Estimation of initial values of the HMS model parameters: application to the basin of Bin El Ouidane (Azilal, Morocco)

The availability, accessibility and quality of data are significant obstacles to hydrological modelling. Estimating the initial values of the hydrological model´’ ’s parameters is a laborious and determining task requiring much attention. Geographic information systems (GIS) and spatial remote sensing are prometting tools for processing and collecting data. In this work, we use an innovative approach to estimate the HEC-HMS hydrological model parameters from the soil map of Africa (250m), the land use map GLC30, the depth to bedrock map, the digital elevation model and observed flow data. The estimation approach is applied to the Ouergha basin (Sebou, Morocco). The proposed approach’s interest is to feed the HEC-HMS hydrological model with initial values of parameters close to the study area reality instead of using random parameters.

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Investigation of Error Distribution in the Back-Calculation of Breakage Function Model Parameters via Nonlinear Programming

Minerals ◽

10.3390/min11040425 ◽

2021 ◽

Vol 11 (4) ◽

pp. 425

Author(s):

Jihoe Kwon ◽

Heechan Cho

Keyword(s):

Flat Surface ◽

Error Function ◽

Model Parameters ◽

Dimensional Parameter ◽

Parameter Spaces ◽

Initial Values ◽

Wide Range ◽

Minimum Number ◽

Breakage Function ◽

Back Calculation

Despite its effectiveness in determining breakage function parameters (BFPs) for quantifying breakage characteristics in mineral grinding processes, the back-calculation method has limitations owing to the uncertainty regarding the distribution of the error function. In this work, using Korean uranium and molybdenum ores, we show that the limitation can be overcome by searching over a wide range of initial values based on the conjugate gradient method. We also visualized the distribution of the sum of squares of the error in the two-dimensional parameter space. The results showed that the error function was strictly convex, and the main problem in the back-calculation of the breakage functions was the flat surface of the objective function rather than the occurrence of local minima. Based on our results, we inferred that the flat surface problem could be significantly mitigated by searching over a wide range of initial values. Back-calculation using a wide range of initial values yields BFPs similar to those obtained from single-sized-feed breakage tests (SSFBTs) up to four-dimensional parameter spaces. Therefore, by searching over a wide range of initial values, the feasibility of the back-calculation approach can be significantly improved with a minimum number of SSFBTs.

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Online Modeling of a Fuel Cell System for an Energy Management Strategy Design

Energies ◽

10.3390/en13143713 ◽

2020 ◽

Vol 13 (14) ◽

pp. 3713 ◽

Cited By ~ 2

Author(s):

Mohsen Kandidayeni ◽

Alvaro Macias ◽

Loïc Boulon ◽

João Pedro F. Trovão

Keyword(s):

Fuel Cell ◽

Energy Management ◽

Management Strategy ◽

Proton Exchange Membrane ◽

Cell System ◽

Proton Exchange ◽

Fuel Cell Vehicle ◽

Model Parameters ◽

Energy Management Strategy ◽

Initial Values

An energy management strategy (EMS) efficiently splits the power among different sources in a hybrid fuel cell vehicle (HFCV). Most of the existing EMSs are based on static maps while a proton exchange membrane fuel cell (PEMFC) has time-varying characteristics, which can cause mismanagement in the operation of a HFCV. This paper proposes a framework for the online parameters identification of a PMEFC model while the vehicle is under operation. This identification process can be conveniently integrated into an EMS loop, regardless of the EMS type. To do so, Kalman filter (KF) is utilized to extract the parameters of a PEMFC model online. Unlike the other similar papers, special attention is given to the initialization of KF in this work. In this regard, an optimization algorithm, shuffled frog-leaping algorithm (SFLA), is employed for the initialization of the KF. The SFLA is first used offline to find the right initial values for the PEMFC model parameters using the available polarization curve. Subsequently, it tunes the covariance matrices of the KF by utilizing the initial values obtained from the first step. Finally, the tuned KF is employed online to update the parameters. The ultimate results show good accuracy and convergence improvement in the PEMFC characteristics estimation.

