Geohydrology of the stratified-drift aquifer system in the lower Sixmile Creek and Willseyville Creek trough, Tompkins County, New York

Science.gov (United States)

Miller, Todd S.; Karig, Daniel E.

2010-01-01

In 2002, the U.S. Geological Survey, in cooperation with the Tompkins County Planning Department began a series of studies of the stratified-drift aquifers in Tompkins County to provide geohydrologic data for planners to develop a strategy to manage and protect their water resources. This aquifer study in lower Sixmile Creek and Willseyville Creek trough is the second in a series of aquifer studies in Tompkins County. The study area is within the northern area of the Appalachian Plateau and extends about 9 miles from the boundary between Tompkins County and Tioga County in the south to just south of the City of Ithaca in the north. In lower Sixmile Creek and Willseyville Creek trough, confined sand and gravel aquifers comprise the major water-bearing units while less extensive unconfined units form minor aquifers. About 600 people who live in lower Sixmile Creek and Willseyville Creek trough rely on groundwater from the stratified-drift aquifer system. In addition, water is used by non-permanent residents such as staff at commercial facilities. The estimated total groundwater withdrawn for domestic use is about 45,000 gallons per day (gal/d) or 0.07 cubic foot per second (ft3/s) based on an average water use of 75 gal/d per person for self-supplied water systems in New York. Scouring of bedrock in the preglacial lower Sixmile Creek and Willseyville Creek valleys by glaciers and subglacial meltwaters truncated hillside spurs, formed U-shaped, transverse valley profiles, smoothed valley walls, and deepened the valleys by as much as 300 feet (ft), forming a continuous trough. The unconsolidated deposits in the study area consist mostly of glacial drift, both unstratified drift (till) and stratified drift (laminated lake, deltaic, and glaciofluvial sediments), as well as some post-glacial stratified sediments (lake-bottom sediments that were deposited in reservoirs, peat and muck that were deposited in wetlands, and alluvium deposited by streams). Multiple advances and

Calibration and simulation of Heston model

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Mrázek Milan

2017-05-01

Full Text Available We calibrate Heston stochastic volatility model to real market data using several optimization techniques. We compare both global and local optimizers for different weights showing remarkable differences even for data (DAX options from two consecutive days. We provide a novel calibration procedure that incorporates the usage of approximation formula and outperforms significantly other existing calibration methods.

A Method to Test Model Calibration Techniques: Preprint

Energy Technology Data Exchange (ETDEWEB)

Judkoff, Ron; Polly, Ben; Neymark, Joel

2016-09-01

This paper describes a method for testing model calibration techniques. Calibration is commonly used in conjunction with energy retrofit audit models. An audit is conducted to gather information about the building needed to assemble an input file for a building energy modeling tool. A calibration technique is used to reconcile model predictions with utility data, and then the 'calibrated model' is used to predict energy savings from a variety of retrofit measures and combinations thereof. Current standards and guidelines such as BPI-2400 and ASHRAE-14 set criteria for 'goodness of fit' and assume that if the criteria are met, then the calibration technique is acceptable. While it is logical to use the actual performance data of the building to tune the model, it is not certain that a good fit will result in a model that better predicts post-retrofit energy savings. Therefore, the basic idea here is that the simulation program (intended for use with the calibration technique) is used to generate surrogate utility bill data and retrofit energy savings data against which the calibration technique can be tested. This provides three figures of merit for testing a calibration technique, 1) accuracy of the post-retrofit energy savings prediction, 2) closure on the 'true' input parameter values, and 3) goodness of fit to the utility bill data. The paper will also discuss the pros and cons of using this synthetic surrogate data approach versus trying to use real data sets of actual buildings.

Financial model calibration using consistency hints.

Science.gov (United States)

Abu-Mostafa, Y S

2001-01-01

We introduce a technique for forcing the calibration of a financial model to produce valid parameters. The technique is based on learning from hints. It converts simple curve fitting into genuine calibration, where broad conclusions can be inferred from parameter values. The technique augments the error function of curve fitting with consistency hint error functions based on the Kullback-Leibler distance. We introduce an efficient EM-type optimization algorithm tailored to this technique. We also introduce other consistency hints, and balance their weights using canonical errors. We calibrate the correlated multifactor Vasicek model of interest rates, and apply it successfully to Japanese Yen swaps market and US dollar yield market.

Model validation and calibration based on component functions of model output

International Nuclear Information System (INIS)

Wu, Danqing; Lu, Zhenzhou; Wang, Yanping; Cheng, Lei

2015-01-01

The target in this work is to validate the component functions of model output between physical observation and computational model with the area metric. Based on the theory of high dimensional model representations (HDMR) of independent input variables, conditional expectations are component functions of model output, and the conditional expectations reflect partial information of model output. Therefore, the model validation of conditional expectations tells the discrepancy between the partial information of the computational model output and that of the observations. Then a calibration of the conditional expectations is carried out to reduce the value of model validation metric. After that, a recalculation of the model validation metric of model output is taken with the calibrated model parameters, and the result shows that a reduction of the discrepancy in the conditional expectations can help decrease the difference in model output. At last, several examples are employed to demonstrate the rationality and necessity of the methodology in case of both single validation site and multiple validation sites. - Highlights: • A validation metric of conditional expectations of model output is proposed. • HDRM explains the relationship of conditional expectations and model output. • An improved approach of parameter calibration updates the computational models. • Validation and calibration process are applied at single site and multiple sites. • Validation and calibration process show a superiority than existing methods

CALIBRATED HYDRODYNAMIC MODEL

Directory of Open Access Journals (Sweden)

Sezar Gülbaz

2015-01-01

Full Text Available The land development and increase in urbanization in a watershed affect water quantityand water quality. On one hand, urbanization provokes the adjustment of geomorphicstructure of the streams, ultimately raises peak flow rate which causes flood; on theother hand, it diminishes water quality which results in an increase in Total SuspendedSolid (TSS. Consequently, sediment accumulation in downstream of urban areas isobserved which is not preferred for longer life of dams. In order to overcome thesediment accumulation problem in dams, the amount of TSS in streams and inwatersheds should be taken under control. Low Impact Development (LID is a BestManagement Practice (BMP which may be used for this purpose. It is a land planningand engineering design method which is applied in managing storm water runoff inorder to reduce flooding as well as simultaneously improve water quality. LID includestechniques to predict suspended solid loads in surface runoff generated over imperviousurban surfaces. In this study, the impact of LID-BMPs on surface runoff and TSS isinvestigated by employing a calibrated hydrodynamic model for Sazlidere Watershedwhich is located in Istanbul, Turkey. For this purpose, a calibrated hydrodynamicmodel was developed by using Environmental Protection Agency Storm WaterManagement Model (EPA SWMM. For model calibration and validation, we set up arain gauge and a flow meter into the field and obtain rainfall and flow rate data. Andthen, we select several LID types such as retention basins, vegetative swales andpermeable pavement and we obtain their influence on peak flow rate and pollutantbuildup and washoff for TSS. Consequently, we observe the possible effects ofLID on surface runoff and TSS in Sazlidere Watershed.

Cloud-Based Model Calibration Using OpenStudio: Preprint

Energy Technology Data Exchange (ETDEWEB)

Hale, E.; Lisell, L.; Goldwasser, D.; Macumber, D.; Dean, J.; Metzger, I.; Parker, A.; Long, N.; Ball, B.; Schott, M.; Weaver, E.; Brackney, L.

2014-03-01

OpenStudio is a free, open source Software Development Kit (SDK) and application suite for performing building energy modeling and analysis. The OpenStudio Parametric Analysis Tool has been extended to allow cloud-based simulation of multiple OpenStudio models parametrically related to a baseline model. This paper describes the new cloud-based simulation functionality and presents a model cali-bration case study. Calibration is initiated by entering actual monthly utility bill data into the baseline model. Multiple parameters are then varied over multiple iterations to reduce the difference between actual energy consumption and model simulation results, as calculated and visualized by billing period and by fuel type. Simulations are per-formed in parallel using the Amazon Elastic Cloud service. This paper highlights model parameterizations (measures) used for calibration, but the same multi-nodal computing architecture is available for other purposes, for example, recommending combinations of retrofit energy saving measures using the calibrated model as the new baseline.

Fermentation process tracking through enhanced spectral calibration modeling.

Science.gov (United States)

Triadaphillou, Sophia; Martin, Elaine; Montague, Gary; Norden, Alison; Jeffkins, Paul; Stimpson, Sarah

2007-06-15

The FDA process analytical technology (PAT) initiative will materialize in a significant increase in the number of installations of spectroscopic instrumentation. However, to attain the greatest benefit from the data generated, there is a need for calibration procedures that extract the maximum information content. For example, in fermentation processes, the interpretation of the resulting spectra is challenging as a consequence of the large number of wavelengths recorded, the underlying correlation structure that is evident between the wavelengths and the impact of the measurement environment. Approaches to the development of calibration models have been based on the application of partial least squares (PLS) either to the full spectral signature or to a subset of wavelengths. This paper presents a new approach to calibration modeling that combines a wavelength selection procedure, spectral window selection (SWS), where windows of wavelengths are automatically selected which are subsequently used as the basis of the calibration model. However, due to the non-uniqueness of the windows selected when the algorithm is executed repeatedly, multiple models are constructed and these are then combined using stacking thereby increasing the robustness of the final calibration model. The methodology is applied to data generated during the monitoring of broth concentrations in an industrial fermentation process from on-line near-infrared (NIR) and mid-infrared (MIR) spectrometers. It is shown that the proposed calibration modeling procedure outperforms traditional calibration procedures, as well as enabling the identification of the critical regions of the spectra with regard to the fermentation process.

Cumulative error models for the tank calibration problem

International Nuclear Information System (INIS)

Goldman, A.; Anderson, L.G.; Weber, J.

1983-01-01

The purpose of a tank calibration equation is to obtain an estimate of the liquid volume that corresponds to a liquid level measurement. Calibration experimental errors occur in both liquid level and liquid volume measurements. If one of the errors is relatively small, the calibration equation can be determined from wellknown regression and calibration methods. If both variables are assumed to be in error, then for linear cases a prototype model should be considered. Many investigators are not familiar with this model or do not have computing facilities capable of obtaining numerical solutions. This paper discusses and compares three linear models that approximate the prototype model and have the advantage of much simpler computations. Comparisons among the four models and recommendations of suitability are made from simulations and from analyses of six sets of experimental data

Root zone water quality model (RZWQM2): Model use, calibration and validation

Science.gov (United States)

Ma, Liwang; Ahuja, Lajpat; Nolan, B.T.; Malone, Robert; Trout, Thomas; Qi, Z.

2012-01-01

The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.

Calibration of the Site-Scale Saturated Zone Flow Model

International Nuclear Information System (INIS)

Zyvoloski, G. A.

2001-01-01

The purpose of the flow calibration analysis work is to provide Performance Assessment (PA) with the calibrated site-scale saturated zone (SZ) flow model that will be used to make radionuclide transport calculations. As such, it is one of the most important models developed in the Yucca Mountain project. This model will be a culmination of much of our knowledge of the SZ flow system. The objective of this study is to provide a defensible site-scale SZ flow and transport model that can be used for assessing total system performance. A defensible model would include geologic and hydrologic data that are used to form the hydrogeologic framework model; also, it would include hydrochemical information to infer transport pathways, in-situ permeability measurements, and water level and head measurements. In addition, the model should include information on major model sensitivities. Especially important are those that affect calibration, the direction of transport pathways, and travel times. Finally, if warranted, alternative calibrations representing different conceptual models should be included. To obtain a defensible model, all available data should be used (or at least considered) to obtain a calibrated model. The site-scale SZ model was calibrated using measured and model-generated water levels and hydraulic head data, specific discharge calculations, and flux comparisons along several of the boundaries. Model validity was established by comparing model-generated permeabilities with the permeability data from field and laboratory tests; by comparing fluid pathlines obtained from the SZ flow model with those inferred from hydrochemical data; and by comparing the upward gradient generated with the model with that observed in the field. This analysis is governed by the Office of Civilian Radioactive Waste Management (OCRWM) Analysis and Modeling Report (AMR) Development Plan ''Calibration of the Site-Scale Saturated Zone Flow Model'' (CRWMS M and O 1999a)

MT3DMS: Model use, calibration, and validation

Science.gov (United States)

Zheng, C.; Hill, Mary C.; Cao, G.; Ma, R.

2012-01-01

MT3DMS is a three-dimensional multi-species solute transport model for solving advection, dispersion, and chemical reactions of contaminants in saturated groundwater flow systems. MT3DMS interfaces directly with the U.S. Geological Survey finite-difference groundwater flow model MODFLOW for the flow solution and supports the hydrologic and discretization features of MODFLOW. MT3DMS contains multiple transport solution techniques in one code, which can often be important, including in model calibration. Since its first release in 1990 as MT3D for single-species mass transport modeling, MT3DMS has been widely used in research projects and practical field applications. This article provides a brief introduction to MT3DMS and presents recommendations about calibration and validation procedures for field applications of MT3DMS. The examples presented suggest the need to consider alternative processes as models are calibrated and suggest opportunities and difficulties associated with using groundwater age in transport model calibration.

A single model procedure for estimating tank calibration equations

International Nuclear Information System (INIS)

Liebetrau, A.M.

1997-10-01

A fundamental component of any accountability system for nuclear materials is a tank calibration equation that relates the height of liquid in a tank to its volume. Tank volume calibration equations are typically determined from pairs of height and volume measurements taken in a series of calibration runs. After raw calibration data are standardized to a fixed set of reference conditions, the calibration equation is typically fit by dividing the data into several segments--corresponding to regions in the tank--and independently fitting the data for each segment. The estimates obtained for individual segments must then be combined to obtain an estimate of the entire calibration function. This process is tedious and time-consuming. Moreover, uncertainty estimates may be misleading because it is difficult to properly model run-to-run variability and between-segment correlation. In this paper, the authors describe a model whose parameters can be estimated simultaneously for all segments of the calibration data, thereby eliminating the need for segment-by-segment estimation. The essence of the proposed model is to define a suitable polynomial to fit to each segment and then extend its definition to the domain of the entire calibration function, so that it (the entire calibration function) can be expressed as the sum of these extended polynomials. The model provides defensible estimates of between-run variability and yields a proper treatment of between-segment correlations. A portable software package, called TANCS, has been developed to facilitate the acquisition, standardization, and analysis of tank calibration data. The TANCS package was used for the calculations in an example presented to illustrate the unified modeling approach described in this paper. With TANCS, a trial calibration function can be estimated and evaluated in a matter of minutes

Influence of rainfall observation network on model calibration and application

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A. Bárdossy

2008-01-01

Full Text Available The objective in this study is to investigate the influence of the spatial resolution of the rainfall input on the model calibration and application. The analysis is carried out by varying the distribution of the raingauge network. A meso-scale catchment located in southwest Germany has been selected for this study. First, the semi-distributed HBV model is calibrated with the precipitation interpolated from the available observed rainfall of the different raingauge networks. An automatic calibration method based on the combinatorial optimization algorithm simulated annealing is applied. The performance of the hydrological model is analyzed as a function of the raingauge density. Secondly, the calibrated model is validated using interpolated precipitation from the same raingauge density used for the calibration as well as interpolated precipitation based on networks of reduced and increased raingauge density. Lastly, the effect of missing rainfall data is investigated by using a multiple linear regression approach for filling in the missing measurements. The model, calibrated with the complete set of observed data, is then run in the validation period using the above described precipitation field. The simulated hydrographs obtained in the above described three sets of experiments are analyzed through the comparisons of the computed Nash-Sutcliffe coefficient and several goodness-of-fit indexes. The results show that the model using different raingauge networks might need re-calibration of the model parameters, specifically model calibrated on relatively sparse precipitation information might perform well on dense precipitation information while model calibrated on dense precipitation information fails on sparse precipitation information. Also, the model calibrated with the complete set of observed precipitation and run with incomplete observed data associated with the data estimated using multiple linear regressions, at the locations treated as

The cost of uniqueness in groundwater model calibration

Science.gov (United States)

Moore, Catherine; Doherty, John

2006-04-01

Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained. The "cost of uniqueness" is this: no matter which regularization methodology is employed, the inevitable consequence of its use is a loss of detail in the calibrated field. This, in turn, can lead to erroneous predictions made by a model that is ostensibly "well calibrated". Information made available as a by-product of the regularized inversion process allows the reasons for this loss of detail to be better understood. In particular, it is easily demonstrated that the estimated value for an hydraulic property at any point within a model domain is, in fact, a weighted average of the true hydraulic property over a much larger area. This averaging process causes loss of resolution in the estimated field. Where hydraulic conductivity is the hydraulic property being estimated, high averaging weights exist in areas that are strategically disposed with respect to measurement wells, while other areas may contribute very little to the estimated hydraulic conductivity at any point within the model domain, this possibly making the detection of hydraulic conductivity anomalies in these latter areas almost impossible. A study of the post-calibration parameter field covariance matrix allows further insights into the loss of system detail incurred through the calibration process to be gained. A comparison of pre- and post-calibration

Hand-eye calibration using a target registration error model.

Science.gov (United States)

Chen, Elvis C S; Morgan, Isabella; Jayarathne, Uditha; Ma, Burton; Peters, Terry M

2017-10-01

Surgical cameras are prevalent in modern operating theatres and are often used as a surrogate for direct vision. Visualisation techniques (e.g. image fusion) made possible by tracking the camera require accurate hand-eye calibration between the camera and the tracking system. The authors introduce the concept of 'guided hand-eye calibration', where calibration measurements are facilitated by a target registration error (TRE) model. They formulate hand-eye calibration as a registration problem between homologous point-line pairs. For each measurement, the position of a monochromatic ball-tip stylus (a point) and its projection onto the image (a line) is recorded, and the TRE of the resulting calibration is predicted using a TRE model. The TRE model is then used to guide the placement of the calibration tool, so that the subsequent measurement minimises the predicted TRE. Assessing TRE after each measurement produces accurate calibration using a minimal number of measurements. As a proof of principle, they evaluated guided calibration using a webcam and an endoscopic camera. Their endoscopic camera results suggest that millimetre TRE is achievable when at least 15 measurements are acquired with the tracker sensor ∼80 cm away on the laparoscope handle for a target ∼20 cm away from the camera.

Calibration of CORSIM models under saturated traffic flow conditions.

Science.gov (United States)

2013-09-01

This study proposes a methodology to calibrate microscopic traffic flow simulation models. : The proposed methodology has the capability to calibrate simultaneously all the calibration : parameters as well as demand patterns for any network topology....

Calibrating cellular automaton models for pedestrians walking through corners

Science.gov (United States)

Dias, Charitha; Lovreglio, Ruggiero

2018-05-01

Cellular Automata (CA) based pedestrian simulation models have gained remarkable popularity as they are simpler and easier to implement compared to other microscopic modeling approaches. However, incorporating traditional floor field representations in CA models to simulate pedestrian corner navigation behavior could result in unrealistic behaviors. Even though several previous studies have attempted to enhance CA models to realistically simulate pedestrian maneuvers around bends, such modifications have not been calibrated or validated against empirical data. In this study, two static floor field (SFF) representations, namely 'discrete representation' and 'continuous representation', are calibrated for CA-models to represent pedestrians' walking behavior around 90° bends. Trajectory data collected through a controlled experiment are used to calibrate these model representations. Calibration results indicate that although both floor field representations can represent pedestrians' corner navigation behavior, the 'continuous' representation fits the data better. Output of this study could be beneficial for enhancing the reliability of existing CA-based models by representing pedestrians' corner navigation behaviors more realistically.

Investigation of the transferability of hydrological models and a method to improve model calibration

Directory of Open Access Journals (Sweden)

G. Hartmann

2005-01-01

Full Text Available In order to find a model parameterization such that the hydrological model performs well even under different conditions, appropriate model performance measures have to be determined. A common performance measure is the Nash Sutcliffe efficiency. Usually it is calculated comparing observed and modelled daily values. In this paper a modified version is suggested in order to calibrate a model on different time scales simultaneously (days up to years. A spatially distributed hydrological model based on HBV concept was used. The modelling was applied on the Upper Neckar catchment, a mesoscale river in south western Germany with a basin size of about 4000 km2. The observation period 1961-1990 was divided into four different climatic periods, referred to as "warm", "cold", "wet" and "dry". These sub periods were used to assess the transferability of the model calibration and of the measure of performance. In a first step, the hydrological model was calibrated on a certain period and afterwards applied on the same period. Then, a validation was performed on the climatologically opposite period than the calibration, e.g. the model calibrated on the cold period was applied on the warm period. Optimal parameter sets were identified by an automatic calibration procedure based on Simulated Annealing. The results show, that calibrating a hydrological model that is supposed to handle short as well as long term signals becomes an important task. Especially the objective function has to be chosen very carefully.

Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection

Science.gov (United States)

Poole, Sandra; Vis, Marc; Knight, Rodney; Seibert, Jan

2017-01-01

Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.

Calibration of hydrological models using flow-duration curves

Directory of Open Access Journals (Sweden)

I. K. Westerberg

2011-07-01

Full Text Available The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1 uncertain discharge data, (2 variable sensitivity of different performance measures to different flow magnitudes, (3 influence of unknown input/output errors and (4 inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested – based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e.g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of

Logarithmic transformed statistical models in calibration

International Nuclear Information System (INIS)

Zeis, C.D.

1975-01-01

A general type of statistical model used for calibration of instruments having the property that the standard deviations of the observed values increase as a function of the mean value is described. The application to the Helix Counter at the Rocky Flats Plant is primarily from a theoretical point of view. The Helix Counter measures the amount of plutonium in certain types of chemicals. The method described can be used also for other calibrations. (U.S.)

Using genetic algorithms to calibrate a water quality model.

Science.gov (United States)

Liu, Shuming; Butler, David; Brazier, Richard; Heathwaite, Louise; Khu, Soon-Thiam

2007-03-15

With the increasing concern over the impact of diffuse pollution on water bodies, many diffuse pollution models have been developed in the last two decades. A common obstacle in using such models is how to determine the values of the model parameters. This is especially true when a model has a large number of parameters, which makes a full range of calibration expensive in terms of computing time. Compared with conventional optimisation approaches, soft computing techniques often have a faster convergence speed and are more efficient for global optimum searches. This paper presents an attempt to calibrate a diffuse pollution model using a genetic algorithm (GA). Designed to simulate the export of phosphorus from diffuse sources (agricultural land) and point sources (human), the Phosphorus Indicators Tool (PIT) version 1.1, on which this paper is based, consisted of 78 parameters. Previous studies have indicated the difficulty of full range model calibration due to the number of parameters involved. In this paper, a GA was employed to carry out the model calibration in which all parameters were involved. A sensitivity analysis was also performed to investigate the impact of operators in the GA on its effectiveness in optimum searching. The calibration yielded satisfactory results and required reasonable computing time. The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated. The annual P loss was predicted as 4.4 kg P/ha/yr, which showed a good fitness to the observed value.

Cosmic CARNage I: on the calibration of galaxy formation models

Science.gov (United States)

Knebe, Alexander; Pearce, Frazer R.; Gonzalez-Perez, Violeta; Thomas, Peter A.; Benson, Andrew; Asquith, Rachel; Blaizot, Jeremy; Bower, Richard; Carretero, Jorge; Castander, Francisco J.; Cattaneo, Andrea; Cora, Sofía A.; Croton, Darren J.; Cui, Weiguang; Cunnama, Daniel; Devriendt, Julien E.; Elahi, Pascal J.; Font, Andreea; Fontanot, Fabio; Gargiulo, Ignacio D.; Helly, John; Henriques, Bruno; Lee, Jaehyun; Mamon, Gary A.; Onions, Julian; Padilla, Nelson D.; Power, Chris; Pujol, Arnau; Ruiz, Andrés N.; Srisawat, Chaichalit; Stevens, Adam R. H.; Tollet, Edouard; Vega-Martínez, Cristian A.; Yi, Sukyoung K.

2018-04-01

We present a comparison of nine galaxy formation models, eight semi-analytical, and one halo occupation distribution model, run on the same underlying cold dark matter simulation (cosmological box of comoving width 125h-1 Mpc, with a dark-matter particle mass of 1.24 × 109h-1M⊙) and the same merger trees. While their free parameters have been calibrated to the same observational data sets using two approaches, they nevertheless retain some `memory' of any previous calibration that served as the starting point (especially for the manually tuned models). For the first calibration, models reproduce the observed z = 0 galaxy stellar mass function (SMF) within 3σ. The second calibration extended the observational data to include the z = 2 SMF alongside the z ˜ 0 star formation rate function, cold gas mass, and the black hole-bulge mass relation. Encapsulating the observed evolution of the SMF from z = 2 to 0 is found to be very hard within the context of the physics currently included in the models. We finally use our calibrated models to study the evolution of the stellar-to-halo mass (SHM) ratio. For all models, we find that the peak value of the SHM relation decreases with redshift. However, the trends seen for the evolution of the peak position as well as the mean scatter in the SHM relation are rather weak and strongly model dependent. Both the calibration data sets and model results are publicly available.

Stochastic calibration and learning in nonstationary hydroeconomic models

Science.gov (United States)

Maneta, M. P.; Howitt, R.

2014-05-01

Concern about water scarcity and adverse climate events over agricultural regions has motivated a number of efforts to develop operational integrated hydroeconomic models to guide adaptation and optimal use of water. Once calibrated, these models are used for water management and analysis assuming they remain valid under future conditions. In this paper, we present and demonstrate a methodology that permits the recursive calibration of economic models of agricultural production from noisy but frequently available data. We use a standard economic calibration approach, namely positive mathematical programming, integrated in a data assimilation algorithm based on the ensemble Kalman filter equations to identify the economic model parameters. A moving average kernel ensures that new and past information on agricultural activity are blended during the calibration process, avoiding loss of information and overcalibration for the conditions of a single year. A regularization constraint akin to the standard Tikhonov regularization is included in the filter to ensure its stability even in the presence of parameters with low sensitivity to observations. The results show that the implementation of the PMP methodology within a data assimilation framework based on the enKF equations is an effective method to calibrate models of agricultural production even with noisy information. The recursive nature of the method incorporates new information as an added value to the known previous observations of agricultural activity without the need to store historical information. The robustness of the method opens the door to the use of new remote sensing algorithms for operational water management.

High Accuracy Transistor Compact Model Calibrations

Energy Technology Data Exchange (ETDEWEB)

Hembree, Charles E. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Mar, Alan [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Robertson, Perry J. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

2015-09-01

Typically, transistors are modeled by the application of calibrated nominal and range models. These models consists of differing parameter values that describe the location and the upper and lower limits of a distribution of some transistor characteristic such as current capacity. Correspond- ingly, when using this approach, high degrees of accuracy of the transistor models are not expected since the set of models is a surrogate for a statistical description of the devices. The use of these types of models describes expected performances considering the extremes of process or transistor deviations. In contrast, circuits that have very stringent accuracy requirements require modeling techniques with higher accuracy. Since these accurate models have low error in transistor descriptions, these models can be used to describe part to part variations as well as an accurate description of a single circuit instance. Thus, models that meet these stipulations also enable the calculation of quantifi- cation of margins with respect to a functional threshold and uncertainties in these margins. Given this need, new model high accuracy calibration techniques for bipolar junction transis- tors have been developed and are described in this report.

A calibration hierarchy for risk models was defined: from utopia to empirical data.

Science.gov (United States)

Van Calster, Ben; Nieboer, Daan; Vergouwe, Yvonne; De Cock, Bavo; Pencina, Michael J; Steyerberg, Ewout W

2016-06-01

Calibrated risk models are vital for valid decision support. We define four levels of calibration and describe implications for model development and external validation of predictions. We present results based on simulated data sets. A common definition of calibration is "having an event rate of R% among patients with a predicted risk of R%," which we refer to as "moderate calibration." Weaker forms of calibration only require the average predicted risk (mean calibration) or the average prediction effects (weak calibration) to be correct. "Strong calibration" requires that the event rate equals the predicted risk for every covariate pattern. This implies that the model is fully correct for the validation setting. We argue that this is unrealistic: the model type may be incorrect, the linear predictor is only asymptotically unbiased, and all nonlinear and interaction effects should be correctly modeled. In addition, we prove that moderate calibration guarantees nonharmful decision making. Finally, results indicate that a flexible assessment of calibration in small validation data sets is problematic. Strong calibration is desirable for individualized decision support but unrealistic and counter productive by stimulating the development of overly complex models. Model development and external validation should focus on moderate calibration. Copyright © 2016 Elsevier Inc. All rights reserved.

Bayesian calibration of the Community Land Model using surrogates

Energy Technology Data Exchange (ETDEWEB)

Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Swiler, Laura Painton

2014-02-01

We present results from the Bayesian calibration of hydrological parameters of the Community Land Model (CLM), which is often used in climate simulations and Earth system models. A statistical inverse problem is formulated for three hydrological parameters, conditional on observations of latent heat surface fluxes over 48 months. Our calibration method uses polynomial and Gaussian process surrogates of the CLM, and solves the parameter estimation problem using a Markov chain Monte Carlo sampler. Posterior probability densities for the parameters are developed for two sites with different soil and vegetation covers. Our method also allows us to examine the structural error in CLM under two error models. We find that surrogate models can be created for CLM in most cases. The posterior distributions are more predictive than the default parameter values in CLM. Climatologically averaging the observations does not modify the parameters' distributions significantly. The structural error model reveals a correlation time-scale which can be used to identify the physical process that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.

Application of heuristic and machine-learning approach to engine model calibration

Science.gov (United States)

Cheng, Jie; Ryu, Kwang R.; Newman, C. E.; Davis, George C.

1993-03-01

Automation of engine model calibration procedures is a very challenging task because (1) the calibration process searches for a goal state in a huge, continuous state space, (2) calibration is often a lengthy and frustrating task because of complicated mutual interference among the target parameters, and (3) the calibration problem is heuristic by nature, and often heuristic knowledge for constraining a search cannot be easily acquired from domain experts. A combined heuristic and machine learning approach has, therefore, been adopted to improve the efficiency of model calibration. We developed an intelligent calibration program called ICALIB. It has been used on a daily basis for engine model applications, and has reduced the time required for model calibrations from many hours to a few minutes on average. In this paper, we describe the heuristic control strategies employed in ICALIB such as a hill-climbing search based on a state distance estimation function, incremental problem solution refinement by using a dynamic tolerance window, and calibration target parameter ordering for guiding the search. In addition, we present the application of a machine learning program called GID3* for automatic acquisition of heuristic rules for ordering target parameters.

Model Calibration of Exciter and PSS Using Extended Kalman Filter

Energy Technology Data Exchange (ETDEWEB)

Kalsi, Karanjit; Du, Pengwei; Huang, Zhenyu

2012-07-26

Power system modeling and controls continue to become more complex with the advent of smart grid technologies and large-scale deployment of renewable energy resources. As demonstrated in recent studies, inaccurate system models could lead to large-scale blackouts, thereby motivating the need for model calibration. Current methods of model calibration rely on manual tuning based on engineering experience, are time consuming and could yield inaccurate parameter estimates. In this paper, the Extended Kalman Filter (EKF) is used as a tool to calibrate exciter and Power System Stabilizer (PSS) models of a particular type of machine in the Western Electricity Coordinating Council (WECC). The EKF-based parameter estimation is a recursive prediction-correction process which uses the mismatch between simulation and measurement to adjust the model parameters at every time step. Numerical simulations using actual field test data demonstrate the effectiveness of the proposed approach in calibrating the parameters.

Multi-Site Calibration of Linear Reservoir Based Geomorphologic Rainfall-Runoff Models

Directory of Open Access Journals (Sweden)

Bahram Saeidifarzad

2014-09-01

Full Text Available Multi-site optimization of two adapted event-based geomorphologic rainfall-runoff models was presented using Non-dominated Sorting Genetic Algorithm (NSGA-II method for the South Fork Eel River watershed, California. The first model was developed based on Unequal Cascade of Reservoirs (UECR and the second model was presented as a modified version of Geomorphological Unit Hydrograph based on Nash’s model (GUHN. Two calibration strategies were considered as semi-lumped and semi-distributed for imposing (or unimposing the geomorphology relations in the models. The results of models were compared with Nash’s model. Obtained results using the observed data of two stations in the multi-site optimization framework showed reasonable efficiency values in both the calibration and the verification steps. The outcomes also showed that semi-distributed calibration of the modified GUHN model slightly outperformed other models in both upstream and downstream stations during calibration. Both calibration strategies for the developed UECR model during the verification phase showed slightly better performance in the downstream station, but in the upstream station, the modified GUHN model in the semi-lumped strategy slightly outperformed the other models. The semi-lumped calibration strategy could lead to logical lag time parameters related to the basin geomorphology and may be more suitable for data-based statistical analyses of the rainfall-runoff process.

SURFplus Model Calibration for PBX 9502

Energy Technology Data Exchange (ETDEWEB)

Menikoff, Ralph [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-12-06

The SURFplus reactive burn model is calibrated for the TATB based explosive PBX 9502 at three initial temperatures; hot (75 C), ambient (23 C) and cold (-55 C). The CJ state depends on the initial temperature due to the variation in the initial density and initial specific energy of the PBX reactants. For the reactants, a porosity model for full density TATB is used. This allows the initial PBX density to be set to its measured value even though the coeffcient of thermal expansion for the TATB and the PBX differ. The PBX products EOS is taken as independent of the initial PBX state. The initial temperature also affects the sensitivity to shock initiation. The model rate parameters are calibrated to Pop plot data, the failure diameter, the limiting detonation speed just above the failure diameters, and curvature effect data for small curvature.

Bayesian model calibration of computational models in velocimetry diagnosed dynamic compression experiments.

Energy Technology Data Exchange (ETDEWEB)

Brown, Justin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hund, Lauren [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-02-01

Dynamic compression experiments are being performed on complicated materials using increasingly complex drivers. The data produced in these experiments are beginning to reach a regime where traditional analysis techniques break down; requiring the solution of an inverse problem. A common measurement in dynamic experiments is an interface velocity as a function of time, and often this functional output can be simulated using a hydrodynamics code. Bayesian model calibration is a statistical framework to estimate inputs into a computational model in the presence of multiple uncertainties, making it well suited to measurements of this type. In this article, we apply Bayesian model calibration to high pressure (250 GPa) ramp compression measurements in tantalum. We address several issues speci c to this calibration including the functional nature of the output as well as parameter and model discrepancy identi ability. Speci cally, we propose scaling the likelihood function by an e ective sample size rather than modeling the autocorrelation function to accommodate the functional output and propose sensitivity analyses using the notion of `modularization' to assess the impact of experiment-speci c nuisance input parameters on estimates of material properties. We conclude that the proposed Bayesian model calibration procedure results in simple, fast, and valid inferences on the equation of state parameters for tantalum.

Using Active Learning for Speeding up Calibration in Simulation Models.

Science.gov (United States)

Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2016-07-01

Most cancer simulation models include unobservable parameters that determine disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality, and their values are typically estimated via a lengthy calibration procedure, which involves evaluating a large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We developed an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs and therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using the previously developed University of Wisconsin breast cancer simulation model (UWBCS). In a recent study, calibration of the UWBCS required the evaluation of 378 000 input parameter combinations to build a race-specific model, and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378 000 combinations. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. © The Author(s) 2015.

Grid based calibration of SWAT hydrological models

Directory of Open Access Journals (Sweden)

D. Gorgan

2012-07-01

Full Text Available The calibration and execution of large hydrological models, such as SWAT (soil and water assessment tool, developed for large areas, high resolution, and huge input data, need not only quite a long execution time but also high computation resources. SWAT hydrological model supports studies and predictions of the impact of land management practices on water, sediment, and agricultural chemical yields in complex watersheds. The paper presents the gSWAT application as a web practical solution for environmental specialists to calibrate extensive hydrological models and to run scenarios, by hiding the complex control of processes and heterogeneous resources across the grid based high computation infrastructure. The paper highlights the basic functionalities of the gSWAT platform, and the features of the graphical user interface. The presentation is concerned with the development of working sessions, interactive control of calibration, direct and basic editing of parameters, process monitoring, and graphical and interactive visualization of the results. The experiments performed on different SWAT models and the obtained results argue the benefits brought by the grid parallel and distributed environment as a solution for the processing platform. All the instances of SWAT models used in the reported experiments have been developed through the enviroGRIDS project, targeting the Black Sea catchment area.

Calibration of a stochastic health evolution model using NHIS data

Science.gov (United States)

Gupta, Aparna; Li, Zhisheng

2011-10-01

This paper presents and calibrates an individual's stochastic health evolution model. In this health evolution model, the uncertainty of health incidents is described by a stochastic process with a finite number of possible outcomes. We construct a comprehensive health status index (HSI) to describe an individual's health status, as well as a health risk factor system (RFS) to classify individuals into different risk groups. Based on the maximum likelihood estimation (MLE) method and the method of nonlinear least squares fitting, model calibration is formulated in terms of two mixed-integer nonlinear optimization problems. Using the National Health Interview Survey (NHIS) data, the model is calibrated for specific risk groups. Longitudinal data from the Health and Retirement Study (HRS) is used to validate the calibrated model, which displays good validation properties. The end goal of this paper is to provide a model and methodology, whose output can serve as a crucial component of decision support for strategic planning of health related financing and risk management.

Calibration of PMIS pavement performance prediction models.

Science.gov (United States)

2012-02-01

Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

A simple topography-driven, calibration-free runoff generation model

Science.gov (United States)

Gao, H.; Birkel, C.; Hrachowitz, M.; Tetzlaff, D.; Soulsby, C.; Savenije, H. H. G.

2017-12-01

Determining the amount of runoff generation from rainfall occupies a central place in rainfall-runoff modelling. Moreover, reading landscapes and developing calibration-free runoff generation models that adequately reflect land surface heterogeneities remains the focus of much hydrological research. In this study, we created a new method to estimate runoff generation - HAND-based Storage Capacity curve (HSC) which uses a topographic index (HAND, Height Above the Nearest Drainage) to identify hydrological similarity and partially the saturated areas of catchments. We then coupled the HSC model with the Mass Curve Technique (MCT) method to estimate root zone storage capacity (SuMax), and obtained the calibration-free runoff generation model HSC-MCT. Both the two models (HSC and HSC-MCT) allow us to estimate runoff generation and simultaneously visualize the spatial dynamic of saturated area. We tested the two models in the data-rich Bruntland Burn (BB) experimental catchment in Scotland with an unusual time series of the field-mapped saturation area extent. The models were subsequently tested in 323 MOPEX (Model Parameter Estimation Experiment) catchments in the United States. HBV and TOPMODEL were used as benchmarks. We found that the HSC performed better in reproducing the spatio-temporal pattern of the observed saturated areas in the BB catchment compared with TOPMODEL which is based on the topographic wetness index (TWI). The HSC also outperformed HBV and TOPMODEL in the MOPEX catchments for both calibration and validation. Despite having no calibrated parameters, the HSC-MCT model also performed comparably well with the calibrated HBV and TOPMODEL, highlighting the robustness of the HSC model to both describe the spatial distribution of the root zone storage capacity and the efficiency of the MCT method to estimate the SuMax. Moreover, the HSC-MCT model facilitated effective visualization of the saturated area, which has the potential to be used for broader

A single model procedure for tank calibration function estimation

International Nuclear Information System (INIS)

York, J.C.; Liebetrau, A.M.

