scholarly journals Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters

2021 ◽  
Author(s):  
Adam Yonge ◽  
M. Kunz ◽  
Gabriel Gusmão ◽  
Zongtang Fang ◽  
Rakesh Batchu ◽  
...  
Keyword(s):  
Covariance Matrix ◽  
Temporal Analysis ◽  
Initial Surface ◽  
Parameter Uncertainties ◽  
Initial State ◽  
Pulse Delay ◽  
Sources Of Uncertainty ◽  
Experimental Noise ◽  
Temporal Analysis Of Products ◽  
The Impact

The temporal analysis of products (TAP) reactor provides a route to extract intrinsic kinetics from transient measurements. Current TAP uncertainty quantification only considers the experimental noise present in the outlet flow signal. Additional sources of uncertainty such as initial surface coverages, catalyst zone location, inert void fraction, gas pulse intensity and pulse delay, are not included. For this reason, a framework for quantifying initial state uncertainties present in TAP experiments is presented and applied to a carbon monoxide oxidation case study. Two methods for quantifying these sources of uncertainty are introduced. The first utilizes initial state sensitivities to approximate the parameter variances and provide insights into the structural certainty of the model. The second generates parameter confidence distributions through an ensemble-based sampling algorithm. The initial state covariance matrix can ultimately be merged with the experimental noise covariance matrix, providing a unified description of the parameter uncertainties for a TAP experiment.

scholarly journals Assessing sensitivity and persistence of updated initial conditions through Particle filter and EnKF for streamflow forecasting

2020 ◽  
Author(s):  
Gaia Piazzi ◽  
Guillaume Thirel ◽  
Charles Perrin
Keyword(s):  
Particle Filter ◽  
Predictive Accuracy ◽  
Initial Conditions ◽  
Internal State ◽  
Streamflow Forecasting ◽  
Parameter Uncertainties ◽  
Sources Of Uncertainty ◽  
Model State ◽  
Streamflow Forecasts ◽  
The Impact

<p>Skillful streamflow forecasts provide a key support to several water-related applications. Ensemble forecasting systems are gaining a widespread interest, since they allow accounting for different sources of uncertainty. Because of the critical impact of the initial conditions (ICs) on the forecast accuracy, it is essential to improve their estimates via data assimilation (DA). This study aims at assessing the sensitivity of the DA-based estimation of forecast ICs to several sources of uncertainty and to the update of different model states and parameters of a conceptual rainfall-runoff model. The performance of two sequential ensemble-based techniques are compared, namely Ensemble Kalman filter and Particle filter, in terms of both efficiency and temporal persistence of the updating effect through the assimilation of observed discharges at the forecast time. Several experiments specifically address the impact of the meteorological, model state and parameter uncertainties over 232 catchments in France. Results show that the benefit of the DA-based estimation of ICs for forecasting is the largest when focusing on the level of the model routing store, which is the internal state the most correlated to streamflow. While the EnKF-based forecasts outperform the PF-based ones when accounting for the meteorological uncertainty, the representation of the model state uncertainty allows greatly improving the accuracy of the PF-based predictions, with a longer-lasting updating effect (up to 10 days). Conversely, the forecasting skill is undermined when accounting for the parameter uncertainty, due to the change in the hydrological responsiveness through the update of both the production and routing store levels. A further effort is focused on assessing the impact of the spatial resolution of the hydrological model on the predictive accuracy of DA-based streamflow forecasts.</p>

Comparative study of the impact of two mechanical perforation densities on the behavior of a sandy soil

2012 ◽  
Vol 8 (1) ◽  
pp. 37-48
Author(s):  
S. Chehaibi ◽  
K. Abrougui ◽  
F. Haouala
Keyword(s):  
Soil Water ◽  
Sandy Soil ◽  
Water Infiltration ◽  
Cone Penetration ◽  
Initial State ◽  
Soil Water Infiltration ◽  
Good Improvement ◽  
The Impact ◽  
Positive Effect ◽  
Resistance To Penetration

