerical aids to diagnosis, risk prediction, intervention and clinical treatment. Nevertheless, the reliability of these models is inevitably impacted by rough modeling assumptions. A strong in-tegration of patient-specific data into numerical modeling is therefore needed in order to improve the accuracy of the predictions through the calibration of important physiological parameters. The Bayesian statistical framework to inverse problems is a powerful approach that relies on posterior sampling techniques, such as Markov chain Monte Carlo algorithms. The generation of samples re-quires many evaluations of the cardiovascular parameter-to-observable model. In practice, the use of a full cardiovascular numerical model is prohibitively expensive and a computational strategy based on approximations of the system response, or surrogate models, is needed to perform the data as-similation. As the support of the parameters distribution typically concentrates on a small fraction of the initial prior distribution, a worthy improvement consists in gradually adapting the surrogate model to minimize the approximation error for parameter values corresponding to high posterior den-sity. We introduce a novel numerical pathway to construct a series of polynomial surrogate models, by regression, using samples drawn from a sequence of distributions likely to converge to the posterior distribution. The approach yields substantial gains in efficiency and accuracy over direct prior-based surrogate models, as demonstrated via application to pulse wave velocities identification in a human lower limb arterial network.
3
Mishra, Manish. "Review on Analysis of Free Vibrational Horizontally Curved Bridges." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 31, 2021): 3463–69. http://dx.doi.org/10.22214/ijraset.2021.36682.
Анотація:
Curved I-girder concrete bridges give an outstanding answer to urban congestion, traffic, and pollution concerns, but the combined flexibility and torque responses of the bridges make their behavior exceedingly complex. That is why structural design parameters for simplified design procedures are in high demand, as measured by empirical equations. To analyze the effect on the free vibrational reaction of curve composite steel-concreteI-girder bridge with varying vibration parameters, this research employs a sensitivity analysis. To learn the fundamental frequency and the geometric configuration of the model forms, a parametric investigation is performed. Finite element Modelling of composite steel/concrete frameworks, deformable shear model, fine element formula, finite element mounting, finite element calibration, and finite element modeling, etc. Modeling finite element. Sensitivity research to draw the fundamental frequencies for the evaluated bridges. The parametric research outcomes. The results. Curved I-girder bridges of composite steel with single span or multi-span lengths are presented.
4
Rzehak, Roland, and Eckhard Krepper. "CFD for Subcooled Flow Boiling: Parametric Variations." Science and Technology of Nuclear Installations 2013 (2013): 1–22. http://dx.doi.org/10.1155/2013/687494.
Анотація:
We investigate the present capabilities of CFD for wall boiling. The computational model used combines the Euler/Euler two-phase flow description with heat flux partitioning. Very similar modeling was previously applied to boiling water under high pressure conditions relevant to nuclear power systems. Similar conditions in terms of the relevant nondimensional numbers have been realized in the DEBORA tests using dichlorodifluoromethane (R12) as the working fluid. This facilitated measurements of radial profiles for gas volume fraction, gas velocity, liquid temperature, and bubble size. Robust predictive capabilities of the modeling require that it is validated for a wide range of parameters. It is known that a careful calibration of correlations used in the wall boiling model is necessary to obtain agreement with the measured data. We here consider tests under a variety of conditions concerning liquid subcooling, flow rate, and heat flux. It is investigated to which extent a set of calibrated model parameters suffices to cover at least a certain parameter range.
5
Schepen, Andrew, Yvette Everingham, and Quan J. Wang. "On the Joint Calibration of Multivariate Seasonal Climate Forecasts from GCMs." Monthly Weather Review 148, no. 1 (January 1, 2020): 437–56. http://dx.doi.org/10.1175/mwr-d-19-0046.1.
Анотація:
Abstract Multivariate seasonal climate forecasts are increasingly required for quantitative modeling in support of natural resources management and agriculture. GCM forecasts typically require postprocessing to reduce biases and improve reliability; however, current seasonal postprocessing methods often ignore multivariate dependence. In low-dimensional settings, fully parametric methods may sufficiently model intervariable covariance. On the other hand, empirical ensemble reordering techniques can inject desired multivariate dependence in ensembles from template data after univariate postprocessing. To investigate the best approach for seasonal forecasting, this study develops and tests several strategies for calibrating seasonal GCM forecasts of rainfall, minimum temperature, and maximum temperature with intervariable dependence: 1) simultaneous calibration of multiple climate variables using the Bayesian joint probability modeling approach; 2) univariate BJP calibration coupled with an ensemble reordering method (the Schaake shuffle); and 3) transformation-based quantile mapping, which borrows intervariable dependence from the raw forecasts. Applied to Australian seasonal forecasts from the ECMWF System4 model, univariate calibration paired with empirical ensemble reordering performs best in terms of univariate and multivariate forecast verification metrics, including the energy and variogram scores. However, the performance of empirical ensemble reordering using the Schaake shuffle is influenced by the selection of historical data in constructing a dependence template. Direct multivariate calibration is the second-best method, with its far superior performance in in-sample testing vanishing in cross validation, likely because of insufficient data relative to the number of parameters. The continued development of multivariate forecast calibration methods will support the uptake of seasonal climate forecasts in complex application domains such as agriculture and hydrology.
6
Ghnatios, Chady, Khalil El Rai, Nicolas Hascoet, Pierre-Adrien Pires, Jean-Louis Duval, Jon Lambarri, Jean-Yves Hascoet, and Francisco Chinesta. "Reduced order modeling of selective laser melting: from calibration to parametric part distortion." International Journal of Material Forming 14, no. 5 (March 31, 2021): 973–86. http://dx.doi.org/10.1007/s12289-021-01613-z.
Анотація:
AbstractAdditive manufacturing is an appealing solution to produce geometrically complex parts, difficult to manufacture using traditional technologies. The extreme process conditions, in particular the high temperature, complex interactions and couplings, and rich metallurgical transformations that this process entails, are at the origin of numerous process defects. Therefore, the numerical simulation of the process is gaining the interest of both the scientific and the industrial communities. However, simulating that process demands impressive computational resources, limiting high resolution simulations to the microscopic and mesoscopic scales. This paper proposes a thermo-mechanical modeling framework at the process scale as well as its associated reduced order simulation counterpart, enabling the parametric evaluation of the part distortion. It deeply addresses the process calibration using a high-resolution computational procedure based on the use of an in-plane-out-of-plane separated representation at the heart of the so-called Proper Generalized Decomposition (PGD), as well as the analysis of the transient thermal effects, defining the conditions in which the thermal and mechanical analyses can be decoupled.
7
Chen, Hua-Zhou, Kai Shi, Ken Cai, Li-Li Xu, and Quan-Xi Feng. "Investigation of sample partitioning in quantitative near-infrared analysis of soil organic carbon based on parametric LS-SVR modeling." RSC Advances 5, no. 98 (2015): 80612–19. http://dx.doi.org/10.1039/c5ra12468a.
Анотація:
A framework for sample partitioning is proposed to take into account the tunable ratio of numbers of calibration and prediction samples, in consideration with the randomness, stability and robustness of calibration models.
8
Mang, Andreas, Spyridon Bakas, Shashank Subramanian, Christos Davatzikos, and George Biros. "Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology." Annual Review of Biomedical Engineering 22, no. 1 (June 4, 2020): 309–41. http://dx.doi.org/10.1146/annurev-bioeng-062117-121105.
Анотація:
Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI) and the inverse problem of calibrating biophysical models to mpMRI data, assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved ( a) detection/segmentation of tumor subregions and ( b) computer-aided diagnostic/prognostic/predictive modeling. This article presents a summary of ( a) biophysical growth modeling and simulation,( b) inverse problems for model calibration, ( c) these models' integration with imaging workflows, and ( d) their application to clinically relevant studies. We anticipate that such quantitative integrative analysis may even be beneficial in a future revision of the World Health Organization (WHO) classification for CNS tumors, ultimately improving patient survival prospects.
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Ghnatios, Chady, Khalil El Rai, Nicolas Hascoet, Pierre-Adrien Pires, Jean-Louis Duval, Jon Lambarri, Jean-Yves Hascoet, and Francisco Chinesta. "Correction to: reduced order modeling of selective laser melting: from calibration to parametric part distortion." International Journal of Material Forming 14, no. 5 (August 4, 2021): 987. http://dx.doi.org/10.1007/s12289-021-01638-4.
10
Sheng, J., S.-Y. Yang, and W. Tong. "Implicitization of the Vegter Yield Criterion." IOP Conference Series: Materials Science and Engineering 1238, no. 1 (May 1, 2022): 012007. http://dx.doi.org/10.1088/1757-899x/1238/1/012007.