1995-01-01

Reliable tank calibrations are a vital component of any measurement control and accountability program for bulk materials in a nuclear reprocessing facility. Tank volume calibration functions used in nuclear materials safeguards and accountability programs are typically constructed from several segments, each of which is estimated independently. Ideally, the segments correspond to structural features in the tank. In this paper the authors use an extension of the Thomas-Liebetrau model to estimate the entire calibration function in a single step. This procedure automatically takes significant run-to-run differences into account and yields an estimate of the entire calibration function in one operation. As with other procedures, the first step is to define suitable calibration segments. Next, a polynomial of low degree is specified for each segment. In contrast with the conventional practice of constructing a separate model for each segment, this information is used to set up the design matrix for a single model that encompasses all of the calibration data. Estimation of the model parameters is then done using conventional statistical methods. The method described here has several advantages over traditional methods. First, modeled run-to-run differences can be taken into account automatically at the estimation step. Second, no interpolation is required between successive segments. Third, variance estimates are based on all the data, rather than that from a single segment, with the result that discontinuities in confidence intervals at segment boundaries are eliminated. Fourth, the restrictive assumption of the Thomas-Liebetrau method, that the measured volumes be the same for all runs, is not required. Finally, the proposed methods are readily implemented using standard statistical procedures and widely-used software packages

A global model for residential energy use: Uncertainty in calibration to regional data

International Nuclear Information System (INIS)

van Ruijven, Bas; van Vuuren, Detlef P.; de Vries, Bert; van der Sluijs, Jeroen P.

2010-01-01

Uncertainties in energy demand modelling allow for the development of different models, but also leave room for different calibrations of a single model. We apply an automated model calibration procedure to analyse calibration uncertainty of residential sector energy use modelling in the TIMER 2.0 global energy model. This model simulates energy use on the basis of changes in useful energy intensity, technology development (AEEI) and price responses (PIEEI). We find that different implementations of these factors yield behavioural model results. Model calibration uncertainty is identified as influential source for variation in future projections: amounting 30% to 100% around the best estimate. Energy modellers should systematically account for this and communicate calibration uncertainty ranges. (author)

Predictive sensor based x-ray calibration using a physical model

International Nuclear Information System (INIS)

Fuente, Matias de la; Lutz, Peter; Wirtz, Dieter C.; Radermacher, Klaus

2007-01-01

Many computer assisted surgery systems are based on intraoperative x-ray images. To achieve reliable and accurate results these images have to be calibrated concerning geometric distortions, which can be distinguished between constant distortions and distortions caused by magnetic fields. Instead of using an intraoperative calibration phantom that has to be visible within each image resulting in overlaying markers, the presented approach directly takes advantage of the physical background of the distortions. Based on a computed physical model of an image intensifier and a magnetic field sensor, an online compensation of distortions can be achieved without the need of an intraoperative calibration phantom. The model has to be adapted once to each specific image intensifier through calibration, which is based on an optimization algorithm systematically altering the physical model parameters, until a minimal error is reached. Once calibrated, the model is able to predict the distortions caused by the measured magnetic field vector and build an appropriate dewarping function. The time needed for model calibration is not yet optimized and takes up to 4 h on a 3 GHz CPU. In contrast, the time needed for distortion correction is less than 1 s and therefore absolutely acceptable for intraoperative use. First evaluations showed that by using the model based dewarping algorithm the distortions of an XRII with a 21 cm FOV could be significantly reduced. The model was able to predict and compensate distortions by approximately 80% to a remaining error of 0.45 mm (max) (0.19 mm rms)

Calibration models for high enthalpy calorimetric probes.

Science.gov (United States)

Kannel, A

1978-07-01

The accuracy of gas-aspirated liquid-cooled calorimetric probes used for measuring the enthalpy of high-temperature gas streams is studied. The error in the differential temperature measurements caused by internal and external heat transfer interactions is considered and quantified by mathematical models. The analysis suggests calibration methods for the evaluation of dimensionless heat transfer parameters in the models, which then can give a more accurate value for the enthalpy of the sample. Calibration models for four types of calorimeters are applied to results from the literature and from our own experiments: a circular slit calorimeter developed by the author, single-cooling jacket probe, double-cooling jacket probe, and split-flow cooling jacket probe. The results show that the models are useful for describing and correcting the temperature measurements.

SURF Model Calibration Strategy

Energy Technology Data Exchange (ETDEWEB)

Menikoff, Ralph [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-03-10

SURF and SURFplus are high explosive reactive burn models for shock initiation and propagation of detonation waves. They are engineering models motivated by the ignition & growth concept of high spots and for SURFplus a second slow reaction for the energy release from carbon clustering. A key feature of the SURF model is that there is a partial decoupling between model parameters and detonation properties. This enables reduced sets of independent parameters to be calibrated sequentially for the initiation and propagation regimes. Here we focus on a methodology for tting the initiation parameters to Pop plot data based on 1-D simulations to compute a numerical Pop plot. In addition, the strategy for tting the remaining parameters for the propagation regime and failure diameter is discussed.

Modeling and Calibration of a Novel One-Mirror Galvanometric Laser Scanner

Directory of Open Access Journals (Sweden)

Chengyi Yu

2017-01-01

Full Text Available A laser stripe sensor has limited application when a point cloud of geometric samples on the surface of the object needs to be collected, so a galvanometric laser scanner is designed by using a one-mirror galvanometer element as its mechanical device to drive the laser stripe to sweep along the object. A novel mathematical model is derived for the proposed galvanometer laser scanner without any position assumptions and then a model-driven calibration procedure is proposed. Compared with available model-driven approaches, the influence of machining and assembly errors is considered in the proposed model. Meanwhile, a plane-constraint-based approach is proposed to extract a large number of calibration points effectively and accurately to calibrate the galvanometric laser scanner. Repeatability and accuracy of the galvanometric laser scanner are evaluated on the automobile production line to verify the efficiency and accuracy of the proposed calibration method. Experimental results show that the proposed calibration approach yields similar measurement performance compared with a look-up table calibration method.

Testing of a one dimensional model for Field II calibration

DEFF Research Database (Denmark)

Bæk, David; Jensen, Jørgen Arendt; Willatzen, Morten

2008-01-01

Field II is a program for simulating ultrasound transducer fields. It is capable of calculating the emitted and pulse-echoed fields for both pulsed and continuous wave transducers. To make it fully calibrated a model of the transducer’s electro-mechanical impulse response must be included. We...... examine an adapted one dimensional transducer model originally proposed by Willatzen [9] to calibrate Field II. This model is modified to calculate the required impulse responses needed by Field II for a calibrated field pressure and external circuit current calculation. The testing has been performed...... to the calibrated Field II program for 1, 4, and 10 cycle excitations. Two parameter sets were applied for modeling, one real valued Pz27 parameter set, manufacturer supplied, and one complex valued parameter set found in literature, Alguer´o et al. [11]. The latter implicitly accounts for attenuation. Results show...

Comparison of global optimization approaches for robust calibration of hydrologic model parameters

Science.gov (United States)

Jung, I. W.

2015-12-01

Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

The effects of model complexity and calibration period on groundwater recharge simulations

Science.gov (United States)

Moeck, Christian; Van Freyberg, Jana; Schirmer, Mario

2017-04-01

A significant number of groundwater recharge models exist that vary in terms of complexity (i.e., structure and parametrization). Typically, model selection and conceptualization is very subjective and can be a key source of uncertainty in the recharge simulations. Another source of uncertainty is the implicit assumption that model parameters, calibrated over historical periods, are also valid for the simulation period. To the best of our knowledge there is no systematic evaluation of the effect of the model complexity and calibration strategy on the performance of recharge models. To address this gap, we utilized a long-term recharge data set (20 years) from a large weighting lysimeter. We performed a differential split sample test with four groundwater recharge models that vary in terms of complexity. They were calibrated using six calibration periods with climatically contrasting conditions in a constrained Monte Carlo approach. Despite the climatically contrasting conditions, all models performed similarly well during the calibration. However, during validation a clear effect of the model structure on model performance was evident. The more complex, physically-based models predicted recharge best, even when calibration and prediction periods had very different climatic conditions. In contrast, more simplistic soil-water balance and lumped model performed poorly under such conditions. For these models we found a strong dependency on the chosen calibration period. In particular, our analysis showed that this can have relevant implications when using recharge models as decision-making tools in a broad range of applications (e.g. water availability, climate change impact studies, water resource management, etc.).

Model Robust Calibration: Method and Application to Electronically-Scanned Pressure Transducers

Science.gov (United States)

Walker, Eric L.; Starnes, B. Alden; Birch, Jeffery B.; Mays, James E.

2010-01-01

This article presents the application of a recently developed statistical regression method to the controlled instrument calibration problem. The statistical method of Model Robust Regression (MRR), developed by Mays, Birch, and Starnes, is shown to improve instrument calibration by reducing the reliance of the calibration on a predetermined parametric (e.g. polynomial, exponential, logarithmic) model. This is accomplished by allowing fits from the predetermined parametric model to be augmented by a certain portion of a fit to the residuals from the initial regression using a nonparametric (locally parametric) regression technique. The method is demonstrated for the absolute scale calibration of silicon-based pressure transducers.

Calibration process of highly parameterized semi-distributed hydrological model

Science.gov (United States)

Vidmar, Andrej; Brilly, Mitja

2017-04-01

Hydrological phenomena take place in the hydrological system, which is governed by nature, and are essentially stochastic. These phenomena are unique, non-recurring, and changeable across space and time. Since any river basin with its own natural characteristics and any hydrological event therein, are unique, this is a complex process that is not researched enough. Calibration is a procedure of determining the parameters of a model that are not known well enough. Input and output variables and mathematical model expressions are known, while only some parameters are unknown, which are determined by calibrating the model. The software used for hydrological modelling nowadays is equipped with sophisticated algorithms for calibration purposes without possibility to manage process by modeler. The results are not the best. We develop procedure for expert driven process of calibration. We use HBV-light-CLI hydrological model which has command line interface and coupling it with PEST. PEST is parameter estimation tool which is used widely in ground water modeling and can be used also on surface waters. Process of calibration managed by expert directly, and proportionally to the expert knowledge, affects the outcome of the inversion procedure and achieves better results than if the procedure had been left to the selected optimization algorithm. First step is to properly define spatial characteristic and structural design of semi-distributed model including all morphological and hydrological phenomena, like karstic area, alluvial area and forest area. This step includes and requires geological, meteorological, hydraulic and hydrological knowledge of modeler. Second step is to set initial parameter values at their preferred values based on expert knowledge. In this step we also define all parameter and observation groups. Peak data are essential in process of calibration if we are mainly interested in flood events. Each Sub Catchment in the model has own observations group

A mathematical model for camera calibration based on straight lines

Directory of Open Access Journals (Sweden)

Antonio M. G. Tommaselli

2005-12-01

Full Text Available In other to facilitate the automation of camera calibration process, a mathematical model using straight lines was developed, which is based on the equivalent planes mathematical model. Parameter estimation of the developed model is achieved by the Least Squares Method with Conditions and Observations. The same method of adjustment was used to implement camera calibration with bundles, which is based on points. Experiments using simulated and real data have shown that the developed model based on straight lines gives results comparable to the conventional method with points. Details concerning the mathematical development of the model and experiments with simulated and real data will be presented and the results with both methods of camera calibration, with straight lines and with points, will be compared.

Model calibration and beam control systems for storage rings

International Nuclear Information System (INIS)

Corbett, W.J.; Lee, M.J.; Ziemann, V.

1993-04-01

Electron beam storage rings and linear accelerators are rapidly gaining worldwide popularity as scientific devices for the production of high-brightness synchrotron radiation. Today, everybody agrees that there is a premium on calibrating the storage ring model and determining errors in the machine as soon as possible after the beam is injected. In addition, the accurate optics model enables machine operators to predictably adjust key performance parameters, and allows reliable identification of new errors that occur during operation of the machine. Since the need for model calibration and beam control systems is common to all storage rings, software packages should be made that are portable between different machines. In this paper, we report on work directed toward achieving in-situ calibration of the optics model, detection of alignment errors, and orbit control techniques, with an emphasis on developing a portable system incorporating these tools

Improvement, calibration and validation of a distributed hydrological model over France

Directory of Open Access Journals (Sweden)

P. Quintana Seguí

2009-02-01

Full Text Available The hydrometeorological model SAFRAN-ISBA-MODCOU (SIM computes water and energy budgets on the land surface and riverflows and the level of several aquifers at the scale of France. SIM is composed of a meteorological analysis system (SAFRAN, a land surface model (ISBA, and a hydrogeological model (MODCOU. In this study, an exponential profile of hydraulic conductivity at saturation is introduced to the model and its impact analysed. It is also studied how calibration modifies the performance of the model. A very simple method of calibration is implemented and applied to the parameters of hydraulic conductivity and subgrid runoff. The study shows that a better description of the hydraulic conductivity of the soil is important to simulate more realistic discharges. It also shows that the calibrated model is more robust than the original SIM. In fact, the calibration mainly affects the processes related to the dynamics of the flow (drainage and runoff, and the rest of relevant processes (like evaporation remain stable. It is also proven that it is only worth introducing the new empirical parameterization of hydraulic conductivity if it is accompanied by a calibration of its parameters, otherwise the simulations can be degraded. In conclusion, it is shown that the new parameterization is necessary to obtain good simulations. Calibration is a tool that must be used to improve the performance of distributed models like SIM that have some empirical parameters.

Calibration of Mine Ventilation Network Models Using the Non-Linear Optimization Algorithm

Directory of Open Access Journals (Sweden)

Guang Xu

2017-12-01

Full Text Available Effective ventilation planning is vital to underground mining. To ensure stable operation of the ventilation system and to avoid airflow disorder, mine ventilation network (MVN models have been widely used in simulating and optimizing the mine ventilation system. However, one of the challenges for MVN model simulation is that the simulated airflow distribution results do not match the measured data. To solve this problem, a simple and effective calibration method is proposed based on the non-linear optimization algorithm. The calibrated model not only makes simulated airflow distribution results in accordance with the on-site measured data, but also controls the errors of other parameters within a minimum range. The proposed method was then applied to calibrate an MVN model in a real case, which is built based on ventilation survey results and Ventsim software. Finally, airflow simulation experiments are carried out respectively using data before and after calibration, whose results were compared and analyzed. This showed that the simulated airflows in the calibrated model agreed much better to the ventilation survey data, which verifies the effectiveness of calibrating method.

An Open-Source Auto-Calibration Routine Supporting the Stormwater Management Model

Science.gov (United States)

Tiernan, E. D.; Hodges, B. R.

2017-12-01

The stormwater management model (SWMM) is a clustered model that relies on subcatchment-averaged parameter assignments to correctly capture catchment stormwater runoff behavior. Model calibration is considered a critical step for SWMM performance, an arduous task that most stormwater management designers undertake manually. This research presents an open-source, automated calibration routine that increases the efficiency and accuracy of the model calibration process. The routine makes use of a preliminary sensitivity analysis to reduce the dimensions of the parameter space, at which point a multi-objective function, genetic algorithm (modified Non-dominated Sorting Genetic Algorithm II) determines the Pareto front for the objective functions within the parameter space. The solutions on this Pareto front represent the optimized parameter value sets for the catchment behavior that could not have been reasonably obtained through manual calibration.

Hydrological processes and model representation: impact of soft data on calibration

Science.gov (United States)

J.G. Arnold; M.A. Youssef; H. Yen; M.J. White; A.Y. Sheshukov; A.M. Sadeghi; D.N. Moriasi; J.L. Steiner; Devendra Amatya; R.W. Skaggs; E.B. Haney; J. Jeong; M. Arabi; P.H. Gowda

2015-01-01

Hydrologic and water quality models are increasingly used to determine the environmental impacts of climate variability and land management. Due to differing model objectives and differences in monitored data, there are currently no universally accepted procedures for model calibration and validation in the literature. In an effort to develop accepted model calibration...

Stochastic isotropic hyperelastic materials: constitutive calibration and model selection

Science.gov (United States)

Mihai, L. Angela; Woolley, Thomas E.; Goriely, Alain

2018-03-01

Biological and synthetic materials often exhibit intrinsic variability in their elastic responses under large strains, owing to microstructural inhomogeneity or when elastic data are extracted from viscoelastic mechanical tests. For these materials, although hyperelastic models calibrated to mean data are useful, stochastic representations accounting also for data dispersion carry extra information about the variability of material properties found in practical applications. We combine finite elasticity and information theories to construct homogeneous isotropic hyperelastic models with random field parameters calibrated to discrete mean values and standard deviations of either the stress-strain function or the nonlinear shear modulus, which is a function of the deformation, estimated from experimental tests. These quantities can take on different values, corresponding to possible outcomes of the experiments. As multiple models can be derived that adequately represent the observed phenomena, we apply Occam's razor by providing an explicit criterion for model selection based on Bayesian statistics. We then employ this criterion to select a model among competing models calibrated to experimental data for rubber and brain tissue under single or multiaxial loads.

A critical comparison of systematic calibration protocols for activated sludge models: a SWOT analysis.

Science.gov (United States)

Sin, Gürkan; Van Hulle, Stijn W H; De Pauw, Dirk J W; van Griensven, Ann; Vanrolleghem, Peter A

2005-07-01

Modelling activated sludge systems has gained an increasing momentum after the introduction of activated sludge models (ASMs) in 1987. Application of dynamic models for full-scale systems requires essentially a calibration of the chosen ASM to the case under study. Numerous full-scale model applications have been performed so far which were mostly based on ad hoc approaches and expert knowledge. Further, each modelling study has followed a different calibration approach: e.g. different influent wastewater characterization methods, different kinetic parameter estimation methods, different selection of parameters to be calibrated, different priorities within the calibration steps, etc. In short, there was no standard approach in performing the calibration study, which makes it difficult, if not impossible, to (1) compare different calibrations of ASMs with each other and (2) perform internal quality checks for each calibration study. To address these concerns, systematic calibration protocols have recently been proposed to bring guidance to the modeling of activated sludge systems and in particular to the calibration of full-scale models. In this contribution four existing calibration approaches (BIOMATH, HSG, STOWA and WERF) will be critically discussed using a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis. It will also be assessed in what way these approaches can be further developed in view of further improving the quality of ASM calibration. In this respect, the potential of automating some steps of the calibration procedure by use of mathematical algorithms is highlighted.

Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

Energy Technology Data Exchange (ETDEWEB)

and Ben Polly, Joseph Robertson [National Renewable Energy Lab. (NREL), Golden, CO (United States); Polly, Ben [National Renewable Energy Lab. (NREL), Golden, CO (United States); Collis, Jon [Colorado School of Mines, Golden, CO (United States)

2013-09-01

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define "explicit" input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.

Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation

Energy Technology Data Exchange (ETDEWEB)

Robertson, J.; Polly, B.; Collis, J.

2013-09-01

This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define 'explicit' input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.

Bayesian calibration of power plant models for accurate performance prediction

International Nuclear Information System (INIS)

Boksteen, Sowande Z.; Buijtenen, Jos P. van; Pecnik, Rene; Vecht, Dick van der

2014-01-01

Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions

Evaluation of multivariate calibration models transferred between spectroscopic instruments

DEFF Research Database (Denmark)

Eskildsen, Carl Emil Aae; Hansen, Per W.; Skov, Thomas

2016-01-01

In a setting where multiple spectroscopic instruments are used for the same measurements it may be convenient to develop the calibration model on a single instrument and then transfer this model to the other instruments. In the ideal scenario, all instruments provide the same predictions for the ......In a setting where multiple spectroscopic instruments are used for the same measurements it may be convenient to develop the calibration model on a single instrument and then transfer this model to the other instruments. In the ideal scenario, all instruments provide the same predictions...... for the same samples using the transferred model. However, sometimes the success of a model transfer is evaluated by comparing the transferred model predictions with the reference values. This is not optimal, as uncertainties in the reference method will impact the evaluation. This paper proposes a new method...... for calibration model transfer evaluation. The new method is based on comparing predictions from different instruments, rather than comparing predictions and reference values. A total of 75 flour samples were available for the study. All samples were measured on ten near infrared (NIR) instruments from two...

Model calibration for building energy efficiency simulation

International Nuclear Information System (INIS)

Mustafaraj, Giorgio; Marini, Dashamir; Costa, Andrea; Keane, Marcus

2014-01-01

Highlights: • Developing a 3D model relating to building architecture, occupancy and HVAC operation. • Two calibration stages developed, final model providing accurate results. • Using an onsite weather station for generating the weather data file in EnergyPlus. • Predicting thermal behaviour of underfloor heating, heat pump and natural ventilation. • Monthly energy saving opportunities related to heat pump of 20–27% was identified. - Abstract: This research work deals with an Environmental Research Institute (ERI) building where an underfloor heating system and natural ventilation are the main systems used to maintain comfort condition throughout 80% of the building areas. Firstly, this work involved developing a 3D model relating to building architecture, occupancy and HVAC operation. Secondly, the calibration methodology, which consists of two levels, was then applied in order to insure accuracy and reduce the likelihood of errors. To further improve the accuracy of calibration a historical weather data file related to year 2011, was created from the on-site local weather station of ERI building. After applying the second level of calibration process, the values of Mean bias Error (MBE) and Cumulative Variation of Root Mean Squared Error (CV(RMSE)) on hourly based analysis for heat pump electricity consumption varied within the following ranges: (MBE) hourly from −5.6% to 7.5% and CV(RMSE) hourly from 7.3% to 25.1%. Finally, the building was simulated with EnergyPlus to identify further possibilities of energy savings supplied by a water to water heat pump to underfloor heating system. It found that electricity consumption savings from the heat pump can vary between 20% and 27% on monthly bases

Calibration of two complex ecosystem models with different likelihood functions

Science.gov (United States)

Hidy, Dóra; Haszpra, László; Pintér, Krisztina; Nagy, Zoltán; Barcza, Zoltán

2014-05-01

The biosphere is a sensitive carbon reservoir. Terrestrial ecosystems were approximately carbon neutral during the past centuries, but they became net carbon sinks due to climate change induced environmental change and associated CO2 fertilization effect of the atmosphere. Model studies and measurements indicate that the biospheric carbon sink can saturate in the future due to ongoing climate change which can act as a positive feedback. Robustness of carbon cycle models is a key issue when trying to choose the appropriate model for decision support. The input parameters of the process-based models are decisive regarding the model output. At the same time there are several input parameters for which accurate values are hard to obtain directly from experiments or no local measurements are available. Due to the uncertainty associated with the unknown model parameters significant bias can be experienced if the model is used to simulate the carbon and nitrogen cycle components of different ecosystems. In order to improve model performance the unknown model parameters has to be estimated. We developed a multi-objective, two-step calibration method based on Bayesian approach in order to estimate the unknown parameters of PaSim and Biome-BGC models. Biome-BGC and PaSim are a widely used biogeochemical models that simulate the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere, and within the components of the terrestrial ecosystems (in this research the developed version of Biome-BGC is used which is referred as BBGC MuSo). Both models were calibrated regardless the simulated processes and type of model parameters. The calibration procedure is based on the comparison of measured data with simulated results via calculating a likelihood function (degree of goodness-of-fit between simulated and measured data). In our research different likelihood function formulations were used in order to examine the effect of the different model

Efficient Calibration of Distributed Catchment Models Using Perceptual Understanding and Hydrologic Signatures

Science.gov (United States)

Hutton, C.; Wagener, T.; Freer, J. E.; Duffy, C.; Han, D.

2015-12-01

Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models may contain a large number of model parameters which are computationally expensive to calibrate. Even when calibration is possible, insufficient data can result in model parameter and structural equifinality. In order to help reduce the space of feasible models and supplement traditional outlet discharge calibration data, semi-quantitative information (e.g. knowledge of relative groundwater levels), may also be used to identify behavioural models when applied to constrain spatially distributed predictions of states and fluxes. The challenge is to combine these different sources of information together to identify a behavioural region of state-space, and efficiently search a large, complex parameter space to identify behavioural parameter sets that produce predictions that fall within this behavioural region. Here we present a methodology to incorporate different sources of data to efficiently calibrate distributed catchment models. Metrics of model performance may be derived from multiple sources of data (e.g. perceptual understanding and measured or regionalised hydrologic signatures). For each metric, an interval or inequality is used to define the behaviour of the catchment system, accounting for data uncertainties. These intervals are then combined to produce a hyper-volume in state space. The state space is then recast as a multi-objective optimisation problem, and the Borg MOEA is applied to first find, and then populate the hyper-volume, thereby identifying acceptable model parameter sets. We apply the methodology to calibrate the PIHM model at Plynlimon, UK by incorporating perceptual and hydrologic data into the calibration problem. Furthermore, we explore how to improve calibration efficiency through search initialisation from shorter model runs.

Nitrous oxide emissions from cropland: a procedure for calibrating the DayCent biogeochemical model using inverse modelling

Science.gov (United States)

Rafique, Rashad; Fienen, Michael N.; Parkin, Timothy B.; Anex, Robert P.

2013-01-01

DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameterized through a traditional “trial and error” approach and has not been calibrated using statistical inverse modelling (i.e. algorithmic parameter estimation). The aim of this study is to establish and demonstrate a procedure for calibration of DayCent to improve estimation of GHG emissions. We coupled DayCent with the parameter estimation (PEST) software for inverse modelling. The PEST software can be used for calibration through regularized inversion as well as model sensitivity and uncertainty analysis. The DayCent model was analysed and calibrated using N2O flux data collected over 2 years at the Iowa State University Agronomy and Agricultural Engineering Research Farms, Boone, IA. Crop year 2003 data were used for model calibration and 2004 data were used for validation. The optimization of DayCent model parameters using PEST significantly reduced model residuals relative to the default DayCent parameter values. Parameter estimation improved the model performance by reducing the sum of weighted squared residual difference between measured and modelled outputs by up to 67 %. For the calibration period, simulation with the default model parameter values underestimated mean daily N2O flux by 98 %. After parameter estimation, the model underestimated the mean daily fluxes by 35 %. During the validation period, the calibrated model reduced sum of weighted squared residuals by 20 % relative to the default simulation. Sensitivity analysis performed provides important insights into the model structure providing guidance for model improvement.

Validation and calibration of structural models that combine information from multiple sources.

Science.gov (United States)

Dahabreh, Issa J; Wong, John B; Trikalinos, Thomas A

2017-02-01

Mathematical models that attempt to capture structural relationships between their components and combine information from multiple sources are increasingly used in medicine. Areas covered: We provide an overview of methods for model validation and calibration and survey studies comparing alternative approaches. Expert commentary: Model validation entails a confrontation of models with data, background knowledge, and other models, and can inform judgments about model credibility. Calibration involves selecting parameter values to improve the agreement of model outputs with data. When the goal of modeling is quantitative inference on the effects of interventions or forecasting, calibration can be viewed as estimation. This view clarifies issues related to parameter identifiability and facilitates formal model validation and the examination of consistency among different sources of information. In contrast, when the goal of modeling is the generation of qualitative insights about the modeled phenomenon, calibration is a rather informal process for selecting inputs that result in model behavior that roughly reproduces select aspects of the modeled phenomenon and cannot be equated to an estimation procedure. Current empirical research on validation and calibration methods consists primarily of methodological appraisals or case-studies of alternative techniques and cannot address the numerous complex and multifaceted methodological decisions that modelers must make. Further research is needed on different approaches for developing and validating complex models that combine evidence from multiple sources.

Optical model and calibration of a sun tracker

International Nuclear Information System (INIS)

Volkov, Sergei N.; Samokhvalov, Ignatii V.; Cheong, Hai Du; Kim, Dukhyeon

2016-01-01

Sun trackers are widely used to investigate scattering and absorption of solar radiation in the Earth's atmosphere. We present a method for optimization of the optical altazimuth sun tracker model with output radiation direction aligned with the axis of a stationary spectrometer. The method solves the problem of stability loss in tracker pointing at the Sun near the zenith. An optimal method for tracker calibration at the measurement site is proposed in the present work. A method of moving calibration is suggested for mobile applications in the presence of large temperature differences and errors in the alignment of the optical system of the tracker. - Highlights: • We present an optimal optical sun tracker model for atmospheric spectroscopy. • The problem of loss of stability of tracker pointing at the Sun has been solved. • We propose an optimal method for tracker calibration at a measurement site. • Test results demonstrate the efficiency of the proposed optimization methods.

Evaluation of an ASM1 Model Calibration Precedure on a Municipal-Industrial Wastewater Treatment Plant

DEFF Research Database (Denmark)

Petersen, Britta; Gernaey, Krist; Henze, Mogens

2002-01-01

treatment plant. In the case that was studied it was important to have a detailed description of the process dynamics, since the model was to be used as the basis for optimisation scenarios in a later phase. Therefore, a complete model calibration procedure was applied including: (1) a description......The purpose of the calibrated model determines how to approach a model calibration, e.g. which information is needed and to which level of detail the model should be calibrated. A systematic model calibration procedure was therefore defined and evaluated for a municipal–industrial wastewater...

Secondary clarifier hybrid model calibration in full scale pulp and paper activated sludge wastewater treatment

Energy Technology Data Exchange (ETDEWEB)

Sreckovic, G.; Hall, E.R. [British Columbia Univ., Dept. of Civil Engineering, Vancouver, BC (Canada); Thibault, J. [Laval Univ., Dept. of Chemical Engineering, Ste-Foy, PQ (Canada); Savic, D. [Exeter Univ., School of Engineering, Exeter (United Kingdom)

1999-05-01

The issue of proper model calibration techniques applied to mechanistic mathematical models relating to activated sludge systems was discussed. Such calibrations are complex because of the non-linearity and multi-model objective functions of the process. This paper presents a hybrid model which was developed using two techniques to model and calibrate secondary clarifier parts of an activated sludge system. Genetic algorithms were used to successfully calibrate the settler mechanistic model, and neural networks were used to reduce the error between the mechanistic model output and real world data. Results of the modelling study show that the long term response of a one-dimensional settler mechanistic model calibrated by genetic algorithms and compared to full scale plant data can be improved by coupling the calibrated mechanistic model to as black-box model, such as a neural network. 11 refs., 2 figs.

CALIBRATING THE JOHNSON-HOLMQUIST CERAMIC MODEL FOR SIC USING CTH

International Nuclear Information System (INIS)

Cazamias, J. U.; Bilyk, S. R.

2009-01-01

The Johnson-Holmquist ceramic material model has been calibrated and successfully applied to numerically simulate ballistic events using the Lagrangian code EPIC. While the majority of the constants are ''physics'' based, two of the constants for the failed material response are calibrated using ballistic experiments conducted on a confined cylindrical ceramic target. The maximum strength of the failed ceramic is calibrated by matching the penetration velocity. The second refers to the equivalent plastic strain at failure under constant pressure and is calibrated using the dwell time. Use of these two constants in the CTH Eulerian hydrocode does not predict the ballistic response. This difference may be due to the phenomenological nature of the model and the different numerical schemes used by the codes. This paper determines the aforementioned material constants for SiC suitable for simulating ballistic events using CTH.

Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

Science.gov (United States)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters

Iowa calibration of MEPDG performance prediction models.

Science.gov (United States)

2013-06-01

This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

Effect of calibration data series length on performance and optimal parameters of hydrological model

Directory of Open Access Journals (Sweden)

Chuan-zhe Li

2010-12-01

Full Text Available In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments (data are non-continuous and fragmental in some catchments, we used non-continuous calibration periods for more independent streamflow data for SIMHYD (simple hydrology model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization (PSO method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.

Effect of Using Extreme Years in Hydrologic Model Calibration Performance

Science.gov (United States)

Goktas, R. K.; Tezel, U.; Kargi, P. G.; Ayvaz, T.; Tezyapar, I.; Mesta, B.; Kentel, E.

2017-12-01

Hydrological models are useful in predicting and developing management strategies for controlling the system behaviour. Specifically they can be used for evaluating streamflow at ungaged catchments, effect of climate change, best management practices on water resources, or identification of pollution sources in a watershed. This study is a part of a TUBITAK project named "Development of a geographical information system based decision-making tool for water quality management of Ergene Watershed using pollutant fingerprints". Within the scope of this project, first water resources in Ergene Watershed is studied. Streamgages found in the basin are identified and daily streamflow measurements are obtained from State Hydraulic Works of Turkey. Streamflow data is analysed using box-whisker plots, hydrographs and flow-duration curves focusing on identification of extreme periods, dry or wet. Then a hydrological model is developed for Ergene Watershed using HEC-HMS in the Watershed Modeling System (WMS) environment. The model is calibrated for various time periods including dry and wet ones and the performance of calibration is evaluated using Nash-Sutcliffe Efficiency (NSE), correlation coefficient, percent bias (PBIAS) and root mean square error. It is observed that calibration period affects the model performance, and the main purpose of the development of the hydrological model should guide calibration period selection. Acknowledgement: This study is funded by The Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 115Y064.

Matching Images to Models: Camera Calibration for 3-D Surface Reconstruction

Science.gov (United States)

Morris, Robin D.; Smelyanskiy, Vadim N.; Cheeseman. Peter C.; Norvig, Peter (Technical Monitor)

2001-01-01

In a previous paper we described a system which recursively recovers a super-resolved three dimensional surface model from a set of images of the surface. In that paper we assumed that the camera calibration for each image was known. In this paper we solve two problems. Firstly, if an estimate of the surface is already known, the problem is to calibrate a new image relative to the existing surface model. Secondly, if no surface estimate is available, the relative camera calibration between the images in the set must be estimated. This will allow an initial surface model to be estimated. Results of both types of estimation are given.

Calibration and analysis of genome-based models for microbial ecology.

Science.gov (United States)

Louca, Stilianos; Doebeli, Michael

2015-10-16

Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.

Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure

Science.gov (United States)

Cheng, Chun-Tian; Zhao, Ming-Yan; Chau, K. W.; Wu, Xin-Yu

2006-01-01

Genetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. Journal of Hydrology, 268, 72-86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall-runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.

Multivariate Calibration Models for Sorghum Composition using Near-Infrared Spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Wolfrum, E.; Payne, C.; Stefaniak, T.; Rooney, W.; Dighe, N.; Bean, B.; Dahlberg, J.

2013-03-01

NREL developed calibration models based on near-infrared (NIR) spectroscopy coupled with multivariate statistics to predict compositional properties relevant to cellulosic biofuels production for a variety of sorghum cultivars. A robust calibration population was developed in an iterative fashion. The quality of models developed using the same sample geometry on two different types of NIR spectrometers and two different sample geometries on the same spectrometer did not vary greatly.

Evaluation of Uncertainties in hydrogeological modeling and groundwater flow analyses. Model calibration

International Nuclear Information System (INIS)

Ijiri, Yuji; Ono, Makoto; Sugihara, Yutaka; Shimo, Michito; Yamamoto, Hajime; Fumimura, Kenichi

2003-03-01

This study involves evaluation of uncertainty in hydrogeological modeling and groundwater flow analysis. Three-dimensional groundwater flow in Shobasama site in Tono was analyzed using two continuum models and one discontinuous model. The domain of this study covered area of four kilometers in east-west direction and six kilometers in north-south direction. Moreover, for the purpose of evaluating how uncertainties included in modeling of hydrogeological structure and results of groundwater simulation decreased with progress of investigation research, updating and calibration of the models about several modeling techniques of hydrogeological structure and groundwater flow analysis techniques were carried out, based on the information and knowledge which were newly acquired. The acquired knowledge is as follows. As a result of setting parameters and structures in renewal of the models following to the circumstances by last year, there is no big difference to handling between modeling methods. The model calibration is performed by the method of matching numerical simulation with observation, about the pressure response caused by opening and closing of a packer in MIU-2 borehole. Each analysis technique attains reducing of residual sum of squares of observations and results of numerical simulation by adjusting hydrogeological parameters. However, each model adjusts different parameters as water conductivity, effective porosity, specific storage, and anisotropy. When calibrating models, sometimes it is impossible to explain the phenomena only by adjusting parameters. In such case, another investigation may be required to clarify details of hydrogeological structure more. As a result of comparing research from beginning to this year, the following conclusions are obtained about investigation. (1) The transient hydraulic data are effective means in reducing the uncertainty of hydrogeological structure. (2) Effective porosity for calculating pore water velocity of

Ideas for fast accelerator model calibration

International Nuclear Information System (INIS)

Corbett, J.

1997-05-01

With the advent of a simple matrix inversion technique, measurement-based storage ring modeling has made rapid progress in recent years. Using fast computers with large memory, the matrix inversion procedure typically adjusts up to 10 3 model variables to fit the order of 10 5 measurements. The results have been surprisingly accurate. Physics aside, one of the next frontiers is to simplify the process and to reduce computation time. In this paper, the authors discuss two approaches to speed up the model calibration process: recursive least-squares fitting and a piecewise fitting approach

Spatial and Temporal Self-Calibration of a Hydroeconomic Model

Science.gov (United States)

Howitt, R. E.; Hansen, K. M.

2008-12-01

Hydroeconomic modeling of water systems where risk and reliability of water supply are of critical importance must address explicitly how to model water supply uncertainty. When large fluctuations in annual precipitation and significant variation in flows by location are present, a model which solves with perfect foresight of future water conditions may be inappropriate for some policy and research questions. We construct a simulation-optimization model with limited foresight of future water conditions using positive mathematical programming and self-calibration techniques. This limited foresight netflow (LFN) model signals the value of storing water for future use and reflects a more accurate economic value of water at key locations, given that future water conditions are unknown. Failure to explicitly model this uncertainty could lead to undervaluation of storage infrastructure and contractual mechanisms for managing water supply risk. A model based on sequentially updated information is more realistic, since water managers make annual storage decisions without knowledge of yet to be realized future water conditions. The LFN model runs historical hydrological conditions through the current configuration of the California water system to determine the economically efficient allocation of water under current economic conditions and infrastructure. The model utilizes current urban and agricultural demands, storage and conveyance infrastructure, and the state's hydrological history to indicate the scarcity value of water at key locations within the state. Further, the temporal calibration penalty functions vary by year type, reflecting agricultural water users' ability to alter cropping patterns in response to water conditions. The model employs techniques from positive mathematical programming (Howitt, 1995; Howitt, 1998; Cai and Wang, 2006) to generate penalty functions that are applied to deviations from observed data. The functions are applied to monthly flows

On the Bayesian calibration of computer model mixtures through experimental data, and the design of predictive models

Science.gov (United States)

Karagiannis, Georgios; Lin, Guang

2017-08-01

For many real systems, several computer models may exist with different physics and predictive abilities. To achieve more accurate simulations/predictions, it is desirable for these models to be properly combined and calibrated. We propose the Bayesian calibration of computer model mixture method which relies on the idea of representing the real system output as a mixture of the available computer model outputs with unknown input dependent weight functions. The method builds a fully Bayesian predictive model as an emulator for the real system output by combining, weighting, and calibrating the available models in the Bayesian framework. Moreover, it fits a mixture of calibrated computer models that can be used by the domain scientist as a mean to combine the available computer models, in a flexible and principled manner, and perform reliable simulations. It can address realistic cases where one model may be more accurate than the others at different input values because the mixture weights, indicating the contribution of each model, are functions of the input. Inference on the calibration parameters can consider multiple computer models associated with different physics. The method does not require knowledge of the fidelity order of the models. We provide a technique able to mitigate the computational overhead due to the consideration of multiple computer models that is suitable to the mixture model framework. We implement the proposed method in a real-world application involving the Weather Research and Forecasting large-scale climate model.

