scholarly journals Parameter Dependencies of a Biomechanical Cervical Spine FSU - The Process of Finding Optimal Model Parameters by Sensitivity Analysis

2021 ◽  
Author(s):  
Sabine Bauer ◽  
Ivanna Kramer
Keyword(s):  
Sensitivity Analysis ◽  
Intervertebral Discs ◽  
Model Parameters ◽  
Biomechanical Behavior ◽  
Functional Spinal Unit ◽  
Spine Model ◽  
Biomechanical Parameters ◽  
Multi Body ◽  
The Impact

The knowledge about the impact of structure-specific parameters on the biomechanical behavior of a computer model has an essential meaning for the realistic modeling and system improving. Especially the biomechanical parameters of the intervertebral discs, the ligamentous structures and the facet joints are seen in the literature as significant components of a spine model, which define the quality of the model. Therefore, it is important to understand how the variations of input parameters for these components affect the entire model and its individual structures. Sensitivity analysis can be used to gain the required knowledge about the correlation of the input and output variables in a complex spinal model. The present study analyses the influence of the biomechanical parameters of the intervertebral disc using different sensitivity analysis methods to optimize the spine model parameters. The analysis is performed with a multi-body simulation model of the cervical functional spinal unit C6-C7.

Estimating OLED Display Device Lifetime from pixel and screen brightness and its application

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan
Keyword(s):  
Image Processing ◽  
Power Consumption ◽  
Model Parameters ◽  
Display Device ◽  
Image Processing Algorithm ◽  
Pixel Value ◽  
Device Lifetime ◽  
The Impact ◽  
Oled Display

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.

Nonintrusive Global Sensitivity Analysis for Linear Systems With Process Noise

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
Souransu Nandi ◽  
Tarunraj Singh
Keyword(s):  
Sensitivity Analysis ◽  
Linear Systems ◽  
Global Sensitivity Analysis ◽  
Benchmark Problems ◽  
Model Parameters ◽  
Parameter Uncertainties ◽  
Sobol Indices ◽  
Global Sensitivity ◽  
Time Invariant ◽  
The Impact

The focus of this paper is on the global sensitivity analysis (GSA) of linear systems with time-invariant model parameter uncertainties and driven by stochastic inputs. The Sobol' indices of the evolving mean and variance estimates of states are used to assess the impact of the time-invariant uncertain model parameters and the statistics of the stochastic input on the uncertainty of the output. Numerical results on two benchmark problems help illustrate that it is conceivable that parameters, which are not so significant in contributing to the uncertainty of the mean, can be extremely significant in contributing to the uncertainty of the variances. The paper uses a polynomial chaos (PC) approach to synthesize a surrogate probabilistic model of the stochastic system after using Lagrange interpolation polynomials (LIPs) as PC bases. The Sobol' indices are then directly evaluated from the PC coefficients. Although this concept is not new, a novel interpretation of stochastic collocation-based PC and intrusive PC is presented where they are shown to represent identical probabilistic models when the system under consideration is linear. This result now permits treating linear models as black boxes to develop intrusive PC surrogates.

Numerical Towing Model for LNG Carrier Approach in Exposed Environment Calibrated With Full-Scale Measurements and Operability Criterion

2021 ◽  
Author(s):  
Erwan Auburtin ◽  
Quentin Delivré ◽  
Jason McConochie ◽  
Jim Brown ◽  
Yuriy Drobyshevski
Keyword(s):  
Numerical Model ◽  
Degrees Of Freedom ◽  
Line Tension ◽  
Full Scale ◽  
Model Parameters ◽  
Wave Loads ◽  
Simplified Approach ◽  
Large Matrix ◽  
Multi Body ◽  
The Impact