Анотація:
Abstract An advanced yield criterion plays a central role in rate-independent plasticity modeling of sheet metals in automotive and other industrial applications. Different from many non-quadratic yield criteria based on implicit polynomials, Vegter yield criterion is piecewise and quadratic as it is originally constructed by interpolation of several biaxial stress states using multiple second-order Bézier curves. Additional efforts in recent years have made Vetger yield criterion more user-friendly, flexible and robust for sheet metal forming applications. Nevertheless, Vetger yield criterion has only been presented in its parametric formulation in the literature. This work describes a method of reformulating the existing Vetger Lite yield criterion into the implicit form that is more commonly used in the conventional sheet metal plasticity modeling. The potential benefits of using both the original parametric and the new implicit forms of Vegter yield criterion for material parameter calibration, convexity certification, and computational simulations are discussed.
11
Sapkota, Madhu Sudan, Edward Apeh, Mark Hadfield, Roya Haratian, Robert Adey, and John Baynham. "Surrogate-assisted parametric calibration using design of experiment platform within digital twinning." International Journal of Computational Methods and Experimental Measurements 10, no. 2 (May 17, 2022): 158–71. http://dx.doi.org/10.2495/cmem-v10-n2-158-171.
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Loridan, T., S. Khare, E. Scherer, M. Dixon, and E. Bellone. "Parametric Modeling of Transitioning Cyclone Wind Fields for Risk Assessment Studies in the Western North Pacific." Journal of Applied Meteorology and Climatology 54, no. 3 (March 2015): 624–42. http://dx.doi.org/10.1175/jamc-d-14-0095.1.
Анотація:
AbstractProbabilistic risk assessment systems for tropical cyclone hazards rely on large ensembles of model simulations to characterize cyclones tracks, intensities, and the extent of the associated damaging winds. Given the computational costs, the wind field is often modeled using parametric formulations that make assumptions that are based on observations of tropical systems (e.g., satellite, or aircraft reconnaissance). In particular, for the Northern Hemisphere, most of the damaging contribution is assumed to be from the right of the moving cyclone, with the left-hand-side winds being much weaker because of the direction of storm motion. Recent studies have highlighted that this asymmetry assumption does not hold for cyclones undergoing extratropical transitions around Japan. Transitioning systems can exhibit damaging winds on both sides of the moving cyclone, with wind fields often characterized as resembling a horseshoe. This study develops a new parametric formulation of the extratropical transition phase for application in risk assessment systems. A compromise is sought between the need to characterize the horseshoe shape while keeping the formulation simple to allow for implementation within a risk assessment framework. For that purpose the tropical wind model developed by Willoughby et al. is selected as a starting point and parametric bias correction fields are applied to build the target shape. Model calibration is performed against a set of 37 extratropical transition cases simulated using the Weather Research and Forecasting Model. This newly developed parametric model of the extratropical transition phase shows an ability to reproduce wind field features observed in the western North Pacific Ocean while using only a restricted number of input parameters.
13
Lee, T. S., S. H. Advani, and J. K. Lee. "Three-Dimensional Modeling of Hydraulic Fractures in Layered Media: Part II—Calibrations, Parametric Sensitivity and Field Simulations." Journal of Energy Resources Technology 112, no. 1 (March 1, 1990): 10–19. http://dx.doi.org/10.1115/1.2905705.
Анотація:
A comprehensive finite element model formulation for the simulation of vertical hydraulic fracture propagation in a multi-layered reservoir has been presented in Part I of the companion paper (Advani et al., 1990). This paper presents a numerical calibration of this model by comparing results with selected benchmark cases. Parametric sensitivity investigations are also performed to illustrate the role of different variables on hydraulic fracture configuration evolution in multi-layered formations. In addition, field simulations for a multi-layered reservoir with differential in-situ stress and mechanical property contrasts are conducted to illustrate the scope of the developed model.
14
Vermiglio, Simona, Victor Champaney, Abel Sancarlos, Fatima Daim, Jean Claude Kedzia, Jean Louis Duval, Pedro Diez, and Francisco Chinesta. "Parametric Electromagnetic Analysis of Radar-Based Advanced Driver Assistant Systems." Sensors 20, no. 19 (October 5, 2020): 5686. http://dx.doi.org/10.3390/s20195686.
Анотація:
Efficient and optimal design of radar-based Advanced Driver Assistant Systems (ADAS) needs the evaluation of many different electromagnetic solutions for evaluating the impact of the radome on the electromagnetic wave propagation. Because of the very high frequency at which these devices operate, with the associated extremely small wavelength, very fine meshes are needed to accurately discretize the electromagnetic equations. Thus, the computational cost of each numerical solution for a given choice of the design or operation parameters, is high (CPU time consuming and needing significant computational resources) compromising the efficiency of standard optimization algorithms. In order to alleviate the just referred difficulties the present paper proposes an approach based on the use of reduced order modeling, in particular the construction of a parametric solution by employing a non-intrusive formulation of the Proper Generalized Decomposition, combined with a powerful phase-angle unwrapping strategy for accurately addressing the electric and magnetic fields interpolation, contributing to improve the design, the calibration and the operational use of those systems.
15
Duma, Virgil-Florin, Cosmin Sinescu, Adrian Bradu, and Adrian Podoleanu. "Optical Coherence Tomography Investigations and Modeling of the Sintering of Ceramic Crowns." Materials 12, no. 6 (March 21, 2019): 947. http://dx.doi.org/10.3390/ma12060947.
Анотація:
Dental prostheses are sintered in ovens that sometimes suffer from a loss of calibration. This can lead to variations of the sintering temperature outside the range recommended by the manufacturer. Stress and even fractures in dental ceramics may occur, and this leads to the necessity to rebuild the dental construct. The aim of this work is to monitor the quality of sintering processes using an established biomedical imaging technique—optical coherence tomography (OCT). Conventional current procedures imply the fabrication of supplemental samples that add to the expenses and are only evaluated visually. To our knowledge, we were the first to propose the use of OCT, a non-destructive method that brings objectivity for such assessments, focusing, in a previous study, on metal ceramic dental prostheses. Here, a different material, pressed ceramics, is considered, while we propose a quantitative assessment of the results—using reflectivity profiles of en-face (i.e., constant-depth) OCT images of sintered samples. The results for both the pressed ceramics and metal ceramics prostheses are discussed by obtaining the analytic functions of their reflectivity profiles. A multi-parametric analysis demonstrates the best parameter to characterize the loss of calibration of dental ovens. Rules-of-thumb are extracted; producing dental prostheses with defects can thus be avoided.
16
Zhao, Yi, Zhuotong Nan, Wenjun Yu, and Ling Zhang. "Calibrating a Hydrological Model by Stratifying Frozen Ground Types and Seasons in a Cold Alpine Basin." Water 11, no. 5 (May 10, 2019): 985. http://dx.doi.org/10.3390/w11050985.
Анотація:
Frozen ground and precipitation seasonality may strongly affect hydrological processes in a cold alpine basin, but the calibration of a hydrological model rarely considers their impacts on model parameters, likely leading to considerable simulation biases. In this study, we conducted a case study in a typical alpine catchment, the Babao River basin, in Northwest China, using the distributed hydrology–soil–vegetation model (DHSVM), to investigate the impacts of frozen ground type and precipitation seasonality on model parameters. The sensitivity analysis identified seven sensitive parameters in the DHSVM, amid which soil model parameters are found sensitive to the frozen ground type and land cover/vegetation parameters sensitive to dry and wet seasons. A stratified calibration approach that considers the impacts on model parameters of frozen soil types and seasons was then proposed and implemented by the particle swarm optimization method. The results show that the proposed calibration approach can obviously improve simulation accuracy in modeling streamflow in the study basin. The seasonally stratified calibration has an advantage in controlling evapotranspiration and surface flow in rainy periods, while the spatially stratified calibration considering frozen soil type enhances the simulation of base flow. In a typical cold alpine area without sufficient measured parametric values, this approach can outperform conventional calibration approaches in providing more robust parameter values. The underestimation in the April streamflow also highlights the importance of improved physics in a hydrological model, without which the model calibration cannot fully compensate the gap.
17
McIntyre, Neil, Howard Wheater, and Matthew Lees. "Estimation and propagation of parametric uncertainty in environmental models." Journal of Hydroinformatics 4, no. 3 (July 1, 2002): 177–98. http://dx.doi.org/10.2166/hydro.2002.0018.