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

Science.gov (United States)

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

Bayesian model calibration of ramp compression experiments on Z

Science.gov (United States)

Brown, Justin; Hund, Lauren

2017-06-01

Bayesian model calibration (BMC) is a statistical framework to estimate inputs for a computational model in the presence of multiple uncertainties, making it well suited to dynamic experiments which must be coupled with numerical simulations to interpret the results. Often, dynamic experiments are diagnosed using velocimetry and this output can be modeled using a hydrocode. Several calibration issues unique to this type of scenario including the functional nature of the output, uncertainty of nuisance parameters within the simulation, and model discrepancy identifiability are addressed, and a novel BMC process is proposed. As a proof of concept, we examine experiments conducted on Sandia National Laboratories' Z-machine which ramp compressed tantalum to peak stresses of 250 GPa. The proposed BMC framework is used to calibrate the cold curve of Ta (with uncertainty), and we conclude that the procedure results in simple, fast, and valid inferences. Sandia National Laboratories is a multi-mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

The Value of Hydrograph Partitioning Curves for Calibrating Hydrological Models in Glacierized Basins

Science.gov (United States)

He, Zhihua; Vorogushyn, Sergiy; Unger-Shayesteh, Katy; Gafurov, Abror; Kalashnikova, Olga; Omorova, Elvira; Merz, Bruno

2018-03-01

This study refines the method for calibrating a glacio-hydrological model based on Hydrograph Partitioning Curves (HPCs), and evaluates its value in comparison to multidata set optimization approaches which use glacier mass balance, satellite snow cover images, and discharge. The HPCs are extracted from the observed flow hydrograph using catchment precipitation and temperature gradients. They indicate the periods when the various runoff processes, such as glacier melt or snow melt, dominate the basin hydrograph. The annual cumulative curve of the difference between average daily temperature and melt threshold temperature over the basin, as well as the annual cumulative curve of average daily snowfall on the glacierized areas are used to identify the starting and end dates of snow and glacier ablation periods. Model parameters characterizing different runoff processes are calibrated on different HPCs in a stepwise and iterative way. Results show that the HPC-based method (1) delivers model-internal consistency comparably to the tri-data set calibration method; (2) improves the stability of calibrated parameter values across various calibration periods; and (3) estimates the contributions of runoff components similarly to the tri-data set calibration method. Our findings indicate the potential of the HPC-based approach as an alternative for hydrological model calibration in glacierized basins where other calibration data sets than discharge are often not available or very costly to obtain.

Modified calibration protocol evaluated in a model-based testing of SBR flexibility

DEFF Research Database (Denmark)

Corominas, Lluís; Sin, Gürkan; Puig, Sebastià

2011-01-01

The purpose of this paper is to refine the BIOMATH calibration protocol for SBR systems, in particular to develop a pragmatic calibration protocol that takes advantage of SBR information-rich data, defines a simulation strategy to obtain proper initial conditions for model calibration and provide...

A new method to calibrate Lagrangian model with ASAR images for oil slick trajectory.

Science.gov (United States)

Tian, Siyu; Huang, Xiaoxia; Li, Hongga

2017-03-15

Since Lagrangian model coefficients vary with different conditions, it is necessary to calibrate the model to obtain optimal coefficient combination for special oil spill accident. This paper focuses on proposing a new method to calibrate Lagrangian model with time series of Envisat ASAR images. Oil slicks extracted from time series images form a detected trajectory of special oil slick. Lagrangian model is calibrated by minimizing the difference between simulated trajectory and detected trajectory. mean center position distance difference (MCPD) and rotation difference (RD) of Oil slicks' or particles' standard deviational ellipses (SDEs) are calculated as two evaluations. The two parameters are taken to evaluate the performance of Lagrangian transport model with different coefficient combinations. This method is applied to Penglai 19-3 oil spill accident. The simulation result with calibrated model agrees well with related satellite observations. It is suggested the new method is effective to calibrate Lagrangian model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Calibrating corneal material model parameters using only inflation data: an ill-posed problem

CSIR Research Space (South Africa)

Kok, S

2014-08-01

Full Text Available is to perform numerical modelling using the finite element method, for which a calibrated material model is required. These material models are typically calibrated using experimental inflation data by solving an inverse problem. In the inverse problem...

A multi-objective approach to improve SWAT model calibration in alpine catchments

Science.gov (United States)

Tuo, Ye; Marcolini, Giorgia; Disse, Markus; Chiogna, Gabriele

2018-04-01

Multi-objective hydrological model calibration can represent a valuable solution to reduce model equifinality and parameter uncertainty. The Soil and Water Assessment Tool (SWAT) model is widely applied to investigate water quality and water management issues in alpine catchments. However, the model calibration is generally based on discharge records only, and most of the previous studies have defined a unique set of snow parameters for an entire basin. Only a few studies have considered snow observations to validate model results or have taken into account the possible variability of snow parameters for different subbasins. This work presents and compares three possible calibration approaches. The first two procedures are single-objective calibration procedures, for which all parameters of the SWAT model were calibrated according to river discharge alone. Procedures I and II differ from each other by the assumption used to define snow parameters: The first approach assigned a unique set of snow parameters to the entire basin, whereas the second approach assigned different subbasin-specific sets of snow parameters to each subbasin. The third procedure is a multi-objective calibration, in which we considered snow water equivalent (SWE) information at two different spatial scales (i.e. subbasin and elevation band), in addition to discharge measurements. We tested these approaches in the Upper Adige river basin where a dense network of snow depth measurement stations is available. Only the set of parameters obtained with this multi-objective procedure provided an acceptable prediction of both river discharge and SWE. These findings offer the large community of SWAT users a strategy to improve SWAT modeling in alpine catchments.

Innovative Calibration Method for System Level Simulation Models of Internal Combustion Engines

Directory of Open Access Journals (Sweden)

Ivo Prah

2016-09-01

Full Text Available The paper outlines a procedure for the computer-controlled calibration of the combined zero-dimensional (0D and one-dimensional (1D thermodynamic simulation model of a turbocharged internal combustion engine (ICE. The main purpose of the calibration is to determine input parameters of the simulation model in such a way as to achieve the smallest difference between the results of the measurements and the results of the numerical simulations with minimum consumption of the computing time. An innovative calibration methodology is based on a novel interaction between optimization methods and physically based methods of the selected ICE sub-systems. Therein physically based methods were used for steering the division of the integral ICE to several sub-models and for determining parameters of selected components considering their governing equations. Innovative multistage interaction between optimization methods and physically based methods allows, unlike the use of well-established methods that rely only on the optimization techniques, for successful calibration of a large number of input parameters with low time consumption. Therefore, the proposed method is suitable for efficient calibration of simulation models of advanced ICEs.

Visible spectroscopy calibration transfer model in determining pH of Sala mangoes

International Nuclear Information System (INIS)

Yahaya, O.K.M.; MatJafri, M.Z.; Aziz, A.A.; Omar, A.F.

2015-01-01

The purpose of this study is to compare the efficiency of calibration transfer procedures between three spectrometers involving two Ocean Optics Inc. spectrometers, namely, QE65000 and Jaz, and also, ASD FieldSpec 3 in measuring the pH of Sala mango by visible reflectance spectroscopy. This study evaluates the ability of these spectrometers in measuring the pH of Sala mango by applying similar calibration algorithms through direct calibration transfer. This visible reflectance spectroscopy technique defines a spectrometer as a master instrument and another spectrometer as a slave. The multiple linear regression (MLR) of calibration model generated using the QE65000 spectrometer is transferred to the Jaz spectrometer and vice versa for Set 1. The same technique is applied for Set 2 with QE65000 spectrometer is transferred to the FieldSpec3 spectrometer and vice versa. For Set 1, the result showed that the QE65000 spectrometer established a calibration model with higher accuracy than that of the Jaz spectrometer. In addition, the calibration model developed on Jaz spectrometer successfully predicted the pH of Sala mango, which was measured using QE65000 spectrometer, with a root means square error of prediction RMSEP = 0.092 pH and coefficients of determination R 2  = 0.892. Moreover, the best prediction result is obtained for Set 2 when the calibration model developed on QE65000 spectrometer is successfully transferred to FieldSpec 3 with R 2  = 0.839 and RMSEP = 0.16 pH

Hydrogeology and water quality of the stratified-drift aquifer in the Pony Hollow Creek Valley, Tompkins County, New York

Science.gov (United States)

Bugliosi, Edward F.; Miller, Todd S.; Reynolds, Richard J.

2014-01-01

The lithology, areal extent, and the water-table configuration in stratified-drift aquifers in the northern part of the Pony Hollow Creek valley in the Town of Newfield, New York, were mapped as part of an ongoing aquifer mapping program in Tompkins County. Surficial geologic and soil maps, well and test-boring records, light detection and ranging (lidar) data, water-level measurements, and passive-seismic surveys were used to map the aquifer geometry, construct geologic sections, and determine the depth to bedrock at selected locations throughout the valley. Additionally, water-quality samples were collected from selected streams and wells to characterize the quality of surface and groundwater in the study area. Sedimentary bedrock underlies the study area and is overlain by unstratified drift (till), stratified drift (glaciolacustrine and glaciofluvial deposits), and recent post glacial alluvium. The major type of unconsolidated, water-yielding material in the study area is stratified drift, which consists of glaciofluvial sand and gravel, and is present in sufficient amounts in most places to form an extensive unconfined aquifer throughout the study area, which is the source of water for most residents, farms, and businesses in the valleys. A map of the water table in the unconfined aquifer was constructed by using (1) measurements made between the mid-1960s through 2010, (2) control on the altitudes of perennial streams at 10-foot contour intervals from lidar data collected by Tompkins County, and (3) water surfaces of ponds and wetlands that are hydraulically connected to the unconfined aquifer. Water-table contours indicate that the direction of groundwater flow within the stratified-drift aquifer is predominantly from the valley walls toward the streams and ponds in the central part of the valley where groundwater then flows southwestward (down valley) toward the confluence with the Cayuta Creek valley. Locally, the direction of groundwater flow is radially

Nested sampling algorithm for subsurface flow model selection, uncertainty quantification, and nonlinear calibration

KAUST Repository

Elsheikh, A. H.

2013-12-01

Calibration of subsurface flow models is an essential step for managing ground water aquifers, designing of contaminant remediation plans, and maximizing recovery from hydrocarbon reservoirs. We investigate an efficient sampling algorithm known as nested sampling (NS), which can simultaneously sample the posterior distribution for uncertainty quantification, and estimate the Bayesian evidence for model selection. Model selection statistics, such as the Bayesian evidence, are needed to choose or assign different weights to different models of different levels of complexities. In this work, we report the first successful application of nested sampling for calibration of several nonlinear subsurface flow problems. The estimated Bayesian evidence by the NS algorithm is used to weight different parameterizations of the subsurface flow models (prior model selection). The results of the numerical evaluation implicitly enforced Occam\\'s razor where simpler models with fewer number of parameters are favored over complex models. The proper level of model complexity was automatically determined based on the information content of the calibration data and the data mismatch of the calibrated model.

On Inertial Body Tracking in the Presence of Model Calibration Errors.

Science.gov (United States)

Miezal, Markus; Taetz, Bertram; Bleser, Gabriele

2016-07-22

In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments-the IMU-to-segment calibrations, subsequently called I2S calibrations-to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and

Multi-objective calibration of a reservoir model: aggregation and non-dominated sorting approaches

Science.gov (United States)

Huang, Y.

2012-12-01

Numerical reservoir models can be helpful tools for water resource management. These models are generally calibrated against historical measurement data made in reservoirs. In this study, two methods are proposed for the multi-objective calibration of such models: aggregation and non-dominated sorting methods. Both methods use a hybrid genetic algorithm as an optimization engine and are different in fitness assignment. In the aggregation method, a weighted sum of scaled simulation errors is designed as an overall objective function to measure the fitness of solutions (i.e. parameter values). The contribution of this study to the aggregation method is the correlation analysis and its implication to the choice of weight factors. In the non-dominated sorting method, a novel method based on non-dominated sorting and the method of minimal distance is used to calculate the dummy fitness of solutions. The proposed methods are illustrated using a water quality model that was set up to simulate the water quality of Pepacton Reservoir, which is located to the north of New York City and is used for water supply of city. The study also compares the aggregation and the non-dominated sorting methods. The purpose of this comparison is not to evaluate the pros and cons between the two methods but to determine whether the parameter values, objective function values (simulation errors) and simulated results obtained are significantly different with each other. The final results (objective function values) from the two methods are good compromise between all objective functions, and none of these results are the worst for any objective function. The calibrated model provides an overall good performance and the simulated results with the calibrated parameter values match the observed data better than the un-calibrated parameters, which supports and justifies the use of multi-objective calibration. The results achieved in this study can be very useful for the calibration of water

Applying Hierarchical Model Calibration to Automatically Generated Items.

Science.gov (United States)

Williamson, David M.; Johnson, Matthew S.; Sinharay, Sandip; Bejar, Isaac I.

This study explored the application of hierarchical model calibration as a means of reducing, if not eliminating, the need for pretesting of automatically generated items from a common item model prior to operational use. Ultimately the successful development of automatic item generation (AIG) systems capable of producing items with highly similar…

Seepage Calibration Model and Seepage Testing Data

International Nuclear Information System (INIS)

Dixon, P.

2004-01-01

The purpose of this Model Report is to document the Seepage Calibration Model (SCM). The SCM is developed (1) to establish the conceptual basis for the Seepage Model for Performance Assessment (SMPA), and (2) to derive seepage-relevant, model-related parameters and their distributions for use in the SMPA and seepage abstraction in support of the Total System Performance Assessment for License Application (TSPA-LA). The SCM is intended to be used only within this Model Report for the estimation of seepage-relevant parameters through calibration of the model against seepage-rate data from liquid-release tests performed in several niches along the Exploratory Studies Facility (ESF) Main Drift and in the Cross Drift. The SCM does not predict seepage into waste emplacement drifts under thermal or ambient conditions. Seepage predictions for waste emplacement drifts under ambient conditions will be performed with the SMPA (see upcoming REV 02 of CRWMS M and O 2000 [153314]), which inherits the conceptual basis and model-related parameters from the SCM. Seepage during the thermal period is examined separately in the Thermal Hydrologic (TH) Seepage Model (see BSC 2003 [161530]). The scope of this work is (1) to evaluate seepage rates measured during liquid-release experiments performed in several niches in the Exploratory Studies Facility (ESF) and in the Cross Drift, which was excavated for enhanced characterization of the repository block (ECRB); (2) to evaluate air-permeability data measured in boreholes above the niches and the Cross Drift to obtain the permeability structure for the seepage model; (3) to use inverse modeling to calibrate the SCM and to estimate seepage-relevant, model-related parameters on the drift scale; (4) to estimate the epistemic uncertainty of the derived parameters, based on the goodness-of-fit to the observed data and the sensitivity of calculated seepage with respect to the parameters of interest; (5) to characterize the aleatory uncertainty

Influence of smoothing of X-ray spectra on parameters of calibration model

International Nuclear Information System (INIS)

Antoniak, W.; Urbanski, P.; Kowalska, E.

1998-01-01

Parameters of the calibration model before and after smoothing of X-ray spectra have been investigated. The calibration model was calculated using multivariate procedure - namely the partial least square regression (PLS). Investigations have been performed on an example of six sets of various standards used for calibration of some instruments based on X-ray fluorescence principle. The smoothing methods were compared: regression splines, Savitzky-Golay and Discrete Fourier Transform. The calculations were performed using a software package MATLAB and some home-made programs. (author)

More efficient evolutionary strategies for model calibration with watershed model for demonstration

Science.gov (United States)

Baggett, J. S.; Skahill, B. E.

2008-12-01

Evolutionary strategies allow automatic calibration of more complex models than traditional gradient based approaches, but they are more computationally intensive. We present several efficiency enhancements for evolution strategies, many of which are not new, but when combined have been shown to dramatically decrease the number of model runs required for calibration of synthetic problems. To reduce the number of expensive model runs we employ a surrogate objective function for an adaptively determined fraction of the population at each generation (Kern et al., 2006). We demonstrate improvements to the adaptive ranking strategy that increase its efficiency while sacrificing little reliability and further reduce the number of model runs required in densely sampled parts of parameter space. Furthermore, we include a gradient individual in each generation that is usually not selected when the search is in a global phase or when the derivatives are poorly approximated, but when selected near a smooth local minimum can dramatically increase convergence speed (Tahk et al., 2007). Finally, the selection of the gradient individual is used to adapt the size of the population near local minima. We show, by incorporating these enhancements into the Covariance Matrix Adaption Evolution Strategy (CMAES; Hansen, 2006), that their synergetic effect is greater than their individual parts. This hybrid evolutionary strategy exploits smooth structure when it is present but degrades to an ordinary evolutionary strategy, at worst, if smoothness is not present. Calibration of 2D-3D synthetic models with the modified CMAES requires approximately 10%-25% of the model runs of ordinary CMAES. Preliminary demonstration of this hybrid strategy will be shown for watershed model calibration problems. Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of

Application of Iterative Robust Model-based Optimal Experimental Design for the Calibration of Biocatalytic Models

DEFF Research Database (Denmark)

Van Daele, Timothy; Gernaey, Krist V.; Ringborg, Rolf Hoffmeyer

2017-01-01

The aim of model calibration is to estimate unique parameter values from available experimental data, here applied to a biocatalytic process. The traditional approach of first gathering data followed by performing a model calibration is inefficient, since the information gathered during...... experimentation is not actively used to optimise the experimental design. By applying an iterative robust model-based optimal experimental design, the limited amount of data collected is used to design additional informative experiments. The algorithm is used here to calibrate the initial reaction rate of an ω......-transaminase catalysed reaction in a more accurate way. The parameter confidence region estimated from the Fisher Information Matrix is compared with the likelihood confidence region, which is a more accurate, but also a computationally more expensive method. As a result, an important deviation between both approaches...

How does higher frequency monitoring data affect the calibration of a process-based water quality model?

Science.gov (United States)

Jackson-Blake, Leah; Helliwell, Rachel

2015-04-01

Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, spanning all hydrochemical conditions. However, regulatory agencies and research organisations generally only sample at a fortnightly or monthly frequency, even in well-studied catchments, often missing peak flow events. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by a process-based, semi-distributed catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the Markov Chain Monte Carlo - DiffeRential Evolution Adaptive Metropolis (MCMC-DREAM) algorithm. Calibration to daily data resulted in improved simulation of peak TDP concentrations and improved model performance statistics. Parameter-related uncertainty in simulated TDP was large when fortnightly data was used for calibration, with a 95% credible interval of 26 μg/l. This uncertainty is comparable in size to the difference between Water Framework Directive (WFD) chemical status classes, and would therefore make it difficult to use this calibration to predict shifts in WFD status. The 95% credible interval reduced markedly with the higher frequency monitoring data, to 6 μg/l. The number of parameters that could be reliably auto-calibrated

Our calibrated model has poor predictive value: An example from the petroleum industry

Energy Technology Data Exchange (ETDEWEB)

Carter, J.N. [Department of Earth Science and Engineering, Imperial College, London (United Kingdom)]. E-mail: j.n.carter@ic.ac.uk; Ballester, P.J. [Department of Earth Science and Engineering, Imperial College, London (United Kingdom); Tavassoli, Z. [Department of Earth Science and Engineering, Imperial College, London (United Kingdom); King, P.R. [Department of Earth Science and Engineering, Imperial College, London (United Kingdom)

2006-10-15

It is often assumed that once a model has been calibrated to measurements then it will have some level of predictive capability, although this may be limited. If the model does not have predictive capability then the assumption is that the model needs to be improved in some way. Using an example from the petroleum industry, we show that cases can exit where calibrated models have limited predictive capability. This occurs even when there is no modelling error present. It is also shown that the introduction of a small modelling error can make it impossible to obtain any models with useful predictive capability. We have been unable to find ways of identifying which calibrated models will have some predictive capacity and those which will not.

Our calibrated model has poor predictive value: An example from the petroleum industry

International Nuclear Information System (INIS)

Carter, J.N.; Ballester, P.J.; Tavassoli, Z.; King, P.R.

2006-01-01

It is often assumed that once a model has been calibrated to measurements then it will have some level of predictive capability, although this may be limited. If the model does not have predictive capability then the assumption is that the model needs to be improved in some way. Using an example from the petroleum industry, we show that cases can exit where calibrated models have limited predictive capability. This occurs even when there is no modelling error present. It is also shown that the introduction of a small modelling error can make it impossible to obtain any models with useful predictive capability. We have been unable to find ways of identifying which calibrated models will have some predictive capacity and those which will not

Calibration of a distributed hydrology and land surface model using energy flux measurements

DEFF Research Database (Denmark)

Larsen, Morten Andreas Dahl; Refsgaard, Jens Christian; Jensen, Karsten H.

2016-01-01

In this study we develop and test a calibration approach on a spatially distributed groundwater-surface water catchment model (MIKE SHE) coupled to a land surface model component with particular focus on the water and energy fluxes. The model is calibrated against time series of eddy flux measure...

Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin

Science.gov (United States)

Hay, L.E.; Leavesley, G.H.; Clark, M.P.; Markstrom, S.L.; Viger, R.J.; Umemoto, M.

2006-01-01

The ability to apply a hydrologic model to large numbers of basins for forecasting purposes requires a quick and effective calibration strategy. This paper presents a step wise, multiple objective, automated procedure for hydrologic model calibration. This procedure includes the sequential calibration of a model's simulation of solar radiation (SR), potential evapotranspiration (PET), water balance, and daily runoff. The procedure uses the Shuffled Complex Evolution global search algorithm to calibrate the U.S. Geological Survey's Precipitation Runoff Modeling System in the Yampa River basin of Colorado. This process assures that intermediate states of the model (SR and PET on a monthly mean basis), as well as the water balance and components of the daily hydrograph are simulated, consistently with measured values.

Intercomparison of hydrological model structures and calibration approaches in climate scenario impact projections

Science.gov (United States)

Vansteenkiste, Thomas; Tavakoli, Mohsen; Ntegeka, Victor; De Smedt, Florimond; Batelaan, Okke; Pereira, Fernando; Willems, Patrick

2014-11-01

The objective of this paper is to investigate the effects of hydrological model structure and calibration on climate change impact results in hydrology. The uncertainty in the hydrological impact results is assessed by the relative change in runoff volumes and peak and low flow extremes from historical and future climate conditions. The effect of the hydrological model structure is examined through the use of five hydrological models with different spatial resolutions and process descriptions. These were applied to a medium sized catchment in Belgium. The models vary from the lumped conceptual NAM, PDM and VHM models over the intermediate detailed and distributed WetSpa model to the fully distributed MIKE SHE model. The latter model accounts for the 3D groundwater processes and interacts bi-directionally with a full hydrodynamic MIKE 11 river model. After careful and manual calibration of these models, accounting for the accuracy of the peak and low flow extremes and runoff subflows, and the changes in these extremes for changing rainfall conditions, the five models respond in a similar way to the climate scenarios over Belgium. Future projections on peak flows are highly uncertain with expected increases as well as decreases depending on the climate scenario. The projections on future low flows are more uniform; low flows decrease (up to 60%) for all models and for all climate scenarios. However, the uncertainties in the impact projections are high, mainly in the dry season. With respect to the model structural uncertainty, the PDM model simulates significantly higher runoff peak flows under future wet scenarios, which is explained by its specific model structure. For the low flow extremes, the MIKE SHE model projects significantly lower low flows in dry scenario conditions in comparison to the other models, probably due to its large difference in process descriptions for the groundwater component, the groundwater-river interactions. The effect of the model

A new sewage exfiltration model--parameters and calibration.

Science.gov (United States)

Karpf, Christian; Krebs, Peter

2011-01-01

Exfiltration of waste water from sewer systems represents a potential danger for the soil and the aquifer. Common models, which are used to describe the exfiltration process, are based on the law of Darcy, extended by a more or less detailed consideration of the expansion of leaks, the characteristics of the soil and the colmation layer. But, due to the complexity of the exfiltration process, the calibration of these models includes a significant uncertainty. In this paper, a new exfiltration approach is introduced, which implements the dynamics of the clogging process and the structural conditions near sewer leaks. The calibration is realised according to experimental studies and analysis of groundwater infiltration to sewers. Furthermore, exfiltration rates and the sensitivity of the approach are estimated and evaluated, respectively, by Monte-Carlo simulations.

Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

Science.gov (United States)

Wright, David; Thyer, Mark; Westra, Seth

2015-04-01

Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this

Calibration of the APEX Model to Simulate Management Practice Effects on Runoff, Sediment, and Phosphorus Loss.

Science.gov (United States)

Bhandari, Ammar B; Nelson, Nathan O; Sweeney, Daniel W; Baffaut, Claire; Lory, John A; Senaviratne, Anomaa; Pierzynski, Gary M; Janssen, Keith A; Barnes, Philip L

2017-11-01

Process-based computer models have been proposed as a tool to generate data for Phosphorus (P) Index assessment and development. Although models are commonly used to simulate P loss from agriculture using managements that are different from the calibration data, this use of models has not been fully tested. The objective of this study is to determine if the Agricultural Policy Environmental eXtender (APEX) model can accurately simulate runoff, sediment, total P, and dissolved P loss from 0.4 to 1.5 ha of agricultural fields with managements that are different from the calibration data. The APEX model was calibrated with field-scale data from eight different managements at two locations (management-specific models). The calibrated models were then validated, either with the same management used for calibration or with different managements. Location models were also developed by calibrating APEX with data from all managements. The management-specific models resulted in satisfactory performance when used to simulate runoff, total P, and dissolved P within their respective systems, with > 0.50, Nash-Sutcliffe efficiency > 0.30, and percent bias within ±35% for runoff and ±70% for total and dissolved P. When applied outside the calibration management, the management-specific models only met the minimum performance criteria in one-third of the tests. The location models had better model performance when applied across all managements compared with management-specific models. Our results suggest that models only be applied within the managements used for calibration and that data be included from multiple management systems for calibration when using models to assess management effects on P loss or evaluate P Indices. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

Science.gov (United States)

Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan

2017-01-01

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.

Calibration Under Uncertainty.

Energy Technology Data Exchange (ETDEWEB)

Swiler, Laura Painton; Trucano, Timothy Guy

2005-03-01

This report is a white paper summarizing the literature and different approaches to the problem of calibrating computer model parameters in the face of model uncertainty. Model calibration is often formulated as finding the parameters that minimize the squared difference between the model-computed data (the predicted data) and the actual experimental data. This approach does not allow for explicit treatment of uncertainty or error in the model itself: the model is considered the %22true%22 deterministic representation of reality. While this approach does have utility, it is far from an accurate mathematical treatment of the true model calibration problem in which both the computed data and experimental data have error bars. This year, we examined methods to perform calibration accounting for the error in both the computer model and the data, as well as improving our understanding of its meaning for model predictability. We call this approach Calibration under Uncertainty (CUU). This talk presents our current thinking on CUU. We outline some current approaches in the literature, and discuss the Bayesian approach to CUU in detail.

Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

Science.gov (United States)

Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model

Improving SWAT model prediction using an upgraded denitrification scheme and constrained auto calibration

Science.gov (United States)

The reliability of common calibration practices for process based water quality models has recently been questioned. A so-called “adequately calibrated model” may contain input errors not readily identifiable by model users, or may not realistically represent intra-watershed responses. These short...

A Linear Viscoelastic Model Calibration of Sylgard 184.

Energy Technology Data Exchange (ETDEWEB)

Long, Kevin Nicholas; Brown, Judith Alice

2017-04-01

We calibrate a linear thermoviscoelastic model for solid Sylgard 184 (90-10 formulation), a lightly cross-linked, highly flexible isotropic elastomer for use both in Sierra / Solid Mechanics via the Universal Polymer Model as well as in Sierra / Structural Dynamics (Salinas) for use as an isotropic viscoelastic material. Material inputs for the calibration in both codes are provided. The frequency domain master curve of oscillatory shear was obtained from a report from Los Alamos National Laboratory (LANL). However, because the form of that data is different from the constitutive models in Sierra, we also present the mapping of the LANL data onto Sandia’s constitutive models. Finally, blind predictions of cyclic tension and compression out to moderate strains of 40 and 20% respectively are compared with Sandia’s legacy cure schedule material. Although the strain rate of the data is unknown, the linear thermoviscoelastic model accurately predicts the experiments out to moderate strains for the slower strain rates, which is consistent with the expectation that quasistatic test procedures were likely followed. This good agreement comes despite the different cure schedules between the Sandia and LANL data.

Technical note: Bayesian calibration of dynamic ruminant nutrition models.

Science.gov (United States)

Reed, K F; Arhonditsis, G B; France, J; Kebreab, E

2016-08-01

Mechanistic models of ruminant digestion and metabolism have advanced our understanding of the processes underlying ruminant animal physiology. Deterministic modeling practices ignore the inherent variation within and among individual animals and thus have no way to assess how sources of error influence model outputs. We introduce Bayesian calibration of mathematical models to address the need for robust mechanistic modeling tools that can accommodate error analysis by remaining within the bounds of data-based parameter estimation. For the purpose of prediction, the Bayesian approach generates a posterior predictive distribution that represents the current estimate of the value of the response variable, taking into account both the uncertainty about the parameters and model residual variability. Predictions are expressed as probability distributions, thereby conveying significantly more information than point estimates in regard to uncertainty. Our study illustrates some of the technical advantages of Bayesian calibration and discusses the future perspectives in the context of animal nutrition modeling. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

CALIBRATION OF DISTRIBUTED SHALLOW LANDSLIDE MODELS IN FORESTED LANDSCAPES

Directory of Open Access Journals (Sweden)

Gian Battista Bischetti

2010-09-01

Full Text Available In mountainous-forested soil mantled landscapes all around the world, rainfall-induced shallow landslides are one of the most common hydro-geomorphic hazards, which frequently impact the environment and human lives and properties. In order to produce shallow landslide susceptibility maps, several models have been proposed in the last decade, combining simplified steady state topography- based hydrological models with the infinite slope scheme, in a GIS framework. In the present paper, two of the still open issues are investigated: the assessment of the validity of slope stability models and the inclusion of root cohesion values. In such a perspective the “Stability INdex MAPping” has been applied to a small forested pre-Alpine catchment, adopting different calibrating approaches and target indexes. The Single and the Multiple Calibration Regions modality and three quantitative target indexes – the common Success Rate (SR, the Modified Success Rate (MSR, and a Weighted Modified Success Rate (WMSR herein introduced – are considered. The results obtained show that the target index can 34 003_Bischetti(569_23 1-12-2010 9:48 Pagina 34 significantly affect the values of a model’s parameters and lead to different proportions of stable/unstable areas, both for the Single and the Multiple Calibration Regions approach. The use of SR as the target index leads to an over-prediction of the unstable areas, whereas the use of MSR and WMSR, seems to allow a better discrimination between stable and unstable areas. The Multiple Calibration Regions approach should be preferred, using information on space distribution of vegetation to define the Regions. The use of field-based estimation of root cohesion and sliding depth allows the implementation of slope stability models (SINMAP in our case also without the data needed for calibration. To maximize the inclusion of such parameters into SINMAP, however, the assumption of a uniform distribution of

A Generic Software Framework for Data Assimilation and Model Calibration

NARCIS (Netherlands)

Van Velzen, N.

2010-01-01

The accuracy of dynamic simulation models can be increased by using observations in conjunction with a data assimilation or model calibration algorithm. However, implementing such algorithms usually increases the complexity of the model software significantly. By using concepts from object oriented

Seepage Calibration Model and Seepage Testing Data

Energy Technology Data Exchange (ETDEWEB)

S. Finsterle

2004-09-02

The purpose of this Model Report is to document the Seepage Calibration Model (SCM). The SCM was developed (1) to establish the conceptual basis for the Seepage Model for Performance Assessment (SMPA), and (2) to derive seepage-relevant, model-related parameters and their distributions for use in the SMPA and seepage abstraction in support of the Total System Performance Assessment for License Application (TSPA-LA). This Model Report has been revised in response to a comprehensive, regulatory-focused evaluation performed by the Regulatory Integration Team [''Technical Work Plan for: Regulatory Integration Evaluation of Analysis and Model Reports Supporting the TSPA-LA'' (BSC 2004 [DIRS 169653])]. The SCM is intended to be used only within this Model Report for the estimation of seepage-relevant parameters through calibration of the model against seepage-rate data from liquid-release tests performed in several niches along the Exploratory Studies Facility (ESF) Main Drift and in the Cross-Drift. The SCM does not predict seepage into waste emplacement drifts under thermal or ambient conditions. Seepage predictions for waste emplacement drifts under ambient conditions will be performed with the SMPA [''Seepage Model for PA Including Drift Collapse'' (BSC 2004 [DIRS 167652])], which inherits the conceptual basis and model-related parameters from the SCM. Seepage during the thermal period is examined separately in the Thermal Hydrologic (TH) Seepage Model [see ''Drift-Scale Coupled Processes (DST and TH Seepage) Models'' (BSC 2004 [DIRS 170338])]. The scope of this work is (1) to evaluate seepage rates measured during liquid-release experiments performed in several niches in the Exploratory Studies Facility (ESF) and in the Cross-Drift, which was excavated for enhanced characterization of the repository block (ECRB); (2) to evaluate air-permeability data measured in boreholes above the niches and the Cross

Seepage Calibration Model and Seepage Testing Data

International Nuclear Information System (INIS)

Finsterle, S.

2004-01-01

The purpose of this Model Report is to document the Seepage Calibration Model (SCM). The SCM was developed (1) to establish the conceptual basis for the Seepage Model for Performance Assessment (SMPA), and (2) to derive seepage-relevant, model-related parameters and their distributions for use in the SMPA and seepage abstraction in support of the Total System Performance Assessment for License Application (TSPA-LA). This Model Report has been revised in response to a comprehensive, regulatory-focused evaluation performed by the Regulatory Integration Team [''Technical Work Plan for: Regulatory Integration Evaluation of Analysis and Model Reports Supporting the TSPA-LA'' (BSC 2004 [DIRS 169653])]. The SCM is intended to be used only within this Model Report for the estimation of seepage-relevant parameters through calibration of the model against seepage-rate data from liquid-release tests performed in several niches along the Exploratory Studies Facility (ESF) Main Drift and in the Cross-Drift. The SCM does not predict seepage into waste emplacement drifts under thermal or ambient conditions. Seepage predictions for waste emplacement drifts under ambient conditions will be performed with the SMPA [''Seepage Model for PA Including Drift Collapse'' (BSC 2004 [DIRS 167652])], which inherits the conceptual basis and model-related parameters from the SCM. Seepage during the thermal period is examined separately in the Thermal Hydrologic (TH) Seepage Model [see ''Drift-Scale Coupled Processes (DST and TH Seepage) Models'' (BSC 2004 [DIRS 170338])]. The scope of this work is (1) to evaluate seepage rates measured during liquid-release experiments performed in several niches in the Exploratory Studies Facility (ESF) and in the Cross-Drift, which was excavated for enhanced characterization of the repository block (ECRB); (2) to evaluate air-permeability data measured in boreholes above the niches and the Cross-Drift to obtain the permeability structure for the seepage model

SWAT application in intensive irrigation systems: Model modification, calibration and validation

Science.gov (United States)

Dechmi, Farida; Burguete, Javier; Skhiri, Ahmed

2012-11-01

SummaryThe Soil and Water Assessment Tool (SWAT) is a well established, distributed, eco-hydrologic model. However, using the study case of an agricultural intensive irrigated watershed, it was shown that all the model versions are not able to appropriately reproduce the total streamflow in such system when the irrigation source is outside the watershed. The objective of this study was to modify the SWAT2005 version for correctly simulating the main hydrological processes. Crop yield, total streamflow, total suspended sediment (TSS) losses and phosphorus load calibration and validation were performed using field survey information and water quantity and quality data recorded during 2008 and 2009 years in Del Reguero irrigated watershed in Spain. The goodness of the calibration and validation results was assessed using five statistical measures, including the Nash-Sutcliffe efficiency (NSE). Results indicated that the average annual crop yield and actual evapotranspiration estimations were quite satisfactory. On a monthly basis, the values of NSE were 0.90 (calibration) and 0.80 (validation) indicating that the modified model could reproduce accurately the observed streamflow. The TSS losses were also satisfactorily estimated (NSE = 0.72 and 0.52 for the calibration and validation steps). The monthly temporal patterns and all the statistical parameters indicated that the modified SWAT-IRRIG model adequately predicted the total phosphorus (TP) loading. Therefore, the model could be used to assess the impacts of different best management practices on nonpoint phosphorus losses in irrigated systems.

Beyond discrimination: A comparison of calibration methods and clinical usefulness of predictive models of readmission risk.

Science.gov (United States)

Walsh, Colin G; Sharman, Kavya; Hripcsak, George

2017-12-01

Prior to implementing predictive models in novel settings, analyses of calibration and clinical usefulness remain as important as discrimination, but they are not frequently discussed. Calibration is a model's reflection of actual outcome prevalence in its predictions. Clinical usefulness refers to the utilities, costs, and harms of using a predictive model in practice. A decision analytic approach to calibrating and selecting an optimal intervention threshold may help maximize the impact of readmission risk and other preventive interventions. To select a pragmatic means of calibrating predictive models that requires a minimum amount of validation data and that performs well in practice. To evaluate the impact of miscalibration on utility and cost via clinical usefulness analyses. Observational, retrospective cohort study with electronic health record data from 120,000 inpatient admissions at an urban, academic center in Manhattan. The primary outcome was thirty-day readmission for three causes: all-cause, congestive heart failure, and chronic coronary atherosclerotic disease. Predictive modeling was performed via L1-regularized logistic regression. Calibration methods were compared including Platt Scaling, Logistic Calibration, and Prevalence Adjustment. Performance of predictive modeling and calibration was assessed via discrimination (c-statistic), calibration (Spiegelhalter Z-statistic, Root Mean Square Error [RMSE] of binned predictions, Sanders and Murphy Resolutions of the Brier Score, Calibration Slope and Intercept), and clinical usefulness (utility terms represented as costs). The amount of validation data necessary to apply each calibration algorithm was also assessed. C-statistics by diagnosis ranged from 0.7 for all-cause readmission to 0.86 (0.78-0.93) for congestive heart failure. Logistic Calibration and Platt Scaling performed best and this difference required analyzing multiple metrics of calibration simultaneously, in particular Calibration

Calibration of the heat balance model for prediction of car climate

Science.gov (United States)

Pokorný, Jan; Fišer, Jan; Jícha, Miroslav

2012-04-01

In the paper, the authors refer to development a heat balance model to predict car climate and power heat load. Model is developed in Modelica language using Dymola as interpreter. It is a dynamical system, which describes a heat exchange between car cabin and ambient. Inside a car cabin, there is considered heat exchange between air zone, interior and air-conditioning system. It is considered 1D heat transfer with a heat accumulation and a relative movement Sun respect to the car cabin, whilst car is moving. Measurements of the real operating conditions of gave us data for model calibration. The model was calibrated for Škoda Felicia parking-summer scenarios.

Dynamic calibration of agent-based models using data assimilation.

Science.gov (United States)

Ward, Jonathan A; Evans, Andrew J; Malleson, Nicolas S

2016-04-01

A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.

An Expectation-Maximization Method for Calibrating Synchronous Machine Models

Energy Technology Data Exchange (ETDEWEB)

Meng, Da; Zhou, Ning; Lu, Shuai; Lin, Guang

2013-07-21

The accuracy of a power system dynamic model is essential to its secure and efficient operation. Lower confidence in model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, this paper proposes an expectation-maximization (EM) method to calibrate the synchronous machine model using phasor measurement unit (PMU) data. First, an extended Kalman filter (EKF) is applied to estimate the dynamic states using measurement data. Then, the parameters are calculated based on the estimated states using maximum likelihood estimation (MLE) method. The EM method iterates over the preceding two steps to improve estimation accuracy. The proposed EM method’s performance is evaluated using a single-machine infinite bus system and compared with a method where both state and parameters are estimated using an EKF method. Sensitivity studies of the parameter calibration using EM method are also presented to show the robustness of the proposed method for different levels of measurement noise and initial parameter uncertainty.

SWAT Model Configuration, Calibration and Validation for Lake Champlain Basin

Science.gov (United States)

The Soil and Water Assessment Tool (SWAT) model was used to develop phosphorus loading estimates for sources in the Lake Champlain Basin. This document describes the model setup and parameterization, and presents calibration results.