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The assessment of potential observability for joint chemical states and emissions in atmospheric modelings

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-021-02113-x ◽

2021 ◽

Author(s):

Xueran Wu ◽

Hendrik Elbern ◽

Birgit Jacob

Keyword(s):

Data Assimilation ◽

Assessment Method ◽

Model Systems ◽

Model Parameters ◽

Emission Rates ◽

Practical Applications ◽

Initial Values ◽

Geophysical Model ◽

Chemical States ◽

Transport Diffusion

AbstractIn predictive geophysical model systems, uncertain initial values and model parameters jointly influence the temporal evolution of the system. This renders initial-value-only optimization by traditional data assimilation methods as insufficient. However, blindly extending the optimization parameter set jeopardizes the validity of the resulting analysis because of the increase of the ill-posedness of the inversion task. Hence, it becomes important to assess the potential observability of measurement networks for model state and parameters in atmospheric modelings in advance of the optimization. In this paper, we novelly establish the dynamic model of emission rates and extend the transport-diffusion model extended by emission rates. Considering the Kalman smoother as underlying assimilation technique, we develop a quantitative assessment method to evaluate the potential observability and the sensitivity of observation networks to initial values and emission rates jointly. This benefits us to determine the optimizable parameters to observation configurations before the data assimilation procedure and make the optimization more efficiently. For high-dimensional models in practical applications, we derive an ensemble based version of the approach and give several elementary experiments for illustrations.

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Parameter Estimation in Modeling of Photovoltaic Panels Based on Datasheet Values

Journal of Solar Energy Engineering ◽

10.1115/1.4024923 ◽

2013 ◽

Vol 136 (2) ◽

Cited By ~ 11

Author(s):

Hayrettin Can ◽

Damla Ickilli

Keyword(s):

Parameter Estimation ◽

Large Scale ◽

Renewable Energy Sources ◽

Model Parameters ◽

New Approach ◽

Numerical Convergence ◽

Initial Values ◽

Pv Panel ◽

Panel Model ◽

Increasing Demand

The increasing demand for renewable energy sources in recent years has triggered technological advancements in photovoltaic (PV) panels. Widespread use of large-scale PV units has revealed the sensitivity in PV panel modeling needed to estimate the amount of energy produced in different environmental conditions. For the formation of a PV panel model, parameters should be obtained by numerically solving characteristic equations of a transcendental nature. This study preferred using the Newton Raphson (NR) method owing to the suitability of equation structure. It is crucial that numerical solution starts with proper initial values. This study proposes a new approach to identifying initial values in order to decrease calculation time and increase the speed of numerical convergence. The proposed method was used in parameter estimation for different panel models. And, it was observed that owing to this method, the system converged with less iteration and the problem of failing to solve the system because of inappropriate initial values were eliminated. Convergence was obtained and the solution needed less iteration in all models.

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The Assessment of Potential Observability for Joint Chemical States and Emissions in Atmospheric Modelings

10.21203/rs.3.rs-750110/v1 ◽

2021 ◽

Author(s):

Xueran Wu ◽

Hendrik Elbern ◽

Birgit Jacob

Keyword(s):

Assessment Method ◽

Model Systems ◽

Model Parameters ◽

Emission Rates ◽

Practical Applications ◽

Initial Values ◽

Geophysical Model ◽

Chemical States ◽

The Impact ◽

Observation Networks

Abstract In predictive geophysical model systems, uncertain initial values and model parameters jointly influence the temporal evolution of the system. As for chemistry-transport models, emission rates are at least as important as initial values for model evolution controls. This renders initial-value-only optimization by traditional data assimilation methods as insufficient. However, blindly extending the optimization parameter set jeopardizes the validity of the resulting analysis since the ill-posedness of the inversion task is increased. Hence, it becomes important to assess the potential observability of measurement networks for model state and parameters in atmospheric modelings in advance of the optimization. In this paper, we introduce an approach to quantify the impact of observation networks jointly for initial trace gas state and emission rates for transport-diffusion models extended by emissions. Applying a Kalman smoother as underlying assimilation technique, we develop a quantitative assessment method to evaluate the potential observability and the sensitivity of observation networks to initial values and emission rates. For practical applications, we derive an ensemble based version of the approach and give several elementary experiments for illustration.

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The degree of freedom for signal assessment of measurement networks for joint chemical state and emission analysis

10.5194/gmd-2017-220 ◽

2017 ◽

Author(s):

Xueran Wu ◽

Hendrik Elbern ◽

Birgit Jacob

Keyword(s):

Degree Of Freedom ◽

Model Systems ◽

Practical Reasons ◽

Model Parameters ◽

Analysis Tool ◽

Emission Rates ◽

State Variables ◽

Emission Analysis ◽

Initial Values ◽

Observation Networks

Abstract. The Degree of Freedom for Signal (DFS) is generalized and applied to estimate the potential observability of observation networks for augmented model state and parameter estimations. The control of predictive geophysical model systems by measurements is dependent on a sufficient observational basis. Control parameters may include prognostic state variables, mostly the initial values, and insufficiently known model parameters, to which the simulation is sensitive. As for chemistry-transport models, emission rates are at least as important as initial values for model evolution control. Extending the optimisation parameter set must be met by observation networks, which allows for controlling the entire optimisation task. In this paper, we introduce a DFS based approach with respect to address both, emission rates and initial value observability. By applying a Kalman smoother, a quantitative assessment method on the efficiency of observation configurations is developed based on the singular value decomposition. For practical reasons an ensemble based version is derived for covariance modelling. The observability analysis tool can be generalized to additional model parameters.