Анотація:
It is proposed that a numerical environmental model cannot be justified for predictive tasks without an implicit uncertainty analysis which uses reliable and transparent methods. Various methods of uncertainty-based model calibration are reviewed and demonstrated. Monte Carlo simulation of data, Generalised Likelihood Uncertainty Estimation (GLUE), the Metropolis algorithm and a set-based approach are compared using the Streeter–Phelps model of dissolved oxygen in a stream. Using idealised data, the first three of these calibration methods are shown to converge the parameter distributions to the same end result. However, in practice, when the properties of the data and model structural errors are less well defined, GLUE and the set-based approach are proposed as more versatile for the robust estimation of parametric uncertainty. Methods of propagation of parametric uncertainty are also reviewed. Rosenblueth's two-point method, first-order variance propagation, Monte Carlo sampling and set theory are applied to the Streeter–Phelps example. The methods are then shown to be equally successful in application to the example, and their relative merits for more complex modelling problems are discussed.
18
Cuamatzi-Meléndez, Ruben. "Parametric Modelling of Rousselier ́s Damage Model Parameters with Instrumented Charpy Tests." Advanced Engineering Forum 50 (September 6, 2023): 39–58. http://dx.doi.org/10.4028/p-6dqbxn.
Анотація:
This work presents Rousselier´s damage model parameters effect and their physical meaning on Charpy fracture propagation curves. Therefore, instrumented Charpy tests were performed at room test temperature to measure the load-displacement curve. The parameters were measured from a Grade A ship plate steel, employed for the construction of merchant ships. The effect of Rousselier´s model parameter was done by performing cellular automata finite element (CAFE) modelling, where Rousselier’s damage model was coded, and therefore Rousselier´s model parameters were incorporated using random number generators in the ductile arrays of cells, using Weibull distributions. Consequently, in each CAFE simulation, the model evaluates random values of Rousselier´s damage model parameters performing a more physically based modelling. The results showed that the present CAFE modelling was able to reproduce the hardening and fracture propagation regions of instrumented Charpy data. Furthermore, the present work showed a suitable Rousselier´s damage model parameters calibration procedure with Charpy data, and how each Rousselier´s model parameter can affect the hardening and fracture propagations regions when they are not properly calibrated, producing unrealistic results. Additionally, it can be observed that the present results can be used as a template for a better calibration of Rousselier´s damage model parameters in CAFE modelling.
19
NUSA SETIAWAN PASARIBU, SAPTA. "THE EFFECT OF JOB PROMOTION, WORK DISCIPLINE, ORGANIZATIONAL CULTURE ON WORK PERFORMANCE IN THE REGIONAL REVENUE AGENCY (BAPENDA) IN KEPRI PROVINCE THROUGH JOB SATISFACTION AS INTERVENING VARIABLE." International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) 1, no. 12 (November 19, 2022): 725–36. http://dx.doi.org/10.54443/ijset.v1i12.78.
Анотація:
Promotion of Position, Work Discipline, Organizational Culture, Job Satisfaction, and Work Performance were variables in this study. SEM-PLS is used to analyze data using both parametric and non-parametric statistics (Structural Equation Modeling-Partial Least Square) Research variable data analysis using both parametric and non-parametric statistics, calibration and pilot tests, validity and reliability, analysis of the outer and inner models, and discussion of the findings of hypothesis testing or Path Analysis Path. In this study, route analysis is used to look at the distribution of relationships that show the direct and indirect effects of a variable or collection of variables on other variables. SmartPLS Ver 3.2.9 2022 assists in this study's path coefficient calculation.The findings of this study suggest that Work Performance is positively and negligibly impacted by Job Promotion and Work Discipline. Job Satisfaction Has A Positive And Significant Influence On Work Performance, Job Promotion Has A Positive And Significant Influence On Work Performance, Work Discipline Has A Positive And Significant Influence On Work Performance, Organizational Culture Has A Significant Positive Influence On Employee Work Performance, Job Satisfaction Has A Positive And Significant Influence On Interv Moderating the Impact of Organizational Culture on the Work Performance of the Riau Islands Province's Regional Revenue Agency (Bapenda).
20
Cledat, E., D. A. Cucci, and J. Skaloud. "CAMERA CALIBRATION MODELS AND METHODS FOR CORRIDOR MAPPING WITH UAVS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2020 (August 3, 2020): 231–38. http://dx.doi.org/10.5194/isprs-annals-v-1-2020-231-2020.
Анотація:
Abstract. Camera calibration refers to the modeling of the relationship between the coordinates of object points and their projections on the image plane. This is usually done by parametric models that describe the physical properties of the lens systems and camera assemblies, such as the camera principal distance, the principal point, and various types of optical distortions. In photogrammetry, accurate knowledge of the parameters of such models, often referred to as Interior Orientation (IO), is of ultimate importance. In this work, we target advanced corridor mapping applications with UAVs. In this scenario, the camera calibration is not completely observable due to the unfavorable geometry of the flight trajectory (e.g., no cross flight lines available and a single altitude) and needs to be determined beforehand. Further challenges are introduced by the limited mechanical stability of UAV-grade cameras. This may cause slight variations in the IO that need to be recovered while processing production flights. We review and compare two well known camera models, the Brown-Conrady and the Ebner’s self-calibration functions, in 36 calibration setups and provide a discussion of the results, where sub ground sampling distance accuracy in the checkpoints was achieved for some, but not all, configurations.
21
Lowe, Samuel, Daniel G. Partridge, David Topping, and Philip Stier. "Inverse modelling of Köhler theory – Part 1: A response surface analysis of CCN spectra with respect to surface-active organic species." Atmospheric Chemistry and Physics 16, no. 17 (September 6, 2016): 10941–63. http://dx.doi.org/10.5194/acp-16-10941-2016.
Анотація:
Abstract. In this study a novel framework for inverse modelling of cloud condensation nuclei (CCN) spectra is developed using Köhler theory. The framework is established by using model-generated synthetic measurements as calibration data for a parametric sensitivity analysis. Assessment of the relative importance of aerosol physicochemical parameters, while accounting for bulk–surface partitioning of surface-active organic species, is carried out over a range of atmospherically relevant supersaturations. By introducing an objective function that provides a scalar metric for diagnosing the deviation of modelled CCN concentrations from synthetic observations, objective function response surfaces are presented as a function of model input parameters. Crucially, for the chosen calibration data, aerosol–CCN spectrum closure is confirmed as a well-posed inverse modelling exercise for a subset of the parameters explored herein. The response surface analysis indicates that the appointment of appropriate calibration data is particularly important. To perform an inverse aerosol–CCN closure analysis and constrain parametric uncertainties, it is shown that a high-resolution CCN spectrum definition of the calibration data is required where single-valued definitions may be expected to fail. Using Köhler theory to model CCN concentrations requires knowledge of many physicochemical parameters, some of which are difficult to measure in situ on the scale of interest and introduce a considerable amount of parametric uncertainty to model predictions. For all partitioning schemes and environments modelled, model output showed significant sensitivity to perturbations in aerosol log-normal parameters describing the accumulation mode, surface tension, organic : inorganic mass ratio, insoluble fraction, and solution ideality. Many response surfaces pertaining to these parameters contain well-defined minima and are therefore good candidates for calibration using a Monte Carlo Markov Chain (MCMC) approach to constraining parametric uncertainties.A complete treatment of bulk–surface partitioning is shown to predict CCN spectra similar to those calculated using classical Köhler theory with the surface tension of a pure water drop, as found in previous studies. In addition, model sensitivity to perturbations in the partitioning parameters was found to be negligible. As a result, this study supports previously held recommendations that complex surfactant effects might be neglected, and the continued use of classical Köhler theory in global climate models (GCMs) is recommended to avoid an additional computational burden. The framework developed is suitable for application to many additional composition-dependent processes that might impact CCN activation potential. However, the focus of this study is to demonstrate the efficacy of the applied sensitivity analysis to identify important parameters in those processes and will be extended to facilitate a global sensitivity analysis and inverse aerosol–CCN closure analysis.
22
Hong, Huajie, Xiaoyao Zhou, Zhiyong Zhang, and Dapeng Fan. "Modeling and calibration of pointing errors using a semi-parametric regression method with applications in inertially stabilized platforms." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 227, no. 10 (August 16, 2013): 1492–503. http://dx.doi.org/10.1177/0954405413475559.
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Misir, Ibrahim Serkan, and Gokhan Yucel. "Numerical Model Calibration and a Parametric Study Based on the Out-Of-Plane Drift Capacity of Stone Masonry Walls." Buildings 13, no. 2 (February 4, 2023): 437. http://dx.doi.org/10.3390/buildings13020437.