Sensitivity analysis and calibration of a dynamic physically based slope stability model

Science.gov (United States)

Zieher, Thomas; Rutzinger, Martin; Schneider-Muntau, Barbara; Perzl, Frank; Leidinger, David; Formayer, Herbert; Geitner, Clemens

2017-06-01

Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological-geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 behavioural model runs with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that

Hydrologic Model Development and Calibration: Contrasting a Single- and Multi-Objective Approach for Comparing Model Performance

Science.gov (United States)

Asadzadeh, M.; Maclean, A.; Tolson, B. A.; Burn, D. H.

2009-05-01

Hydrologic model calibration aims to find a set of parameters that adequately simulates observations of watershed behavior, such as streamflow, or a state variable, such as snow water equivalent (SWE). There are different metrics for evaluating calibration effectiveness that involve quantifying prediction errors, such as the Nash-Sutcliffe (NS) coefficient and bias evaluated for the entire calibration period, on a seasonal basis, for low flows, or for high flows. Many of these metrics are conflicting such that the set of parameters that maximizes the high flow NS differs from the set of parameters that maximizes the low flow NS. Conflicting objectives are very likely when different calibration objectives are based on different fluxes and/or state variables (e.g., NS based on streamflow versus SWE). One of the most popular ways to balance different metrics is to aggregate them based on their importance and find the set of parameters that optimizes a weighted sum of the efficiency metrics. Comparing alternative hydrologic models (e.g., assessing model improvement when a process or more detail is added to the model) based on the aggregated objective might be misleading since it represents one point on the tradeoff of desired error metrics. To derive a more comprehensive model comparison, we solved a bi-objective calibration problem to estimate the tradeoff between two error metrics for each model. Although this approach is computationally more expensive than the aggregation approach, it results in a better understanding of the effectiveness of selected models at each level of every error metric and therefore provides a better rationale for judging relative model quality. The two alternative models used in this study are two MESH hydrologic models (version 1.2) of the Wolf Creek Research basin that differ in their watershed spatial discretization (a single Grouped Response Unit, GRU, versus multiple GRUs). The MESH model, currently under development by Environment

Statistical validation of engineering and scientific models : bounds, calibration, and extrapolation.

Energy Technology Data Exchange (ETDEWEB)

Dowding, Kevin J.; Hills, Richard Guy (New Mexico State University, Las Cruces, NM)

2005-04-01

Numerical models of complex phenomena often contain approximations due to our inability to fully model the underlying physics, the excessive computational resources required to fully resolve the physics, the need to calibrate constitutive models, or in some cases, our ability to only bound behavior. Here we illustrate the relationship between approximation, calibration, extrapolation, and model validation through a series of examples that use the linear transient convective/dispersion equation to represent the nonlinear behavior of Burgers equation. While the use of these models represents a simplification relative to the types of systems we normally address in engineering and science, the present examples do support the tutorial nature of this document without obscuring the basic issues presented with unnecessarily complex models.

Hydrological model calibration for flood prediction in current and future climates using probability distributions of observed peak flows and model based rainfall

Science.gov (United States)

Haberlandt, Uwe; Wallner, Markus; Radtke, Imke

2013-04-01

Derived flood frequency analysis based on continuous hydrological modelling is very demanding regarding the required length and temporal resolution of precipitation input data. Often such flood predictions are obtained using long precipitation time series from stochastic approaches or from regional climate models as input. However, the calibration of the hydrological model is usually done using short time series of observed data. This inconsistent employment of different data types for calibration and application of a hydrological model increases its uncertainty. Here, it is proposed to calibrate a hydrological model directly on probability distributions of observed peak flows using model based rainfall in line with its later application. Two examples are given to illustrate the idea. The first one deals with classical derived flood frequency analysis using input data from an hourly stochastic rainfall model. The second one concerns a climate impact analysis using hourly precipitation from a regional climate model. The results show that: (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated on extreme conditions works quite well for average conditions but not vice versa, (III) the calibration of the hydrological model using regional climate model data works as an implicit bias correction method and (IV) the best performance for flood estimation is usually obtained when model based precipitation and observed probability distribution of peak flows are used for model calibration.

Calibration of hydrological model with programme PEST

Science.gov (United States)

Brilly, Mitja; Vidmar, Andrej; Kryžanowski, Andrej; Bezak, Nejc; Šraj, Mojca

2016-04-01

PEST is tool based on minimization of an objective function related to the root mean square error between the model output and the measurement. We use "singular value decomposition", section of the PEST control file, and Tikhonov regularization method for successfully estimation of model parameters. The PEST sometimes failed if inverse problems were ill-posed, but (SVD) ensures that PEST maintains numerical stability. The choice of the initial guess for the initial parameter values is an important issue in the PEST and need expert knowledge. The flexible nature of the PEST software and its ability to be applied to whole catchments at once give results of calibration performed extremely well across high number of sub catchments. Use of parallel computing version of PEST called BeoPEST was successfully useful to speed up calibration process. BeoPEST employs smart slaves and point-to-point communications to transfer data between the master and slaves computers. The HBV-light model is a simple multi-tank-type model for simulating precipitation-runoff. It is conceptual balance model of catchment hydrology which simulates discharge using rainfall, temperature and estimates of potential evaporation. Version of HBV-light-CLI allows the user to run HBV-light from the command line. Input and results files are in XML form. This allows to easily connecting it with other applications such as pre and post-processing utilities and PEST itself. The procedure was applied on hydrological model of Savinja catchment (1852 km2) and consists of twenty one sub-catchments. Data are temporary processed on hourly basis.

PEST modules with regularization for the acceleration of the automatic calibration in hydrodynamic models

Directory of Open Access Journals (Sweden)

Polomčić Dušan M.

2015-01-01

Full Text Available The calibration process of hydrodynamic model is done usually manually by 'testing' with different values of hydrogeological parameters and hydraulic characteristics of the boundary conditions. By using the PEST program, automatic calibration of models has been introduced, and it has proved to significantly reduce the subjective influence of the model creator on results. With the relatively new approach of PEST, i.e. with the introduction of so-called 'pilot points', the concept of homogeneous zones with parameter values of porous media or zones with the given boundary conditions has been outdated. However, the consequence of this kind of automatic calibration is that a significant amount of time is required to perform the calculation. The duration of calibration is measured in hours, sometimes even days. PEST contains two modules for the shortening of that process - Parallel PEST and BeoPEST. The paper presents performed experiments and analysis of different cases of PEST module usage, based on which the reduction in the time required to calibrate the model is done.

[Outlier sample discriminating methods for building calibration model in melons quality detecting using NIR spectra].

Science.gov (United States)

Tian, Hai-Qing; Wang, Chun-Guang; Zhang, Hai-Jun; Yu, Zhi-Hong; Li, Jian-Kang

2012-11-01

Outlier samples strongly influence the precision of the calibration model in soluble solids content measurement of melons using NIR Spectra. According to the possible sources of outlier samples, three methods (predicted concentration residual test; Chauvenet test; leverage and studentized residual test) were used to discriminate these outliers respectively. Nine suspicious outliers were detected from calibration set which including 85 fruit samples. Considering the 9 suspicious outlier samples maybe contain some no-outlier samples, they were reclaimed to the model one by one to see whether they influence the model and prediction precision or not. In this way, 5 samples which were helpful to the model joined in calibration set again, and a new model was developed with the correlation coefficient (r) 0. 889 and root mean square errors for calibration (RMSEC) 0.6010 Brix. For 35 unknown samples, the root mean square errors prediction (RMSEP) was 0.854 degrees Brix. The performance of this model was more better than that developed with non outlier was eliminated from calibration set (r = 0.797, RMSEC= 0.849 degrees Brix, RMSEP = 1.19 degrees Brix), and more representative and stable with all 9 samples were eliminated from calibration set (r = 0.892, RMSEC = 0.605 degrees Brix, RMSEP = 0.862 degrees).

Calibration of a complex activated sludge model for the full-scale wastewater treatment plant

OpenAIRE

Liwarska-Bizukojc, Ewa; Olejnik, Dorota; Biernacki, Rafal; Ledakowicz, Stanislaw

2011-01-01

In this study, the results of the calibration of the complex activated sludge model implemented in BioWin software for the full-scale wastewater treatment plant are presented. Within the calibration of the model, sensitivity analysis of its parameters and the fractions of carbonaceous substrate were performed. In the steady-state and dynamic calibrations, a successful agreement between the measured and simulated values of the output variables was achieved. Sensitivity analysis revealed that u...

Calibration of the heat balance model for prediction of car climate

Directory of Open Access Journals (Sweden)

Jícha Miroslav

2012-04-01

Full Text Available In the paper, the authors refer to development a heat balance model to predict car climate and power heat load. Model is developed in Modelica language using Dymola as interpreter. It is a dynamical system, which describes a heat exchange between car cabin and ambient. Inside a car cabin, there is considered heat exchange between air zone, interior and air-conditioning system. It is considered 1D heat transfer with a heat accumulation and a relative movement Sun respect to the car cabin, whilst car is moving. Measurements of the real operating conditions of gave us data for model calibration. The model was calibrated for Škoda Felicia parking-summer scenarios.

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

Science.gov (United States)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global

The design and realization of calibration apparatus for measuring the concentration of radon in three models

Energy Technology Data Exchange (ETDEWEB)

Huiping, Guo [The Second Artillery Engineering College, Xi' an (China)

2007-06-15

For satisfying calibration request of radon measure in the laboratory, the calibration apparatus for radon activity measure is designed and realized. The calibration apparatus can auto-control and auto-measure in three models. sequent mode, pulse mode and constant mode. The stability and reliability of the calibration apparatus was tested under the three models. The experimental result shows that the apparatus can provides an adjustable and steady radon activity concentration environment for the research of radon and its progeny and for the calibration of its measure. (authors)

Absolute radiometric calibration of Landsat using a pseudo invariant calibration site

Science.gov (United States)

Helder, D.; Thome, K.J.; Mishra, N.; Chander, G.; Xiong, Xiaoxiong; Angal, A.; Choi, Tae-young

2013-01-01

Pseudo invariant calibration sites (PICS) have been used for on-orbit radiometric trending of optical satellite systems for more than 15 years. This approach to vicarious calibration has demonstrated a high degree of reliability and repeatability at the level of 1-3% depending on the site, spectral channel, and imaging geometries. A variety of sensors have used this approach for trending because it is broadly applicable and easy to implement. Models to describe the surface reflectance properties, as well as the intervening atmosphere have also been developed to improve the precision of the method. However, one limiting factor of using PICS is that an absolute calibration capability has not yet been fully developed. Because of this, PICS are primarily limited to providing only long term trending information for individual sensors or cross-calibration opportunities between two sensors. This paper builds an argument that PICS can be used more extensively for absolute calibration. To illustrate this, a simple empirical model is developed for the well-known Libya 4 PICS based on observations by Terra MODIS and EO-1 Hyperion. The model is validated by comparing model predicted top-of-atmosphere reflectance values to actual measurements made by the Landsat ETM+ sensor reflective bands. Following this, an outline is presented to develop a more comprehensive and accurate PICS absolute calibration model that can be Système international d'unités (SI) traceable. These initial concepts suggest that absolute calibration using PICS is possible on a broad scale and can lead to improved on-orbit calibration capabilities for optical satellite sensors.

Procedure for the Selection and Validation of a Calibration Model I-Description and Application.

Science.gov (United States)

Desharnais, Brigitte; Camirand-Lemyre, Félix; Mireault, Pascal; Skinner, Cameron D

2017-05-01

Calibration model selection is required for all quantitative methods in toxicology and more broadly in bioanalysis. This typically involves selecting the equation order (quadratic or linear) and weighting factor correctly modelizing the data. A mis-selection of the calibration model will generate lower quality control (QC) accuracy, with an error up to 154%. Unfortunately, simple tools to perform this selection and tests to validate the resulting model are lacking. We present a stepwise, analyst-independent scheme for selection and validation of calibration models. The success rate of this scheme is on average 40% higher than a traditional "fit and check the QCs accuracy" method of selecting the calibration model. Moreover, the process was completely automated through a script (available in Supplemental Data 3) running in RStudio (free, open-source software). The need for weighting was assessed through an F-test using the variances of the upper limit of quantification and lower limit of quantification replicate measurements. When weighting was required, the choice between 1/x and 1/x2 was determined by calculating which option generated the smallest spread of weighted normalized variances. Finally, model order was selected through a partial F-test. The chosen calibration model was validated through Cramer-von Mises or Kolmogorov-Smirnov normality testing of the standardized residuals. Performance of the different tests was assessed using 50 simulated data sets per possible calibration model (e.g., linear-no weight, quadratic-no weight, linear-1/x, etc.). This first of two papers describes the tests, procedures and outcomes of the developed procedure using real LC-MS-MS results for the quantification of cocaine and naltrexone. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Thermodynamically consistent model calibration in chemical kinetics

Directory of Open Access Journals (Sweden)

Goutsias John

2011-05-01

Full Text Available Abstract Background The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. Results We introduce a thermodynamically consistent model calibration (TCMC method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. Conclusions TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new

Diagnosing the impact of alternative calibration strategies on coupled hydrologic models

Science.gov (United States)

Smith, T. J.; Perera, C.; Corrigan, C.

2017-12-01

Hydrologic models represent a significant tool for understanding, predicting, and responding to the impacts of water on society and society on water resources and, as such, are used extensively in water resources planning and management. Given this important role, the validity and fidelity of hydrologic models is imperative. While extensive focus has been paid to improving hydrologic models through better process representation, better parameter estimation, and better uncertainty quantification, significant challenges remain. In this study, we explore a number of competing model calibration scenarios for simple, coupled snowmelt-runoff models to better understand the sensitivity / variability of parameterizations and its impact on model performance, robustness, fidelity, and transferability. Our analysis highlights the sensitivity of coupled snowmelt-runoff model parameterizations to alterations in calibration approach, underscores the concept of information content in hydrologic modeling, and provides insight into potential strategies for improving model robustness / fidelity.

Calibration of a distributed hydrologic model for six European catchments using remote sensing data

Science.gov (United States)

Stisen, S.; Demirel, M. C.; Mendiguren González, G.; Kumar, R.; Rakovec, O.; Samaniego, L. E.

2017-12-01

While observed streamflow has been the single reference for most conventional hydrologic model calibration exercises, the availability of spatially distributed remote sensing observations provide new possibilities for multi-variable calibration assessing both spatial and temporal variability of different hydrologic processes. In this study, we first identify the key transfer parameters of the mesoscale Hydrologic Model (mHM) controlling both the discharge and the spatial distribution of actual evapotranspiration (AET) across six central European catchments (Elbe, Main, Meuse, Moselle, Neckar and Vienne). These catchments are selected based on their limited topographical and climatic variability which enables to evaluate the effect of spatial parameterization on the simulated evapotranspiration patterns. We develop a European scale remote sensing based actual evapotranspiration dataset at a 1 km grid scale driven primarily by land surface temperature observations from MODIS using the TSEB approach. Using the observed AET maps we analyze the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mHM model. This model allows calibrating one-basin-at-a-time or all-basins-together using its unique structure and multi-parameter regionalization approach. Results will indicate any tradeoffs between spatial pattern and discharge simulation during model calibration and through validation against independent internal discharge locations. Moreover, added value on internal water balances will be analyzed.

Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.

Science.gov (United States)

Enns, Eva A; Cipriano, Lauren E; Simons, Cyrena T; Kong, Chung Yin

2015-02-01

To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single goodness-of-fit (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. We demonstrate the Pareto frontier approach in the calibration of 2 models: a simple, illustrative Markov model and a previously published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to 2 possible weighted-sum GOF scoring systems, and we compare the health economic conclusions arising from these different definitions of best-fitting. For the simple model, outcomes evaluated over the best-fitting input sets according to the 2 weighted-sum GOF schemes were virtually nonoverlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95% CI 72,500-87,600] v. $139,700 [95% CI 79,900-182,800] per quality-adjusted life-year [QALY] gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95% CI 64,900-156,200] per QALY gained). The TAVR model yielded similar results. Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets. © The Author(s) 2014.

Uncertainty analyses of the calibrated parameter values of a water quality model

Science.gov (United States)

Rode, M.; Suhr, U.; Lindenschmidt, K.-E.

2003-04-01

For river basin management water quality models are increasingly used for the analysis and evaluation of different management measures. However substantial uncertainties exist in parameter values depending on the available calibration data. In this paper an uncertainty analysis for a water quality model is presented, which considers the impact of available model calibration data and the variance of input variables. The investigation was conducted based on four extensive flowtime related longitudinal surveys in the River Elbe in the years 1996 to 1999 with varying discharges and seasonal conditions. For the model calculations the deterministic model QSIM of the BfG (Germany) was used. QSIM is a one dimensional water quality model and uses standard algorithms for hydrodynamics and phytoplankton dynamics in running waters, e.g. Michaelis Menten/Monod kinetics, which are used in a wide range of models. The multi-objective calibration of the model was carried out with the nonlinear parameter estimator PEST. The results show that for individual flow time related measuring surveys very good agreements between model calculation and measured values can be obtained. If these parameters are applied to deviating boundary conditions, substantial errors in model calculation can occur. These uncertainties can be decreased with an increased calibration database. More reliable model parameters can be identified, which supply reasonable results for broader boundary conditions. The extension of the application of the parameter set on a wider range of water quality conditions leads to a slight reduction of the model precision for the specific water quality situation. Moreover the investigations show that highly variable water quality variables like the algal biomass always allow a smaller forecast accuracy than variables with lower coefficients of variation like e.g. nitrate.

A Fundamental Parameter-Based Calibration Model for an Intrinsic Germanium X-Ray Fluorescence Spectrometer

DEFF Research Database (Denmark)

Christensen, Leif Højslet; Pind, Niels

1982-01-01

A matrix-independent fundamental parameter-based calibration model for an energy-dispersive X-ray fluorescence spectrometer has been developed. This model, which is part of a fundamental parameter approach quantification method, accounts for both the excitation and detection probability. For each...... secondary target a number of relative calibration constants are calculated on the basis of knowledge of the irradiation geometry, the detector specifications, and tabulated fundamental physical parameters. The absolute calibration of the spectrometer is performed by measuring one pure element standard per...

The Wally plot approach to assess the calibration of clinical prediction models.

Science.gov (United States)

Blanche, Paul; Gerds, Thomas A; Ekstrøm, Claus T

2017-12-06

A prediction model is calibrated if, roughly, for any percentage x we can expect that x subjects out of 100 experience the event among all subjects that have a predicted risk of x%. Typically, the calibration assumption is assessed graphically but in practice it is often challenging to judge whether a "disappointing" calibration plot is the consequence of a departure from the calibration assumption, or alternatively just "bad luck" due to sampling variability. We propose a graphical approach which enables the visualization of how much a calibration plot agrees with the calibration assumption to address this issue. The approach is mainly based on the idea of generating new plots which mimic the available data under the calibration assumption. The method handles the common non-trivial situations in which the data contain censored observations and occurrences of competing events. This is done by building on ideas from constrained non-parametric maximum likelihood estimation methods. Two examples from large cohort data illustrate our proposal. The 'wally' R package is provided to make the methodology easily usable.

ANN-based calibration model of FTIR used in transformer online monitoring

Science.gov (United States)

Li, Honglei; Liu, Xian-yong; Zhou, Fangjie; Tan, Kexiong

2005-02-01

Recently, chromatography column and gas sensor have been used in online monitoring device of dissolved gases in transformer oil. But some disadvantages still exist in these devices: consumption of carrier gas, requirement of calibration, etc. Since FTIR has high accuracy, consume no carrier gas and require no calibration, the researcher studied the application of FTIR in such monitoring device. Experiments of "Flow gas method" were designed, and spectrum of mixture composed of different gases was collected with A BOMEM MB104 FTIR Spectrometer. A key question in the application of FTIR is that: the absorbance spectrum of 3 fault key gases, including C2H4, CH4 and C2H6, are overlapped seriously at 2700~3400cm-1. Because Absorbance Law is no longer appropriate, a nonlinear calibration model based on BP ANN was setup to in the quantitative analysis. The height absorbance of C2H4, CH4 and C2H6 were adopted as quantitative feature, and all the data were normalized before training the ANN. Computing results show that the calibration model can effectively eliminate the cross disturbance to measurement.

How does observation uncertainty influence which stream water samples are most informative for model calibration?

Science.gov (United States)

Wang, Ling; van Meerveld, Ilja; Seibert, Jan

2016-04-01

Streamflow isotope samples taken during rainfall-runoff events are very useful for multi-criteria model calibration because they can help decrease parameter uncertainty and improve internal model consistency. However, the number of samples that can be collected and analysed is often restricted by practical and financial constraints. It is, therefore, important to choose an appropriate sampling strategy and to obtain samples that have the highest information content for model calibration. We used the Birkenes hydrochemical model and synthetic rainfall, streamflow and isotope data to explore which samples are most informative for model calibration. Starting with error-free observations, we investigated how many samples are needed to obtain a certain model fit. Based on different parameter sets, representing different catchments, and different rainfall events, we also determined which sampling times provide the most informative data for model calibration. Our results show that simulation performance for models calibrated with the isotopic data from two intelligently selected samples was comparable to simulations based on isotopic data for all 100 time steps. The models calibrated with the intelligently selected samples also performed better than the model calibrations with two benchmark sampling strategies (random selection and selection based on hydrologic information). Surprisingly, samples on the rising limb and at the peak were less informative than expected and, generally, samples taken at the end of the event were most informative. The timing of the most informative samples depends on the proportion of different flow components (baseflow, slow response flow, fast response flow and overflow). For events dominated by baseflow and slow response flow, samples taken at the end of the event after the fast response flow has ended were most informative; when the fast response flow was dominant, samples taken near the peak were most informative. However when overflow

Calibration of the 7—Equation Transition Model for High Reynolds Flows at Low Mach

Science.gov (United States)

Colonia, S.; Leble, V.; Steijl, R.; Barakos, G.

2016-09-01

The numerical simulation of flows over large-scale wind turbine blades without considering the transition from laminar to fully turbulent flow may result in incorrect estimates of the blade loads and performance. Thanks to its relative simplicity and promising results, the Local-Correlation based Transition Modelling concept represents a valid way to include transitional effects into practical CFD simulations. However, the model involves coefficients that need tuning. In this paper, the γ—equation transition model is assessed and calibrated, for a wide range of Reynolds numbers at low Mach, as needed for wind turbine applications. An aerofoil is used to evaluate the original model and calibrate it; while a large scale wind turbine blade is employed to show that the calibrated model can lead to reliable solutions for complex three-dimensional flows. The calibrated model shows promising results for both two-dimensional and three-dimensional flows, even if cross-flow instabilities are neglected.

An alternative method for calibration of narrow band radiometer using a radiative transfer model

Energy Technology Data Exchange (ETDEWEB)

Salvador, J; Wolfram, E; D' Elia, R [Centro de Investigaciones en Laseres y Aplicaciones, CEILAP (CITEFA-CONICET), Juan B. de La Salle 4397 (B1603ALO), Villa Martelli, Buenos Aires (Argentina); Zamorano, F; Casiccia, C [Laboratorio de Ozono y Radiacion UV, Universidad de Magallanes, Punta Arenas (Chile) (Chile); Rosales, A [Universidad Nacional de la Patagonia San Juan Bosco, UNPSJB, Facultad de Ingenieria, Trelew (Argentina) (Argentina); Quel, E, E-mail: jsalvador@citefa.gov.ar [Universidad Nacional de la Patagonia Austral, Unidad Academica Rio Gallegos Avda. Lisandro de la Torre 1070 ciudad de Rio Gallegos-Sta Cruz (Argentina) (Argentina)

2011-01-01

The continual monitoring of solar UV radiation is one of the major objectives proposed by many atmosphere research groups. The purpose of this task is to determine the status and degree of progress over time of the anthropogenic composition perturbation of the atmosphere. Such changes affect the intensity of the UV solar radiation transmitted through the atmosphere that then interacts with living organisms and all materials, causing serious consequences in terms of human health and durability of materials that interact with this radiation. One of the many challenges that need to be faced to perform these measurements correctly is the maintenance of periodic calibrations of these instruments. Otherwise, damage caused by the UV radiation received will render any one calibration useless after the passage of some time. This requirement makes the usage of these instruments unattractive, and the lack of frequent calibration may lead to the loss of large amounts of acquired data. Motivated by this need to maintain calibration or, at least, know the degree of stability of instrumental behavior, we have developed a calibration methodology that uses the potential of radiative transfer models to model solar radiation with 5% accuracy or better relative to actual conditions. Voltage values in each radiometer channel involved in the calibration process are carefully selected from clear sky data. Thus, tables are constructed with voltage values corresponding to various atmospheric conditions for a given solar zenith angle. Then we model with a radiative transfer model using the same conditions as for the measurements to assemble sets of values for each zenith angle. The ratio of each group (measured and modeled) allows us to calculate the calibration coefficient value as a function of zenith angle as well as the cosine response presented by the radiometer. The calibration results obtained by this method were compared with those obtained with a Brewer MKIII SN 80 located in the

A case study on robust optimal experimental design for model calibration of ω-Transaminase

DEFF Research Database (Denmark)

Daele, Timothy, Van; Van Hauwermeiren, Daan; Ringborg, Rolf Hoffmeyer

the experimental space. However, it is expected that more informative experiments can be designed to increase the confidence of the parameter estimates. Therefore, we apply Optimal Experimental Design (OED) to the calibrated model of Shin and Kim (1998). The total number of samples was retained to allow fair......” parameter values are not known before finishing the model calibration. However, it is important that the chosen parameter values are close to the real parameter values, otherwise the OED can possibly yield non-informative experiments. To counter this problem, one can use robust OED. The idea of robust OED......Proper calibration of models describing enzyme kinetics can be quite challenging. This is especially the case for more complex models like transaminase models (Shin and Kim, 1998). The latter fitted model parameters, but the confidence on the parameter estimation was not derived. Hence...

Balance between calibration objectives in a conceptual hydrological model

NARCIS (Netherlands)

Booij, Martijn J.; Krol, Martinus S.

2010-01-01

Three different measures to determine the optimum balance between calibration objectives are compared: the combined rank method, parameter identifiability and model validation. Four objectives (water balance, hydrograph shape, high flows, low flows) are included in each measure. The contributions of

When to Make Mountains out of Molehills: The Pros and Cons of Simple and Complex Model Calibration Procedures

Science.gov (United States)

Smith, K. A.; Barker, L. J.; Harrigan, S.; Prudhomme, C.; Hannaford, J.; Tanguy, M.; Parry, S.

2017-12-01

Earth and environmental models are relied upon to investigate system responses that cannot otherwise be examined. In simulating physical processes, models have adjustable parameters which may, or may not, have a physical meaning. Determining the values to assign to these model parameters is an enduring challenge for earth and environmental modellers. Selecting different error metrics by which the models results are compared to observations will lead to different sets of calibrated model parameters, and thus different model results. Furthermore, models may exhibit `equifinal' behaviour, where multiple combinations of model parameters lead to equally acceptable model performance against observations. These decisions in model calibration introduce uncertainty that must be considered when model results are used to inform environmental decision-making. This presentation focusses on the uncertainties that derive from the calibration of a four parameter lumped catchment hydrological model (GR4J). The GR models contain an inbuilt automatic calibration algorithm that can satisfactorily calibrate against four error metrics in only a few seconds. However, a single, deterministic model result does not provide information on parameter uncertainty. Furthermore, a modeller interested in extreme events, such as droughts, may wish to calibrate against more low flows specific error metrics. In a comprehensive assessment, the GR4J model has been run with 500,000 Latin Hypercube Sampled parameter sets across 303 catchments in the United Kingdom. These parameter sets have been assessed against six error metrics, including two drought specific metrics. This presentation compares the two approaches, and demonstrates that the inbuilt automatic calibration can outperform the Latin Hypercube experiment approach in single metric assessed performance. However, it is also shown that there are many merits of the more comprehensive assessment, which allows for probabilistic model results, multi

Model independent approach to the single photoelectron calibration of photomultiplier tubes

Energy Technology Data Exchange (ETDEWEB)

Saldanha, R.; Grandi, L.; Guardincerri, Y.; Wester, T.

2017-08-01

The accurate calibration of photomultiplier tubes is critical in a wide variety of applications in which it is necessary to know the absolute number of detected photons or precisely determine the resolution of the signal. Conventional calibration methods rely on fitting the photomultiplier response to a low intensity light source with analytical approximations to the single photoelectron distribution, often leading to biased estimates due to the inability to accurately model the full distribution, especially at low charge values. In this paper we present a simple statistical method to extract the relevant single photoelectron calibration parameters without making any assumptions about the underlying single photoelectron distribution. We illustrate the use of this method through the calibration of a Hamamatsu R11410 photomultiplier tube and study the accuracy and precision of the method using Monte Carlo simulations. The method is found to have significantly reduced bias compared to conventional methods and works under a wide range of light intensities, making it suitable for simultaneously calibrating large arrays of photomultiplier tubes.

Calibration of HEC-Ras hydrodynamic model using gauged discharge data and flood inundation maps

Science.gov (United States)

Tong, Rui; Komma, Jürgen

2017-04-01

The estimation of flood is essential for disaster alleviation. Hydrodynamic models are implemented to predict the occurrence and variance of flood in different scales. In practice, the calibration of hydrodynamic models aims to search the best possible parameters for the representation the natural flow resistance. Recent years have seen the calibration of hydrodynamic models being more actual and faster following the advance of earth observation products and computer based optimization techniques. In this study, the Hydrologic Engineering River Analysis System (HEC-Ras) model was set up with high-resolution digital elevation model from Laser scanner for the river Inn in Tyrol, Austria. 10 largest flood events from 19 hourly discharge gauges and flood inundation maps were selected to calibrate the HEC-Ras model. Manning roughness values and lateral inflow factors as parameters were automatically optimized with the Shuffled complex with Principal component analysis (SP-UCI) algorithm developed from the Shuffled Complex Evolution (SCE-UA). Different objective functions (Nash-Sutcliffe model efficiency coefficient, the timing of peak, peak value and Root-mean-square deviation) were used in single or multiple way. It was found that the lateral inflow factor was the most sensitive parameter. SP-UCI algorithm could avoid the local optimal and achieve efficient and effective parameters in the calibration of HEC-Ras model using flood extension images. As results showed, calibration by means of gauged discharge data and flood inundation maps, together with objective function of Nash-Sutcliffe model efficiency coefficient, was very robust to obtain more reliable flood simulation, and also to catch up with the peak value and the timing of peak.

Modeling microelectrode biosensors: free-flow calibration can substantially underestimate tissue concentrations.

Science.gov (United States)

Newton, Adam J H; Wall, Mark J; Richardson, Magnus J E

2017-03-01

Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments. NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue

Calibration of discrete element model parameters: soybeans

Science.gov (United States)

Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal

2018-05-01

Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.

Technical Note: Calibration and validation of geophysical observation models

NARCIS (Netherlands)

Salama, M.S.; van der Velde, R.; van der Woerd, H.J.; Kromkamp, J.C.; Philippart, C.J.M.; Joseph, A.T.; O'Neill, P.E.; Lang, R.H.; Gish, T.; Werdell, P.J.; Su, Z.

2012-01-01

We present a method to calibrate and validate observational models that interrelate remotely sensed energy fluxes to geophysical variables of land and water surfaces. Coincident sets of remote sensing observation of visible and microwave radiations and geophysical data are assembled and subdivided

Calibrating Vadose Zone Models with Time-Lapse Gravity Data

DEFF Research Database (Denmark)

Christiansen, Lars; Hansen, A. B.; Looms, M. C.

2009-01-01

A change in soil water content is a change in mass stored in the subsurface. Given that the mass change is big enough, the change can be measured with a gravity meter. Attempts have been made with varying success over the last decades to use ground-based time-lapse gravity measurements to infer...... hydrogeological parameters. These studies focused on the saturated zone with specific yield as the most prominent target parameter. Any change in storage in the vadose zone has been considered as noise. Our modeling results show a measureable change in gravity from the vadose zone during a forced infiltration...... experiment on 10m by 10m grass land. Simulation studies show a potential for vadose zone model calibration using gravity data in conjunction with other geophysical data, e.g. cross-borehole georadar. We present early field data and calibration results from a forced infiltration experiment conducted over 30...

Model calibration of a variable refrigerant flow system with a dedicated outdoor air system: A case study

Energy Technology Data Exchange (ETDEWEB)

Kim, Dongsu [Mississippi State Univ., Starkville, MS (United States); Cox, Sam J. [Mississippi State Univ., Starkville, MS (United States); Cho, Heejin [Mississippi State Univ., Starkville, MS (United States); Im, Piljae [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2017-10-16

With increased use of variable refrigerant flow (VRF) systems in the U.S. building sector, interests in capability and rationality of various building energy modeling tools to simulate VRF systems are rising. This paper presents the detailed procedures for model calibration of a VRF system with a dedicated outdoor air system (DOAS) by comparing to detailed measured data from an occupancy emulated small office building. The building energy model is first developed based on as-built drawings, and building and system characteristics available. The whole building energy modeling tool used for the study is U.S. DOE’s EnergyPlus version 8.1. The initial model is, then, calibrated with the hourly measured data from the target building and VRF-DOAS system. In a detailed calibration procedures of the VRF-DOAS, the original EnergyPlus source code is modified to enable the modeling of the specific VRF-DOAS installed in the building. After a proper calibration during cooling and heating seasons, the VRF-DOAS model can reasonably predict the performance of the actual VRF-DOAS system based on the criteria from ASHRAE Guideline 14-2014. The calibration results show that hourly CV-RMSE and NMBE would be 15.7% and 3.8%, respectively, which is deemed to be calibrated. As a result, the whole-building energy usage after calibration of the VRF-DOAS model is 1.9% (78.8 kWh) lower than that of the measurements during comparison period.

Electroweak Calibration of the Higgs Characterization Model

CERN Multimedia

CERN. Geneva

2015-01-01

I will present the preliminary results of histogram fits using the Higgs Combine histogram fitting package. These fits can be used to estimate the effects of electroweak contributions to the p p -> H mu+ mu- Higgs production channel and calibrate Beyond Standard Model (BSM) simulations which ignore these effects. I will emphasize my findings' significance in the context of other research here at CERN and in the broader world of high energy physics.

A fundamental parameter-based calibration model for an intrinsic germanium X-ray fluorescence spectrometer

International Nuclear Information System (INIS)

Christensen, L.H.; Pind, N.

1982-01-01

A matrix-independent fundamental parameter-based calibration model for an energy-dispersive X-ray fluorescence spectrometer has been developed. This model, which is part of a fundamental parameter approach quantification method, accounts for both the excitation and detection probability. For each secondary target a number of relative calibration constants are calculated on the basis of knowledge of the irradiation geometry, the detector specifications, and tabulated fundamental physical parameters. The absolute calibration of the spectrometer is performed by measuring one pure element standard per secondary target. For sample systems where all elements can be analyzed by means of the same secondary target the absolute calibration constant can be determined during the iterative solution of the basic equation. Calculated and experimentally determined relative calibration constants agree to within 5-10% of each other and so do the results obtained from the analysis of an NBS certified alloy using the two sets of constants. (orig.)

Multiple-Objective Stepwise Calibration Using Luca

Science.gov (United States)

Hay, Lauren E.; Umemoto, Makiko

2007-01-01

This report documents Luca (Let us calibrate), a multiple-objective, stepwise, automated procedure for hydrologic model calibration and the associated graphical user interface (GUI). Luca is a wizard-style user-friendly GUI that provides an easy systematic way of building and executing a calibration procedure. The calibration procedure uses the Shuffled Complex Evolution global search algorithm to calibrate any model compiled with the U.S. Geological Survey's Modular Modeling System. This process assures that intermediate and final states of the model are simulated consistently with measured values.

LED-based Photometric Stereo: Modeling, Calibration and Numerical Solutions

DEFF Research Database (Denmark)

Quéau, Yvain; Durix, Bastien; Wu, Tao

2018-01-01

We conduct a thorough study of photometric stereo under nearby point light source illumination, from modeling to numerical solution, through calibration. In the classical formulation of photometric stereo, the luminous fluxes are assumed to be directional, which is very difficult to achieve in pr...

Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

International Nuclear Information System (INIS)

Marseguerra, Marzio; Zio, Enrico; Canetta, Raffaele

2004-01-01

In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved

Using genetic algorithms for calibrating simplified models of nuclear reactor dynamics

Energy Technology Data Exchange (ETDEWEB)

Marseguerra, Marzio E-mail: marzio.marseguerra@polimi.it; Zio, Enrico E-mail: enrico.zio@polimi.it; Canetta, Raffaele

2004-07-01

In this paper the use of genetic algorithms for the estimation of the effective parameters of a model of nuclear reactor dynamics is investigated. The calibration of the effective parameters is achieved by best fitting the model responses of the quantities of interest (e.g., reactor power, average fuel and coolant temperatures) to the actual evolution profiles, here simulated by the Quandry based reactor kinetics (Quark) code available from the Nuclear Energy Agency. Alternative schemes of single- and multi-objective optimization are investigated. The efficiency of convergence of the algorithm with respect to the different effective parameters to be calibrated is studied with reference to the physical relationships involved.

Calibration of Airframe and Occupant Models for Two Full-Scale Rotorcraft Crash Tests

Science.gov (United States)

Annett, Martin S.; Horta, Lucas G.; Polanco, Michael A.

2012-01-01

Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. Accelerations and kinematic data collected from the crash tests were compared to a system integrated finite element model of the test article. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the second full-scale crash test. This combination of heuristic and quantitative methods was used to identify modeling deficiencies, evaluate parameter importance, and propose required model changes. It is shown that the multi-dimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and co-pilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. This approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and test planning guidance. Complete crash simulations with validated finite element models can be used

Calibration of Yucca Mountain unsaturated zone flow and transport model using porewater chloride data

International Nuclear Information System (INIS)

Liu, Jianchun; Sonnenthal, Eric L.; Bodvarsson, Gudmundur S.

2002-01-01

In this study, porewater chloride data from Yucca Mountain, Nevada, are analyzed and modeled by 3-D chemical transport simulations and analytical methods. The simulation modeling approach is based on a continuum formulation of coupled multiphase fluid flow and tracer transport processes through fractured porous rock, using a dual-continuum concept. Infiltration-rate calibrations were using the pore water chloride data. Model results of chloride distributions were improved in matching the observed data with the calibrated infiltration rates. Statistical analyses of the frequency distribution for overall percolation fluxes and chloride concentration in the unsaturated zone system demonstrate that the use of the calibrated infiltration rates had insignificant effect on the distribution of simulated percolation fluxes but significantly changed the predicated distribution of simulated chloride concentrations. An analytical method was also applied to model transient chloride transport. The method was verified by 3-D simulation results as able to capture major chemical transient behavior and trends. Effects of lateral flow in the Paintbrush nonwelded unit on percolation fluxes and chloride distribution were studied by 3-D simulations with increased horizontal permeability. The combined results from these model calibrations furnish important information for the UZ model studies, contributing to performance assessment of the potential repository

Calibration of uncertain inputs to computer models using experimentally measured quantities and the BMARS emulator

International Nuclear Information System (INIS)

Stripling, H.F.; McClarren, R.G.; Kuranz, C.C.; Grosskopf, M.J.; Rutter, E.; Torralva, B.R.