Abstract The Prelude Floating Liquefied Natural Gas (FLNG) platform is designed to offload liquefied natural and petroleum gas products to carrier vessels moored in a Side-by-Side (SBS) configuration. Prior to the mooring operation, the carrier vessel is escorted and held alongside the FLNG with the assistance of tugs connected to her bow and stern to ensure sufficient control over the vessel in this critical phase. In order to better understand the impact of environmental conditions, to determine the optimum length, strength, material and configuration of the towline stretcher, and to estimate the maximum operable environments, coupled multi-body simulations have been performed in time domain. The numerical model, which considered both the LNG carrier and the forward tug, was calibrated using full-scale measurements of tug motions and tow line tension recorded during a real approach and berthing manoeuvre at Prelude FLNG. The measured environment effects were generated numerically and the model parameters were adjusted to reproduce the recorded behavior as accurately as possible. Since actions of the tug master are difficult to model numerically and only the statistical environment parameters are known, a simplified approach has been adopted for modelling the tug propulsion and steering using a combination of static forces, stiffness and linear and quadratic damping for relevant horizontal degrees of freedom. The calibrated numerical model was first subjected to several sensitivity assessments of the modelling level (single- or multi-body, inclusion of second-order wave loads, inclusion of forward speed). Then sensitivity studies were performed to help address operational requirements related to the wave height and direction, and the stretcher length and strength. The conclusions have been taken into consideration for the selection of the tow line configurations for future operations. Finally, the calibrated coupled LNG carrier and tug model was used to derive Prelude-specific tug operability criteria that may be used for decision-making based on weather forecasts, prior to the SBS offloading operations. A large matrix of swell and wind driven waves was simulated over a range of wave heights, periods, directions and static towing forces to allow a criterion to be developed based on a stochastic extreme tow line tension. Such criterion considers relevant wave parameters while remaining simplified enough for easy use in operations. This paper describes the assumptions and process to numerically model the towing configuration and calibrate the different coefficients, discusses the results obtained for the various sensitivities, and explains the operability criteria. Important conclusions and lessons learnt are also shared.

scholarly journals A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments

2011 ◽  
Vol 11 (9) ◽  
pp. 2567-2582 ◽  
Author(s):  
H. Roux ◽  
D. Labat ◽  
P.-A. Garambois ◽  
M.-M. Maubourguet ◽  
J. Chorda ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Soil Properties ◽  
Overland Flow ◽  
Hydrological Model ◽  
Extreme Event ◽  
Model Parameters ◽  
Peak Time ◽  
Efficiency Coefficient ◽  
Soil Saturation ◽  
The Impact

Abstract. A spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing). Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures.

Sensitivity analysis of an integrated numerical flow model output to key parameters used in common qualitative vulnerability assessment methods

2020 ◽  
Author(s):  
Joanna Doummar ◽  
Assaad H. Kassem
Keyword(s):  
Sensitivity Analysis ◽  
Vulnerability Assessment ◽  
Groundwater Vulnerability ◽  
Assessment Methods ◽  
Qualitative Assessment ◽  
Model Parameters ◽  
Karst Aquifers ◽  
Model Output ◽  
Local Sensitivity ◽  
The Impact

<p>Qualitative vulnerability assessment methods applied in karst aquifers rely on key factors in the hydrological compartments usually assigned different weights according to their estimated impact on groundwater vulnerability. Based on an integrated numerical groundwater model on a snow-governed karst catchment area (Assal Spring- Lebanon), the aim of this work is to quantify the importance of the most influential parameters on recharge and spring discharge and outline potential parameters that are not accounted for in standard methods, when in fact they do play a role in the intrinsic vulnerability of a system. The assessment of the model sensitivity and the ranking of parameters are conducted using an automatic calibration tool for local sensitivity analysis in addition to a variance-based local sensitivity assessment of model output time series (recharge and discharge)  for two consecutive years (2016-2017) to various model parameters. The impact of each parameter was normalized to estimate standardized weights for each of the process based key-controlling parameters. Parameters to which model was sensitive were factors related to soil, 2) fast infiltration (bypass function) typical of karst aquifers, 3) climatic parameters (melting temperature and degree day coefficient) and 4) aquifer hydraulic properties that play a major role in groundwater vulnerability inducing a temporal effect and varied recession. Other less important parameters play different roles according to different assigned weights proportional to their ranking. Additionally, the effect of slope/geomorphology (e.g., dolines) was further investigated.  In general, this study shows that the weighting coefficients assigned to key vulnerability factors in the qualitative assessment methods can be reevaluated based on this process-based approach.</p><p> </p><p> </p><p> </p>