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Instrumental and Ideological Union Commitment: Longitudinal Assessment of Construct Validity

European Journal of Psychological Assessment ◽

10.1027//1015-5759.17.2.98 ◽

2001 ◽

Vol 17 (2) ◽

pp. 98-111 ◽

Cited By ~ 1

Author(s):

Anders Sjöberg ◽

Magnus Sverke

Keyword(s):

Construct Validity ◽

Temporal Stability ◽

Strong Support ◽

Internal Consistency Reliability ◽

Measurement Model ◽

Two Dimensions ◽

Model Parameters ◽

Longitudinal Assessment ◽

Union Commitment ◽

Union Participation

Summary: Previous research has identified instrumentality and ideology as important aspects of member attachment to labor unions. The present study evaluated the construct validity of a scale designed to reflect the two dimensions of instrumental and ideological union commitment using a sample of 1170 Swedish blue-collar union members. Longitudinal data were used to test seven propositions referring to the dimensionality, internal consistency reliability, and temporal stability of the scale as well as postulated group differences in union participation to which the scale should be sensitive. Support for the hypothesized factor structure of the scale and for adequate reliabilities of the dimensions was obtained and was also replicated 18 months later. Tests for equality of measurement model parameters and test-retest correlations indicated support for the temporal stability of the scale. In addition, the results were consistent with most of the predicted differences between groups characterized by different patterns of change/stability in union participation status. The study provides strong support for the construct validity of the scale and indicates that it can be used in future theory testing on instrumental and ideological union commitment.

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Representation of bolted joints in a structure using finite element modelling and model updating

JOURNAL OF MECHANICAL ENGINEERING AND SCIENCES ◽

10.15282/jmes.14.3.2020.15.0560 ◽

2020 ◽

Vol 14 (3) ◽

pp. 7141-7151 ◽

Cited By ~ 1

Author(s):

R. Omar ◽

M. N. Abdul Rani ◽

M. A. Yunus

Keyword(s):

Finite Element ◽

Dynamic Behaviour ◽

Model Updating ◽

Complex Structure ◽

Bolted Joints ◽

Model Parameters ◽

Fe Model ◽

Bolted Joint ◽

Fe Modelling ◽

Joint Structure

Efficient and accurate finite element (FE) modelling of bolted joints is essential for increasing confidence in the investigation of structural vibrations. However, modelling of bolted joints for the investigation is often found to be very challenging. This paper proposes an appropriate FE representation of bolted joints for the prediction of the dynamic behaviour of a bolted joint structure. Two different FE models of the bolted joint structure with two different FE element connectors, which are CBEAM and CBUSH, representing the bolted joints are developed. Modal updating is used to correlate the two FE models with the experimental model. The dynamic behaviour of the two FE models is compared with experimental modal analysis to evaluate and determine the most appropriate FE model of the bolted joint structure. The comparison reveals that the CBUSH element connectors based FE model has a greater capability in representing the bolted joints with 86 percent accuracy and greater efficiency in updating the model parameters. The proposed modelling technique will be useful in the modelling of a complex structure with a large number of bolted joints.

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THE INFLUENCE OF VITAMIN C ON EOSINOPHIL RESPONSE TO ACUTE ALCOHOL INTOXICATION IN RATS

Acta Endocrinologica ◽

10.1530/acta.0.xxxv0585 ◽

1960 ◽

Vol XXXV (IV) ◽

pp. 585-593 ◽

Cited By ~ 4

Author(s):

T. P. J. Vanha-Perttula

Keyword(s):

Vitamin C ◽

Ethyl Alcohol ◽

Intraperitoneal Injection ◽

Alcohol Intoxication ◽

Albino Rats ◽

Acute Alcohol Intoxication ◽

Alcohol Administration ◽

Initial Values

ABSTRACT The effect of ethyl alcohol on the circulating eosinophil cells has been studied in female albino rats. An intoxicating dose of alcohol caused a marked depletion of circulating eosinophils which was most clearly evident four hours after the administration of the alcohol. The initial values were not reached before 24 hours had elapsed. Intraperitoneal injection of vitamin C 12 hours prior to the alcohol administration very effectively prevented this eosinopenic reaction. The mechanism of regulation of the eosinophil cells in the circulation has been discussed in the light of previous results and of those obtained in this study.

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