2011-01-01

We present a method for calibrating the uncertain inputs to a computer model using available experimental data. The goal of the procedure is to produce posterior distributions of the uncertain inputs such that when samples from the posteriors are used as inputs to future model runs, the model is more likely to replicate (or predict) the experimental response. The calibration is performed by sampling the space of the uncertain inputs, using the computer model (or, more likely, an emulator for the computer model) to assign weights to the samples, and applying the weights to produce the posterior distributions and generate predictions of new experiments within confidence bounds. The method is similar to the Markov chain Monte Carlo (MCMC) calibration methods with independent sampling with the exception that we generate samples beforehand and replace the candidate acceptance routine with a weighting scheme. We apply our method to the calibration of a Hyades 2D model of laser energy deposition in beryllium. We employ a Bayesian Multivariate Adaptive Regression Splines (BMARS) emulator as a surrogate for Hyades 2D. We treat a range of uncertainties in our system, including uncertainties in the experimental inputs, experimental measurement error, and systematic experimental timing errors. The results of the calibration are posterior distributions that both agree with intuition and improve the accuracy and decrease the uncertainty in experimental predictions. (author)

Presentation, calibration and validation of the low-order, DCESS Earth System Model

DEFF Research Database (Denmark)

Shaffer, G.; Olsen, S. Malskaer; Pedersen, Jens Olaf Pepke

2008-01-01

A new, low-order Earth system model is described, calibrated and tested against Earth system data. The model features modules for the atmosphere, ocean, ocean sediment, land biosphere and lithosphere and has been designed to simulate global change on time scales of years to millions of years...... remineralization. The lithosphere module considers outgassing, weathering of carbonate and silicate rocks and weathering of rocks containing old organic carbon and phosphorus. Weathering rates are related to mean atmospheric temperatures. A pre-industrial, steady state calibration to Earth system data is carried...

Regional Calibration of SCS-CN L-THIA Model: Application for Ungauged Basins

Directory of Open Access Journals (Sweden)

Ji-Hong Jeon

2014-05-01

Full Text Available Estimating surface runoff for ungauged watershed is an important issue. The Soil Conservation Service Curve Number (SCS-CN method developed from long-term experimental data is widely used to estimate surface runoff from gaged or ungauged watersheds. Many modelers have used the documented SCS-CN parameters without calibration, sometimes resulting in significant errors in estimating surface runoff. Several methods for regionalization of SCS-CN parameters were evaluated. The regionalization methods include: (1 average; (2 land use area weighted average; (3 hydrologic soil group area weighted average; (4 area combined land use and hydrologic soil group weighted average; (5 spatial nearest neighbor; (6 inverse distance weighted average; and (7 global calibration method, and model performance for each method was evaluated with application to 14 watersheds located in Indiana. Eight watersheds were used for calibration and six watersheds for validation. For the validation results, the spatial nearest neighbor method provided the highest average Nash-Sutcliffe (NS value at 0.58 for six watersheds but it included the lowest NS value and variance of NS values of this method was the highest. The global calibration method provided the second highest average NS value at 0.56 with low variation of NS values. Although the spatial nearest neighbor method provided the highest average NS value, this method was not statistically different than other methods. However, the global calibration method was significantly different than other methods except the spatial nearest neighbor method. Therefore, we conclude that the global calibration method is appropriate to regionalize SCS-CN parameters for ungauged watersheds.

Generator Dynamic Model Validation and Parameter Calibration Using Phasor Measurements at the Point of Connection

Energy Technology Data Exchange (ETDEWEB)

Huang, Zhenyu; Du, Pengwei; Kosterev, Dmitry; Yang, Steve

2013-05-01

Disturbance data recorded by phasor measurement units (PMU) offers opportunities to improve the integrity of dynamic models. However, manually tuning parameters through play-back events demands significant efforts and engineering experiences. In this paper, a calibration method using the extended Kalman filter (EKF) technique is proposed. The formulation of EKF with parameter calibration is discussed. Case studies are presented to demonstrate its validity. The proposed calibration method is cost-effective, complementary to traditional equipment testing for improving dynamic model quality.

PEST modules with regularization for the acceleration of the automatic calibration in hydrodynamic models

OpenAIRE

Polomčić, Dušan M.; Bajić, Dragoljub I.; Močević, Jelena M.

2015-01-01

The calibration process of hydrodynamic model is done usually manually by 'testing' with different values of hydrogeological parameters and hydraulic characteristics of the boundary conditions. By using the PEST program, automatic calibration of models has been introduced, and it has proved to significantly reduce the subjective influence of the model creator on results. With the relatively new approach of PEST, i.e. with the introduction of so-called 'pilot points', the concept of homogeneou...

Radiolytic modelling of spent fuel oxidative dissolution mechanism. Calibration against UO2 dynamic leaching experiments

International Nuclear Information System (INIS)

Merino, J.; Cera, E.; Bruno, J.; Quinones, J.; Casas, I.; Clarens, F.; Gimenez, J.; Pablo, J. de; Rovira, M.; Martinez-Esparza, A.

2005-01-01

Calibration and testing are inherent aspects of any modelling exercise and consequently they are key issues in developing a model for the oxidative dissolution of spent fuel. In the present work we present the outcome of the calibration process for the kinetic constants of a UO 2 oxidative dissolution mechanism developed for using in a radiolytic model. Experimental data obtained in dynamic leaching experiments of unirradiated UO 2 has been used for this purpose. The iterative calibration process has provided some insight into the detailed mechanism taking place in the alteration of UO 2 , particularly the role of · OH radicals and their interaction with the carbonate system. The results show that, although more simulations are needed for testing in different experimental systems, the calibrated oxidative dissolution mechanism could be included in radiolytic models to gain confidence in the prediction of the long-term alteration rate of the spent fuel under repository conditions

HYDROGRAV - Hydrological model calibration and terrestrial water storage monitoring from GRACE gravimetry and satellite altimetry, First results

DEFF Research Database (Denmark)

Andersen, O.B.; Krogh, P.E.; Michailovsky, C.

2008-01-01

Space-borne and ground-based time-lapse gravity observations provide new data for water balance monitoring and hydrological model calibration in the future. The HYDROGRAV project (www.hydrograv.dk) will explore the utility of time-lapse gravity surveys for hydrological model calibration and terre...... change from 2002 to 2008 along with in-situ gravity time-lapse observations and radar altimetry monitoring of surface water for the southern Africa river basins will be presented.......Space-borne and ground-based time-lapse gravity observations provide new data for water balance monitoring and hydrological model calibration in the future. The HYDROGRAV project (www.hydrograv.dk) will explore the utility of time-lapse gravity surveys for hydrological model calibration...... and terrestrial water storage monitoring. Merging remote sensing data from GRACE with other remote sensing data like satellite altimetry and also ground based observations are important to hydrological model calibration and water balance monitoring of large regions and can serve as either supplement or as vital...

Linear model correction: A method for transferring a near-infrared multivariate calibration model without standard samples

Science.gov (United States)

Liu, Yan; Cai, Wensheng; Shao, Xueguang

2016-12-01

Calibration transfer is essential for practical applications of near infrared (NIR) spectroscopy because the measurements of the spectra may be performed on different instruments and the difference between the instruments must be corrected. For most of calibration transfer methods, standard samples are necessary to construct the transfer model using the spectra of the samples measured on two instruments, named as master and slave instrument, respectively. In this work, a method named as linear model correction (LMC) is proposed for calibration transfer without standard samples. The method is based on the fact that, for the samples with similar physical and chemical properties, the spectra measured on different instruments are linearly correlated. The fact makes the coefficients of the linear models constructed by the spectra measured on different instruments are similar in profile. Therefore, by using the constrained optimization method, the coefficients of the master model can be transferred into that of the slave model with a few spectra measured on slave instrument. Two NIR datasets of corn and plant leaf samples measured with different instruments are used to test the performance of the method. The results show that, for both the datasets, the spectra can be correctly predicted using the transferred partial least squares (PLS) models. Because standard samples are not necessary in the method, it may be more useful in practical uses.

Stochastic Modeling of Overtime Occupancy and Its Application in Building Energy Simulation and Calibration

Energy Technology Data Exchange (ETDEWEB)

Sun, Kaiyu; Yan, Da; Hong, Tianzhen; Guo, Siyue

2014-02-28

Overtime is a common phenomenon around the world. Overtime drives both internal heat gains from occupants, lighting and plug-loads, and HVAC operation during overtime periods. Overtime leads to longer occupancy hours and extended operation of building services systems beyond normal working hours, thus overtime impacts total building energy use. Current literature lacks methods to model overtime occupancy because overtime is stochastic in nature and varies by individual occupants and by time. To address this gap in the literature, this study aims to develop a new stochastic model based on the statistical analysis of measured overtime occupancy data from an office building. A binomial distribution is used to represent the total number of occupants working overtime, while an exponential distribution is used to represent the duration of overtime periods. The overtime model is used to generate overtime occupancy schedules as an input to the energy model of a second office building. The measured and simulated cooling energy use during the overtime period is compared in order to validate the overtime model. A hybrid approach to energy model calibration is proposed and tested, which combines ASHRAE Guideline 14 for the calibration of the energy model during normal working hours, and a proposed KS test for the calibration of the energy model during overtime. The developed stochastic overtime model and the hybrid calibration approach can be used in building energy simulations to improve the accuracy of results, and better understand the characteristics of overtime in office buildings.

Calibration plots for risk prediction models in the presence of competing risks.

Science.gov (United States)

Gerds, Thomas A; Andersen, Per K; Kattan, Michael W

2014-08-15

A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks such as death due to other causes. For personalized medicine and patient counseling, it is necessary to check that the model is calibrated in the sense that it provides reliable predictions for all subjects. There are three often encountered practical problems when the aim is to display or test if a risk prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves for competing risks models based on jackknife pseudo-values that are combined with a nearest neighborhood smoother and a cross-validation approach to deal with all three problems. Copyright © 2014 John Wiley & Sons, Ltd.

Comparison of different multi-objective calibration criteria using a conceptual rainfall-runoff model of flood events

Directory of Open Access Journals (Sweden)

R. Moussa

2009-04-01

Full Text Available A conceptual lumped rainfall-runoff flood event model was developed and applied on the Gardon catchment located in Southern France and various single-objective and multi-objective functions were used for its calibration. The model was calibrated on 15 events and validated on 14 others. The results of both the calibration and validation phases are compared on the basis of their performance with regards to six criteria, three global criteria and three relative criteria representing volume, peakflow, and the root mean square error. The first type of criteria gives more weight to large events whereas the second considers all events to be of equal weight. The results show that the calibrated parameter values are dependent on the type of criteria used. Significant trade-offs are observed between the different objectives: no unique set of parameters is able to satisfy all objectives simultaneously. Instead, the solution to the calibration problem is given by a set of Pareto optimal solutions. From this set of optimal solutions, a balanced aggregated objective function is proposed, as a compromise between up to three objective functions. The single-objective and multi-objective calibration strategies are compared both in terms of parameter variation bounds and simulation quality. The results of this study indicate that two well chosen and non-redundant objective functions are sufficient to calibrate the model and that the use of three objective functions does not necessarily yield different results. The problems of non-uniqueness in model calibration, and the choice of the adequate objective functions for flood event models, emphasise the importance of the modeller's intervention. The recent advances in automatic optimisation techniques do not minimise the user's responsibility, who has to choose multiple criteria based on the aims of the study, his appreciation on the errors induced by data and model structure and his knowledge of the

A Novel Error Model of Optical Systems and an On-Orbit Calibration Method for Star Sensors

Directory of Open Access Journals (Sweden)

Shuang Wang

2015-12-01

Full Text Available In order to improve the on-orbit measurement accuracy of star sensors, the effects of image-plane rotary error, image-plane tilt error and distortions of optical systems resulting from the on-orbit thermal environment were studied in this paper. Since these issues will affect the precision of star image point positions, in this paper, a novel measurement error model based on the traditional error model is explored. Due to the orthonormal characteristics of image-plane rotary-tilt errors and the strong nonlinearity among these error parameters, it is difficult to calibrate all the parameters simultaneously. To solve this difficulty, for the new error model, a modified two-step calibration method based on the Extended Kalman Filter (EKF and Least Square Methods (LSM is presented. The former one is used to calibrate the main point drift, focal length error and distortions of optical systems while the latter estimates the image-plane rotary-tilt errors. With this calibration method, the precision of star image point position influenced by the above errors is greatly improved from 15.42% to 1.389%. Finally, the simulation results demonstrate that the presented measurement error model for star sensors has higher precision. Moreover, the proposed two-step method can effectively calibrate model error parameters, and the calibration precision of on-orbit star sensors is also improved obviously.

Technical Note: Procedure for the calibration and validation of kilo-voltage cone-beam CT models

Energy Technology Data Exchange (ETDEWEB)

Vilches-Freixas, Gloria; Létang, Jean Michel; Rit, Simon, E-mail: simon.rit@creatis.insa-lyon.fr [Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1206, INSA-Lyon, Université Lyon 1, Centre Léon Bérard, Lyon 69373 Cedex 08 (France); Brousmiche, Sébastien [Ion Beam Application, Louvain-la-Neuve 1348 (Belgium); Romero, Edward; Vila Oliva, Marc [Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1206, INSA-Lyon, Université Lyon 1, Centre Léon Bérard, Lyon 69373 Cedex 08, France and Ion Beam Application, Louvain-la-Neuve 1348 (Belgium); Kellner, Daniel; Deutschmann, Heinz; Keuschnigg, Peter; Steininger, Philipp [Institute for Research and Development on Advanced Radiation Technologies, Paracelsus Medical University, Salzburg 5020 (Austria)

2016-09-15

Purpose: The aim of this work is to propose a general and simple procedure for the calibration and validation of kilo-voltage cone-beam CT (kV CBCT) models against experimental data. Methods: The calibration and validation of the CT model is a two-step procedure: the source model then the detector model. The source is described by the direction dependent photon energy spectrum at each voltage while the detector is described by the pixel intensity value as a function of the direction and the energy of incident photons. The measurements for the source consist of a series of dose measurements in air performed at each voltage with varying filter thicknesses and materials in front of the x-ray tube. The measurements for the detector are acquisitions of projection images using the same filters and several tube voltages. The proposed procedure has been applied to calibrate and assess the accuracy of simple models of the source and the detector of three commercial kV CBCT units. If the CBCT system models had been calibrated differently, the current procedure would have been exclusively used to validate the models. Several high-purity attenuation filters of aluminum, copper, and silver combined with a dosimeter which is sensitive to the range of voltages of interest were used. A sensitivity analysis of the model has also been conducted for each parameter of the source and the detector models. Results: Average deviations between experimental and theoretical dose values are below 1.5% after calibration for the three x-ray sources. The predicted energy deposited in the detector agrees with experimental data within 4% for all imaging systems. Conclusions: The authors developed and applied an experimental procedure to calibrate and validate any model of the source and the detector of a CBCT unit. The present protocol has been successfully applied to three x-ray imaging systems. The minimum requirements in terms of material and equipment would make its implementation suitable in

Model calibration and validation for OFMSW and sewage sludge co-digestion reactors

International Nuclear Information System (INIS)

Esposito, G.; Frunzo, L.; Panico, A.; Pirozzi, F.

2011-01-01

Highlights: → Disintegration is the limiting step of the anaerobic co-digestion process. → Disintegration kinetic constant does not depend on the waste particle size. → Disintegration kinetic constant depends only on the waste nature and composition. → The model calibration can be performed on organic waste of any particle size. - Abstract: A mathematical model has recently been proposed by the authors to simulate the biochemical processes that prevail in a co-digestion reactor fed with sewage sludge and the organic fraction of municipal solid waste. This model is based on the Anaerobic Digestion Model no. 1 of the International Water Association, which has been extended to include the co-digestion processes, using surface-based kinetics to model the organic waste disintegration and conversion to carbohydrates, proteins and lipids. When organic waste solids are present in the reactor influent, the disintegration process is the rate-limiting step of the overall co-digestion process. The main advantage of the proposed modeling approach is that the kinetic constant of such a process does not depend on the waste particle size distribution (PSD) and rather depends only on the nature and composition of the waste particles. The model calibration aimed to assess the kinetic constant of the disintegration process can therefore be conducted using organic waste samples of any PSD, and the resulting value will be suitable for all the organic wastes of the same nature as the investigated samples, independently of their PSD. This assumption was proven in this study by biomethane potential experiments that were conducted on organic waste samples with different particle sizes. The results of these experiments were used to calibrate and validate the mathematical model, resulting in a good agreement between the simulated and observed data for any investigated particle size of the solid waste. This study confirms the strength of the proposed model and calibration procedure

Calibration and validation of a model describing complete autotrophic nitrogen removal in a granular SBR system

DEFF Research Database (Denmark)

Vangsgaard, Anna Katrine; Mutlu, Ayten Gizem; Gernaey, Krist

2013-01-01

BACKGROUND: A validated model describing the nitritation-anammox process in a granular sequencing batch reactor (SBR) system is an important tool for: a) design of future experiments and b) prediction of process performance during optimization, while applying process control, or during system scale......-up. RESULTS: A model was calibrated using a step-wise procedure customized for the specific needs of the system. The important steps in the procedure were initialization, steady-state and dynamic calibration, and validation. A fast and effective initialization approach was developed to approximate pseudo...... screening of the parameter space proposed by Sin et al. (2008) - to find the best fit of the model to dynamic data. Finally, the calibrated model was validated with an independent data set. CONCLUSION: The presented calibration procedure is the first customized procedure for this type of system...

Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE Model for a large watershed in northern China

Directory of Open Access Journals (Sweden)

S. Wang

2012-12-01

Full Text Available Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped calibration protocol that used streamflow measured at one single watershed outlet to a multi-site calibration method which employed streamflow measurements at three stations within the large Chaohe River basin in northern China. Simulation results showed that the single-site calibrated model was able to sufficiently simulate the hydrographs for two of the three stations (Nash-Sutcliffe coefficient of 0.65–0.75, and correlation coefficient 0.81–0.87 during the testing period, but the model performed poorly for the third station (Nash-Sutcliffe coefficient only 0.44. Sensitivity analysis suggested that streamflow of upstream area of the watershed was dominated by slow groundwater, whilst streamflow of middle- and down- stream areas by relatively quick interflow. Therefore, a multi-site calibration protocol was deemed necessary. Due to the potential errors and uncertainties with respect to the representation of spatial variability, performance measures from the multi-site calibration protocol slightly decreased for two of the three stations, whereas it was improved greatly for the third station. We concluded that multi-site calibration protocol reached a compromise in term of model performance for the three stations, reasonably representing the hydrographs of all three stations with Nash-Sutcliffe coefficient ranging from 0.59–072. The multi-site calibration protocol applied in the analysis generally has advantages to the single site calibration protocol.

A joint calibration model for combining predictive distributions

Directory of Open Access Journals (Sweden)

Patrizia Agati

2013-05-01

Full Text Available In many research fields, as for example in probabilistic weather forecasting, valuable predictive information about a future random phenomenon may come from several, possibly heterogeneous, sources. Forecast combining methods have been developed over the years in order to deal with ensembles of sources: the aim is to combine several predictions in such a way to improve forecast accuracy and reduce risk of bad forecasts.In this context, we propose the use of a Bayesian approach to information combining, which consists in treating the predictive probability density functions (pdfs from the individual ensemble members as data in a Bayesian updating problem. The likelihood function is shown to be proportional to the product of the pdfs, adjusted by a joint “calibration function” describing the predicting skill of the sources (Morris, 1977. In this paper, after rephrasing Morris’ algorithm in a predictive context, we propose to model the calibration function in terms of bias, scale and correlation and to estimate its parameters according to the least squares criterion. The performance of our method is investigated and compared with that of Bayesian Model Averaging (Raftery, 2005 on simulated data.

Calibration and Validation Parameter of Hydrologic Model HEC-HMS using Particle Swarm Optimization Algorithms – Single Objective

Directory of Open Access Journals (Sweden)

R. Garmeh

2016-02-01

Full Text Available Introduction: Planning and management of water resource and river basins needs use of conceptual hydrologic models which play a significant role in predicting basins response to different climatic and meteorological processes. Evaluating watershed response through mathematical hydrologic models requires finding a set of parameter values of the model which provides thebest fit between observed and estimated hydrographs in a procedure called calibration. Asmanual calibration is tedious, time consuming and requires personal experience, automaticcalibration methods make application of more significant CRR models which are based onusing a systematic search procedure to find good parameter sets in terms of at least oneobjective function. Materials and Methods: Conceptual hydrologic models play a significant role inpredicting a basin’s response to different climatic and meteorological processes within natural systems. However, these models require a number of estimated parameters. Model calibration is the procedure of adjusting the parametervalues until the model predictions match the observed data. Manual calibration of high-fidelity hydrologic (simulation models is tedious, time consuming and sometimesimpractical, especially when the number of parameters islarge. Moreover, the high degrees of nonlinearity involved in different hydrologic processes and non-uniqueness ofinverse-type calibration problems make it difficult to find asingle set of parameter values. In this research, the conceptual HEC-HMS model is integrated with the Particle Swarm Optimization (PSO algorithm.The HEC-HMS model was developed as areplacement for HEC-1, which has long been considered as astandard model for hydrologic simulation. Most of thehydrologic models employed in HEC-HMS are event-basedmodels simulating a single storm requiring the specificationof all conditions at the beginning of the simulation. The soil moistureaccounting model in the HEC-HMS is the onlycontinuous

Robustness of near-infrared calibration models for the prediction of milk constituents during the milking process.

Science.gov (United States)

Melfsen, Andreas; Hartung, Eberhard; Haeussermann, Angelika

2013-02-01

The robustness of in-line raw milk analysis with near-infrared spectroscopy (NIRS) was tested with respect to the prediction of the raw milk contents fat, protein and lactose. Near-infrared (NIR) spectra of raw milk (n = 3119) were acquired on three different farms during the milking process of 354 milkings over a period of six months. Calibration models were calculated for: a random data set of each farm (fully random internal calibration); first two thirds of the visits per farm (internal calibration); whole datasets of two of the three farms (external calibration), and combinations of external and internal datasets. Validation was done either on the remaining data set per farm (internal validation) or on data of the remaining farms (external validation). Excellent calibration results were obtained when fully randomised internal calibration sets were used for milk analysis. In this case, RPD values of around ten, five and three for the prediction of fat, protein and lactose content, respectively, were achieved. Farm internal calibrations achieved much poorer prediction results especially for the prediction of protein and lactose with RPD values of around two and one respectively. The prediction accuracy improved when validation was done on spectra of an external farm, mainly due to the higher sample variation in external calibration sets in terms of feeding diets and individual cow effects. The results showed that further improvements were achieved when additional farm information was added to the calibration set. One of the main requirements towards a robust calibration model is the ability to predict milk constituents in unknown future milk samples. The robustness and quality of prediction increases with increasing variation of, e.g., feeding and cow individual milk composition in the calibration model.

A new calibration model for pointing a radio telescope that considers nonlinear errors in the azimuth axis

International Nuclear Information System (INIS)

Kong De-Qing; Wang Song-Gen; Zhang Hong-Bo; Wang Jin-Qing; Wang Min

2014-01-01

A new calibration model of a radio telescope that includes pointing error is presented, which considers nonlinear errors in the azimuth axis. For a large radio telescope, in particular for a telescope with a turntable, it is difficult to correct pointing errors using a traditional linear calibration model, because errors produced by the wheel-on-rail or center bearing structures are generally nonlinear. Fourier expansion is made for the oblique error and parameters describing the inclination direction along the azimuth axis based on the linear calibration model, and a new calibration model for pointing is derived. The new pointing model is applied to the 40m radio telescope administered by Yunnan Observatories, which is a telescope that uses a turntable. The results show that this model can significantly reduce the residual systematic errors due to nonlinearity in the azimuth axis compared with the linear model

Calibration plots for risk prediction models in the presence of competing risks

DEFF Research Database (Denmark)

Gerds, Thomas A; Andersen, Per K; Kattan, Michael W

2014-01-01

A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks...... prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves...

Calibration of a Distributed Hydrological Model using Remote Sensing Evapotranspiration data in the Semi-Arid Punjab Region of Pakista

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Becker, R.; Usman, M.

2017-12-01

A SWAT (Soil Water Assessment Tool) model is applied in the semi-arid Punjab region in Pakistan. The physically based hydrological model is set up to simulate hydrological processes and water resources demands under future land use, climate change and irrigation management scenarios. In order to successfully run the model, detailed focus is laid on the calibration procedure of the model. The study deals with the following calibration issues:i. lack of reliable calibration/validation data, ii. difficulty to accurately model a highly managed system with a physically based hydrological model and iii. use of alternative and spatially distributed data sets for model calibration. In our study area field observations are rare and the entirely human controlled irrigation system renders central calibration parameters (e.g. runoff/curve number) unsuitable, as it can't be assumed that they represent the natural behavior of the hydrological system. From evapotranspiration (ET) however principal hydrological processes can still be inferred. Usman et al. (2015) derived satellite based monthly ET data for our study area based on SEBAL (Surface Energy Balance Algorithm) and created a reliable ET data set which we use in this study to calibrate our SWAT model. The initial SWAT model performance is evaluated with respect to the SEBAL results using correlation coefficients, RMSE, Nash-Sutcliffe efficiencies and mean differences. Particular focus is laid on the spatial patters, investigating the potential of a spatially differentiated parameterization instead of just using spatially uniform calibration data. A sensitivity analysis reveals the most sensitive parameters with respect to changes in ET, which are then selected for the calibration process.Using the SEBAL-ET product we calibrate the SWAT model for the time period 2005-2006 using a dynamically dimensioned global search algorithm to minimize RMSE. The model improvement after the calibration procedure is finally evaluated based

The worth of data to reduce predictive uncertainty of an integrated catchment model by multi-constraint calibration

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Koch, J.; Jensen, K. H.; Stisen, S.

2017-12-01

Hydrological models that integrate numerical process descriptions across compartments of the water cycle are typically required to undergo thorough model calibration in order to estimate suitable effective model parameters. In this study, we apply a spatially distributed hydrological model code which couples the saturated zone with the unsaturated zone and the energy portioning at the land surface. We conduct a comprehensive multi-constraint model calibration against nine independent observational datasets which reflect both the temporal and the spatial behavior of hydrological response of a 1000km2 large catchment in Denmark. The datasets are obtained from satellite remote sensing and in-situ measurements and cover five keystone hydrological variables: discharge, evapotranspiration, groundwater head, soil moisture and land surface temperature. Results indicate that a balanced optimization can be achieved where errors on objective functions for all nine observational datasets can be reduced simultaneously. The applied calibration framework was tailored with focus on improving the spatial pattern performance; however results suggest that the optimization is still more prone to improve the temporal dimension of model performance. This study features a post-calibration linear uncertainty analysis. This allows quantifying parameter identifiability which is the worth of a specific observational dataset to infer values to model parameters through calibration. Furthermore the ability of an observation to reduce predictive uncertainty is assessed as well. Such findings determine concrete implications on the design of model calibration frameworks and, in more general terms, the acquisition of data in hydrological observatories.

Model- and calibration-independent test of cosmic acceleration

International Nuclear Information System (INIS)

Seikel, Marina; Schwarz, Dominik J.

2009-01-01

We present a calibration-independent test of the accelerated expansion of the universe using supernova type Ia data. The test is also model-independent in the sense that no assumptions about the content of the universe or about the parameterization of the deceleration parameter are made and that it does not assume any dynamical equations of motion. Yet, the test assumes the universe and the distribution of supernovae to be statistically homogeneous and isotropic. A significant reduction of systematic effects, as compared to our previous, calibration-dependent test, is achieved. Accelerated expansion is detected at significant level (4.3σ in the 2007 Gold sample, 7.2σ in the 2008 Union sample) if the universe is spatially flat. This result depends, however, crucially on supernovae with a redshift smaller than 0.1, for which the assumption of statistical isotropy and homogeneity is less well established

Fiction and reality in the modelling world - Balance between simplicity and complexity, calibration and identifiability, verification and falsification

DEFF Research Database (Denmark)

Harremoës, P.; Madsen, H.

1999-01-01

Where is the balance between simplicity and complexity in model prediction of urban drainage structures? The calibration/verification approach to testing of model performance gives an exaggerated sense of certainty. Frequently, the model structure and the parameters are not identifiable by calibr......Where is the balance between simplicity and complexity in model prediction of urban drainage structures? The calibration/verification approach to testing of model performance gives an exaggerated sense of certainty. Frequently, the model structure and the parameters are not identifiable...... by calibration/verification on the basis of the data series available, which generates elements of sheer guessing - unless the universality of the model is be based on induction, i.e. experience from the sum of all previous investigations. There is a need to deal more explicitly with uncertainty...

Electronic transport in VO2—Experimentally calibrated Boltzmann transport modeling

International Nuclear Information System (INIS)

Kinaci, Alper; Rosenmann, Daniel; Chan, Maria K. Y.; Kado, Motohisa; Ling, Chen; Zhu, Gaohua; Banerjee, Debasish

2015-01-01

Materials that undergo metal-insulator transitions (MITs) are under intense study, because the transition is scientifically fascinating and technologically promising for various applications. Among these materials, VO 2 has served as a prototype due to its favorable transition temperature. While the physical underpinnings of the transition have been heavily investigated experimentally and computationally, quantitative modeling of electronic transport in the two phases has yet to be undertaken. In this work, we establish a density-functional-theory (DFT)-based approach with Hubbard U correction (DFT + U) to model electronic transport properties in VO 2 in the semiconducting and metallic regimes, focusing on band transport using the Boltzmann transport equations. We synthesized high quality VO 2 films and measured the transport quantities across the transition, in order to calibrate the free parameters in the model. We find that the experimental calibration of the Hubbard correction term can efficiently and adequately model the metallic and semiconducting phases, allowing for further computational design of MIT materials for desirable transport properties

Calibration of a Plastic Classification System with the Ccw Model

International Nuclear Information System (INIS)

Barcala Riveira, J. M.; Fernandez Marron, J. L.; Alberdi Primicia, J.; Navarrete Marin, J. J.; Oller Gonzalez, J. C.

2003-01-01

This document describes the calibration of a plastic Classification system with the Ccw model (Classification by Quantum's built with Wavelet Coefficients). The method is applied to spectra of plastics usually present in domestic wastes. Obtained results are showed. (Author) 16 refs

Calibration of a simple and a complex model of global marine biogeochemistry

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Kriest, Iris

2017-11-01

The assessment of the ocean biota's role in climate change is often carried out with global biogeochemical ocean models that contain many components and involve a high level of parametric uncertainty. Because many data that relate to tracers included in a model are only sparsely observed, assessment of model skill is often restricted to tracers that can be easily measured and assembled. Examination of the models' fit to climatologies of inorganic tracers, after the models have been spun up to steady state, is a common but computationally expensive procedure to assess model performance and reliability. Using new tools that have become available for global model assessment and calibration in steady state, this paper examines two different model types - a complex seven-component model (MOPS) and a very simple four-component model (RetroMOPS) - for their fit to dissolved quantities. Before comparing the models, a subset of their biogeochemical parameters has been optimised against annual-mean nutrients and oxygen. Both model types fit the observations almost equally well. The simple model contains only two nutrients: oxygen and dissolved organic phosphorus (DOP). Its misfit and large-scale tracer distributions are sensitive to the parameterisation of DOP production and decay. The spatio-temporal decoupling of nitrogen and oxygen, and processes involved in their uptake and release, renders oxygen and nitrate valuable tracers for model calibration. In addition, the non-conservative nature of these tracers (with respect to their upper boundary condition) introduces the global bias (fixed nitrogen and oxygen inventory) as a useful additional constraint on model parameters. Dissolved organic phosphorus at the surface behaves antagonistically to phosphate, and suggests that observations of this tracer - although difficult to measure - may be an important asset for model calibration.

Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

Science.gov (United States)

Wentworth, Mami Tonoe

Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification

Evaluating the Efficiency of a Multi-core Aware Multi-objective Optimization Tool for Calibrating the SWAT Model

Energy Technology Data Exchange (ETDEWEB)

Zhang, X. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Izaurralde, R. C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zong, Z. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zhao, K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Thomson, A. M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2012-08-20

The efficiency of calibrating physically-based complex hydrologic models is a major concern in the application of those models to understand and manage natural and human activities that affect watershed systems. In this study, we developed a multi-core aware multi-objective evolutionary optimization algorithm (MAMEOA) to improve the efficiency of calibrating a worldwide used watershed model (Soil and Water Assessment Tool (SWAT)). The test results show that MAMEOA can save about 1-9%, 26-51%, and 39-56% time consumed by calibrating SWAT as compared with sequential method by using dual-core, quad-core, and eight-core machines, respectively. Potential and limitations of MAMEOA for calibrating SWAT are discussed. MAMEOA is open source software.

Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

Science.gov (United States)

Lu, Dan; Ricciuto, Daniel; Walker, Anthony; Safta, Cosmin; Munger, William

2017-09-01

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.

Calibration of Automatically Generated Items Using Bayesian Hierarchical Modeling.

Science.gov (United States)

Johnson, Matthew S.; Sinharay, Sandip

For complex educational assessments, there is an increasing use of "item families," which are groups of related items. However, calibration or scoring for such an assessment requires fitting models that take into account the dependence structure inherent among the items that belong to the same item family. C. Glas and W. van der Linden…

A multimethod Global Sensitivity Analysis to aid the calibration of geomechanical models via time-lapse seismic data

Science.gov (United States)

Price, D. C.; Angus, D. A.; Garcia, A.; Fisher, Q. J.; Parsons, S.; Kato, J.

2018-03-01

Time-lapse seismic attributes are used extensively in the history matching of production simulator models. However, although proven to contain information regarding production induced stress change, it is typically only loosely (i.e. qualitatively) used to calibrate geomechanical models. In this study we conduct a multimethod Global Sensitivity Analysis (GSA) to assess the feasibility and aid the quantitative calibration of geomechanical models via near-offset time-lapse seismic data. Specifically, the calibration of mechanical properties of the overburden. Via the GSA, we analyse the near-offset overburden seismic traveltimes from over 4000 perturbations of a Finite Element (FE) geomechanical model of a typical High Pressure High Temperature (HPHT) reservoir in the North Sea. We find that, out of an initially large set of material properties, the near-offset overburden traveltimes are primarily affected by Young's modulus and the effective stress (i.e. Biot) coefficient. The unexpected significance of the Biot coefficient highlights the importance of modelling fluid flow and pore pressure outside of the reservoir. The FE model is complex and highly nonlinear. Multiple combinations of model parameters can yield equally possible model realizations. Consequently, numerical calibration via a large number of random model perturbations is unfeasible. However, the significant differences in traveltime results suggest that more sophisticated calibration methods could potentially be feasible for finding numerous suitable solutions. The results of the time-varying GSA demonstrate how acquiring multiple vintages of time-lapse seismic data can be advantageous. However, they also suggest that significant overburden near-offset seismic time-shifts, useful for model calibration, may take up to 3 yrs after the start of production to manifest. Due to the nonlinearity of the model behaviour, similar uncertainty in the reservoir mechanical properties appears to influence overburden

Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

Science.gov (United States)

Haberlandt, U.; Radtke, I.

2014-01-01

Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the

Calibration of a complex activated sludge model for the full-scale wastewater treatment plant.

Science.gov (United States)

Liwarska-Bizukojc, Ewa; Olejnik, Dorota; Biernacki, Rafal; Ledakowicz, Stanislaw

2011-08-01

In this study, the results of the calibration of the complex activated sludge model implemented in BioWin software for the full-scale wastewater treatment plant are presented. Within the calibration of the model, sensitivity analysis of its parameters and the fractions of carbonaceous substrate were performed. In the steady-state and dynamic calibrations, a successful agreement between the measured and simulated values of the output variables was achieved. Sensitivity analysis revealed that upon the calculations of normalized sensitivity coefficient (S(i,j)) 17 (steady-state) or 19 (dynamic conditions) kinetic and stoichiometric parameters are sensitive. Most of them are associated with growth and decay of ordinary heterotrophic organisms and phosphorus accumulating organisms. The rankings of ten most sensitive parameters established on the basis of the calculations of the mean square sensitivity measure (δ(msqr)j) indicate that irrespective of the fact, whether the steady-state or dynamic calibration was performed, there is an agreement in the sensitivity of parameters.

Parallel Genetic Algorithms for calibrating Cellular Automata models: Application to lava flows

International Nuclear Information System (INIS)

D'Ambrosio, D.; Spataro, W.; Di Gregorio, S.; Calabria Univ., Cosenza; Crisci, G.M.; Rongo, R.; Calabria Univ., Cosenza

2005-01-01

Cellular Automata are highly nonlinear dynamical systems which are suitable far simulating natural phenomena whose behaviour may be specified in terms of local interactions. The Cellular Automata model SCIARA, developed far the simulation of lava flows, demonstrated to be able to reproduce the behaviour of Etnean events. However, in order to apply the model far the prediction of future scenarios, a thorough calibrating phase is required. This work presents the application of Genetic Algorithms, general-purpose search algorithms inspired to natural selection and genetics, far the parameters optimisation of the model SCIARA. Difficulties due to the elevated computational time suggested the adoption a Master-Slave Parallel Genetic Algorithm far the calibration of the model with respect to the 2001 Mt. Etna eruption. Results demonstrated the usefulness of the approach, both in terms of computing time and quality of performed simulations

Calibration and verification of numerical runoff and erosion model

Directory of Open Access Journals (Sweden)

Gabrić Ognjen

2015-01-01

Full Text Available Based on the field and laboratory measurements, and analogous with development of computational techniques, runoff and erosion models based on equations which describe the physics of the process are also developed. Based on the KINEROS2 model, this paper presents basic modelling principles of runoff and erosion processes based on the St. Venant's equations. Alternative equations for friction calculation, calculation of source and deposition elements and transport capacity are also shown. Numerical models based on original and alternative equations are calibrated and verified on laboratory scale model. According to the results, friction calculation based on the analytic solution of laminar flow must be included in all runoff and erosion models.

Calibrating the sqHIMMELI v1.0 wetland methane emission model with hierarchical modeling and adaptive MCMC

Science.gov (United States)

Susiluoto, Jouni; Raivonen, Maarit; Backman, Leif; Laine, Marko; Makela, Jarmo; Peltola, Olli; Vesala, Timo; Aalto, Tuula

2018-03-01

Estimating methane (CH4) emissions from natural wetlands is complex, and the estimates contain large uncertainties. The models used for the task are typically heavily parameterized and the parameter values are not well known. In this study, we perform a Bayesian model calibration for a new wetland CH4 emission model to improve the quality of the predictions and to understand the limitations of such models.The detailed process model that we analyze contains descriptions for CH4 production from anaerobic respiration, CH4 oxidation, and gas transportation by diffusion, ebullition, and the aerenchyma cells of vascular plants. The processes are controlled by several tunable parameters. We use a hierarchical statistical model to describe the parameters and obtain the posterior distributions of the parameters and uncertainties in the processes with adaptive Markov chain Monte Carlo (MCMC), importance resampling, and time series analysis techniques. For the estimation, the analysis utilizes measurement data from the Siikaneva flux measurement site in southern Finland. The uncertainties related to the parameters and the modeled processes are described quantitatively. At the process level, the flux measurement data are able to constrain the CH4 production processes, methane oxidation, and the different gas transport processes. The posterior covariance structures explain how the parameters and the processes are related. Additionally, the flux and flux component uncertainties are analyzed both at the annual and daily levels. The parameter posterior densities obtained provide information regarding importance of the different processes, which is also useful for development of wetland methane emission models other than the square root HelsinkI Model of MEthane buiLd-up and emIssion for peatlands (sqHIMMELI). The hierarchical modeling allows us to assess the effects of some of the parameters on an annual basis. The results of the calibration and the cross validation suggest that

Calibration of a Chemistry Test Using the Rasch Model

Directory of Open Access Journals (Sweden)

Nancy Coromoto Martín Guaregua

2011-11-01

Full Text Available The Rasch model was used to calibrate a general chemistry test for the purpose of analyzing the advantages and information the model provides. The sample was composed of 219 college freshmen. Of the 12 questions used, good fit was achieved in 10. The evaluation shows that although there are items of variable difficulty, there are gaps on the scale; in order to make the test complete, it will be necessary to design new items to fill in these gaps.