A Sensitivity Analysis of Two Mesoscale Models: COAMPS and WRF

2020 ◽  
Vol 148 (7) ◽  
pp. 2997-3014
Author(s):  
Caren Marzban ◽  
Robert Tardif ◽  
Scott Sandgathe
Keyword(s):  
Sensitivity Analysis ◽  
Spatial Structure ◽  
Latin Hypercube Sampling ◽  
Forecast Model ◽  
The United States ◽  
Model Parameters ◽  
Analysis Methodology ◽  
Trigger Function ◽  
Multivariate Multiple Regression

Abstract A sensitivity analysis methodology recently developed by the authors is applied to COAMPS and WRF. The method involves varying model parameters according to Latin Hypercube Sampling, and developing multivariate multiple regression models that map the model parameters to forecasts over a spatial domain. The regression coefficients and p values testing whether the coefficients are zero serve as measures of sensitivity of forecasts with respect to model parameters. Nine model parameters are selected from COAMPS and WRF, and their impact is examined on nine forecast quantities (water vapor, convective and gridscale precipitation, and air temperature and wind speed at three altitudes). Although the conclusions depend on the model parameters and specific forecast quantities, it is shown that sensitivity to model parameters is often accompanied by nontrivial spatial structure, which itself depends on the underlying forecast model (i.e., COAMPS vs WRF). One specific difference between these models is in their sensitivity with respect to a parameter that controls temperature increments in the Kain–Fritsch trigger function; whereas this parameter has a distinct spatial structure in COAMPS, that structure is completely absent in WRF. The differences between COAMPS and WRF also extend to the quality of the statistical models used to assess sensitivity; specifically, the differences are largest over the waters off the southeastern coast of the United States. The implication of these findings is twofold: not only is the spatial structure of sensitivities different between COAMPS and WRF, the underlying relationship between the model parameters and the forecasts is also different between the two models.

scholarly journals Uncertainty and sensitivity analysis of GIS based continuous hydrological modelling

2021 ◽  
Author(s):  
Harry R. Manson
Keyword(s):  
Sensitivity Analysis ◽  
Curve Number ◽  
Monte Carlo Analysis ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Daily Average ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

The impact of uncertainty in spatial and a-spatial lumped model parameters for a continuous rainfall-runoff model is evaluated with respect to model prediction. The model uses a modified SCS-Curve Number approach that is loosely coupled with a geographic information system (GIS). The rainfall-runoff model uses daily average inputs and is calibrated using a daily average streamflow record for the study site. A Monte Carlo analysis is used to identify total model uncertainty while sensitivity analysis is applied using both a one-at-a-time (OAT) approach as well as through application of the extended Fourier Amplitude Sensitivity Technique (FAST). Conclusions suggest that the model is highly followed by model inputs and finally the Curve Number. While the model does not indicate a high degree of sensitivity to the Curve Number at present conditions, uncertainties in Curve Number estimation can potentially be the cause of high predictive errors when future development scenarios are evaluated.

scholarly journals Modelling gastrointestinal parasitism infection in a sheep flock over two reproductive seasons:in silicoexploration and sensitivity analysis

Parasitology ◽  
2016 ◽  
Vol 143 (12) ◽  
pp. 1509-1531 ◽  
Author(s):  
M. SACCAREAU ◽  
C. R. MORENO ◽  
I. KYRIAZAKIS ◽  
R. FAIVRE ◽  
S. C. BISHOP
Keyword(s):  
Sensitivity Analysis ◽  
Control Strategies ◽  
Real Data ◽  
Published Data ◽  
Model Parameters ◽  
Sheep Flock ◽  
Source Of Infection ◽  
Teladorsagia Circumcincta ◽  
Host Nutrition ◽  
The Impact