Анотація:
Failure under seismic action generally occurs in the form of out-of-plane collapses of walls before reaching their in-plane strength in historical stone masonry buildings. Consistent finite element (FE) macro modeling has emerged as a need for use in seismic assessments of these walls. This paper presents the numerical model calibration of U-shaped multi-leaf stone masonry wall specimens tested under ambient vibrations and out-of-plane (OOP) load reversals. The uncertain elastic parameters were obtained by manual calibration of the numerical models based on ambient vibration test (AVT) data of the specimens. To obtain nonlinear calibration parameters, static pushover analyses were performed on FE models simulating quasi-static tests. The calibrated numerical models matched well with the experimental results in terms of load–drift response and damage distribution. As a result, the modulus of elasticity and tensile and compressive degrading strength parameters of masonry walls were proposed. A parametric study was conducted to examine the effects of different materials and geometric properties (tensile strength, aspect ratio, slenderness ratio, and geometric scale) on the OOP behavior of stone masonry walls. A quite different strain distribution was obtained in the case of a large aspect ratio, while it was determined that the geometric scale had no effect on the strain distribution. Tensile strength was the dominant parameter affecting the load–drift response of the models. Within the presented work, a practical tool for out-of-plane seismic assessment has been proposed for the structures covered in this paper.
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Nandan, Rohit, Varaprasad Bandaru, Jiaying He, Craig Daughtry, Prasanna Gowda, and Andrew E. Suyker. "Evaluating Optical Remote Sensing Methods for Estimating Leaf Area Index for Corn and Soybean." Remote Sensing 14, no. 21 (October 23, 2022): 5301. http://dx.doi.org/10.3390/rs14215301.
Анотація:
The leaf area index (LAI) is a key crop biophysical variable influencing many vegetation processes. Spatial LAI estimates are essential to develop and improve spatial modeling tools to monitor vegetation conditions at large regional scales. Numerous optical remote sensing methods have been explored to retrieve crop-specific LAI at a regional scale using satellite observations. However, a major challenge is selecting a method that performance well under various conditions without local scale calibration. As such, we assessed the performance of existing statistical and physical approaches, developed based on parametric, non-parametric and radiative transfer model (RTM)-look-up-table based inversion, using field observations from two geographically distant locations and Landsat 5, 7, and 8 satellite observations. These methods were implemented for corn and soybeans cultivated at two locations in the U.S (i.e., Mead, Nebraska, and Bushland, Texas). The evaluation metrics (i.e., Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R2)) were used to study the performance of each method, and then the methods were ranked based on these metrics. Our study showed that overall parametric methods outperformed other methods. The RMSE (MAE) for the top five methods was less than 1.3 (0.95) for corn and 1.0 (0.8) for soybeans, irrespective of location. Even though they outperformed, parametric methods exhibited inconsistency in their performance. For instance, the SR_CA_cross method ranked 1 for corn, however, it performed poorly for soybean (ranked 15). The non-parametric methods showed moderate accuracy partly due to the availability of a smaller number of observations for training. The RTM-LUT inversion physical-based approach was found to perform reasonably well RMSE (MAE) less than 1.5 (1.0) consistently irrespective of location and crop, implying that this approach is more suitable for regional-scale LAI estimation. The results of this study highlighted the drawbacks and advantages of available optical remote sensing approaches to estimate LAI for corn and soybean crops using Landsat imagery. These results are of interest for remote sensing and modeling communities developing spatial-scale approaches to model and monitor agricultural vegetation.
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Skafida, S., L. Koutas, and S. N. Bousias. "Analytical Modeling of Masonry Infilled RC Frames and Verification with Experimental Data." Journal of Structures 2014 (April 22, 2014): 1–17. http://dx.doi.org/10.1155/2014/216549.
Анотація:
The assessment of the response of masonry infilled RC frame structures has been a major challenge over the last decades. While several modeling approaches have been proposed, none can cover all aspects observed in the tests. The present paper introduces a simplified model built on the approach established by Crisafulli and Carr (2007) and addresses its calibration and implementation in a nonlinear analysis software for the evaluation of the in-plane lateral response of infilled RC frames. The proposed model uses a set of elements/springs to account separately for the compressive and shear behavior of masonry. The efficiency of the modeling approach is validated with available experimental data, yielding satisfactory matching. The most intricate issue encountered when attempting to represent a masonry panel is the plethora of the material parameters involved and the lack of complete and available test results. Thus, the numerical investigation is accompanied by a parametric study on the sensitivity of the model to the various parameters to identify the critical modeling quantities and provide guidance on their selection.
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Xie, Shao-Ming. "COMPARATIVE MODELS IN CUSTOMER BASE ANALYSIS: PARAMETRIC MODEL AND OBSERVATION-DRIVEN MODEL." Journal of Business Economics and Management 21, no. 6 (October 19, 2020): 1731–51. http://dx.doi.org/10.3846/jbem.2020.13194.
Анотація:
This study conducts a dynamic rolling comparison between the Pareto/NBD model (parametric model) and machine learning algorithms (observation-driven models) in customer base analysis, which the literature has not comprehensively investigated before. The aim is to find the comparative edge of these two approaches under customer base analysis and to define the implementation timing of these two paradigms. This research utilizes Pareto/NBD (Abe) as representative of Buy-Till-You-Die (BTYD) models in order to compete with machine learning algorithms and presents the following results. (1) The parametric model wins in transaction frequency prediction, whereas it loses in inactivity prediction. (2) The BTYD model outperforms machine learning in inactivity prediction when the customer base is active, performs better in an inactive customer base when competing with Poisson regression, and wins in a short-term active customer base when competing with a neural network algorithm in transaction frequency prediction. (3) The parametric model benefits more from a short calibration length and a long holdout/target period, which exhibit uncertainty. (4) The covariate effect helps Pareto/NBD (Abe) gain a better predictive result. These findings assist in defining the comparative edge and implementation timing of these two approaches and are useful for modeling and business decision making.
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Issa, Hayder M. "Parametric and Nonparametric Approaches of Reid Vapor Pressure Prediction for Gasoline Containing Oxygenates: A Comparative Analysis Using Partial Least Squares, Nonlinear, and LOWESS Regression Modelling Strategies with Physical Properties." Modelling and Simulation in Engineering 2024 (March 11, 2024): 1–15. http://dx.doi.org/10.1155/2024/8442457.
Анотація:
This study provides insights into the challenges involved in predicting the Reid vapor pressure (RVP) of gasoline-oxygenate blends (GOB), which is an important indicator of fuel quality and compliance with environmental and performance standards. Given the enormous variety of gasoline compositions and ratios available, there is a significant demand for a fast, straightforward, and cost-effective technique to predict RVP without relying on costly instruments or complicated spectral measurements that involve numerous input variables. A comparative performance analysis has been performed for different regression modelling strategies for predicting RVP in GOB, which is valuable for researchers and practitioners in the petroleum industry for saving time and money. Parametric and nonparametric approaches were compared using partial least squares regression (PLSR), nonlinear regression (NLR), and nonparametric regression (NPR) models. Locally weighted scatterplot smoothing (LOWESS) approach was applied to the NPR model. The gasoline’s physical characteristics (distillation curves and density) formed the basis for the analysis of these models’ performances. Acceptable error metrics have been reached for root mean square error of calibration and prediction (RMSEC and RMSEP) values, for the PLSR, NLR, and NPR models, which are 4.790, 6.235, 4.739, 6.149, 3.968, and 6.029, respectively, which are close for those reported in literature. The NPR model eliminates parametric constraints and allows for a different kind of data structure to emerge. The established models here demonstrate a sound ability to overcome barriers by omitting the use of inconvenient spectral measurements to save expense and simplify data calibration, making them a promising approach for RVP detection of GOB. This finding aids in the development of more accurate RVP prediction models and contributes to the optimization of fuel formulations.
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Men, Yifan, Ibrahim Haskara, and Guoming Zhu. "Multi-zone reaction-based modeling of combustion for multiple-injection diesel engines." International Journal of Engine Research 21, no. 6 (July 18, 2018): 1012–25. http://dx.doi.org/10.1177/1468087418788488.