The hydrological calibration and validation of a complexly-linked watershed reservoir model for the Occoquan watershed, Virginia

Science.gov (United States)

Xu, Zhongyan; Godrej, Adil N.; Grizzard, Thomas J.

2007-10-01

SummaryRunoff models such as HSPF and reservoir models such as CE-QUAL-W2 are used to model water quality in watersheds. Most often, the models are independently calibrated to observed data. While this approach can achieve good calibration, it does not replicate the physically-linked nature of the system. When models are linked by using the model output from an upstream model as input to a downstream model, the physical reality of a continuous watershed, where the overland and waterbody portions are parts of the whole, is better represented. There are some additional challenges in the calibration of such linked models, because the aim is to simulate the entire system as a whole, rather than piecemeal. When public entities are charged with model development, one of the driving forces is to use public-domain models. This paper describes the use of two such models, HSPF and CE-QUAL-W2, in the linked modeling of the Occoquan watershed located in northern Virginia, USA. The description of the process is provided, and results from the hydrological calibration and validation are shown. The Occoquan model consists of six HSPF and two CE-QUAL-W2 models, linked in a complex way, to simulate two major reservoirs and the associated drainage areas. The overall linked model was calibrated for a three-year period and validated for a two-year period. The results show that a successful calibration can be achieved using the linked approach, with moderate additional effort. Overall flow balances based on the three-year calibration period at four stream stations showed agreement ranging from -3.95% to +3.21%. Flow balances for the two reservoirs, compared via the daily water surface elevations, also showed good agreement ( R2 values of 0.937 for Lake Manassas and 0.926 for Occoquan Reservoir), when missing (un-monitored) flows were included. Validation of the models ranged from poor to fair for the watershed models and excellent for the waterbody models, thus indicating that the

Calibrating a numerical model's morphology using high-resolution spatial and temporal datasets from multithread channel flume experiments.

Science.gov (United States)

Javernick, L.; Bertoldi, W.; Redolfi, M.

2017-12-01

Accessing or acquiring high quality, low-cost topographic data has never been easier due to recent developments of the photogrammetric techniques of Structure-from-Motion (SfM). Researchers can acquire the necessary SfM imagery with various platforms, with the ability to capture millimetre resolution and accuracy, or large-scale areas with the help of unmanned platforms. Such datasets in combination with numerical modelling have opened up new opportunities to study river environments physical and ecological relationships. While numerical models overall predictive accuracy is most influenced by topography, proper model calibration requires hydraulic data and morphological data; however, rich hydraulic and morphological datasets remain scarce. This lack in field and laboratory data has limited model advancement through the inability to properly calibrate, assess sensitivity, and validate the models performance. However, new time-lapse imagery techniques have shown success in identifying instantaneous sediment transport in flume experiments and their ability to improve hydraulic model calibration. With new capabilities to capture high resolution spatial and temporal datasets of flume experiments, there is a need to further assess model performance. To address this demand, this research used braided river flume experiments and captured time-lapse observed sediment transport and repeat SfM elevation surveys to provide unprecedented spatial and temporal datasets. Through newly created metrics that quantified observed and modeled activation, deactivation, and bank erosion rates, the numerical model Delft3d was calibrated. This increased temporal data of both high-resolution time series and long-term temporal coverage provided significantly improved calibration routines that refined calibration parameterization. Model results show that there is a trade-off between achieving quantitative statistical and qualitative morphological representations. Specifically, statistical

Calibration Modeling Methodology to Optimize Performance for Low Range Applications

Science.gov (United States)

McCollum, Raymond A.; Commo, Sean A.; Parker, Peter A.

2010-01-01

Calibration is a vital process in characterizing the performance of an instrument in an application environment and seeks to obtain acceptable accuracy over the entire design range. Often, project requirements specify a maximum total measurement uncertainty, expressed as a percent of full-scale. However in some applications, we seek to obtain enhanced performance at the low range, therefore expressing the accuracy as a percent of reading should be considered as a modeling strategy. For example, it is common to desire to use a force balance in multiple facilities or regimes, often well below its designed full-scale capacity. This paper presents a general statistical methodology for optimizing calibration mathematical models based on a percent of reading accuracy requirement, which has broad application in all types of transducer applications where low range performance is required. A case study illustrates the proposed methodology for the Mars Entry Atmospheric Data System that employs seven strain-gage based pressure transducers mounted on the heatshield of the Mars Science Laboratory mission.

Modeling and Experimental Analysis of Piezoelectric Shakers for High-Frequency Calibration of Accelerometers

International Nuclear Information System (INIS)

Vogl, Gregory W.; Harper, Kari K.; Payne, Bev

2010-01-01

Piezoelectric shakers have been developed and used at the National Institute of Standards and Technology (NIST) for decades for high-frequency calibration of accelerometers. Recently, NIST researchers built new piezoelectric shakers in the hopes of reducing the uncertainties in the calibrations of accelerometers while extending the calibration frequency range beyond 20 kHz. The ability to build and measure piezoelectric shakers invites modeling of these systems in order to improve their design for increased performance, which includes a sinusoidal motion with lower distortion, lower cross-axial motion, and an increased frequency range. In this paper, we present a model of piezoelectric shakers and match it to experimental data. The equations of motion for all masses are solved along with the coupled state equations for the piezoelectric actuator. Finally, additional electrical elements like inductors, capacitors, and resistors are added to the piezoelectric actuator for matching of experimental and theoretical frequency responses.

Multiobjective Optimal Algorithm for Automatic Calibration of Daily Streamflow Forecasting Model

Directory of Open Access Journals (Sweden)

Yi Liu

2016-01-01

Full Text Available Single-objection function cannot describe the characteristics of the complicated hydrologic system. Consequently, it stands to reason that multiobjective functions are needed for calibration of hydrologic model. The multiobjective algorithms based on the theory of nondominate are employed to solve this multiobjective optimal problem. In this paper, a novel multiobjective optimization method based on differential evolution with adaptive Cauchy mutation and Chaos searching (MODE-CMCS is proposed to optimize the daily streamflow forecasting model. Besides, to enhance the diversity performance of Pareto solutions, a more precise crowd distance assigner is presented in this paper. Furthermore, the traditional generalized spread metric (SP is sensitive with the size of Pareto set. A novel diversity performance metric, which is independent of Pareto set size, is put forward in this research. The efficacy of the new algorithm MODE-CMCS is compared with the nondominated sorting genetic algorithm II (NSGA-II on a daily streamflow forecasting model based on support vector machine (SVM. The results verify that the performance of MODE-CMCS is superior to the NSGA-II for automatic calibration of hydrologic model.

Nonlinear propagation model for ultrasound hydrophones calibration in the frequency range up to 100 MHz.

Science.gov (United States)

Radulescu, E G; Wójcik, J; Lewin, P A; Nowicki, A

2003-06-01

To facilitate the implementation and verification of the new ultrasound hydrophone calibration techniques described in the companion paper (somewhere in this issue) a nonlinear propagation model was developed. A brief outline of the theoretical considerations is presented and the model's advantages and disadvantages are discussed. The results of simulations yielding spatial and temporal acoustic pressure amplitude are also presented and compared with those obtained using KZK and Field II models. Excellent agreement between all models is evidenced. The applicability of the model in discrete wideband calibration of hydrophones is documented in the companion paper somewhere in this volume.

Including sugar cane in the agro-ecosystem model ORCHIDEE-STICS: calibration and validation

Science.gov (United States)

Valade, A.; Vuichard, N.; Ciais, P.; Viovy, N.

2011-12-01

Sugarcane is currently the most efficient bioenergy crop with regards to the energy produced per hectare. With approximately half the global bioethanol production in 2005, and a devoted land area expected to expand globally in the years to come, sugar cane is at the heart of the biofuel debate. Dynamic global vegetation models coupled with agronomical models are powerful and novel tools to tackle many of the environmental issues related to biofuels if they are carefully calibrated and validated against field observations. Here we adapt the agro-terrestrial model ORCHIDEE-STICS for sugar cane simulations. Observation data of LAI are used to evaluate the sensitivity of the model to parameters of nitrogen absorption and phenology, which are calibrated in a systematic way for six sites in Australia and La Reunion. We find that the optimal set of parameters is highly dependent on the sites' characteristics and that the model can reproduce satisfactorily the evolution of LAI. This careful calibration of ORCHIDEE-STICS for sugar cane biomass production for different locations and technical itineraries provides a strong basis for further analysis of the impacts of bioenergy-related land use change on carbon cycle budgets. As a next step, a sensitivity analysis is carried out to estimate the uncertainty of the model in biomass and carbon flux simulation due to its parameterization.

Bayesian Calibration, Validation and Uncertainty Quantification for Predictive Modelling of Tumour Growth: A Tutorial.

Science.gov (United States)

Collis, Joe; Connor, Anthony J; Paczkowski, Marcin; Kannan, Pavitra; Pitt-Francis, Joe; Byrne, Helen M; Hubbard, Matthew E

2017-04-01

In this work, we present a pedagogical tumour growth example, in which we apply calibration and validation techniques to an uncertain, Gompertzian model of tumour spheroid growth. The key contribution of this article is the discussion and application of these methods (that are not commonly employed in the field of cancer modelling) in the context of a simple model, whose deterministic analogue is widely known within the community. In the course of the example, we calibrate the model against experimental data that are subject to measurement errors, and then validate the resulting uncertain model predictions. We then analyse the sensitivity of the model predictions to the underlying measurement model. Finally, we propose an elementary learning approach for tuning a threshold parameter in the validation procedure in order to maximize predictive accuracy of our validated model.

Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

Science.gov (United States)

Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

2014-07-01

The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

Calibrated Blade-Element/Momentum Theory Aerodynamic Model of the MARIN Stock Wind Turbine: Preprint

Energy Technology Data Exchange (ETDEWEB)

Goupee, A.; Kimball, R.; de Ridder, E. J.; Helder, J.; Robertson, A.; Jonkman, J.

2015-04-02

In this paper, a calibrated blade-element/momentum theory aerodynamic model of the MARIN stock wind turbine is developed and documented. The model is created using open-source software and calibrated to closely emulate experimental data obtained by the DeepCwind Consortium using a genetic algorithm optimization routine. The provided model will be useful for those interested in validating interested in validating floating wind turbine numerical simulators that rely on experiments utilizing the MARIN stock wind turbine—for example, the International Energy Agency Wind Task 30’s Offshore Code Comparison Collaboration Continued, with Correlation project.

Multi-gauge Calibration for modeling the Semi-Arid Santa Cruz Watershed in Arizona-Mexico Border Area Using SWAT

Science.gov (United States)

Niraula, Rewati; Norman, Laura A.; Meixner, Thomas; Callegary, James B.

2012-01-01

In most watershed-modeling studies, flow is calibrated at one monitoring site, usually at the watershed outlet. Like many arid and semi-arid watersheds, the main reach of the Santa Cruz watershed, located on the Arizona-Mexico border, is discontinuous for most of the year except during large flood events, and therefore the flow characteristics at the outlet do not represent the entire watershed. Calibration is required at multiple locations along the Santa Cruz River to improve model reliability. The objective of this study was to best portray surface water flow in this semiarid watershed and evaluate the effect of multi-gage calibration on flow predictions. In this study, the Soil and Water Assessment Tool (SWAT) was calibrated at seven monitoring stations, which improved model performance and increased the reliability of flow, in the Santa Cruz watershed. The most sensitive parameters to affect flow were found to be curve number (CN2), soil evaporation and compensation coefficient (ESCO), threshold water depth in shallow aquifer for return flow to occur (GWQMN), base flow alpha factor (Alpha_Bf), and effective hydraulic conductivity of the soil layer (Ch_K2). In comparison, when the model was established with a single calibration at the watershed outlet, flow predictions at other monitoring gages were inaccurate. This study emphasizes the importance of multi-gage calibration to develop a reliable watershed model in arid and semiarid environments. The developed model, with further calibration of water quality parameters will be an integral part of the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM), an online decision support tool, to assess the impacts of climate change and urban growth in the Santa Cruz watershed.

DEM Calibration Approach: design of experiment

Science.gov (United States)

Boikov, A. V.; Savelev, R. V.; Payor, V. A.

2018-05-01

The problem of DEM models calibration is considered in the article. It is proposed to divide models input parameters into those that require iterative calibration and those that are recommended to measure directly. A new method for model calibration based on the design of the experiment for iteratively calibrated parameters is proposed. The experiment is conducted using a specially designed stand. The results are processed with technical vision algorithms. Approximating functions are obtained and the error of the implemented software and hardware complex is estimated. The prospects of the obtained results are discussed.

Multi-model analysis of terrestrial carbon cycles in Japan: limitations and implications of model calibration using eddy flux observations

Directory of Open Access Journals (Sweden)

K. Ichii

2010-07-01

Full Text Available Terrestrial biosphere models show large differences when simulating carbon and water cycles, and reducing these differences is a priority for developing more accurate estimates of the condition of terrestrial ecosystems and future climate change. To reduce uncertainties and improve the understanding of their carbon budgets, we investigated the utility of the eddy flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine – based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID, we conducted two simulations: (1 point simulations at four eddy flux sites in Japan and (2 spatial simulations for Japan with a default model (based on original settings and a modified model (based on model parameter tuning using eddy flux data. Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using eddy flux data (GPP, RE and NEP, most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs. This study demonstrated that careful validation and calibration of models with available eddy flux data reduced model-by-model differences. Yet, site history, analysis of model structure changes, and more objective procedure of model calibration should be included in the further analysis.

Multi-model analysis of terrestrial carbon cycles in Japan: limitations and implications of model calibration using eddy flux observations

Science.gov (United States)

Ichii, K.; Suzuki, T.; Kato, T.; Ito, A.; Hajima, T.; Ueyama, M.; Sasai, T.; Hirata, R.; Saigusa, N.; Ohtani, Y.; Takagi, K.

2010-07-01

Terrestrial biosphere models show large differences when simulating carbon and water cycles, and reducing these differences is a priority for developing more accurate estimates of the condition of terrestrial ecosystems and future climate change. To reduce uncertainties and improve the understanding of their carbon budgets, we investigated the utility of the eddy flux datasets to improve model simulations and reduce variabilities among multi-model outputs of terrestrial biosphere models in Japan. Using 9 terrestrial biosphere models (Support Vector Machine - based regressions, TOPS, CASA, VISIT, Biome-BGC, DAYCENT, SEIB, LPJ, and TRIFFID), we conducted two simulations: (1) point simulations at four eddy flux sites in Japan and (2) spatial simulations for Japan with a default model (based on original settings) and a modified model (based on model parameter tuning using eddy flux data). Generally, models using default model settings showed large deviations in model outputs from observation with large model-by-model variability. However, after we calibrated the model parameters using eddy flux data (GPP, RE and NEP), most models successfully simulated seasonal variations in the carbon cycle, with less variability among models. We also found that interannual variations in the carbon cycle are mostly consistent among models and observations. Spatial analysis also showed a large reduction in the variability among model outputs. This study demonstrated that careful validation and calibration of models with available eddy flux data reduced model-by-model differences. Yet, site history, analysis of model structure changes, and more objective procedure of model calibration should be included in the further analysis.

Modeling, Calibration and Control for Extreme-Precision MEMS Deformable Mirrors, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Iris AO will develop electromechanical models and actuator calibration methods to enable open-loop control of MEMS deformable mirrors (DMs) with unprecedented...

Calibration and validation of models for short-term decomposition and N mineralization of plant residues in the tropics

Directory of Open Access Journals (Sweden)

Alexandre Ferreira do Nascimento

2012-12-01

Full Text Available Insight of nutrient release patterns associated with the decomposition of plant residues is important for their effective use as a green manure in food production systems. Thus, this study aimed to evaluate the ability of the Century, APSIM and NDICEA simulation models for predicting the decomposition and N mineralization of crop residues in the tropical Atlantic forest biome, Brazil. The simulation models were calibrated based on actual decomposition and N mineralization rates of three types of crop residues with different chemical and biochemical composition. The models were also validated for different pedo-climatic conditions and crop residues conditions. In general, the accuracy of decomposition and N mineralization improved after calibration. Overall RMSE values for the decomposition and N mineralization of the crop materials varied from 7.4 to 64.6% before models calibration compared to 3.7 to 16.3 % after calibration. Therefore, adequate calibration of the models is indispensable for use them under humid tropical conditions. The NDICEA model generally outperformed the other models. However, the decomposition and N mineralization was not very accurate during the first 30 days of incubation, especially for easily decomposable crop residues. An additional model variable may be required to capture initial microbiological growth as affected by the moisture dynamics of the residues, as is the case in surface residues decomposition models.

Calibration and validation of a general infiltration model

Science.gov (United States)

Mishra, Surendra Kumar; Ranjan Kumar, Shashi; Singh, Vijay P.

1999-08-01

A general infiltration model proposed by Singh and Yu (1990) was calibrated and validated using a split sampling approach for 191 sets of infiltration data observed in the states of Minnesota and Georgia in the USA. Of the five model parameters, fc (the final infiltration rate), So (the available storage space) and exponent n were found to be more predictable than the other two parameters: m (exponent) and a (proportionality factor). A critical examination of the general model revealed that it is related to the Soil Conservation Service (1956) curve number (SCS-CN) method and its parameter So is equivalent to the potential maximum retention of the SCS-CN method and is, in turn, found to be a function of soil sorptivity and hydraulic conductivity. The general model was found to describe infiltration rate with time varying curve number.

Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

Science.gov (United States)

Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

2015-01-01

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

Calibration and Verification of the Hydraulic Model for Blue Nile River from Roseires Dam to Khartoum City

Directory of Open Access Journals (Sweden)

Kamal edin ELsidig Bashar

2015-12-01

Full Text Available This research represents a practical attempt applied to calibrate and verify a hydraulic model for the Blue Nile River. The calibration procedures are performed using the observed data for a previous period and comparing them with the calibration results while verification requirements are achieved with the application of the observed data for another future period and comparing them with the verification results. The study objective covered a relationship of the river terrain with the distance between the assumed points of the dam failures along the river length. The computed model values and the observed data should conform to the theoretical analysis and the overall verification performance of the model by comparing it with another set of data. The model was calibrated using data from gauging stations (Khartoum, Wad Medani, downstream Sennar, and downstream Roseires during the period from the 1st of May to 31 of October 1988 and the verification was done using the data of the same gauging stations for years 2003 and 2010 for the same period. The required available data from these stations were collected, processed and used in the model calibration. The geometry input files for the HEC-RAS models were created using a combination of ArcGIS and HEC-GeoRAS. The results revealed high correlation (R2 ˃ 0.9 between the observed and calibrated water levels in all gauging stations during 1988 and also high correlation between the observed and verification water levels was obtained in years 2003 and 2010. Verification results with the equation and degree of correlation can be used to predict future data of any expected data for the same stations.

Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE Model for a large watershed in northern China

Science.gov (United States)

S. Wang; Z. Zhang; G. Sun; P. Strauss; J. Guo; Y. Tang; A. Yao

2012-01-01

Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped...

Using Bayesian Model Averaging (BMA) to calibrate probabilistic surface temperature forecasts over Iran

Energy Technology Data Exchange (ETDEWEB)

Soltanzadeh, I. [Tehran Univ. (Iran, Islamic Republic of). Inst. of Geophysics; Azadi, M.; Vakili, G.A. [Atmospheric Science and Meteorological Research Center (ASMERC), Teheran (Iran, Islamic Republic of)

2011-07-01

Using Bayesian Model Averaging (BMA), an attempt was made to obtain calibrated probabilistic numerical forecasts of 2-m temperature over Iran. The ensemble employs three limited area models (WRF, MM5 and HRM), with WRF used with five different configurations. Initial and boundary conditions for MM5 and WRF are obtained from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and for HRM the initial and boundary conditions come from analysis of Global Model Europe (GME) of the German Weather Service. The resulting ensemble of seven members was run for a period of 6 months (from December 2008 to May 2009) over Iran. The 48-h raw ensemble outputs were calibrated using BMA technique for 120 days using a 40 days training sample of forecasts and relative verification data. The calibrated probabilistic forecasts were assessed using rank histogram and attribute diagrams. Results showed that application of BMA improved the reliability of the raw ensemble. Using the weighted ensemble mean forecast as a deterministic forecast it was found that the deterministic-style BMA forecasts performed usually better than the best member's deterministic forecast. (orig.)

Using Bayesian Model Averaging (BMA to calibrate probabilistic surface temperature forecasts over Iran

Directory of Open Access Journals (Sweden)

I. Soltanzadeh

2011-07-01

Full Text Available Using Bayesian Model Averaging (BMA, an attempt was made to obtain calibrated probabilistic numerical forecasts of 2-m temperature over Iran. The ensemble employs three limited area models (WRF, MM5 and HRM, with WRF used with five different configurations. Initial and boundary conditions for MM5 and WRF are obtained from the National Centers for Environmental Prediction (NCEP Global Forecast System (GFS and for HRM the initial and boundary conditions come from analysis of Global Model Europe (GME of the German Weather Service. The resulting ensemble of seven members was run for a period of 6 months (from December 2008 to May 2009 over Iran. The 48-h raw ensemble outputs were calibrated using BMA technique for 120 days using a 40 days training sample of forecasts and relative verification data. The calibrated probabilistic forecasts were assessed using rank histogram and attribute diagrams. Results showed that application of BMA improved the reliability of the raw ensemble. Using the weighted ensemble mean forecast as a deterministic forecast it was found that the deterministic-style BMA forecasts performed usually better than the best member's deterministic forecast.

Reactive Burn Model Calibration for PETN Using Ultra-High-Speed Phase Contrast Imaging

Science.gov (United States)

Johnson, Carl; Ramos, Kyle; Bolme, Cindy; Sanchez, Nathaniel; Barber, John; Montgomery, David

2017-06-01

A 1D reactive burn model (RBM) calibration for a plastic bonded high explosive (HE) requires run-to-detonation data. In PETN (pentaerythritol tetranitrate, 1.65 g/cc) the shock to detonation transition (SDT) is on the order of a few millimeters. This rapid SDT imposes experimental length scales that preclude application of traditional calibration methods such as embedded electromagnetic gauge methods (EEGM) which are very effective when used to study 10 - 20 mm thick HE specimens. In recent work at Argonne National Laboratory's Advanced Photon Source we have obtained run-to-detonation data in PETN using ultra-high-speed dynamic phase contrast imaging (PCI). A reactive burn model calibration valid for 1D shock waves is obtained using density profiles spanning the transition to detonation as opposed to particle velocity profiles from EEGM. Particle swarm optimization (PSO) methods were used to operate the LANL hydrocode FLAG iteratively to refine SURF RBM parameters until a suitable parameter set attained. These methods will be presented along with model validation simulations. The novel method described is generally applicable to `sensitive' energetic materials particularly those with areal densities amenable to radiography.

Sensitivity analysis and development of calibration methodology for near-surface hydrogeology model of Laxemar

International Nuclear Information System (INIS)

Aneljung, Maria; Sassner, Mona; Gustafsson, Lars-Goeran

2007-11-01

This report describes modelling where the hydrological modelling system MIKE SHE has been used to describe surface hydrology, near-surface hydrogeology, advective transport mechanisms, and the contact between groundwater and surface water within the SKB site investigation area at Laxemar. In the MIKE SHE system, surface water flow is described with the one-dimensional modelling tool MIKE 11, which is fully and dynamically integrated with the groundwater flow module in MIKE SHE. In early 2008, a supplementary data set will be available and a process of updating, rebuilding and calibrating the MIKE SHE model based on this data set will start. Before the calibration on the new data begins, it is important to gather as much knowledge as possible on calibration methods, and to identify critical calibration parameters and areas within the model that require special attention. In this project, the MIKE SHE model has been further developed. The model area has been extended, and the present model also includes an updated bedrock model and a more detailed description of the surface stream network. The numerical model has been updated and optimized, especially regarding the modelling of evapotranspiration and the unsaturated zone, and the coupling between the surface stream network in MIKE 11 and the overland flow in MIKE SHE. An initial calibration has been made and a base case has been defined and evaluated. In connection with the calibration, the most important changes made in the model were the following: The evapotranspiration was reduced. The infiltration capacity was reduced. The hydraulic conductivities of the Quaternary deposits in the water-saturated part of the subsurface were reduced. Data from one surface water level monitoring station, four surface water discharge monitoring stations and 43 groundwater level monitoring stations (SSM series boreholes) have been used to evaluate and calibrate the model. The base case simulations showed a reasonable agreement

Measurement of oxygen extraction fraction (OEF): An optimized BOLD signal model for use with hypercapnic and hyperoxic calibration.

Science.gov (United States)

Merola, Alberto; Murphy, Kevin; Stone, Alan J; Germuska, Michael A; Griffeth, Valerie E M; Blockley, Nicholas P; Buxton, Richard B; Wise, Richard G

2016-04-01

Several techniques have been proposed to estimate relative changes in cerebral metabolic rate of oxygen consumption (CMRO2) by exploiting combined BOLD fMRI and cerebral blood flow data in conjunction with hypercapnic or hyperoxic respiratory challenges. More recently, methods based on respiratory challenges that include both hypercapnia and hyperoxia have been developed to assess absolute CMRO2, an important parameter for understanding brain energetics. In this paper, we empirically optimize a previously presented "original calibration model" relating BOLD and blood flow signals specifically for the estimation of oxygen extraction fraction (OEF) and absolute CMRO2. To do so, we have created a set of synthetic BOLD signals using a detailed BOLD signal model to reproduce experiments incorporating hypercapnic and hyperoxic respiratory challenges at 3T. A wide range of physiological conditions was simulated by varying input parameter values (baseline cerebral blood volume (CBV0), baseline cerebral blood flow (CBF0), baseline oxygen extraction fraction (OEF0) and hematocrit (Hct)). From the optimization of the calibration model for estimation of OEF and practical considerations of hypercapnic and hyperoxic respiratory challenges, a new "simplified calibration model" is established which reduces the complexity of the original calibration model by substituting the standard parameters α and β with a single parameter θ. The optimal value of θ is determined (θ=0.06) across a range of experimental respiratory challenges. The simplified calibration model gives estimates of OEF0 and absolute CMRO2 closer to the true values used to simulate the experimental data compared to those estimated using the original model incorporating literature values of α and β. Finally, an error propagation analysis demonstrates the susceptibility of the original and simplified calibration models to measurement errors and potential violations in the underlying assumptions of isometabolism

Improved method for calibration of exchange flows for a physical transport box model of Tampa Bay, FL USA

Science.gov (United States)

Results for both sequential and simultaneous calibration of exchange flows between segments of a 10-box, one-dimensional, well-mixed, bifurcated tidal mixing model for Tampa Bay are reported. Calibrations were conducted for three model options with different mathematical expressi...

Performance of the air2stream model that relates air and stream water temperatures depends on the calibration method

Science.gov (United States)

Piotrowski, Adam P.; Napiorkowski, Jaroslaw J.

2018-06-01

A number of physical or data-driven models have been proposed to evaluate stream water temperatures based on hydrological and meteorological observations. However, physical models require a large amount of information that is frequently unavailable, while data-based models ignore the physical processes. Recently the air2stream model has been proposed as an intermediate alternative that is based on physical heat budget processes, but it is so simplified that the model may be applied like data-driven ones. However, the price for simplicity is the need to calibrate eight parameters that, although have some physical meaning, cannot be measured or evaluated a priori. As a result, applicability and performance of the air2stream model for a particular stream relies on the efficiency of the calibration method. The original air2stream model uses an inefficient 20-year old approach called Particle Swarm Optimization with inertia weight. This study aims at finding an effective and robust calibration method for the air2stream model. Twelve different optimization algorithms are examined on six different streams from northern USA (states of Washington, Oregon and New York), Poland and Switzerland, located in both high mountains, hilly and lowland areas. It is found that the performance of the air2stream model depends significantly on the calibration method. Two algorithms lead to the best results for each considered stream. The air2stream model, calibrated with the chosen optimization methods, performs favorably against classical streamwater temperature models. The MATLAB code of the air2stream model and the chosen calibration procedure (CoBiDE) are available as Supplementary Material on the Journal of Hydrology web page.

Geomechanical Simulation of Bayou Choctaw Strategic Petroleum Reserve - Model Calibration.

Energy Technology Data Exchange (ETDEWEB)

Park, Byoung [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-02-01

A finite element numerical analysis model has been constructed that consists of a realistic mesh capturing the geometries of Bayou Choctaw (BC) Strategic Petroleum Reserve (SPR) site and multi - mechanism deformation ( M - D ) salt constitutive model using the daily data of actual wellhead pressure and oil - brine interface. The salt creep rate is not uniform in the salt dome, and the creep test data for BC salt is limited. Therefore, the model calibration is necessary to simulate the geomechanical behavior of the salt dome. The cavern volumetric closures of SPR caverns calculated from CAVEMAN are used for the field baseline measurement. The structure factor, A 2 , and transient strain limit factor, K 0 , in the M - D constitutive model are used for the calibration. The A 2 value obtained experimentally from the BC salt and K 0 value of Waste Isolation Pilot Plant (WIPP) salt are used for the baseline values. T o adjust the magnitude of A 2 and K 0 , multiplication factors A2F and K0F are defined, respectively. The A2F and K0F values of the salt dome and salt drawdown skins surrounding each SPR cavern have been determined through a number of back fitting analyses. The cavern volumetric closures calculated from this model correspond to the predictions from CAVEMAN for six SPR caverns. Therefore, this model is able to predict past and future geomechanical behaviors of the salt dome, caverns, caprock , and interbed layers. The geological concerns issued in the BC site will be explained from this model in a follow - up report .

Calibration and validation of earthquake catastrophe models. Case study: Impact Forecasting Earthquake Model for Algeria

Science.gov (United States)

Trendafiloski, G.; Gaspa Rebull, O.; Ewing, C.; Podlaha, A.; Magee, B.

2012-04-01

Calibration and validation are crucial steps in the production of the catastrophe models for the insurance industry in order to assure the model's reliability and to quantify its uncertainty. Calibration is needed in all components of model development including hazard and vulnerability. Validation is required to ensure that the losses calculated by the model match those observed in past events and which could happen in future. Impact Forecasting, the catastrophe modelling development centre of excellence within Aon Benfield, has recently launched its earthquake model for Algeria as a part of the earthquake model for the Maghreb region. The earthquake model went through a detailed calibration process including: (1) the seismic intensity attenuation model by use of macroseismic observations and maps from past earthquakes in Algeria; (2) calculation of the country-specific vulnerability modifiers by use of past damage observations in the country. The use of Benouar, 1994 ground motion prediction relationship was proven as the most appropriate for our model. Calculation of the regional vulnerability modifiers for the country led to 10% to 40% larger vulnerability indexes for different building types compared to average European indexes. The country specific damage models also included aggregate damage models for residential, commercial and industrial properties considering the description of the buildings stock given by World Housing Encyclopaedia and the local rebuilding cost factors equal to 10% for damage grade 1, 20% for damage grade 2, 35% for damage grade 3, 75% for damage grade 4 and 100% for damage grade 5. The damage grades comply with the European Macroseismic Scale (EMS-1998). The model was validated by use of "as-if" historical scenario simulations of three past earthquake events in Algeria M6.8 2003 Boumerdes, M7.3 1980 El-Asnam and M7.3 1856 Djidjelli earthquake. The calculated return periods of the losses for client market portfolio align with the

Electricity Price Forecast Using Combined Models with Adaptive Weights Selected and Errors Calibrated by Hidden Markov Model

Directory of Open Access Journals (Sweden)

Da Liu

2013-01-01

Full Text Available A combined forecast with weights adaptively selected and errors calibrated by Hidden Markov model (HMM is proposed to model the day-ahead electricity price. Firstly several single models were built to forecast the electricity price separately. Then the validation errors from every individual model were transformed into two discrete sequences: an emission sequence and a state sequence to build the HMM, obtaining a transmission matrix and an emission matrix, representing the forecasting ability state of the individual models. The combining weights of the individual models were decided by the state transmission matrixes in HMM and the best predict sample ratio of each individual among all the models in the validation set. The individual forecasts were averaged to get the combining forecast with the weights obtained above. The residuals of combining forecast were calibrated by the possible error calculated by the emission matrix of HMM. A case study of day-ahead electricity market of Pennsylvania-New Jersey-Maryland (PJM, USA, suggests that the proposed method outperforms individual techniques of price forecasting, such as support vector machine (SVM, generalized regression neural networks (GRNN, day-ahead modeling, and self-organized map (SOM similar days modeling.

Calibration by Hydrological Response Unit of a National Hydrologic Model to Improve Spatial Representation and Distribution of Parameters

Science.gov (United States)

Norton, P. A., II

2015-12-01

The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.

Sensitivity analysis and development of calibration methodology for near-surface hydrogeology model of Laxemar

Energy Technology Data Exchange (ETDEWEB)

Aneljung, Maria; Sassner, Mona; Gustafsson, Lars-Goeran (DHI Sverige AB, Lilla Bommen 1, SE-411 04 Goeteborg (Sweden))

2007-11-15

This report describes modelling where the hydrological modelling system MIKE SHE has been used to describe surface hydrology, near-surface hydrogeology, advective transport mechanisms, and the contact between groundwater and surface water within the SKB site investigation area at Laxemar. In the MIKE SHE system, surface water flow is described with the one-dimensional modelling tool MIKE 11, which is fully and dynamically integrated with the groundwater flow module in MIKE SHE. In early 2008, a supplementary data set will be available and a process of updating, rebuilding and calibrating the MIKE SHE model based on this data set will start. Before the calibration on the new data begins, it is important to gather as much knowledge as possible on calibration methods, and to identify critical calibration parameters and areas within the model that require special attention. In this project, the MIKE SHE model has been further developed. The model area has been extended, and the present model also includes an updated bedrock model and a more detailed description of the surface stream network. The numerical model has been updated and optimized, especially regarding the modelling of evapotranspiration and the unsaturated zone, and the coupling between the surface stream network in MIKE 11 and the overland flow in MIKE SHE. An initial calibration has been made and a base case has been defined and evaluated. In connection with the calibration, the most important changes made in the model were the following: The evapotranspiration was reduced. The infiltration capacity was reduced. The hydraulic conductivities of the Quaternary deposits in the water-saturated part of the subsurface were reduced. Data from one surface water level monitoring station, four surface water discharge monitoring stations and 43 groundwater level monitoring stations (SSM series boreholes) have been used to evaluate and calibrate the model. The base case simulations showed a reasonable agreement

On the calibration strategies of the Johnson–Cook strength model: Discussion and applications to experimental data

International Nuclear Information System (INIS)

Gambirasio, Luca; Rizzi, Egidio

2014-01-01

The present paper aims at assessing the various procedures adoptable for calibrating the parameters of the so-called Johnson–Cook strength model, expressing the deviatoric behavior of elastoplastic materials, with particular reference to the description of High Strain Rate (HSR) phenomena. The procedures rely on input experimental data corresponding to a set of hardening functions recorded at different equivalent plastic strain rates and temperatures. After a brief review of the main characteristics of the Johnson–Cook strength model, five different calibration strategies are framed and widely described. The assessment is implemented through a systematic application of each calibration strategy to three different real material cases, i.e. a DH-36 structural steel, a commercially pure niobium and an AL-6XN stainless steel. Experimental data available in the literature are considered. Results are presented in terms of plots showing the predicted Johnson–Cook hardening functions against the experimental trends, together with tables describing the fitting problematics which arise in each case, by assessing both lower yield stress and overall plastic flow introduced errors. The consequences determined by each calibration approach are then carefully compared and evaluated. A discussion on the positive and negative aspects of each strategy is presented and some suggestions on how to choose the best calibration approach are outlined, by considering the available experimental data and the objectives of the following modeling process. The proposed considerations should provide a useful guideline in the process of determining the best Johnson–Cook parameters in each specific situation in which the model is going to be adopted. A last section introduces some considerations about the calibration of the Johnson–Cook strength model through experimental data different from those consisting in a set of hardening functions relative to different equivalent plastic strain

The dielectric calibration of capacitance probes for soil hydrology using an oscillation frequency response model

Directory of Open Access Journals (Sweden)

D. A. Robinson

1998-01-01

Full Text Available Capacitance probes are a fast, safe and relatively inexpensive means of measuring the relative permittivity of soils, which can then be used to estimate soil water content. Initial experiments with capacitance probes used empirical calibrations between the frequency response of the instrument and soil water content. This has the disadvantage that the calibrations are instrument-dependent. A twofold calibration strategy is described in this paper; the instrument frequency is turned into relative permittivity (dielectric constant which can then be calibrated against soil water content. This approach offers the advantages of making the second calibration, from soil permittivity to soil water content. instrument-independent and allows comparison with other dielectric methods, such as time domain reflectometry. A physically based model, used to calibrate capacitance probes in terms of relative permittivity (εr is presented. The model, which was developed from circuit analysis, predicts, successfully, the frequency response of the instrument in liquids with different relative permittivities, using only measurements in air and water. lt was used successfully to calibrate 10 prototype surface capacitance insertion probes (SCIPS and a depth capacitance probe. The findings demonstrate that the geometric properties of the instrument electrodes were an important parameter in the model, the value of which could be fixed through measurement. The relationship between apparent soil permittivity and volumetric water content has been the subject of much research in the last 30 years. Two lines of investigation have developed, time domain reflectometry (TDR and capacitance. Both methods claim to measure relative permittivity and should therefore be comparable. This paper demonstrates that the IH capacitance probe overestimates relative permittivity as the ionic conductivity of the medium increases. Electrically conducting ionic solutions were used to test the

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

Energy Technology Data Exchange (ETDEWEB)

Thornton, Peter E [ORNL; Wang, Weile [ORNL; Law, Beverly E. [Oregon State University; Nemani, Ramakrishna R [NASA Ames Research Center

2009-01-01

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.

Displaced calibration of PM10 measurements using spatio-temporal models

Directory of Open Access Journals (Sweden)

Daniela Cocchi

2007-12-01

Full Text Available PM10 monitoring networks are equipped with heterogeneous samplers. Some of these samplers are known to underestimate true levels of concentrations (non-reference samplers. In this paper we propose a hierarchical spatio-temporal Bayesian model for the calibration of measurements recorded using non-reference samplers, by borrowing strength from non co-located reference sampler measurements.

Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration.

Science.gov (United States)

Sadeghian, Amir; Hudson, Jeff; Wheater, Howard; Lindenschmidt, Karl-Erich

2017-08-01

In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m 3 /s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

Analysis of variation in calibration curves for Kodak XV radiographic film using model-based parameters.

Science.gov (United States)

Hsu, Shu-Hui; Kulasekere, Ravi; Roberson, Peter L

2010-08-05

Film calibration is time-consuming work when dose accuracy is essential while working in a range of photon scatter environments. This study uses the single-target single-hit model of film response to fit the calibration curves as a function of calibration method, processor condition, field size and depth. Kodak XV film was irradiated perpendicular to the beam axis in a solid water phantom. Standard calibration films (one dose point per film) were irradiated at 90 cm source-to-surface distance (SSD) for various doses (16-128 cGy), depths (0.2, 0.5, 1.5, 5, 10 cm) and field sizes (5 × 5, 10 × 10 and 20 × 20 cm²). The 8-field calibration method (eight dose points per film) was used as a reference for each experiment, taken at 95 cm SSD and 5 cm depth. The delivered doses were measured using an Attix parallel plate chamber for improved accuracy of dose estimation in the buildup region. Three fitting methods with one to three dose points per calibration curve were investigated for the field sizes of 5 × 5, 10 × 10 and 20 × 20 cm². The inter-day variation of model parameters (background, saturation and slope) were 1.8%, 5.7%, and 7.7% (1 σ) using the 8-field method. The saturation parameter ratio of standard to 8-field curves was 1.083 ± 0.005. The slope parameter ratio of standard to 8-field curves ranged from 0.99 to 1.05, depending on field size and depth. The slope parameter ratio decreases with increasing depth below 0.5 cm for the three field sizes. It increases with increasing depths above 0.5 cm. A calibration curve with one to three dose points fitted with the model is possible with 2% accuracy in film dosimetry for various irradiation conditions. The proposed fitting methods may reduce workload while providing energy dependence correction in radiographic film dosimetry. This study is limited to radiographic XV film with a Lumisys scanner.