SUMMARYIn reproducing ewes, a periparturient breakdown of immunity is often observed to result in increased fecal egg excretion, making them the main source of infection for their immunologically naive lambs. In this study, we expanded a simulation model previously developed for growing lambs to explore the impact of the genotype (performance and resistance traits) and host nutrition on the performance and parasitism of both growing lambs and reproducing ewes naturally infected withTeladorsagia circumcincta. Our model accounted for nutrient-demanding phases, such as gestation and lactation, and included a supplementary module to manage the age structure of the ewe flock. The model was validated by comparison with published data. Because model parameters were unknown or poorly estimated, detailed sensitivity analysis of the model was performed for the sheep mortality and the level of infection, following a preliminary screening step. The parameters with the greatest effect on parasite-related outputs were those driving animal growth and milk yield. Our model enables different parasite-control strategies (host nutrition, breeding for resistance and anthelmintic treatments) to be assessed on the long term in a sheep flock. To optimizein silicoexploration, the parameters highlighted by the sensitivity analysis should be refined with real data.

scholarly journals Sensitivity of Direct Runoff to Curve Number Using the SCS-CN Method

2019 ◽  
Vol 5 (12) ◽  
pp. 2738-2746
Author(s):  
Abdul Ghani Soomro ◽  
Muhammad Munir Babar ◽  
Anila Hameem Memon ◽  
Arjumand Zehra Zaidi ◽  
Arshad Ashraf ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Water Availability ◽  
Curve Number ◽  
Resource Planning ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Direct Runoff ◽  
Wide Range ◽  
The Impact ◽  
Scs Cn

This study explores the impact of runoff curve number (CN) on the hydrological model outputs for the Morai watershed, Sindh-Pakistan, using the Soil Conservation Service Curve Number (SCS-CN) method. The SCS-CN method is an empirical technique used to estimate rainfall-runoff volume from precipitation in small watersheds, and CN is an empirically derived parameter used to calculate direct runoff from a rainfall event. CN depends on soil type, its condition, and the land use and land cover (LULC) of an area. Precise knowledge of these factors was not available for the study area, and therefore, a range of values was selected to analyze the sensitivity of the model to the changing CN values. Sensitivity analysis involves a methodological manipulation of model parameters to understand their impacts on model outputs. A range of CN values from 40-90 was selected to determine their effects on model results at the sub-catchment level during the historic flood year of 2010. The model simulated 362 cumecs of peak discharge for CN=90; however, for CN=40, the discharge reduced substantially to 78 cumecs (a 78.46% reduction). Event-based comparison of water volumes for different groups of CN values—90-75, 80-75, 75-70, and 90-40 —showed reductions in water availability of 8.88%, 3.39%, 3.82%, and 41.81%, respectively. Although it is known that the higher the CN, the greater the discharge from direct runoff and the less initial losses, the sensitivity analysis quantifies that impact and determines the amount of associated discharges with changing CN values. The results of the case study suggest that CN is one of the most influential parameters in the simulation of direct runoff. Knowledge of accurate runoff is important in both wet (flood management) and dry periods (water availability). A wide range in the resulting water discharges highlights the importance of precise CN selection. Sensitivity analysis is an essential facet of establishing hydrological models in limited data watersheds. The range of CNs demonstrates an enormous quantitative consequence on direct runoff, the exactness of which is necessary for effective water resource planning and management. The method itself is not novel, but the way it is proposed here can justify investments in determining the accurate CN before initiating mega projects involving rainfall-runoff simulations. Even a small error in CN value may lead to serious consequences. In the current study, the sensitivity analysis challenges the strength of the results of a model in the presence of ambiguity regarding CN value.

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