The effects of mechanical perforation densities by extracting soil cores through an aerator Vertidrain with a working width of 1.6 m and equipped with hollow tines spaced of 65 mm, were studied on a sandy soil of a grassy sward in the Golf Course El Kantaoui in Sousse (Tunisia). The mechanical aeration was performed at two densities: 250 and 350 holes/m2. The cone penetration resistance and soil water infiltration were measured. These parameters were performed at initial state before aeration (E0) and then on the 10th, 20th and 30th day after aeration. These results showed that perforation density of 350 holes/m2 had a positive effect on the soil by reducing its cone resistance to penetration compared to the initial state (Rp = 14.8 daN/cm2). At 5 cm depth the decrease in resistance to penetration was 34% and 43% on the 10th and 20th day after aeration, respectively. However, on the 30th day after aeration the soil resistance to penetration tended to grow and its value compared to the initial state decreased only by 21 and 26%, respectively, at 5 and 15 cm of depth only by 10% and 9% with 250 holes/m2 density. The soil water infiltration made a good improvement after aeration compared to the initial state. This parameter increased from 4.8 cm/h to 8.3, 10.9 and 13.1 cm/h with 250 holes/m2 density and to 10, 12.9 and 14.8 cm/h with 350 holes/m2 density on the 10th, 20th and 30th day following the aeration.

scholarly journals Vibro-Acoustical Sensitivities of Stiffened Aircraft Structures Due to Attached Mass-Spring-Dampers with Uncertain Parameters

Aerospace ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 174
Author(s):  
Johannes Seidel ◽  
Stephan Lippert ◽  
Otto von Estorff
Keyword(s):  
System Response ◽  
Fuzzy Arithmetic ◽  
Parameter Uncertainties ◽  
Excitation Spectra ◽  
Radiated Noise ◽  
Linking Elements ◽  
Manufacturing Tolerances ◽  
Suitable Framework ◽  
Mass Spring ◽  
The Impact

The slightest manufacturing tolerances and variances of material properties can indeed have a significant impact on structural modes. An unintentional shift of eigenfrequencies towards dominant excitation frequencies may lead to increased vibration amplitudes of the structure resulting in radiated noise, e.g., reducing passenger comfort inside an aircraft’s cabin. This paper focuses on so-called non-structural masses of an aircraft, also known as the secondary structure that are attached to the primary structure via clips, brackets, and shock mounts and constitute a significant part of the overall mass of an aircraft’s structure. Using the example of a simplified fuselage panel, the vibro-acoustical consequences of parameter uncertainties in linking elements are studied. Here, the fuzzy arithmetic provides a suitable framework to describe uncertainties, create combination matrices, and evaluate the simulation results regarding target quantities and the impact of each parameter on the overall system response. To assess the vibrations of the fuzzy structure and by taking into account the excitation spectra of engine noise, modal and frequency response analyses are conducted.

Regularized error function-based extended Kalman filter for estimating the cancer chemotherapy dosage: impact of improved grey wolf optimization

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Utkarsha L. Mohite ◽  
Hirenkumar G. Patel
Keyword(s):  
Tumor Cells ◽  
Error Function ◽  
Drug Dosage ◽  
Parameters Estimation ◽  
Gray Wolf ◽  
Robust Performance ◽  
Parameter Uncertainties ◽  
Initial State ◽  
Robust Controller ◽  
Fine Tune

AbstractObjectivesThe main aim of this work is to introduce a robust controller for controlling the drug dosage.MethodsThe presented work establishes a novel robust controller that controls the drug dosage and it also carried out parameters estimation. Along with this, a Regularized Error Function-based EKF (REF-EKF) is introduced for estimating the tumor cells that could be adapted for different conditions. It also assists in solving the overfitting problems, which occur during the drug dosage estimation. Moreover, the performance of the adopted controller is compared over other conventional schemes, and the attained outcomes reveal the appropriate impact of drug dosage injection on immune, normal, and tumor cells. It is also ensured that the presented controller does a robust performance on the parameter uncertainties. Moreover, to enhance the performance of the proposed system and for fast convergence, it is aimed to fine-tune the initial state of EKF optimally using a new Improved Gray Wolf Optimization (GWO) termed as Adaptive GWO (AGWO). Finally, analysis is held to validate the betterment of the presented model.ResultsThe outcomes, the proposed method has accomplished a minimal value of error with an increase in time, when evaluated over the compared models.ConclusionsThus, the improvement of the proposed REF-EKF-AGWO model is proved from the attained results.