Differential Evolution algorithm applied to FSW model calibration

Science.gov (United States)

Idagawa, H. S.; Santos, T. F. A.; Ramirez, A. J.

2014-03-01

Friction Stir Welding (FSW) is a solid state welding process that can be modelled using a Computational Fluid Dynamics (CFD) approach. These models use adjustable parameters to control the heat transfer and the heat input to the weld. These parameters are used to calibrate the model and they are generally determined using the conventional trial and error approach. Since this method is not very efficient, we used the Differential Evolution (DE) algorithm to successfully determine these parameters. In order to improve the success rate and to reduce the computational cost of the method, this work studied different characteristics of the DE algorithm, such as the evolution strategy, the objective function, the mutation scaling factor and the crossover rate. The DE algorithm was tested using a friction stir weld performed on a UNS S32205 Duplex Stainless Steel.

Calibrating emergent phenomena in stock markets with agent based models.

Science.gov (United States)

Fievet, Lucas; Sornette, Didier

2018-01-01

Since the 2008 financial crisis, agent-based models (ABMs), which account for out-of-equilibrium dynamics, heterogeneous preferences, time horizons and strategies, have often been envisioned as the new frontier that could revolutionise and displace the more standard models and tools in economics. However, their adoption and generalisation is drastically hindered by the absence of general reliable operational calibration methods. Here, we start with a different calibration angle that qualifies an ABM for its ability to achieve abnormal trading performance with respect to the buy-and-hold strategy when fed with real financial data. Starting from the common definition of standard minority and majority agents with binary strategies, we prove their equivalence to optimal decision trees. This efficient representation allows us to exhaustively test all meaningful single agent models for their potential anomalous investment performance, which we apply to the NASDAQ Composite index over the last 20 years. We uncover large significant predictive power, with anomalous Sharpe ratio and directional accuracy, in particular during the dotcom bubble and crash and the 2008 financial crisis. A principal component analysis reveals transient convergence between the anomalous minority and majority models. A novel combination of the optimal single-agent models of both classes into a two-agents model leads to remarkable superior investment performance, especially during the periods of bubbles and crashes. Our design opens the field of ABMs to construct novel types of advanced warning systems of market crises, based on the emergent collective intelligence of ABMs built on carefully designed optimal decision trees that can be reversed engineered from real financial data.

Calibrating emergent phenomena in stock markets with agent based models

Science.gov (United States)

Sornette, Didier

2018-01-01

Since the 2008 financial crisis, agent-based models (ABMs), which account for out-of-equilibrium dynamics, heterogeneous preferences, time horizons and strategies, have often been envisioned as the new frontier that could revolutionise and displace the more standard models and tools in economics. However, their adoption and generalisation is drastically hindered by the absence of general reliable operational calibration methods. Here, we start with a different calibration angle that qualifies an ABM for its ability to achieve abnormal trading performance with respect to the buy-and-hold strategy when fed with real financial data. Starting from the common definition of standard minority and majority agents with binary strategies, we prove their equivalence to optimal decision trees. This efficient representation allows us to exhaustively test all meaningful single agent models for their potential anomalous investment performance, which we apply to the NASDAQ Composite index over the last 20 years. We uncover large significant predictive power, with anomalous Sharpe ratio and directional accuracy, in particular during the dotcom bubble and crash and the 2008 financial crisis. A principal component analysis reveals transient convergence between the anomalous minority and majority models. A novel combination of the optimal single-agent models of both classes into a two-agents model leads to remarkable superior investment performance, especially during the periods of bubbles and crashes. Our design opens the field of ABMs to construct novel types of advanced warning systems of market crises, based on the emergent collective intelligence of ABMs built on carefully designed optimal decision trees that can be reversed engineered from real financial data. PMID:29499049

Geomechanical Model Calibration Using Field Measurements for a Petroleum Reserve

Science.gov (United States)

Park, Byoung Yoon; Sobolik, Steven R.; Herrick, Courtney G.

2018-03-01

A finite element numerical analysis model has been constructed that consists of a mesh that effectively captures the geometries of Bayou Choctaw (BC) Strategic Petroleum Reserve (SPR) site and multimechanism deformation (M-D) salt constitutive model using the daily data of actual wellhead pressure and oil-brine interface location. The salt creep rate is not uniform in the salt dome, and the creep test data for BC salt are limited. Therefore, the model calibration is necessary to simulate the geomechanical behavior of the salt dome. The cavern volumetric closures of SPR caverns calculated from CAVEMAN are used as the field baseline measurement. The structure factor, A 2, and transient strain limit factor, K 0, in the M-D constitutive model are used for the calibration. The value of A 2, obtained experimentally from BC salt, and the value of K 0, obtained from Waste Isolation Pilot Plant salt, are used for the baseline values. To adjust the magnitude of A 2 and K 0, multiplication factors A 2 F and K 0 F are defined, respectively. The A 2 F and K 0 F values of the salt dome and salt drawdown skins surrounding each SPR cavern have been determined through a number of back analyses. The cavern volumetric closures calculated from this model correspond to the predictions from CAVEMAN for six SPR caverns. Therefore, this model is able to predict behaviors of the salt dome, caverns, caprock, and interbed layers. The geotechnical concerns associated with the BC site from this analysis will be explained in a follow-up paper.

Modeling Prairie Pothole Lakes: Linking Satellite Observation and Calibration (Invited)

Science.gov (United States)

Schwartz, F. W.; Liu, G.; Zhang, B.; Yu, Z.

2009-12-01

This paper examines the response of a complex lake wetland system to variations in climate. The focus is on the lakes and wetlands of the Missouri Coteau, which is part of the larger Prairie Pothole Region of the Central Plains of North America. Information on lake size was enumerated from satellite images, and yielded power law relationships for different hydrological conditions. More traditional lake-stage data were made available to us from the USGS Cottonwood Lake Study Site in North Dakota. A Probabilistic Hydrologic Model (PHM) was developed to simulate lake complexes comprised of tens-of-thousands or more individual closed-basin lakes and wetlands. What is new about this model is a calibration scheme that utilizes remotely-sensed data on lake area as well as stage data for individual lakes. Some ¼ million individual data points are used within a Genetic Algorithm to calibrate the model by comparing the simulated results with observed lake area-frequency power law relationships derived from Landsat images and water depths from seven individual lakes and wetlands. The simulated lake behaviors show good agreement with the observations under average, dry, and wet climatic conditions. The calibrated model is used to examine the impact of climate variability on a large lake complex in ND, in particular, the “Dust Bowl Drought” 1930s. This most famous drought of the 20th Century devastated the agricultural economy of the Great Plains with health and social impacts lingering for years afterwards. Interestingly, the drought of 1930s is unremarkable in relation to others of greater intensity and frequency before AD 1200 in the Great Plains. Major droughts and deluges have the ability to create marked variability of the power law function (e.g. up to one and a half orders of magnitude variability from the extreme Dust Bowl Drought to the extreme 1993-2001 deluge). This new probabilistic modeling approach provides a novel tool to examine the response of the

Electronic transport in VO{sub 2}—Experimentally calibrated Boltzmann transport modeling

Energy Technology Data Exchange (ETDEWEB)

Kinaci, Alper; Rosenmann, Daniel; Chan, Maria K. Y., E-mail: debasish.banerjee@toyota.com, E-mail: mchan@anl.gov [Center for Nanoscale Materials, Argonne National Laboratory, Argonne, Illinois 60439 (United States); Kado, Motohisa [Higashifuji Technical Center, Toyota Motor Corporation, Susono, Shizuoka 410-1193 (Japan); Ling, Chen; Zhu, Gaohua; Banerjee, Debasish, E-mail: debasish.banerjee@toyota.com, E-mail: mchan@anl.gov [Materials Research Department, Toyota Motor Engineering and Manufacturing North America, Inc., Ann Arbor, Michigan 48105 (United States)

2015-12-28

Materials that undergo metal-insulator transitions (MITs) are under intense study, because the transition is scientifically fascinating and technologically promising for various applications. Among these materials, VO{sub 2} has served as a prototype due to its favorable transition temperature. While the physical underpinnings of the transition have been heavily investigated experimentally and computationally, quantitative modeling of electronic transport in the two phases has yet to be undertaken. In this work, we establish a density-functional-theory (DFT)-based approach with Hubbard U correction (DFT + U) to model electronic transport properties in VO{sub 2} in the semiconducting and metallic regimes, focusing on band transport using the Boltzmann transport equations. We synthesized high quality VO{sub 2} films and measured the transport quantities across the transition, in order to calibrate the free parameters in the model. We find that the experimental calibration of the Hubbard correction term can efficiently and adequately model the metallic and semiconducting phases, allowing for further computational design of MIT materials for desirable transport properties.

Immune Algorithm Complex Method for Transducer Calibration

Directory of Open Access Journals (Sweden)

YU Jiangming

2014-08-01

Full Text Available As a key link in engineering test tasks, the transducer calibration has significant influence on accuracy and reliability of test results. Because of unknown and complex nonlinear characteristics, conventional method can’t achieve satisfactory accuracy. An Immune algorithm complex modeling approach is proposed, and the simulated studies on the calibration of third multiple output transducers is made respectively by use of the developed complex modeling. The simulated and experimental results show that the Immune algorithm complex modeling approach can improve significantly calibration precision comparison with traditional calibration methods.

Radiometric modeling and calibration of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) ground based measurement experiment

Science.gov (United States)

Tian, Jialin; Smith, William L.; Gazarik, Michael J.

2008-12-01

The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere's thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The GIFTS calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts, therefore, enhancing the absolute calibration accuracy. This method is applied to data collected during the GIFTS Ground Based Measurement (GBM) experiment, together with simultaneous observations by the accurately calibrated AERI (Atmospheric Emitted Radiance Interferometer), both simultaneously zenith viewing the sky through the same external scene mirror at ten-minute intervals throughout a cloudless day at Logan Utah on September 13, 2006. The accurately calibrated GIFTS radiances are produced using the first four PC scores in the GIFTS-AERI regression model. Temperature and moisture profiles retrieved from the PC-calibrated GIFTS radiances are verified against radiosonde measurements collected throughout the GIFTS sky measurement period. Using the GIFTS GBM calibration model, we compute the calibrated radiances from data

Optical modeling and polarization calibration for CMB measurements with ACTPol and Advanced ACTPol

Science.gov (United States)

Koopman, Brian; Austermann, Jason; Cho, Hsiao-Mei; Coughlin, Kevin P.; Duff, Shannon M.; Gallardo, Patricio A.; Hasselfield, Matthew; Henderson, Shawn W.; Ho, Shuay-Pwu Patty; Hubmayr, Johannes; Irwin, Kent D.; Li, Dale; McMahon, Jeff; Nati, Federico; Niemack, Michael D.; Newburgh, Laura; Page, Lyman A.; Salatino, Maria; Schillaci, Alessandro; Schmitt, Benjamin L.; Simon, Sara M.; Vavagiakis, Eve M.; Ward, Jonathan T.; Wollack, Edward J.

2016-07-01

The Atacama Cosmology Telescope Polarimeter (ACTPol) is a polarization sensitive upgrade to the Atacama Cosmology Telescope, located at an elevation of 5190 m on Cerro Toco in Chile. ACTPol uses transition edge sensor bolometers coupled to orthomode transducers to measure both the temperature and polarization of the Cosmic Microwave Background (CMB). Calibration of the detector angles is a critical step in producing polarization maps of the CMB. Polarization angle offsets in the detector calibration can cause leakage in polarization from E to B modes and induce a spurious signal in the EB and TB cross correlations, which eliminates our ability to measure potential cosmological sources of EB and TB signals, such as cosmic birefringence. We calibrate the ACTPol detector angles by ray tracing the designed detector angle through the entire optical chain to determine the projection of each detector angle on the sky. The distribution of calibrated detector polarization angles are consistent with a global offset angle from zero when compared to the EB-nulling offset angle, the angle required to null the EB cross-correlation power spectrum. We present the optical modeling process. The detector angles can be cross checked through observations of known polarized sources, whether this be a galactic source or a laboratory reference standard. To cross check the ACTPol detector angles, we use a thin film polarization grid placed in front of the receiver of the telescope, between the receiver and the secondary reflector. Making use of a rapidly rotating half-wave plate (HWP) mount we spin the polarizing grid at a constant speed, polarizing and rotating the incoming atmospheric signal. The resulting sinusoidal signal is used to determine the detector angles. The optical modeling calibration was shown to be consistent with a global offset angle of zero when compared to EB nulling in the first ACTPol results and will continue to be a part of our calibration implementation. The first

Derived flood frequency analysis using different model calibration strategies based on various types of rainfall-runoff data - a comparison

Science.gov (United States)

Haberlandt, U.; Radtke, I.

2013-08-01

Derived flood frequency analysis allows to estimate design floods with hydrological modelling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices about precipitation input, discharge output and consequently regarding the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets. Event based and continuous observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in Northern Germany with the hydrological model HEC-HMS. The results show that: (i) the same type of precipitation input data should be used for calibration and application of the hydrological model, (ii) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, (iii) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.

On the possibility of calibrating urban storm-water drainage models using gauge-based adjusted radar rainfall estimates

OpenAIRE

Ochoa-Rodriguez, S; Wang, L; Simoes, N; Onof, C; Maksimovi?, ?

2013-01-01

24/07/14 meb. Authors did not sign CTA. Traditionally, urban storm water drainage models have been calibrated using only raingauge data, which may result in overly conservative models due to the lack of spatial description of rainfall. With the advent of weather radars, radar rainfall estimates with higher temporal and spatial resolution have become increasingly available and have started to be used operationally for urban storm water model calibration and real time operation. Nonetheless,...

Calibration factor or calibration coefficient?

International Nuclear Information System (INIS)

Meghzifene, A.; Shortt, K.R.

2002-01-01

Full text: The IAEA/WHO network of SSDLs was set up in order to establish links between SSDL members and the international measurement system. At the end of 2001, there were 73 network members in 63 Member States. The SSDL network members provide calibration services to end-users at the national or regional level. The results of the calibrations are summarized in a document called calibration report or calibration certificate. The IAEA has been using the term calibration certificate and will continue using the same terminology. The most important information in a calibration certificate is a list of calibration factors and their related uncertainties that apply to the calibrated instrument for the well-defined irradiation and ambient conditions. The IAEA has recently decided to change the term calibration factor to calibration coefficient, to be fully in line with ISO [ISO 31-0], which recommends the use of the term coefficient when it links two quantities A and B (equation 1) that have different dimensions. The term factor should only be used for k when it is used to link the terms A and B that have the same dimensions A=k.B. However, in a typical calibration, an ion chamber is calibrated in terms of a physical quantity such as air kerma, dose to water, ambient dose equivalent, etc. If the chamber is calibrated together with its electrometer, then the calibration refers to the physical quantity to be measured per electrometer unit reading. In this case, the terms referred have different dimensions. The adoption by the Agency of the term coefficient to express the results of calibrations is consistent with the 'International vocabulary of basic and general terms in metrology' prepared jointly by the BIPM, IEC, ISO, OIML and other organizations. The BIPM has changed from factor to coefficient. The authors believe that this is more than just a matter of semantics and recommend that the SSDL network members adopt this change in terminology. (author)

Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI

Science.gov (United States)

Ruiz-Pérez, Guiomar; Koch, Julian; Manfreda, Salvatore; Caylor, Kelly; Francés, Félix

2017-12-01

Ecohydrological modeling studies in developing countries, such as sub-Saharan Africa, often face the problem of extensive parametrical requirements and limited available data. Satellite remote sensing data may be able to fill this gap, but require novel methodologies to exploit their spatio-temporal information that could potentially be incorporated into model calibration and validation frameworks. The present study tackles this problem by suggesting an automatic calibration procedure, based on the empirical orthogonal function, for distributed ecohydrological daily models. The procedure is tested with the support of remote sensing data in a data-scarce environment - the upper Ewaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model is calibrated using only NDVI (Normalized Difference Vegetation Index) data derived from MODIS. The results demonstrate that (1) satellite data of vegetation dynamics can be used to calibrate and validate ecohydrological models in water-controlled and data-scarce regions, (2) the model calibrated using only satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet and (3) the proposed automatic calibration methodology works satisfactorily and it allows for a straightforward incorporation of spatio-temporal data into the calibration and validation framework of a model.

New error calibration tests for gravity models using subset solutions and independent data - Applied to GEM-T3

Science.gov (United States)

Lerch, F. J.; Nerem, R. S.; Chinn, D. S.; Chan, J. C.; Patel, G. B.; Klosko, S. M.

1993-01-01

A new method has been developed to provide a direct test of the error calibrations of gravity models based on actual satellite observations. The basic approach projects the error estimates of the gravity model parameters onto satellite observations, and the results of these projections are then compared with data residual computed from the orbital fits. To allow specific testing of the gravity error calibrations, subset solutions are computed based on the data set and data weighting of the gravity model. The approach is demonstrated using GEM-T3 to show that the gravity error estimates are well calibrated and that reliable predictions of orbit accuracies can be achieved for independent orbits.

Comparison between two calibration models of a measurement system for thyroid monitoring

International Nuclear Information System (INIS)

Venturini, Luzia

2005-01-01

This paper shows a comparison between two theoretical calibration that use two mathematical models to represent the neck region. In the first model thyroid is considered to be just a region limited by two concentric cylinders whose dimensions are those of trachea and neck. The second model uses functional functions to get a better representation of the thyroid geometry. Efficiency values are obtained using Monte Carlo simulation. (author)

A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

Science.gov (United States)

Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

2018-01-01

Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that

Improving plasma shaping accuracy through consolidation of control model maintenance, diagnostic calibration, and hardware change control

International Nuclear Information System (INIS)

Baggest, D.S.; Rothweil, D.A.; Pang, S.

1995-12-01

With the advent of more sophisticated techniques for control of tokamak plasmas comes the requirement for increasingly more accurate models of plasma processes and tokamak systems. Development of accurate models for DIII-D power systems, vessel, and poloidal coils is already complete, while work continues in development of general plasma response modeling techniques. Increased accuracy in estimates of parameters to be controlled is also required. It is important to ensure that errors in supporting systems such as diagnostic and command circuits do not limit the accuracy of plasma parameter estimates or inhibit the ability to derive accurate plasma/tokamak system models. To address this issue, we have developed more formal power systems change control and power system/magnetic diagnostics calibration procedures. This paper discusses our approach to consolidating the tasks in these closely related areas. This includes, for example, defining criteria for when diagnostics should be re-calibrated along with required calibration tolerances, and implementing methods for tracking power systems hardware modifications and the resultant changes to control models

FAST Model Calibration and Validation of the OC5-DeepCwind Floating Offshore Wind System Against Wave Tank Test Data

Energy Technology Data Exchange (ETDEWEB)

Wendt, Fabian F [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Robertson, Amy N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jonkman, Jason [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-06-03

During the course of the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, which focused on the validation of numerical methods through comparison against tank test data, the authors created a numerical FAST model of the 1:50-scale DeepCwind semisubmersible system that was tested at the Maritime Research Institute Netherlands ocean basin in 2013. This paper discusses several model calibration studies that were conducted to identify model adjustments that improve the agreement between the numerical simulations and the experimental test data. These calibration studies cover wind-field-specific parameters (coherence, turbulence), hydrodynamic and aerodynamic modeling approaches, as well as rotor model (blade-pitch and blade-mass imbalances) and tower model (structural tower damping coefficient) adjustments. These calibration studies were conducted based on relatively simple calibration load cases (wave only/wind only). The agreement between the final FAST model and experimental measurements is then assessed based on more-complex combined wind and wave validation cases.

Preliminary report on NTS spectral gamma logging and calibration models

International Nuclear Information System (INIS)

Mathews, M.A.; Warren, R.G.; Garcia, S.R.; Lavelle, M.J.

1985-01-01

Facilities are now available at the Nevada Test Site (NTS) in Building 2201 to calibrate spectral gamma logging equipment in environments of low radioactivity. Such environments are routinely encountered during logging of holes at the NTS. Four calibration models were delivered to Building 2201 in January 1985. Each model, or test pit, consists of a stone block with a 12-inch diameter cored borehole. Preliminary radioelement values from the core for the test pits range from 0.58 to 3.83% potassium (K), 0.48 to 29.11 ppm thorium (Th), and 0.62 to 40.42 ppm uranium (U). Two satellite holes, U19ab number2 and U19ab number3, were logged during the winter of 1984-1985. The response of these logs correlates with contents of the naturally radioactive elements K. Th. and U determined in samples from petrologic zones that occur within these holes. Based on these comparisons, the spectral gamma log aids in the recognition and mapping of subsurface stratigraphic units and alteration features associated with unusual concentration of these radioactive elements, such as clay-rich zones

Impacts of Spatial Climatic Representation on Hydrological Model Calibration and Prediction Uncertainty: A Mountainous Catchment of Three Gorges Reservoir Region, China

Directory of Open Access Journals (Sweden)

Yan Li

2016-02-01

Full Text Available Sparse climatic observations represent a major challenge for hydrological modeling of mountain catchments with implications for decision-making in water resources management. Employing elevation bands in the Soil and Water Assessment Tool-Sequential Uncertainty Fitting (SWAT2012-SUFI2 model enabled representation of precipitation and temperature variation with altitude in the Daning river catchment (Three Gorges Reservoir Region, China where meteorological inputs are limited in spatial extent and are derived from observations from relatively low lying locations. Inclusion of elevation bands produced better model performance for 1987–1993 with the Nash–Sutcliffe efficiency (NSE increasing by at least 0.11 prior to calibration. During calibration prediction uncertainty was greatly reduced. With similar R-factors from the earlier calibration iterations, a further 11% of observations were included within the 95% prediction uncertainty (95PPU compared to the model without elevation bands. For behavioral simulations defined in SWAT calibration using a NSE threshold of 0.3, an additional 3.9% of observations were within the 95PPU while the uncertainty reduced by 7.6% in the model with elevation bands. The calibrated model with elevation bands reproduced observed river discharges with the performance in the calibration period changing to “very good” from “poor” without elevation bands. The output uncertainty of calibrated model with elevation bands was satisfactory, having 85% of flow observations included within the 95PPU. These results clearly demonstrate the requirement to account for orographic effects on precipitation and temperature in hydrological models of mountainous catchments.

Non-linear calibration models for near infrared spectroscopy

DEFF Research Database (Denmark)

Ni, Wangdong; Nørgaard, Lars; Mørup, Morten

2014-01-01

by ridge regression (RR). The performance of the different methods is demonstrated by their practical applications using three real-life near infrared (NIR) data sets. Different aspects of the various approaches including computational time, model interpretability, potential over-fitting using the non-linear...... models on linear problems, robustness to small or medium sample sets, and robustness to pre-processing, are discussed. The results suggest that GPR and BANN are powerful and promising methods for handling linear as well as nonlinear systems, even when the data sets are moderately small. The LS......-SVM), relevance vector machines (RVM), Gaussian process regression (GPR), artificial neural network (ANN), and Bayesian ANN (BANN). In this comparison, partial least squares (PLS) regression is used as a linear benchmark, while the relationship of the methods is considered in terms of traditional calibration...

Building and calibrating a large-extent and high resolution coupled groundwater-land surface model using globally available data-sets

Science.gov (United States)

Sutanudjaja, E. H.; Van Beek, L. P.; de Jong, S. M.; van Geer, F.; Bierkens, M. F.

2012-12-01

The current generation of large-scale hydrological models generally lacks a groundwater model component simulating lateral groundwater flow. Large-scale groundwater models are rare due to a lack of hydro-geological data required for their parameterization and a lack of groundwater head data required for their calibration. In this study, we propose an approach to develop a large-extent fully-coupled land surface-groundwater model by using globally available datasets and calibrate it using a combination of discharge observations and remotely-sensed soil moisture data. The underlying objective is to devise a collection of methods that enables one to build and parameterize large-scale groundwater models in data-poor regions. The model used, PCR-GLOBWB-MOD, has a spatial resolution of 1 km x 1 km and operates on a daily basis. It consists of a single-layer MODFLOW groundwater model that is dynamically coupled to the PCR-GLOBWB land surface model. This fully-coupled model accommodates two-way interactions between surface water levels and groundwater head dynamics, as well as between upper soil moisture states and groundwater levels, including a capillary rise mechanism to sustain upper soil storage and thus to fulfill high evaporation demands (during dry conditions). As a test bed, we used the Rhine-Meuse basin, where more than 4000 groundwater head time series have been collected for validation purposes. The model was parameterized using globally available data-sets on surface elevation, drainage direction, land-cover, soil and lithology. Next, the model was calibrated using a brute force approach and massive parallel computing, i.e. by running the coupled groundwater-land surface model for more than 3000 different parameter sets. Here, we varied minimal soil moisture storage and saturated conductivities of the soil layers as well as aquifer transmissivities. Using different regularization strategies and calibration criteria we compared three calibration scenarios

Nested sampling algorithm for subsurface flow model selection, uncertainty quantification, and nonlinear calibration

KAUST Repository

Elsheikh, A. H.; Wheeler, M. F.; Hoteit, Ibrahim

2013-01-01

Calibration of subsurface flow models is an essential step for managing ground water aquifers, designing of contaminant remediation plans, and maximizing recovery from hydrocarbon reservoirs. We investigate an efficient sampling algorithm known

Ørsted Pre-Flight Magnetometer Calibration Mission

DEFF Research Database (Denmark)

Risbo, T.; Brauer, Peter; Merayo, José M.G.

2003-01-01

and the overall calibration results are given. The temperature calibrations are explained and reported on. The overall calibration model standard deviation is about 100 pT rms. Comparisons with the later in-flight calibrations show that, except for the unknown satellite offsets, an agreement within 4 n...

Calibration artefacts in radio interferometry - III. Phase-only calibration and primary beam correction

Science.gov (United States)

Grobler, T. L.; Stewart, A. J.; Wijnholds, S. J.; Kenyon, J. S.; Smirnov, O. M.

2016-09-01

This is the third installment in a series of papers in which we investigate calibration artefacts. Calibration artefacts (also known as ghosts or spurious sources) are created when we calibrate with an incomplete model. In the first two papers of this series, we developed a mathematical framework which enabled us to study the ghosting mechanism itself. An interesting concomitant of the second paper was that ghosts appear in symmetrical pairs. This could possibly account for spurious symmetrization. Spurious symmetrization refers to the appearance of a spurious source (the antighost) symmetrically opposite an unmodelled source around a modelled source. The analysis in the first two papers indicates that the antighost is usually very faint, in particular, when a large number of antennas are used. This suggests that spurious symmetrization will mainly occur at an almost undetectable flux level. In this paper, we show that phase-only calibration produces an antighost that is N-times (where N denotes the number of antennas in the array) as bright as the one produced by phase and amplitude calibration and that this already bright ghost can be further amplified by the primary beam correction.

A fully Bayesian method for jointly fitting instrumental calibration and X-ray spectral models

International Nuclear Information System (INIS)

Xu, Jin; Yu, Yaming; Van Dyk, David A.; Kashyap, Vinay L.; Siemiginowska, Aneta; Drake, Jeremy; Ratzlaff, Pete; Connors, Alanna; Meng, Xiao-Li

2014-01-01

Owing to a lack of robust principled methods, systematic instrumental uncertainties have generally been ignored in astrophysical data analysis despite wide recognition of the importance of including them. Ignoring calibration uncertainty can cause bias in the estimation of source model parameters and can lead to underestimation of the variance of these estimates. We previously introduced a pragmatic Bayesian method to address this problem. The method is 'pragmatic' in that it introduced an ad hoc technique that simplified computation by neglecting the potential information in the data for narrowing the uncertainty for the calibration product. Following that work, we use a principal component analysis to efficiently represent the uncertainty of the effective area of an X-ray (or γ-ray) telescope. Here, however, we leverage this representation to enable a principled, fully Bayesian method that coherently accounts for the calibration uncertainty in high-energy spectral analysis. In this setting, the method is compared with standard analysis techniques and the pragmatic Bayesian method. The advantage of the fully Bayesian method is that it allows the data to provide information not only for estimation of the source parameters but also for the calibration product—here the effective area, conditional on the adopted spectral model. In this way, it can yield more accurate and efficient estimates of the source parameters along with valid estimates of their uncertainty. Provided that the source spectrum can be accurately described by a parameterized model, this method allows rigorous inference about the effective area by quantifying which possible curves are most consistent with the data.

Construction of the Calibration Set through Multivariate Analysis in Visible and Near-Infrared Prediction Model for Estimating Soil Organic Matter

Directory of Open Access Journals (Sweden)

Xiaomi Wang

2017-02-01

Full Text Available The visible and near-infrared (VNIR spectroscopy prediction model is an effective tool for the prediction of soil organic matter (SOM content. The predictive accuracy of the VNIR model is highly dependent on the selection of the calibration set. However, conventional methods for selecting the calibration set for constructing the VNIR prediction model merely consider either the gradients of SOM or the soil VNIR spectra and neglect the influence of environmental variables. However, soil samples generally present a strong spatial variability, and, thus, the relationship between the SOM content and VNIR spectra may vary with respect to locations and surrounding environments. Hence, VNIR prediction models based on conventional calibration set selection methods would be biased, especially for estimating highly spatially variable soil content (e.g., SOM. To equip the calibration set selection method with the ability to consider SOM spatial variation and environmental influence, this paper proposes an improved method for selecting the calibration set. The proposed method combines the improved multi-variable association relationship clustering mining (MVARC method and the Rank–Kennard–Stone (Rank-KS method in order to synthetically consider the SOM gradient, spectral information, and environmental variables. In the proposed MVARC-R-KS method, MVARC integrates the Apriori algorithm, a density-based clustering algorithm, and the Delaunay triangulation. The MVARC method is first utilized to adaptively mine clustering distribution zones in which environmental variables exert a similar influence on soil samples. The feasibility of the MVARC method is proven by conducting an experiment on a simulated dataset. The calibration set is evenly selected from the clustering zones and the remaining zone by using the Rank-KS algorithm in order to avoid a single property in the selected calibration set. The proposed MVARC-R-KS approach is applied to select a

A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model

Science.gov (United States)

Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.

2015-05-01

A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.

An efficient multi-stage algorithm for full calibration of the hemodynamic model from BOLD signal responses

KAUST Repository

Zambri, Brian; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

2017-01-01

We propose a computational strategy that falls into the category of prediction/correction iterative-type approaches, for calibrating the hemodynamic model introduced by Friston et al. (2000). The proposed method is employed to estimate consecutively the values of the biophysiological system parameters and the external stimulus characteristics of the model. Numerical results corresponding to both synthetic and real functional Magnetic Resonance Imaging (fMRI) measurements for a single stimulus as well as for multiple stimuli are reported to highlight the capability of this computational methodology to fully calibrate the considered hemodynamic model. This article is protected by copyright. All rights reserved.

An efficient multi-stage algorithm for full calibration of the hemodynamic model from BOLD signal responses

KAUST Repository

Zambri, Brian

2017-02-22

We propose a computational strategy that falls into the category of prediction/correction iterative-type approaches, for calibrating the hemodynamic model introduced by Friston et al. (2000). The proposed method is employed to estimate consecutively the values of the biophysiological system parameters and the external stimulus characteristics of the model. Numerical results corresponding to both synthetic and real functional Magnetic Resonance Imaging (fMRI) measurements for a single stimulus as well as for multiple stimuli are reported to highlight the capability of this computational methodology to fully calibrate the considered hemodynamic model. This article is protected by copyright. All rights reserved.

Mathematical Model and Calibration Procedure of a PSD Sensor Used in Local Positioning Systems.

Science.gov (United States)

Rodríguez-Navarro, David; Lázaro-Galilea, José Luis; Bravo-Muñoz, Ignacio; Gardel-Vicente, Alfredo; Domingo-Perez, Francisco; Tsirigotis, Georgios

2016-09-15

Here, we propose a mathematical model and a calibration procedure for a PSD (position sensitive device) sensor equipped with an optical system, to enable accurate measurement of the angle of arrival of one or more beams of light emitted by infrared (IR) transmitters located at distances of between 4 and 6 m. To achieve this objective, it was necessary to characterize the intrinsic parameters that model the system and obtain their values. This first approach was based on a pin-hole model, to which system nonlinearities were added, and this was used to model the points obtained with the nA currents provided by the PSD. In addition, we analyzed the main sources of error, including PSD sensor signal noise, gain factor imbalances and PSD sensor distortion. The results indicated that the proposed model and method provided satisfactory calibration and yielded precise parameter values, enabling accurate measurement of the angle of arrival with a low degree of error, as evidenced by the experimental results.

Ultrasound data for laboratory calibration of an analytical model to calculate crack depth on asphalt pavements

Directory of Open Access Journals (Sweden)

Miguel A. Franesqui

2017-08-01

Full Text Available This article outlines the ultrasound data employed to calibrate in the laboratory an analytical model that permits the calculation of the depth of partial-depth surface-initiated cracks on bituminous pavements using this non-destructive technique. This initial calibration is required so that the model provides sufficient precision during practical application. The ultrasonic pulse transit times were measured on beam samples of different asphalt mixtures (semi-dense asphalt concrete AC-S; asphalt concrete for very thin layers BBTM; and porous asphalt PA. The cracks on the laboratory samples were simulated by means of notches of variable depths. With the data of ultrasound transmission time ratios, curve-fittings were carried out on the analytical model, thus determining the regression parameters and their statistical dispersion. The calibrated models obtained from laboratory datasets were subsequently applied to auscultate the evolution of the crack depth after microwaves exposure in the research article entitled “Top-down cracking self-healing of asphalt pavements with steel filler from industrial waste applying microwaves” (Franesqui et al., 2017 [1].

Ultrasound data for laboratory calibration of an analytical model to calculate crack depth on asphalt pavements.

Science.gov (United States)

Franesqui, Miguel A; Yepes, Jorge; García-González, Cándida

2017-08-01

This article outlines the ultrasound data employed to calibrate in the laboratory an analytical model that permits the calculation of the depth of partial-depth surface-initiated cracks on bituminous pavements using this non-destructive technique. This initial calibration is required so that the model provides sufficient precision during practical application. The ultrasonic pulse transit times were measured on beam samples of different asphalt mixtures (semi-dense asphalt concrete AC-S; asphalt concrete for very thin layers BBTM; and porous asphalt PA). The cracks on the laboratory samples were simulated by means of notches of variable depths. With the data of ultrasound transmission time ratios, curve-fittings were carried out on the analytical model, thus determining the regression parameters and their statistical dispersion. The calibrated models obtained from laboratory datasets were subsequently applied to auscultate the evolution of the crack depth after microwaves exposure in the research article entitled "Top-down cracking self-healing of asphalt pavements with steel filler from industrial waste applying microwaves" (Franesqui et al., 2017) [1].

Use of two-part regression calibration model to correct for measurement error in episodically consumed foods in a single-replicate study design: EPIC case study.

Science.gov (United States)

Agogo, George O; van der Voet, Hilko; van't Veer, Pieter; Ferrari, Pietro; Leenders, Max; Muller, David C; Sánchez-Cantalejo, Emilio; Bamia, Christina; Braaten, Tonje; Knüppel, Sven; Johansson, Ingegerd; van Eeuwijk, Fred A; Boshuizen, Hendriek

2014-01-01

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Calibration of the century, apsim and ndicea models of decomposition and n mineralization of plant residues in the humid tropics

Directory of Open Access Journals (Sweden)

Alexandre Ferreira do Nascimento

2011-06-01

Full Text Available The aim of this study was to calibrate the CENTURY, APSIM and NDICEA simulation models for estimating decomposition and N mineralization rates of plant organic materials (Arachis pintoi, Calopogonium mucunoides, Stizolobium aterrimum, Stylosanthes guyanensis for 360 days in the Atlantic rainforest bioma of Brazil. The models´ default settings overestimated the decomposition and N-mineralization of plant residues, underlining the fact that the models must be calibrated for use under tropical conditions. For example, the APSIM model simulated the decomposition of the Stizolobium aterrimum and Calopogonium mucunoides residues with an error rate of 37.62 and 48.23 %, respectively, by comparison with the observed data, and was the least accurate model in the absence of calibration. At the default settings, the NDICEA model produced an error rate of 10.46 and 14.46 % and the CENTURY model, 21.42 and 31.84 %, respectively, for Stizolobium aterrimum and Calopogonium mucunoides residue decomposition. After calibration, the models showed a high level of accuracy in estimating decomposition and N- mineralization, with an error rate of less than 20 %. The calibrated NDICEA model showed the highest level of accuracy, followed by the APSIM and CENTURY. All models performed poorly in the first few months of decomposition and N-mineralization, indicating the need of an additional parameter for initial microorganism growth on the residues that would take the effect of leaching due to rainfall into account.

Receiver Operating Characteristic Curve-Based Prediction Model for Periodontal Disease Updated With the Calibrated Community Periodontal Index.

Science.gov (United States)

Su, Chiu-Wen; Yen, Amy Ming-Fang; Lai, Hongmin; Chen, Hsiu-Hsi; Chen, Sam Li-Sheng

2017-12-01

The accuracy of a prediction model for periodontal disease using the community periodontal index (CPI) has been undertaken by using an area under a receiver operating characteristics (AUROC) curve. How the uncalibrated CPI, as measured by general dentists trained by periodontists in a large epidemiologic study, and affects the performance in a prediction model, has not been researched yet. A two-stage design was conducted by first proposing a validation study to calibrate CPI between a senior periodontal specialist and trained general dentists who measured CPIs in the main study of a nationwide survey. A Bayesian hierarchical logistic regression model was applied to estimate the non-updated and updated clinical weights used for building up risk scores. How the calibrated CPI affected performance of the updated prediction model was quantified by comparing AUROC curves between the original and updated models. Estimates regarding calibration of CPI obtained from the validation study were 66% and 85% for sensitivity and specificity, respectively. After updating, clinical weights of each predictor were inflated, and the risk score for the highest risk category was elevated from 434 to 630. Such an update improved the AUROC performance of the two corresponding prediction models from 62.6% (95% confidence interval [CI]: 61.7% to 63.6%) for the non-updated model to 68.9% (95% CI: 68.0% to 69.6%) for the updated one, reaching a statistically significant difference (P prediction model was demonstrated for periodontal disease as measured by the calibrated CPI derived from a large epidemiologic survey.

Compact radiometric microwave calibrator

International Nuclear Information System (INIS)

Fixsen, D. J.; Wollack, E. J.; Kogut, A.; Limon, M.; Mirel, P.; Singal, J.; Fixsen, S. M.

2006-01-01

The calibration methods for the ARCADE II instrument are described and the accuracy estimated. The Steelcast coated aluminum cones which comprise the calibrator have a low reflection while maintaining 94% of the absorber volume within 5 mK of the base temperature (modeled). The calibrator demonstrates an absorber with the active part less than one wavelength thick and only marginally larger than the mouth of the largest horn and yet black (less than -40 dB or 0.01% reflection) over five octaves in frequency

Automatic component calibration and error diagnostics for model-based accelerator control. Phase I final report

International Nuclear Information System (INIS)

Carl Stern; Martin Lee

1999-01-01

Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models

Automatic component calibration and error diagnostics for model-based accelerator control. Phase I final report

CERN Document Server

Carl-Stern

1999-01-01

Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models.