Анотація:
As the requirements for performance and restrictions on emissions become stringent, diesel engines are equipped with advanced air, fuel, exhaust gas recirculation techniques, and associated control strategies, making them incredibly complex systems. To enable model-based engine control, control-oriented combustion models, including Wiebe-based and single-zone reaction-based models, have been developed to predict engine burn rate or in-cylinder pressure. Despite model simplicity, they are not suitable for engines operating outside the normal range because of the large error beyond calibrated region with extremely high calibration effort. The purpose of this article is to obtain a parametric understanding of diesel combustion by developing a physics-based model which can predict the combustion metrics, such as in-cylinder pressure, burn rate, and indicated mean effective pressure accurately, over a wide range of operating conditions, especially with multiple injections. In the proposed model, it is assumed that engine cylinder is divided into three zones: a fuel zone, a reaction zone, and an unmixed zone. The formulation of reaction and unmixed zones is based on the reaction-based modeling methodology, where the interaction between them is governed by Fick’s law of diffusion. The fuel zone is formulated as a virtual zone, which only accounts for mass and heat transfer associated with fuel injection and evaporation. The model is validated using test data under different speed and load conditions, with multiple injections and exhaust gas recirculation rates. It is shown that the multi-zone model outperformed the single-zone model in in-cylinder pressure prediction and calibration effort with a mild penalty in computational time.
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Wu, Robert, Pierrick Lamontagne-Hallé, and Jeffrey M. McKenzie. "Uncertainties in Measuring Soil Moisture Content with Actively Heated Fiber-Optic Distributed Temperature Sensing." Sensors 21, no. 11 (May 27, 2021): 3723. http://dx.doi.org/10.3390/s21113723.
Анотація:
Actively heated fiber-optic distributed temperature sensing (aFO-DTS) measures soil moisture content at sub-meter intervals across kilometres of fiber-optic cable. The technology has great potential for environmental monitoring but calibration at field scales with variable soil conditions is challenging. To better understand and quantify the errors associated with aFO-DTS soil moisture measurements, we use a parametric numerical modeling approach to evaluate different error factors for uniform soil. A thermo-hydrogeologic, unsaturated numerical model is used to simulate a 0.01 m by 0.01 m two-dimensional domain, including soil and a fiber-optic cable. Results from the model are compared to soil moisture values calculated using the commonly used Tcum calibration method for aFO-DTS. The model is found to have high accuracy between measured and observed saturations for static hydrologic conditions but shows discrepancies for more realistic settings with active recharge. We evaluate the performance of aFO-DTS soil moisture calculations for various scenarios, including varying recharge duration and heterogeneous soils. The aFO-DTS accuracy decreases as the variability in soil properties and intensity of recharge events increases. Further, we show that the burial of the fiber-optic cable within soil may adversely affect calculated results. The results demonstrate the need for careful selection of calibration data for this emerging method of measuring soil moisture content.
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Manfren, Massimiliano, and Benedetto Nastasi. "Parametric Performance Analysis and Energy Model Calibration Workflow Integration—A Scalable Approach for Buildings." Energies 13, no. 3 (February 1, 2020): 621. http://dx.doi.org/10.3390/en13030621.
Анотація:
High efficiency paradigms and rigorous normative standards for new and existing buildings are fundamental components of sustainability and energy transitions strategies today. However, optimistic assumptions and simplifications are often considered in the design phase and, even when detailed simulation tools are used, the validation of simulation results remains an issue. Further, empirical evidences indicate that the gap between predicted and measured performance can be quite large owing to different types of errors made in the building life cycle phases. Consequently, the discrepancy between a priori performance assessment and a posteriori measured performance can hinder the development and diffusion of energy efficiency practices, especially considering the investment risk. The approach proposed in the research is rooted on the integration of parametric simulation techniques, adopted in the design phase, and inverse modelling techniques applied in Measurement and Verification (M&V) practice, i.e., model calibration, in the operation phase. The research focuses on the analysis of these technical aspects for a Passive House case study, showing an efficient and transparent way to link design and operation performance analysis, reducing effort in modelling and monitoring. The approach can be used to detect and highlight the impact of critical assumptions in the design phase as well as to guarantee the robustness of energy performance management in the operational phase, providing parametric performance boundaries to ease monitoring process and identification of insights in a simple, robust and scalable way.
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Blouin, Danielle, and Everett V. Smith. "Measuring the continuous quality improvement orientation of medical education programs." International Journal of Health Care Quality Assurance 33, no. 2 (February 25, 2020): 158–71. http://dx.doi.org/10.1108/ijhcqa-06-2019-0102.
Анотація:
PurposeThere is a growing interest in applying continuous quality improvement (CQI) methodologies and tools to medical education contexts. One such tool, the “Are We Making Progress” questionnaire from the Malcolm Baldrige National Quality Award framework, adequately captures the dimensions critical for performance excellence and allows organizations to assess their performance and identify areas for improvement. Its results have been widely validated in business, education, and health care and might be applicable in medical education contexts. The measurement properties of the questionnaire data were analyzed using Rasch modeling to determine if validity evidence, based on Messick's framework, supports the interpretation of results in medical education contexts. Rasch modeling was performed since the questionnaire uses Likert-type scales whose estimates might not be amenable to parametric statistical analyses.Design/methodology/approachLeaders and teachers at 16 of the 17 Canadian medical schools were invited in 2015–2016 to complete the 40-item questionnaire. Data were analyzed using the ConQuest Rasch calibration program, rating scale model.Findings491 faculty members from 11 (69 percent) schools participated. A seven-dimensional, four-point response scale model better fit the data. Overall data fit to model requirements supported the use of person measures with parametric statistics. The structural, content, generalizability, and substantive validity evidence supported the interpretation of results in medical education contexts.Originality/valueFor the first time, the Baldrige questionnaire results were validated in medical education contexts. Medical education leaders are encouraged to serially use this questionnaire to measure progress on their school's CQI focus.
32
Tabrizikahou, Alireza, Mieczysław Kuczma, and Magdalena Łasecka-Plura. "Out-of-Plane Behavior of Masonry Prisms Retrofitted with Shape Memory Alloy Stripes: Numerical and Parametric Analysis." Sensors 22, no. 20 (October 20, 2022): 8004. http://dx.doi.org/10.3390/s22208004.
Анотація:
This paper provides a novel Finite Element (FE) simulation to estimate the out-of-plane response of masonry prisms retrofitted with Shape Memory Alloy (SMA) stripes. Empirical data were utilized to develop the computational analysis parameters (mechanical parameters for brick, mortar, and SMA materials) as well as the calibration of the computational FE-based models. For this purpose, a complete micro-modeling approach was applied, assuming perfect contact between mortar joints and brick units. A Concrete Damage Plasticity (CDP) model was developed to define the constitutive relation between brick and mortar. SMA stripes were mortar-installed on the surface of the prisms with a perfect connection. The masonry prism’s verified computational model was utilized to generate parametric research to explore the effect of varying SMA stripe thicknesses and different SMA usage (Ni-Ti or Cu-Zn-Al). The FE study findings indicated that, independent of their material type or thickness, using SMA stripes greatly minimizes brick prism deterioration. SMA stripes greatly decreased residual displacement and plastic strains. Parametric tests, however, revealed that employing Ni-Ti SMA and increasing its thickness is more effective with respect to the masonry prism out-of-plane response than Cu-Zn-Al SMA.
33
Zapata-Cuartas, Mauricio, Bronson P. Bullock, and Cristian R. Montes. "A Taper Equation for Loblolly Pine Using Penalized Spline Regression." Forest Science 67, no. 1 (January 18, 2021): 1–13. http://dx.doi.org/10.1093/forsci/fxaa037.
Анотація:
Abstract Stem profile needs to be modeled with an accurate taper equation to produce reliable tree volume assessments. We propose a semiparametric method where few a priori functional form assumptions or parametric specification are required. We compared the diameter and volume predictions of a penalized spline regression (P-spline), P-spline extended with an additive dbh-class variable, and six alternative parametric taper equations including single, segmented, and variable-exponent equation forms. We used taper data from 147 loblolly pine (Pinus taeda L.) trees to fit the models and make comparisons. Here we show that the extended P-spline outperforms the parametric taper equations when used to predict outside bark diameter in the lower portion of the stem, up to 40% of the tree height where the more valuable wood products (62% of the total outside bark volume) are located. For volume, both P-spline models perform equal or better than the best parametric model, with taper calibration, which could result in possible savings on inventory costs by not requiring an additional measurement. Our findings suggest that assuming a priori fixed form in taper models imposes restrictions that fail to explain the tree form adequately compared with the proposed P-spline.
34
Mesa Lavista, Milena, Francisco Lamas-Fernández, Eduardo Tejeda-Piusseaut, Rafael Bravo-Pareja, Carolina Cabrera-González, and José Álvarez-Pérez. "Overview of the Constitutive Model and Numerical Calibration by FEM to Compute Bearing Capacity and Embankment-Core Deformability." Ingeniería e Investigación 42, no. 1 (July 19, 2021): e93712. http://dx.doi.org/10.15446/ing.investig.v42n1.93712.