Enhancing the impact of IASI observations through an updated observation-error covariance matrix

2016 ◽  
Vol 142 (697) ◽  
pp. 1767-1780 ◽  
Author(s):  
Niels Bormann ◽  
Massimo Bonavita ◽  
Rossana Dragani ◽  
Reima Eresmaa ◽  
Marco Matricardi ◽  
...  
Keyword(s):  
Covariance Matrix ◽  
Observation Error ◽  
Error Covariance Matrix ◽  
Error Covariance ◽  
The Impact

scholarly journals Assessing the impact of feline immunodeficiency virus and bovine tuberculosis co-infection in African lions

2012 ◽  
Vol 279 (1745) ◽  
pp. 4206-4214 ◽  
Author(s):  
M. Maas ◽  
D. F. Keet ◽  
V. P. M. G. Rutten ◽  
J. A. P. Heesterbeek ◽  
M. Nielen
Keyword(s):  
Feline Immunodeficiency Virus ◽  
Bovine Tuberculosis ◽  
Temporal Analysis ◽  
Blood Chemistry ◽  
The North ◽  
Conservation Problem ◽  
Immunodeficiency Virus ◽  
Spatio Temporal ◽  
The Impact ◽  
African Lions

Bovine tuberculosis (BTB), caused by Mycobacterium bovis , is a disease that was introduced relatively recently into the Kruger National Park (KNP) lion population. Feline immunodeficiency virus (FIV ple ) is thought to have been endemic in lions for a much longer time. In humans, co-infection between Mycobacterium tuberculosis and human immunodeficiency virus increases disease burden. If BTB were to reach high levels of prevalence in lions, and if similar worsening effects would exist between FIV ple and BTB as for their human equivalents, this could pose a lion conservation problem. We collected data on lions in KNP from 1993 to 2008 for spatio-temporal analysis of both FIV ple and BTB, and to assess whether a similar relationship between the two diseases exists in lions. We found that BTB prevalence in the south was higher than in the north (72 versus 19% over the total study period) and increased over time in the northern part of the KNP (0–41%). No significant spatio-temporal differences were seen for FIV ple in the study period, in agreement with the presumed endemic state of the infection. Both infections affected haematology and blood chemistry values, FIV ple in a more pronounced way than BTB. The effect of co-infection on these values, however, was always less than additive. Though a large proportion (31%) of the lions was co-infected with FIV ple and M. bovis , there was no evidence for a synergistic relation as in their human counterparts. Whether this results from different immunopathogeneses remains to be determined.

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.

A Stochastic Parameter Perturbation Method to Represent Uncertainty in a Microphysics Scheme

2021 ◽  
Author(s):  
Gregory Thompson ◽  
Judith Berner ◽  
Maria Frediani ◽  
Jason A. Otkin ◽  
Sarah M. Griffin
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Random Perturbation ◽  
Longwave Radiation ◽  
Parameter Uncertainties ◽  
Microphysics Scheme ◽  
Convective Systems ◽  
Temporal Correlations ◽  
Precipitation Characteristics ◽  
The Impact

AbstractCurrent state-of-the art regional numerical weather forecasts are run at horizontal grid spacings of a few kilometers, which permits medium to large-scale convective systems to be represented explicitly in the model. With the convection parameterization no longer active, much uncertainty in the formulation of subgrid-scale processes moves to other areas such as the cloud microphysical, turbulence, and land-surface parameterizations. The goal of this study is to investigate experiments with stochastically-perturbed parameters (SPP) within a microphysics parameterization and the model’s horizontal diffusion coefficients. To estimate the “true” uncertainty due to parameter uncertainty, the magnitudes of the perturbations are chosen as realistic as possible and not with purposeful intent of maximal forecast impact as some prior work has done. Spatial inhomogeneities and temporal persistence are represented using a random perturbation pattern with spatial and temporal correlations. The impact on the distributions of various hydrometeors, precipitation characteristics, and solar/longwave radiation are quantified for a winter and summer case. In terms of upscale error growth, the impact is relatively small and consists primarily of triggering atmospheric instabilities in convectively unstable regions. In addition, small in situ changes with potentially large socio-economic impacts are observed in the precipitation characteristics such as maximum hail size. Albeit the impact of introducing physically-based parameter uncertainties within the bounds of aerosol uncertainties is small, their influence on the solar and longwave radiation balances may still have important implications for global model simulations of future climate scenarios.

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