Анотація:
Numerical modeling is a powerful tool to determine the stress-strain relationships of structures. However, for a reliable application, physical and mathematical models must be calibrated and validated. This paper presents an overview of numerical calibration through the finite element method and plate-load tests in an embankment. Additionally, an analysis of the constitutive models used in soils is performed, and the elastic-plastic constitutive model of Mohr-Coulomb was selected since it is the best suited for this study. The results from three test areas within a refinery project that the Cuban government undertook in the province of Cienfuegos are used. The numerical model used in this study was calibrated by means of the error theory and the non-parametric hypothesis tests from Mann-Whitney U. From the practical point of view, this study gives two procedures to calibrate the numerical model with experimental results.
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LUPAKOV, S. YU, A. N. BUGAETS, L. V. GONCHUKOV, YU G. MOTOVILOV, O. V. SOKOLOV, and N. D. BUGAETS. "EXPERIENCE IN USING THE GR4J CONCEPTUAL MODEL FOR RUNOFF SIMULATION IN THE USSURI RIVER BASIN." Meteorologiya i Gidrologiya, no. 2 (February 2023): 57–68. http://dx.doi.org/10.52002/0130-2906-2023-2-57-68.
Анотація:
The open-source low-parametric conceptual hydrological model GR4J was used for runoff simulations of 17 nested catchments of the Upper Ussuri River basin with areas ranging from 133 to 24400 km2, including the Kirovskii outlet. The data of standard hydrometeorological observations of Primorye Administration for Hydrometeorology and Environmental Monitoring were used for the model calibration and verification. Runoff simulations were performed with a daily step. The criteria commonly used in hydrological community, namely, the Nash-Sutcliffe model efficiency coefficient (NSE), coefficient of determination ( R 2), and bias (BIAS) were used to assess the modeling efficiency. According to the specified criteria, modeling results are mostly in “satisfactory” or better categories. The base of the unit hydrograph expectedly increases with the catchment area, but there were no other relationships found between the values of calibrated model parameters, the annual water content, and the main morphometric parameters of the catchments. It was shown for the studied catchments that the stabilization and the maxima of the modeling efficiency scores are reached at the catchment areas of 1200-1700 km2. The influence of representativeness of the weather station network on the modeling efficiency was demonstrated using complementary meteorological observations from experimental catchments in the Upper Ussuri basin for the simulation of the catastrophic flood in 2016 that was caused by typhoon Lionrock.
36
Boratyński, Jakub. "Robustness of CGE Simulation Results in the Context of Structural Changes – The Case of Poland." Przegląd Statystyczny. Statistical Review 2014, no. 3 (September 30, 2014): 245–62. http://dx.doi.org/10.59139/ps.2014.03.2.
Анотація:
It is common to address the problem of uncertainty in computable general equilibrium modeling by sensitivity analysis. The relevant studies of the effects of parameter uncertainty usually focus on various elasticity parameters. In this paper we undertake sensitivity analysis with respect to the parameters derived from calibration to a benchmark data set, describing the structure of the economy. We use a time series of benchmark databases for the years 1996-2005 for Poland to sequentially calibrate a static CGE model, and examine the dispersion of endogenous variables’ responses in three distinct simulation experiments. We find a part – though not the most – of the results to be significantly sensitive to the choice of calibration database (including ambiguities about the direction of response). The dispersion of the results and its sources clearly depend on the shock in question. Uncertainty is also quite diverse between variables. It is thus recommended that a thorough parametric sensitivity analysis be a conventional part of a simulation study. Also, the reliability of results would likely benefit even from simple, trend-based updates of the benchmark data, as the responses of endogenous variables exhibit systematic changes, observed when the model is calibrated to the data for consecutive years.
37
Zheng, Hengbiao, Wei Li, Jiale Jiang, Yong Liu, Tao Cheng, Yongchao Tian, Yan Zhu, Weixing Cao, Yu Zhang, and Xia Yao. "A Comparative Assessment of Different Modeling Algorithms for Estimating Leaf Nitrogen Content in Winter Wheat Using Multispectral Images from an Unmanned Aerial Vehicle." Remote Sensing 10, no. 12 (December 13, 2018): 2026. http://dx.doi.org/10.3390/rs10122026.
Анотація:
Unmanned aerial vehicle (UAV)-based remote sensing (RS) possesses the significant advantage of being able to efficiently collect images for precision agricultural applications. Although numerous methods have been proposed to monitor crop nitrogen (N) status in recent decades, just how to utilize an appropriate modeling algorithm to estimate crop leaf N content (LNC) remains poorly understood, especially based on UAV multispectral imagery. A comparative assessment of different modeling algorithms (i.e., simple and non-parametric modeling algorithms alongside the physical model retrieval method) for winter wheat LNC estimation is presented in this study. Experiments were conducted over two consecutive years and involved different winter wheat varieties, N rates, and planting densities. A five-band multispectral camera (i.e., 490 nm, 550 nm, 671 nm, 700 nm, and 800 nm) was mounted on a UAV to acquire canopy images across five critical growth stages. The results of this study showed that the best-performing vegetation index (VI) was the modified renormalized difference VI (RDVI), which had a determination coefficient (R2) of 0.73 and a root mean square error (RMSE) of 0.38. This method was also characterized by a high processing speed (0.03 s) for model calibration and validation. Among the 13 non-parametric modeling algorithms evaluated here, the random forest (RF) approach performed best, characterized by R2 and RMSE values of 0.79 and 0.33, respectively. This method also had the advantage of full optical spectrum utilization and enabled flexible, non-linear fitting with a fast processing speed (2.3 s). Compared to the other two methods assessed here, the use of a look up table (LUT)-based radiative transfer model (RTM) remained challenging with regard to LNC estimation because of low prediction accuracy (i.e., an R2 value of 0.62 and an RMSE value of 0.46) and slow processing speed. The RF approach is a fast and accurate technique for N estimation based on UAV multispectral imagery.
38
Cajka, Radim, Zuzana Marcalikova, Vlastimil Bilek, and Oldrich Sucharda. "Numerical Modeling and Analysis of Concrete Slabs in Interaction with Subsoil." Sustainability 12, no. 23 (November 25, 2020): 9868. http://dx.doi.org/10.3390/su12239868.
Анотація:
This article focuses on the analysis and numerical modeling of a concrete slab interacting with subsoil. This is a complex task for which a number of factors enter into the calculation, including the scope or dimension of the model, the non-linear solution approach, the choice of input parameters, and so forth. The aim of this article is to present one possible approach, which is based on a non-linear analysis and a three-dimensional computational model. Five slabs were chosen for modeling and analysis. The experiments involved slabs of 2000 × 2000 mm and a thickness of 150 mm, which were tested using specialized equipment. The slabs included a reinforced concrete slab, a standard concrete slab, and three fiber-reinforced concrete slabs. The fiber-reinforced slabs had fiber volume fractions of 0.32%, 0.64%, and 0.96%, which corresponded to fiber dosages of 25, 50, and 75 kg/m3. A reinforced concrete slab was chosen for the calibration model and the initial parametric study. The numerical modeling itself was based on a detailed evaluation of experiments, tests, and recommendations. The finite element method was used to solve the three-dimensional numerical model, where the fracture-plastic material of the model was used for concrete and fiber-reinforced concrete. In this paper, the performed numerical analyses are compared and evaluated, and recommendations are made for solving this problem.
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Mirone, Giuseppe, Raffaele Barbagallo, Giuseppe Bua, and Guido La Rosa. "Finite Element Simulation and Sensitivity Analysis of the Cohesive Parameters for Delamination Modeling in Power Electronics Packages." Materials 16, no. 13 (July 4, 2023): 4808. http://dx.doi.org/10.3390/ma16134808.
Анотація:
Delamination is a critical failure mode in power electronics packages that can significantly impact their reliability and performance, due to the large amounts of electrical power managed by the most recent devices which induce remarkable thermomechanical loads. The finite element (FE) simulation of this phenomenon is very challenging for the identification of the appropriate modeling tools and their subsequent calibration. In this study, we present an advanced FE modeling approach for delamination, together with fundamental guidelines to calibrate it. Considering a reference power electronics package subjected to thermomechanical loads, FE simulations with a global–local approach are proposed, also including the implementation of a bi-linear cohesive zone model (CZM) to simulate the complex interfacial behavior between the different layers of the package. A parametric study and sensitivity analysis is presented, exploring the effects of individual CZM variables on the delamination behavior, identifying the most crucial ones and accurately describing their underlying functioning. Then, this work gives valuable insights and guidelines related to advanced and aware FE simulations of delamination in power electronics packages, useful for the design and optimization of these devices to mitigate their vulnerability to thermomechanical loads.
40
Greetham, Gregory M., Ian P. Clark, Benjamin Young, Robby Fritsch, Lucy Minnes, Neil T. Hunt, and Mike Towrie. "Time-Resolved Temperature-Jump Infrared Spectroscopy at a High Repetition Rate." Applied Spectroscopy 74, no. 6 (March 30, 2020): 720–27. http://dx.doi.org/10.1177/0003702820913636.
Анотація:
Time-resolved temperature-jump infrared absorption spectroscopy at a 0.5 to 1 kHz repetition rate is presented. A 1 kHz neodymium-doped yttrium aluminum garnet (Nd:YAG) laser pumping an optical parametric oscillator provided >70 µJ, 3.75 µm pump pulses, which delivered a temperature jump via excitation of the O–D stretch of a D2O solution. A 10 kHz train of mid-infrared probe pulses was used to monitor spectral changes following the temperature jump. Calibration with trifluoroacetic acid solution showed that a temperature jump of 10 K lasting for tens of microseconds was achieved, sufficient to observe fast processes in functionally relevant biomolecular mechanisms. Modeling of heating profiles across ≤10 µm path length cells and subsequent cooling dynamics are used to describe the initial <100 ns cooling at the window surface and subsequent, >10 µs cooling dynamics of the bulk solution.
41
CAITI, ANDREA. "SEAFLOOR PROPERTIES DETERMINATION FROM ACOUSTIC BACKSCATTERING AT NORMAL INCIDENCE WITH A PARAMETRIC SOURCE." Journal of Computational Acoustics 08, no. 02 (June 2000): 365–88. http://dx.doi.org/10.1142/s0218396x00000200.
Анотація:
An inversion technique is proposed for the determination of the geoacoustic and morphological properties of the uppermost sediment layer. The methodology is based on the use of the backscattering acoustic return when the source is a parametric instrument steered at normal incidence with respect to the seafloor. The peculiarity of the parametric sonar (i.e., its narrow beam and the absence of sidelobes) allows for discriminating between the scattering effects due to surface roughness and those due to volume perturbations. The inversion procedure is based on the minimization of a discrepancy measure between data and model predictions. Model predictions are obtained as time series realization of a stochastic process, modeling the backscattering process with the Kirchoff approximation for surface scattering and the small perturbation theory for volume scattering. The BoRIS code is used to generate the time series predictions. It is important to note that the model is stochastic, i.e., the model predicted time series with the same nominal parameters may differ from one realization to another. However, by use of wavelet transform of the signals involved, and measuring the data-model discrepancy in a generalized time-frequency domain, the stochasticity of the problem is greatly reduced. In particular, the wavelet transform is insensitive to different model realizations obtained with the same set of parameters, and sensitive to changes in the parameters. By appropriately weighing the discrepancy in the wavelet domain, and exploiting the properties of the parametric source, it is possible to separately recover the parameters influencing the surface backscattering (acoustic impedance and surface roughness) and those influencing the volume backscattering (P-wave attenuation and volume inhomogeneity), avoiding ambiguities and nonuniqueness problems. The approach proposed requires, however, a precise calibration of the parametric sonar, in terms of source level and beam pattern. Comparison of inversion results with independently measured ground truth at three different sites in the Mediterranean Sea are reported.
42
Pongnikorn, Donsuk, Phichayut Phinyo, Jayanton Patumanond, Karnchana Daoprasert, Pachaya Phothong, and Boonying Siribumrungwong. "Individualized Prediction of Breast Cancer Survival Using Flexible Parametric Survival Modeling: Analysis of a Hospital-Based National Clinical Cancer Registry." Cancers 13, no. 7 (March 29, 2021): 1567. http://dx.doi.org/10.3390/cancers13071567.
Анотація:
Prognostic models for breast cancer developed from Western countries performed less accurately in the Asian population. We aimed to develop a survival prediction model for overall survival (OS) and disease-free survival (DFS) for Thai patients with breast cancer. We conducted a prognostic model research using a multicenter hospital-based cancer clinical registry from the Network of National Cancer Institutes of Thailand. All women diagnosed with breast cancer who underwent surgery between 1 January 2010 and 31 December 2011 were included in the analysis. A flexible parametric survival model was used for developing the prognostic model for OS and DFS prediction. During the study period, 2021 patients were included. Of these, 1386 patients with 590 events were available for a complete-case analysis. The newly derived individualized prediction of breast cancer survival or the IPBS model consists of twelve routinely available predictors. The C-statistics from the OS and the DFS model were 0.72 and 0.70, respectively. The model showed good calibration for the prediction of five-year OS and DFS. The IPBS model provides good performance for the prediction of OS and PFS for breast cancer patients. A further external validation study is required before clinical implementation.
43
Lee, Marcus M. K., and Ellen M. Dexter. "Finite-Element Modelling of Multi-Planar Offshore Tubular Joints." Journal of Offshore Mechanics and Arctic Engineering 126, no. 1 (February 1, 2004): 120–28. http://dx.doi.org/10.1115/1.1643388.
Анотація:
This paper describes the calibration and validation of a finite-element modelling procedure that was used to conduct an extensive parametric study on the strength of multi-planar tubular joints. Various factors that influenced results were investigated. The modelling procedure was calibrated using the International Organization for Standards (ISO) design equations and the underlying test database for compression and tension loaded simple T and Y joints, and was further validated with balanced loaded K joints. Overall, the proposed procedure has been shown to be adequate in predicting the strength of the basic joint types, thereby giving confidence in its use for more complex joints.
44
Kane, Seamus P., and William F. Northrop. "A Quasi-Dimensional Model of Heat Transfer between Multi-Concentric Monolith Structures." Thermo 3, no. 4 (September 26, 2023): 515–36. http://dx.doi.org/10.3390/thermo3040031.
Анотація:
Metallic monolith structures are often used in compact reactor applications due to their superior heat transfer properties and lower pressure drop when compared to ceramic monoliths. Endothermic reactions like steam reforming depend heavily on externally supplied heat, making highly conductive supports especially useful. Simulations are invaluable for designing effective reactors with complex catalyst support structures but are conventionally resource-intensive. Additionally, few dedicated heat transfer experiments between monoliths exist in prior literature. To expand general knowledge of heat transfer between metal monolith structures, this work investigated heat exchange in concentric monoliths brazed to a common mantle. A computationally inexpensive quasi-dimensional model was developed and used to predict the heat exchange effectiveness and intrinsic heat transfer rate. The model used a discretized control volume approach and simplified geometries to reduce computational intensity. The model was calibrated against experimental data collected using a steady-state flow bench. After calibration, a parametric study was performed where monolith construction and flow conditions were varied. A parametric analysis showed that for identical catalyst space velocities and volumes, heat exchange effectiveness can be increased by 43.2% and heat transfer rates by 44.8% simply through increasing the surface area to volume ratio of the monolith. The described approach serves as an alternative framework for modeling catalytic heat exchangers without heavy computation and for quickly matching monolith geometries to their intended use and operating range.
45
Beghini, Marco, Leonardo Bertini, Anoj Giri, Ciro Santus, and Emilio Valentini. "Measuring residual stress in finite thickness plates using the hole-drilling method." Journal of Strain Analysis for Engineering Design 54, no. 1 (January 2019): 65–75. http://dx.doi.org/10.1177/0309324718821832.
Анотація:
Hole-drilling is one of the most popular methods for measuring residual stress in mechanical components. The ASTM E837 standard defines the hole-drilling method for plates that are either thicker or thinner than the size of the hole diameter and provides the related calibration coefficients for these two conditions. Measurements for components with a thickness in the range of a few millimetres, such as typical metal sheets, are not considered. In this article, the effects of thickness on the hole-drilling measurements are examined by a finite element parametric analysis. A method is proposed to analyse the measurements in plates with an intermediate thickness. The procedure is suitable for determining a general in-depth non-uniform residual stress distribution. Mathematical relationships are proposed which enable calibration coefficients to be obtained for any thickness. An experimental application confirms the validity of the procedure.
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Ortiz-Cahun, Miguel, Luis Fernandez-Baqueiro, and Zenon Medina-Cetina. "Calibration of Micro-Parameters of a Mortar Cylinder Specimen under Simple Compression Using a 2D Discrete Element Model." Applied Sciences 13, no. 19 (October 4, 2023): 10952. http://dx.doi.org/10.3390/app131910952.
Анотація:
Masonry systems have been used extensively in historical, commercial, and residential buildings. A large number of experimental and computational studies have been conducted to investigate the behavior of masonry components and systems, including mortar, units (e.g., blocks), and walls. The Discrete Element Method (DEM) has been used to analyze masonry systems with a macro modeling methodology (i.e., structural systems like walls). Masonry systems and their components have not been analyzed using a micro-modeling methodology with the DEM. The objective of this paper is the deterministic calibration of micro-parameters of the mortar cylinder model based on a computationally efficient DEM model. To achieve this objective, a parametric analysis is introduced through a series of models of a mortar specimen tested under simple compression to explore the impact of the model micro-parameters when trying to reproduce a set of experimental observations conducted at the Universidad Autonoma de Yucatan Mexico (UADY). A calibration process based on optimization is implemented to determine the best estimates of the model’s micro-parameters. This paper is divided into three analyses. First, the particle size distribution of the mortar’s aggregate is used as a reference (i.e., scale 1), and then up-scaled 1.5 and two times using four particle sizes; second, using the two-times scaled particle size, the influence of varying particle sizes within a reference particle size distribution was explored (from one particle size to 4 particle sizes following the aggregate particle size distribution); and third, a parametric analysis is performed varying seven micro-parameters, one at the time, varying from 0.25 to 1.5, at 0.25 scale increments, on a model including four particle sizes. The results show micro-parameters and stress-strain curves of mortar for the different analyses, and a representation of the cross sections of the models, indicating the distributions of contact forces. All proposed models showed good agreement with the experimental observations (i.e., stress-strain curve). Also, it was observed from the proposed analyses that some micro-parameters vary as the particle size and the scaled particle size distributions change when using the same experimental stress-strain curve. Also, it was found that the proposed DEM must contain at least two particle sizes to significantly improve the particle interlocking to ensure that the mechanistic behavior reproduces the same experimental observations. Finally, from the results presented in this work, it is concluded that it is possible to produce a computationally efficient model that can later serve as a reference for future research accounting for other control variables such as particle shape, particle size distributions, the exploration of damage propagation effects, and most importantly their corresponding uncertainty quantification and propagation effects in masonry systems.
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Eideh, Abdulhakeem. "On representativeness, informative sampling, nonignorable nonresponse, semiparametric prediction and calibration." Statistics in Transition new series 24, no. 2 (March 15, 2023): 93–111. http://dx.doi.org/10.59170/stattrans-2023-022.
Анотація:
Informative sampling refers to a sampling design for which the sample selection probabilities depend on the values of the model outcome variable. In such cases the model holding for the sample data is different from the model holding for the population data. Similarly, nonignorable nonresponse refers to a nonresponse mechanism in which the response probability depends on the value of a missing outcome variable. For such a nonresponse mechanism the model holding for the response data is different from the model holding for the population data. In this paper, we study, within a modelling framework, the semi-parametric prediction of a finite population total by specifying the probability distribution of the response units under informative sampling and nonignorable nonresponse. This is the most general situation in surveys and other combinations of sampling informativeness and response mechanisms can be considered as special cases. Furthermore, based on the relationship between response distribution and population distribution, we introduce a new measure of the representativeness of a response set and a new test of nonignorable nonresponse and informative sampling, jointly. Finally, a calibration estimator is obtained when the sampling design is informative and the nonresponse mechanism is nonignorable.
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Muhury, Newton, Armando Apan, and Tek Maraseni. "Modelling Floodplain Vegetation Response to Climate Change, Using the Soil and Water Assessment Tool (SWAT) Model Simulated LAI, Applying Different GCM’s Future Climate Data and MODIS LAI Data." Remote Sensing 16, no. 7 (March 29, 2024): 1204. http://dx.doi.org/10.3390/rs16071204.
Анотація:
Scientists widely agree that anthropogenically driven climate change significantly impacts vegetation growth, particularly in floodplain areas, by altering river flow and flood regimes. This impact will accelerate in the future, according to climate change projections. For example, in Australia, climate change has been attributed to a decrease in winter precipitation in the range of 56% to 72.9% and an increase in summer from 11% to 27%, according to different climate scenarios. This research attempts to understand vegetation responses to climate change variability at the floodplain level. Further, this study is an effort to enlighten our understanding of temporal climate change impacts under different climate scenarios. To achieve these aims, a semi-distributed hydrological model was applied at a sub-catchment level to simulate the Leaf Area Index (LAI). The model was simulated against future time series of climate data according to Global Climate Model (GCM) projections. The time series data underwent a non-parametric Mann–Kendall test to detect trends and assess the magnitude of change. To quantify the model’s performance, calibration and validation were conducted against the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI. The calibration and validation results show Nash–Sutcliffe efficiency (NSE) values of 0.85 and 0.78, respectively, suggesting the model’s performance is very good. The modeling results reveal that the rainfall pattern fluctuates under climate projections within the study site, in which vegetation tends to be more vibrant during the warmer seasons. Moreover, the modeling results highlighted increases in the average projected future winter temperatures, which can help vegetation growth during winter. The results of this study may be employed for sustainable floodplain management, restoration, land-use planning, and policymaking, and help floodplain communities better prepare for and respond to changing flood patterns and related challenges under a future changing climate.
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Albaba, Adel, Massimiliano Schwarz, Corinna Wendeler, Bernard Loup, and Luuk Dorren. "Numerical modeling using an elastoplastic-adhesive discrete element code for simulating hillslope debris flows and calibration against field experiments." Natural Hazards and Earth System Sciences 19, no. 11 (October 30, 2019): 2339–58. http://dx.doi.org/10.5194/nhess-19-2339-2019.
Анотація:
Abstract. This paper presents a discrete-element-based elastoplastic-adhesive model which is adapted and tested for producing hillslope debris flows. The numerical model produces three phases of particle contacts: elastic, plastic and adhesive. A parametric study was conducted investigating the effect of model parameters and inclination angle on flow height, velocity and pressure, in order to define the most sensitive parameters to calibrate. The model capabilities of simulating different types of cohesive granular flows were tested with different ranges of flow velocities and heights. The basic model parameters, the microscopic basal friction (ϕb) and ratio between stiffness parameters k1/k2, were calibrated using field experiments of hillslope debris flows impacting a pressure-measuring sensor. Simulations of 50 m3 of material were carried out on a channelized surface that is 41 m long and 8 m wide. The calibration process was based on measurements of flow height, flow velocity and the pressure applied to a sensor. Results of the numerical model matched those of the field data in terms of pressure and flow velocity well while less agreement was observed for flow height. Those discrepancies in results were due in part to the deposition of material in the field test, which is not reproducible in the model. Results of best-fit model parameters against selected experimental tests suggested that a link might exist between the model parameters ϕb and k1/k2 and the initial conditions of the tested granular material (bulk density and water and fine contents). The good performance of the model against the full-scale field experiments encourages further investigation by conducting lab-scale experiments with detailed variation in water and fine content to better understand their link to the model's parameters.
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Herrero, J., and M. J. Polo. "Parameterization of atmospheric long-wave emissivity in a mountainous site for all sky conditions." Hydrology and Earth System Sciences Discussions 9, no. 3 (March 21, 2012): 3789–811. http://dx.doi.org/10.5194/hessd-9-3789-2012.
Анотація:
Abstract. Long-wave radiation is an important component of the energy balance of the Earth's surface. The downward component, emitted by the clouds and aerosols in the atmosphere, is rarely measured, and is still not well understood. In mountainous areas, the models existing for its estimation through the emissivity of the atmosphere do not give good results, and worse still in the presence of clouds. In order to estimate this emissivity for any atmospheric state and in a mountainous site, we related it to the screen-level values of temperature, relative humidity and solar radiation. This permitted the obtaining of: (1) a new set of parametric equations and (2) the modification of the Brutsaert's equation for cloudy skies through the calibration of C factor to 0.34 and the parameterization of the cloud index N. Both fitted to the surface data measured at a weather station at a height of 2500 m a.s.l. in Sierra Nevada, Spain. This study analyzes separately three significant atmospheric states related to cloud cover, which were also deduced from the screen-level meteorological data. Clear and totally overcast skies are accurately represented by the new parametric expressions, while the intermediate situations corresponding to partly clouded skies, concentrate most of the dispersion in the measurements and, hence, the error in the simulation. Thus, the modeling of atmospheric emissivity is greatly improved thanks to the use of different equations for each atmospheric state.