Review of Calibration Methods for Scheimpflug Camera

Directory of Open Access Journals (Sweden)

Cong Sun

2018-01-01

Full Text Available The Scheimpflug camera offers a wide range of applications in the field of typical close-range photogrammetry, particle image velocity, and digital image correlation due to the fact that the depth-of-view of Scheimpflug camera can be greatly extended according to the Scheimpflug condition. Yet, the conventional calibration methods are not applicable in this case because the assumptions used by classical calibration methodologies are not valid anymore for cameras undergoing Scheimpflug condition. Therefore, various methods have been investigated to solve the problem over the last few years. However, no comprehensive review exists that provides an insight into recent calibration methods of Scheimpflug cameras. This paper presents a survey of recent calibration methods of Scheimpflug cameras with perspective lens, including the general nonparametric imaging model, and analyzes in detail the advantages and drawbacks of the mainstream calibration models with respect to each other. Real data experiments including calibrations, reconstructions, and measurements are performed to assess the performance of the models. The results reveal that the accuracies of the RMM, PLVM, PCIM, and GNIM are basically equal, while the accuracy of GNIM is slightly lower compared with the other three parametric models. Moreover, the experimental results reveal that the parameters of the tangential distortion are likely coupled with the tilt angle of the sensor in Scheimpflug calibration models. The work of this paper lays the foundation of further research of Scheimpflug cameras.

Feasibility of the use of optimisation techniques to calibrate the models used in a post-closure radiological assessment

International Nuclear Information System (INIS)

Laundy, R.S.

1991-01-01

This report addresses the feasibility of the use of optimisation techniques to calibrate the models developed for the impact assessment of a radioactive waste repository. The maximum likelihood method for improving parameter estimates is considered in detail, and non-linear optimisation techniques for finding solutions are reviewed. Applications are described for the calibration of groundwater flow, radionuclide transport and biosphere models. (author)

Evaluation of Hydrologic Simulations Developed Using Multi-Model Synthesis and Remotely-Sensed Data within a Portfolio of Calibration Strategies

Science.gov (United States)

Lafontaine, J.; Hay, L.; Markstrom, S. L.

2016-12-01

The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. Hydrologic models for 1,576 gaged watersheds across the CONUS were developed to test the feasibility of improving streamflow simulations linking physically-based hydrologic models with remotely-sensed data products (i.e. snow water equivalent). Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison across multiple calibration strategy tests. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve hydrologic simulations for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of modeled and measured information for hydrologic model development and calibration. In addition, these calibration strategies have been developed to be flexible so that new data products can be assimilated. This analysis provides a foundation to understand how well models work when sufficient streamflow data are not available and could be used to further inform hydrologic model parameter development for ungaged areas.

Recent Improvements to the Calibration Models for RXTE/PCA

Science.gov (United States)

Jahoda, K.

2008-01-01

We are updating the calibration of the PCA to correct for slow variations, primarily in energy to channel relationship. We have also improved the physical model in the vicinity of the Xe K-edge, which should increase the reliability of continuum fits above 20 keV. The improvements to the matrix are especially important to simultaneous observations, where the PCA is often used to constrain the continuum while other higher resolution spectrometers are used to study the shape of lines and edges associated with Iron.

FAST Model Calibration and Validation of the OC5- DeepCwind Floating Offshore Wind System Against Wave Tank Test Data: Preprint

Energy Technology Data Exchange (ETDEWEB)

Wendt, Fabian F [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Robertson, Amy N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jonkman, Jason [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-09

During the course of the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, which focused on the validation of numerical methods through comparison against tank test data, the authors created a numerical FAST model of the 1:50-scale DeepCwind semisubmersible system that was tested at the Maritime Research Institute Netherlands ocean basin in 2013. This paper discusses several model calibration studies that were conducted to identify model adjustments that improve the agreement between the numerical simulations and the experimental test data. These calibration studies cover wind-field-specific parameters (coherence, turbulence), hydrodynamic and aerodynamic modeling approaches, as well as rotor model (blade-pitch and blade-mass imbalances) and tower model (structural tower damping coefficient) adjustments. These calibration studies were conducted based on relatively simple calibration load cases (wave only/wind only). The agreement between the final FAST model and experimental measurements is then assessed based on more-complex combined wind and wave validation cases.

Inverse modeling as a step in the calibration of the LBL-USGS site-scale model of Yucca Mountain

International Nuclear Information System (INIS)

Finsterle, S.; Bodvarsson, G.S.; Chen, G.

1995-05-01

Calibration of the LBL-USGS site-scale model of Yucca Mountain is initiated. Inverse modeling techniques are used to match the results of simplified submodels to the observed pressure, saturation, and temperature data. Hydrologic and thermal parameters are determined and compared to the values obtained from laboratory measurements and conventional field test analysis

Development of a calibration protocol and identification of the most sensitive parameters for the particulate biofilm models used in biological wastewater treatment.

Science.gov (United States)

Eldyasti, Ahmed; Nakhla, George; Zhu, Jesse

2012-05-01

Biofilm models are valuable tools for process engineers to simulate biological wastewater treatment. In order to enhance the use of biofilm models implemented in contemporary simulation software, model calibration is both necessary and helpful. The aim of this work was to develop a calibration protocol of the particulate biofilm model with a help of the sensitivity analysis of the most important parameters in the biofilm model implemented in BioWin® and verify the predictability of the calibration protocol. A case study of a circulating fluidized bed bioreactor (CFBBR) system used for biological nutrient removal (BNR) with a fluidized bed respirometric study of the biofilm stoichiometry and kinetics was used to verify and validate the proposed calibration protocol. Applying the five stages of the biofilm calibration procedures enhanced the applicability of BioWin®, which was capable of predicting most of the performance parameters with an average percentage error (APE) of 0-20%. Copyright © 2012 Elsevier Ltd. All rights reserved.

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

Science.gov (United States)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

Calibrating a surface mass-balance model for Austfonna ice cap, Svalbard

Science.gov (United States)

Schuler, Thomas Vikhamar; Loe, Even; Taurisano, Andrea; Eiken, Trond; Hagen, Jon Ove; Kohler, Jack

2007-10-01

Austfonna (8120 km2) is by far the largest ice mass in the Svalbard archipelago. There is considerable uncertainty about its current state of balance and its possible response to climate change. Over the 2004/05 period, we collected continuous meteorological data series from the ice cap, performed mass-balance measurements using a network of stakes distributed across the ice cap and mapped the distribution of snow accumulation using ground-penetrating radar along several profile lines. These data are used to drive and test a model of the surface mass balance. The spatial accumulation pattern was derived from the snow depth profiles using regression techniques, and ablation was calculated using a temperature-index approach. Model parameters were calibrated using the available field data. Parameter calibration was complicated by the fact that different parameter combinations yield equally acceptable matches to the stake data while the resulting calculated net mass balance differs considerably. Testing model results against multiple criteria is an efficient method to cope with non-uniqueness. In doing so, a range of different data and observations was compared to several different aspects of the model results. We find a systematic underestimation of net balance for parameter combinations that predict observed ice ablation, which suggests that refreezing processes play an important role. To represent these effects in the model, a simple PMAX approach was included in its formulation. Used as a diagnostic tool, the model suggests that the surface mass balance for the period 29 April 2004 to 23 April 2005 was negative (-318 mm w.e.).

A system-theory-based model for monthly river runoff forecasting: model calibration and optimization

Directory of Open Access Journals (Sweden)

Wu Jianhua

2014-03-01

Full Text Available River runoff is not only a crucial part of the global water cycle, but it is also an important source for hydropower and an essential element of water balance. This study presents a system-theory-based model for river runoff forecasting taking the Hailiutu River as a case study. The forecasting model, designed for the Hailiutu watershed, was calibrated and verified by long-term precipitation observation data and groundwater exploitation data from the study area. Additionally, frequency analysis, taken as an optimization technique, was applied to improve prediction accuracy. Following model optimization, the overall relative prediction errors are below 10%. The system-theory-based prediction model is applicable to river runoff forecasting, and following optimization by frequency analysis, the prediction error is acceptable.

Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon

Science.gov (United States)

2016-07-01

was used to drive the transport and water quality kinetics for the simulation of 2007–2009. The sand berm, which controlled the opening/closure of...TECHNICAL REPORT 3015 July 2016 Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei...Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei-Fang Wang Chuck Katz Ripan Barua SSC Pacific James

Usability of Calibrating Monitor for Soft Proof According to CIE CAM02 Colour Appearance Model

Directory of Open Access Journals (Sweden)

Dragoljub Novakovic

2010-06-01

Full Text Available Colour appearance models describe viewing conditions and enable simulating appearance of colours under different illuminants and illumination levels according to human perception. Since it is possible to predict how colour would look like when different illuminants are used, colour appearance models are incorporated in some monitor profiling software. Owing to these software, tone reproduction curve can be defined by taking into consideration viewing condition in which display is observed. In this work assessment of CIE CAM02 colour appearance model usage at calibrating LCD monitor for soft proof was tested in order to determine which tone reproduction curve enables better reproduction of colour. Luminance level was kept constant, whereas tone reproduction curves determined by gamma values and by parameters of CIE CAM02 model were varied. Testing was conducted in case where physical print reference is observed under illuminant which has colour temperature according to iso standard for soft-proofing (D50 and also for illuminants D65.  Based on the results of calibrations assessment, subjective and objective assessment of created profiles, as well as on the perceptual test carried out on human observers, differences in image display were defined and conclusions of the adequacy of CAM02 usage at monitor calibration for each of the viewing conditions reached.

Features calibration of the dynamic force transducers

Science.gov (United States)

Sc., M. Yu Prilepko D.; Lysenko, V. G.

2018-04-01

The article discusses calibration methods of dynamic forces measuring instruments. The relevance of work is dictated by need to valid definition of the dynamic forces transducers metrological characteristics taking into account their intended application. The aim of this work is choice justification of calibration method, which provides the definition dynamic forces transducers metrological characteristics under simulation operating conditions for determining suitability for using in accordance with its purpose. The following tasks are solved: the mathematical model and the main measurements equation of calibration dynamic forces transducers by load weight, the main budget uncertainty components of calibration are defined. The new method of dynamic forces transducers calibration with use the reference converter “force-deformation” based on the calibrated elastic element and measurement of his deformation by a laser interferometer is offered. The mathematical model and the main measurements equation of the offered method is constructed. It is shown that use of calibration method based on measurements by the laser interferometer of calibrated elastic element deformations allows to exclude or to considerably reduce the uncertainty budget components inherent to method of load weight.

Performance and Model Calibration of R-D-N Processes in Pilot Plant

DEFF Research Database (Denmark)

de la Sota, A.; Larrea, L.; Novak, L.

1994-01-01

This paper deals with the first part of an experimental programme in a pilot plant configured for advanced biological nutrient removal processes treating domestic wastewater of Bilbao. The IAWPRC Model No.1 was calibrated in order to optimize the design of the full-scale plant. In this first phas...

hydroPSO: A Versatile Particle Swarm Optimisation R Package for Calibration of Environmental Models

Science.gov (United States)

Zambrano-Bigiarini, M.; Rojas, R.

2012-04-01

Particle Swarm Optimisation (PSO) is a recent and powerful population-based stochastic optimisation technique inspired by social behaviour of bird flocking, which shares similarities with other evolutionary techniques such as Genetic Algorithms (GA). In PSO, however, each individual of the population, known as particle in PSO terminology, adjusts its flying trajectory on the multi-dimensional search-space according to its own experience (best-known personal position) and the one of its neighbours in the swarm (best-known local position). PSO has recently received a surge of attention given its flexibility, ease of programming, low memory and CPU requirements, and efficiency. Despite these advantages, PSO may still get trapped into sub-optimal solutions, suffer from swarm explosion or premature convergence. Thus, the development of enhancements to the "canonical" PSO is an active area of research. To date, several modifications to the canonical PSO have been proposed in the literature, resulting into a large and dispersed collection of codes and algorithms which might well be used for similar if not identical purposes. In this work we present hydroPSO, a platform-independent R package implementing several enhancements to the canonical PSO that we consider of utmost importance to bring this technique to the attention of a broader community of scientists and practitioners. hydroPSO is model-independent, allowing the user to interface any model code with the calibration engine without having to invest considerable effort in customizing PSO to a new calibration problem. Some of the controlling options to fine-tune hydroPSO are: four alternative topologies, several types of inertia weight, time-variant acceleration coefficients, time-variant maximum velocity, regrouping of particles when premature convergence is detected, different types of boundary conditions and many others. Additionally, hydroPSO implements recent PSO variants such as: Improved Particle Swarm

Optimal Operational Monetary Policy Rules in an Endogenous Growth Model: a calibrated analysis

OpenAIRE

Arato, Hiroki

2009-01-01

This paper constructs an endogenous growth New Keynesian model and considers growth and welfare effect of Taylor-type (operational) monetary policy rules. The Ramsey equilibrium and optimal operational monetary policy rule is also computed. In the calibrated model, the Ramseyoptimal volatility of inflation rate is smaller than that in standard exogenous growth New Keynesian model with physical capital accumulation. Optimal operational monetary policy rule makes nominal interest rate respond s...

Fitting and Calibrating a Multilevel Mixed-Effects Stem Taper Model for Maritime Pine in NW Spain

Science.gov (United States)

Arias-Rodil, Manuel; Castedo-Dorado, Fernando; Cámara-Obregón, Asunción; Diéguez-Aranda, Ulises

2015-01-01

Stem taper data are usually hierarchical (several measurements per tree, and several trees per plot), making application of a multilevel mixed-effects modelling approach essential. However, correlation between trees in the same plot/stand has often been ignored in previous studies. Fitting and calibration of a variable-exponent stem taper function were conducted using data from 420 trees felled in even-aged maritime pine (Pinus pinaster Ait.) stands in NW Spain. In the fitting step, the tree level explained much more variability than the plot level, and therefore calibration at plot level was omitted. Several stem heights were evaluated for measurement of the additional diameter needed for calibration at tree level. Calibration with an additional diameter measured at between 40 and 60% of total tree height showed the greatest improvement in volume and diameter predictions. If additional diameter measurement is not available, the fixed-effects model fitted by the ordinary least squares technique should be used. Finally, we also evaluated how the expansion of parameters with random effects affects the stem taper prediction, as we consider this a key question when applying the mixed-effects modelling approach to taper equations. The results showed that correlation between random effects should be taken into account when assessing the influence of random effects in stem taper prediction. PMID:26630156

Calibration of hydrodynamic model MIKE 11 for the sub-basin of the Piauitinga river, Sergipe, Brazil

Directory of Open Access Journals (Sweden)

Marcos Vinicius Folegatti

2010-12-01

Full Text Available In Piauitinga river sub-basin the environment has been suffering from negative actions by humans such as deforestation around springs, inadequate use of the uptaken water, inappropriate use in domestic activities, siltation and sand exploitation, and contamination by domestic, industrial and agricultural residuals. The present study presents the one-dimensional hydrodynamic MIKE 11 model calibration that simulates the water flow in estuary, rivers, irrigation systems, channels and other water bodies. The aim of this work was to fit the MIKE 11 model to available discharge data for this sub-basin. Data from the period of 1994 to 1995 were used for calibration and data from 1996 to 2006 for validation, except the 1997 year, from which data were not available. Manning’s roughness coefficient was the main parameter used for the Piauitinga river sub-basin discharge calibration and other parameters were heat balance, water stratification and groundwater leakage. Results showed that the model had an excellent performance for the Piauitinga basin and had an efficiency coefficient of 0.9 for both periods. This demonstrates that this model can be used to estimate the water quantity in Piauitinga river sub-basin.

U.S. Department of Energy Office of Legacy Management Calibration Facilities - 12103

Energy Technology Data Exchange (ETDEWEB)

Barr, Deborah [U.S. Department of Energy Office of Legacy Management, Grand Junction, Colorado (United States); Traub, David; Widdop, Michael [S.M. Stoller Corporation, Grand Junction, Colorado (United States)

2012-07-01

This paper describes radiometric calibration facilities located in Grand Junction, Colorado, and at three secondary calibration sites. These facilities are available to the public for the calibration of radiometric field instrumentation for in-situ measurements of radium (uranium), thorium, and potassium. Both borehole and hand-held instruments may be calibrated at the facilities. Aircraft or vehicle mounted systems for large area surveys may be calibrated at the Grand Junction Regional Airport facility. These calibration models are recognized internationally as stable, well-characterized radiation sources for calibration. Calibration models built in other countries are referenced to the DOE models, which are also widely used as a standard for calibration within the U.S. Calibration models are used to calibrate radiation detectors used in uranium exploration, remediation, and homeland security. (authors)

Calibration of a semi-distributed hydrological model using discharge and remote sensing data

NARCIS (Netherlands)

Muthuwatta, L.P.; Muthuwatta, Lal P.; Booij, Martijn J.; Rientjes, T.H.M.; Rientjes, Tom H.M.; Bos, M.G.; Gieske, A.S.M.; Ahmad, Mobin-Ud-Din; Yilmaz, Koray; Yucel, Ismail; Gupta, Hoshin V.; Wagener, Thorsten; Yang, Dawen; Savenije, Hubert; Neale, Christopher; Kunstmann, Harald; Pomeroy, John

2009-01-01

The objective of this study is to present an approach to calibrate a semi-distributed hydrological model using observed streamflow data and actual evapotranspiration time series estimates based on remote sensing data. First, daily actual evapotranspiration is estimated using available MODIS

Calibrating a forest landscape model to simulate frequent fire in Mediterranean-type shrublands

Science.gov (United States)

Syphard, A.D.; Yang, J.; Franklin, J.; He, H.S.; Keeley, J.E.

2007-01-01

In Mediterranean-type ecosystems (MTEs), fire disturbance influences the distribution of most plant communities, and altered fire regimes may be more important than climate factors in shaping future MTE vegetation dynamics. Models that simulate the high-frequency fire and post-fire response strategies characteristic of these regions will be important tools for evaluating potential landscape change scenarios. However, few existing models have been designed to simulate these properties over long time frames and broad spatial scales. We refined a landscape disturbance and succession (LANDIS) model to operate on an annual time step and to simulate altered fire regimes in a southern California Mediterranean landscape. After developing a comprehensive set of spatial and non-spatial variables and parameters, we calibrated the model to simulate very high fire frequencies and evaluated the simulations under several parameter scenarios representing hypotheses about system dynamics. The goal was to ensure that observed model behavior would simulate the specified fire regime parameters, and that the predictions were reasonable based on current understanding of community dynamics in the region. After calibration, the two dominant plant functional types responded realistically to different fire regime scenarios. Therefore, this model offers a new alternative for simulating altered fire regimes in MTE landscapes. ?? 2007 Elsevier Ltd. All rights reserved.

Fertilizer Induced Nitrate Pollution in RCW: Calibration of the DNDC Model

Science.gov (United States)

El Hailouch, E.; Hornberger, G.; Crane, J. W.

2012-12-01

Fertilizer is widely used among urban and suburban households due to the socially driven attention of homeowners to lawn appearance. With high nitrogen content, fertilizer considerably impacts the environment through the emission of the highly potent greenhouse gas nitrous oxide and the leaching of nitrate. Nitrate leaching is significantly important because fertilizer sourced nitrate that is partially leached into soil causes groundwater pollution. In an effort to model the effect of fertilizer application on the environment, the geochemical DeNitrification-DeComposition model (DNDC) was previously developed to quantitatively measure the effects of fertilizer use. The purpose of this study is to use this model more effectively on a large scale through a measurement based calibration. For this reason, leaching was measured and studied on 12 sites in the Richland Creek Watershed (RCW). Information about the fertilization and irrigation regimes of these sites was collected, along with lysimeter readings that gave nitrate fluxes in the soil. A study of the amount and variation in nitrate leaching with respect to the varying geographical locations, time of the year, and fertilization and irrigation regimes has lead to a better understanding of the driving forces behind nitrate leaching. Quantifying the influence of each of these parameters allows for a more accurate calibration of the model thus permitting use that extends beyond the RCW. Measurement of nitrate leaching on a statewide or nationwide level in turn will help guide efforts in the reduction of groundwater pollution caused by fertilizer.

The scintillating optical fiber isotope experiment: Bevalac calibrations of test models

International Nuclear Information System (INIS)

Connell, J.J.; Binns, W.R.; Dowkontt, P.F.; Epstein, J.W.; Israel, M.H.; Klarmann, J.; Washington Univ., St. Louis, MO; Webber, W.R.; Kish, J.C.

1990-01-01

The Scintillating Optical Fiber Isotope Experiment (SOFIE) is a Cherenkov dE/dx-range experiment being developed to study the isotopic composition of cosmic rays in the iron region with sufficient resolution to resolve isotopes separated by one mass unit at iron. This instrument images stopping particles with a block of scintillating optical fibers coupled to an image intensified video camera. From the digitized video data the trajectory and range of particles stopping in the fiber bundle can be determined; this information, together with a Cherenkov measurement, is used to determine mass. To facilitate this determination, a new Cherenkov response equation was derived for heavy ions at energies near threshold in thick Cherenkov radiators. Test models of SOFIE were calibrated at the Lawrence Berkeley Laboratory's Bevalac heavy ion accelerator in 1985 and 1986 using beams of iron nuclei with energies of 465 to 515 MeV/nucleon. This paper presents the results of these calibrations and discusses the design of the SOFIE Bevalac test models in the context of the scientific objectives of the eventual balloon experiment. The test models show a mass resolution of σ A ≅0.30 amu and a range resolution of σ R ≅250 μm. These results are sufficient for a successful cosmic ray isotope experiment, thus demonstrating the feasibility of the detector system. The SOFIE test models represent the first successful application in the field of cosmic ray astrophysics of the emerging technology of scintillating optical fibers. (orig.)

Mathematical model and computer programme for theoretical calculation of calibration curves of neutron soil moisture probes with highly effective counters

International Nuclear Information System (INIS)

Kolev, N.A.

1981-07-01

A mathematical model based on the three group theory for theoretical calculation by means of computer of the calibration curves of neutron soil moisture probes with highly effective counters, is described. Methods for experimental correction of the mathematical model are discussed and proposed. The computer programme described allows the calibration of neutron probes with high or low effective counters, and central or end geometry, with or without linearizing of the calibration curve. The use of two calculation variants and printing of output data gives the possibility not only for calibration, but also for other researches. The separate data inputs for soil and probe temperature allow the temperature influence analysis. The computer programme and calculation examples are given. (author)

Experimental calibration of the mathematical model of Air Torque Position dampers with non-cascading blades

Directory of Open Access Journals (Sweden)

Bikić Siniša M.

2016-01-01

Full Text Available This paper is focused on the mathematical model of the Air Torque Position dampers. The mathematical model establishes a link between the velocity of air in front of the damper, position of the damper blade and the moment acting on the blade caused by the air flow. This research aims to experimentally verify the mathematical model for the damper type with non-cascading blades. Four different types of dampers with non-cascading blades were considered: single blade dampers, dampers with two cross-blades, dampers with two parallel blades and dampers with two blades of which one is a fixed blade in the horizontal position. The case of a damper with a straight pipeline positioned in front of and behind the damper was taken in consideration. Calibration and verification of the mathematical model was conducted experimentally. The experiment was conducted on the laboratory facility for testing dampers used for regulation of the air flow rate in heating, ventilation and air conditioning systems. The design and setup of the laboratory facility, as well as construction, adjustment and calibration of the laboratory damper are presented in this paper. The mathematical model was calibrated by using one set of data, while the verification of the mathematical model was conducted by using the second set of data. The mathematical model was successfully validated and it can be used for accurate measurement of the air velocity on dampers with non-cascading blades under different operating conditions. [Projekat Ministarstva nauke Republike Srbije, br. TR31058

Calculations to support JET neutron yield calibration: Modelling of neutron emission from a compact DT neutron generator

Science.gov (United States)

Čufar, Aljaž; Batistoni, Paola; Conroy, Sean; Ghani, Zamir; Lengar, Igor; Milocco, Alberto; Packer, Lee; Pillon, Mario; Popovichev, Sergey; Snoj, Luka; JET Contributors

2017-03-01

At the Joint European Torus (JET) the ex-vessel fission chambers and in-vessel activation detectors are used as the neutron production rate and neutron yield monitors respectively. In order to ensure that these detectors produce accurate measurements they need to be experimentally calibrated. A new calibration of neutron detectors to 14 MeV neutrons, resulting from deuterium-tritium (DT) plasmas, is planned at JET using a compact accelerator based neutron generator (NG) in which a D/T beam impinges on a solid target containing T/D, producing neutrons by DT fusion reactions. This paper presents the analysis that was performed to model the neutron source characteristics in terms of energy spectrum, angle-energy distribution and the effect of the neutron generator geometry. Different codes capable of simulating the accelerator based DT neutron sources are compared and sensitivities to uncertainties in the generator's internal structure analysed. The analysis was performed to support preparation to the experimental measurements performed to characterize the NG as a calibration source. Further extensive neutronics analyses, performed with this model of the NG, will be needed to support the neutron calibration experiments and take into account various differences between the calibration experiment and experiments using the plasma as a source of neutrons.

Calculations to support JET neutron yield calibration: Modelling of neutron emission from a compact DT neutron generator

Energy Technology Data Exchange (ETDEWEB)

Čufar, Aljaž, E-mail: aljaz.cufar@ijs.si [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Batistoni, Paola [ENEA, Department of Fusion and Nuclear Safety Technology, I-00044 Frascati, Rome (Italy); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Conroy, Sean [Uppsala University, Department of Physics and Astronomy, PO Box 516, SE-75120 Uppsala (Sweden); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Ghani, Zamir [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Lengar, Igor [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Milocco, Alberto; Packer, Lee [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Pillon, Mario [ENEA, Department of Fusion and Nuclear Safety Technology, I-00044 Frascati, Rome (Italy); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Popovichev, Sergey [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Snoj, Luka [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom)

2017-03-01

At the Joint European Torus (JET) the ex-vessel fission chambers and in-vessel activation detectors are used as the neutron production rate and neutron yield monitors respectively. In order to ensure that these detectors produce accurate measurements they need to be experimentally calibrated. A new calibration of neutron detectors to 14 MeV neutrons, resulting from deuterium–tritium (DT) plasmas, is planned at JET using a compact accelerator based neutron generator (NG) in which a D/T beam impinges on a solid target containing T/D, producing neutrons by DT fusion reactions. This paper presents the analysis that was performed to model the neutron source characteristics in terms of energy spectrum, angle–energy distribution and the effect of the neutron generator geometry. Different codes capable of simulating the accelerator based DT neutron sources are compared and sensitivities to uncertainties in the generator's internal structure analysed. The analysis was performed to support preparation to the experimental measurements performed to characterize the NG as a calibration source. Further extensive neutronics analyses, performed with this model of the NG, will be needed to support the neutron calibration experiments and take into account various differences between the calibration experiment and experiments using the plasma as a source of neutrons.

Biotrickling filter modeling for styrene abatement. Part 1: Model development, calibration and validation on an industrial scale.

Science.gov (United States)

San-Valero, Pau; Dorado, Antonio D; Martínez-Soria, Vicente; Gabaldón, Carmen

2018-01-01

A three-phase dynamic mathematical model based on mass balances describing the main processes in biotrickling filtration: convection, mass transfer, diffusion, and biodegradation was calibrated and validated for the simulation of an industrial styrene-degrading biotrickling filter. The model considered the key features of the industrial operation of biotrickling filters: variable conditions of loading and intermittent irrigation. These features were included in the model switching from the mathematical description of periods with and without irrigation. Model equations were based on the mass balances describing the main processes in biotrickling filtration: convection, mass transfer, diffusion, and biodegradation. The model was calibrated with steady-state data from a laboratory biotrickling filter treating inlet loads at 13-74 g C m -3 h -1 and at empty bed residence time of 30-15 s. The model predicted the dynamic emission in the outlet of the biotrickling filter, simulating the small peaks of concentration occurring during irrigation. The validation of the model was performed using data from a pilot on-site biotrickling filter treating styrene installed in a fiber-reinforced facility. The model predicted the performance of the biotrickling filter working under high-oscillating emissions at an inlet load in a range of 5-23 g C m -3 h -1 and at an empty bed residence time of 31 s for more than 50 days, with a goodness of fit of 0.84. Copyright © 2017 Elsevier Ltd. All rights reserved.

Calibration of an estuarine sediment transport model to sediment fluxes as an intermediate step for simulation of geomorphic evolution

Science.gov (United States)

Ganju, N.K.; Schoellhamer, D.H.

2009-01-01

Modeling geomorphic evolution in estuaries is necessary to model the fate of legacy contaminants in the bed sediment and the effect of climate change, watershed alterations, sea level rise, construction projects, and restoration efforts. Coupled hydrodynamic and sediment transport models used for this purpose typically are calibrated to water level, currents, and/or suspended-sediment concentrations. However, small errors in these tidal-timescale models can accumulate to cause major errors in geomorphic evolution, which may not be obvious. Here we present an intermediate step towards simulating decadal-timescale geomorphic change: calibration to estimated sediment fluxes (mass/time) at two cross-sections within an estuary. Accurate representation of sediment fluxes gives confidence in representation of sediment supply to and from the estuary during those periods. Several years of sediment flux data are available for the landward and seaward boundaries of Suisun Bay, California, the landward-most embayment of San Francisco Bay. Sediment flux observations suggest that episodic freshwater flows export sediment from Suisun Bay, while gravitational circulation during the dry season imports sediment from seaward sources. The Regional Oceanic Modeling System (ROMS), a three-dimensional coupled hydrodynamic/sediment transport model, was adapted for Suisun Bay, for the purposes of hindcasting 19th and 20th century bathymetric change, and simulating geomorphic response to sea level rise and climatic variability in the 21st century. The sediment transport parameters were calibrated using the sediment flux data from 1997 (a relatively wet year) and 2004 (a relatively dry year). The remaining years of data (1998, 2002, 2003) were used for validation. The model represents the inter-annual and annual sediment flux variability, while net sediment import/export is accurately modeled for three of the five years. The use of sediment flux data for calibrating an estuarine geomorphic

Semi-Empirical Calibration of the Integral Equation Model for Co-Polarized L-Band Backscattering

Directory of Open Access Journals (Sweden)

Nicolas Baghdadi

2015-10-01

Full Text Available The objective of this paper is to extend the semi-empirical calibration of the backscattering Integral Equation Model (IEM initially proposed for Synthetic Aperture Radar (SAR data at C- and X-bands to SAR data at L-band. A large dataset of radar signal and in situ measurements (soil moisture and surface roughness over bare soil surfaces were used. This dataset was collected over numerous agricultural study sites in France, Luxembourg, Belgium, Germany and Italy using various SAR sensors (AIRSAR, SIR-C, JERS-1, PALSAR-1, ESAR. Results showed slightly better simulations with exponential autocorrelation function than with Gaussian function and with HH than with VV. Using the exponential autocorrelation function, the mean difference between experimental data and Integral Equation Model (IEM simulations is +0.4 dB in HH and −1.2 dB in VV with a Root Mean Square Error (RMSE about 3.5 dB. In order to improve the modeling results of the IEM for a better use in the inversion of SAR data, a semi-empirical calibration of the IEM was performed at L-band in replacing the correlation length derived from field experiments by a fitting parameter. Better agreement was observed between the backscattering coefficient provided by the SAR and that simulated by the calibrated version of the IEM (RMSE about 2.2 dB.

The Effect of Sample Size and Data Numbering on Precision of Calibration Model to predict Soil Properties

Directory of Open Access Journals (Sweden)

H Mohamadi Monavar

2017-10-01

Full Text Available Introduction Precision agriculture (PA is a technology that measures and manages within-field variability, such as physical and chemical properties of soil. The nondestructive and rapid VIS-NIR technology detected a significant correlation between reflectance spectra and the physical and chemical properties of soil. On the other hand, quantitatively predict of soil factors such as nitrogen, carbon, cation exchange capacity and the amount of clay in precision farming is very important. The emphasis of this paper is comparing different techniques of choosing calibration samples such as randomly selected method, chemical data and also based on PCA. Since increasing the number of samples is usually time-consuming and costly, then in this study, the best sampling way -in available methods- was predicted for calibration models. In addition, the effect of sample size on the accuracy of the calibration and validation models was analyzed. Materials and Methods Two hundred and ten soil samples were collected from cultivated farm located in Avarzaman in Hamedan province, Iran. The crop rotation was mostly potato and wheat. Samples were collected from a depth of 20 cm above ground and passed through a 2 mm sieve and air dried at room temperature. Chemical analysis was performed in the soil science laboratory, faculty of agriculture engineering, Bu-ali Sina University, Hamadan, Iran. Two Spectrometer (AvaSpec-ULS 2048- UV-VIS and (FT-NIR100N were used to measure the spectral bands which cover the UV-Vis and NIR region (220-2200 nm. Each soil sample was uniformly tiled in a petri dish and was scanned 20 times. Then the pre-processing methods of multivariate scatter correction (MSC and base line correction (BC were applied on the raw signals using Unscrambler software. The samples were divided into two groups: one group for calibration 105 and the second group was used for validation. Each time, 15 samples were selected randomly and tested the accuracy of

Importance of including small-scale tile drain discharge in the calibration of a coupled groundwater-surface water catchment model

DEFF Research Database (Denmark)

Hansen, Anne Lausten; Refsgaard, Jens Christian; Christensen, Britt Stenhøj Baun

2013-01-01

the catchment. In this study, a coupled groundwater-surface water model based on the MIKE SHE code was developed for the 4.7 km2 Lillebæk catchment in Denmark, where tile drain flow is a major contributor to the stream discharge. The catchment model was calibrated in several steps by incrementally including...... the observation data into the calibration to see the effect on model performance of including diverse data types, especially tile drain discharge. For the Lillebæk catchment, measurements of hydraulic head, daily stream discharge, and daily tile drain discharge from five small (1–4 ha) drainage areas exist....... The results showed that including tile drain data in the calibration of the catchment model improved its general performance for hydraulic heads and stream discharges. However, the model failed to correctly describe the local-scale dynamics of the tile drain discharges, and, furthermore, including the drain...

On the Free Vibration Modeling of Spindle Systems: A Calibrated Dynamic Stiffness Matrix

Directory of Open Access Journals (Sweden)

Omar Gaber

2014-01-01

Full Text Available The effect of bearings on the vibrational behavior of machine tool spindles is investigated. This is done through the development of a calibrated dynamic stiffness matrix (CDSM method, where the bearings flexibility is represented by massless linear spring elements with tuneable stiffness. A dedicated MATLAB code is written to develop and to assemble the element stiffness matrices for the system’s multiple components and to apply the boundary conditions. The developed method is applied to an illustrative example of spindle system. When the spindle bearings are modeled as simply supported boundary conditions, the DSM model results in a fundamental frequency much higher than the system’s nominal value. The simply supported boundary conditions are then replaced by linear spring elements, and the spring constants are adjusted such that the resulting calibrated CDSM model leads to the nominal fundamental frequency of the spindle system. The spindle frequency results are also validated against the experimental data. The proposed method can be effectively applied to predict the vibration characteristics of spindle systems supported by bearings.

(Pre-) calibration of a Reduced Complexity Model of the Antarctic Contribution to Sea-level Changes

Science.gov (United States)

Ruckert, K. L.; Guan, Y.; Shaffer, G.; Forest, C. E.; Keller, K.

2015-12-01

(Pre-) calibration of a Reduced Complexity Model of the Antarctic Contribution to Sea-level ChangesKelsey L. Ruckert1*, Yawen Guan2, Chris E. Forest1,3,7, Gary Shaffer 4,5,6, and Klaus Keller1,7,81 Department of Geosciences, The Pennsylvania State University, University Park, Pennsylvania, USA 2 Department of Statistics, The Pennsylvania State University, University Park, Pennsylvania, USA 3 Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania, USA 4 GAIA_Antarctica, University of Magallanes, Punta Arenas, Chile 5 Center for Advanced Studies in Arid Zones, La Serena, Chile 6 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 7 Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, Pennsylvania, USA 8 Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA * Corresponding author. E-mail klr324@psu.eduUnderstanding and projecting future sea-level changes poses nontrivial challenges. Sea-level changes are driven primarily by changes in the density of seawater as well as changes in the size of glaciers and ice sheets. Previous studies have demonstrated that a key source of uncertainties surrounding sea-level projections is the response of the Antarctic ice sheet to warming temperatures. Here we calibrate a previously published and relatively simple model of the Antarctic ice sheet over a hindcast period from the last interglacial period to the present. We apply and compare a range of (pre-) calibration methods, including a Bayesian approach that accounts for heteroskedasticity. We compare the model hindcasts and projections for different levels of model complexity and calibration methods. We compare the projections with the upper bounds from previous studies and find our projections have a narrower range in 2100. Furthermore we discuss the implications for the design of climate risk management strategies.

Calibration of the Nonlinear Accelerator Model at the Diamond Storage Ring

CERN Document Server

Bartolini, Riccardo; Rowland, James; Martin, Ian; Schmidt, Frank

2010-01-01

The correct implementation of the nonlinear ring model is crucial to achieve the top performance of a synchrotron light source. Several dynamics quantities can be used to compare the real machine with the model and eventually to correct the accelerator. Most of these methods are based on the analysis of turn-by-turn data of excited betatron oscillations. We present the experimental results of the campaign of measurements carried out at the Diamond. A combination of Frequency Map Analysis (FMA) and detuning with momentum measurements has allowed a precise calibration of the nonlinear model capable of reproducing the nonlinear beam dynamics in the storage ring

A Solvatochromic Model Calibrates Nitriles’ Vibrational Frequencies to Electrostatic Fields

Science.gov (United States)

Bagchi, Sayan; Fried, Stephen D.; Boxer, Steven G.

2012-01-01

Electrostatic interactions provide a primary connection between a protein’s three-dimensional structure and its function. Infrared (IR) probes are useful because vibrational frequencies of certain chemical groups, such as nitriles, are linearly sensitive to local electrostatic field, and can serve as a molecular electric field meter. IR spectroscopy has been used to study electrostatic changes or fluctuations in proteins, but measured peak frequencies have not been previously mapped to total electric fields, because of the absence of a field-frequency calibration and the complication of local chemical effects such as H-bonds. We report a solvatochromic model that provides a means to assess the H-bonding status of aromatic nitrile vibrational probes, and calibrates their vibrational frequencies to electrostatic field. The analysis involves correlations between the nitrile’s IR frequency and its 13C chemical shift, whose observation is facilitated by a robust method for introducing isotopes into aromatic nitriles. The method is tested on the model protein Ribonuclease S (RNase S) containing a labeled p-CN-Phe near the active site. Comparison of the measurements in RNase S against solvatochromic data gives an estimate of the average total electrostatic field at this location. The value determined agrees quantitatively with MD simulations, suggesting broader potential for the use of IR probes in the study of protein electrostatics. PMID:22694663

PLEIADES ABSOLUTE CALIBRATION : INFLIGHT CALIBRATION SITES AND METHODOLOGY

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S. Lachérade

2012-07-01

Full Text Available In-flight calibration of space sensors once in orbit is a decisive step to be able to fulfil the mission objectives. This article presents the methods of the in-flight absolute calibration processed during the commissioning phase. Four In-flight calibration methods are used: absolute calibration, cross-calibration with reference sensors such as PARASOL or MERIS, multi-temporal monitoring and inter-bands calibration. These algorithms are based on acquisitions over natural targets such as African deserts, Antarctic sites, La Crau (Automatic calibration station and Oceans (Calibration over molecular scattering or also new extra-terrestrial sites such as the Moon and selected stars. After an overview of the instrument and a description of the calibration sites, it is pointed out how each method is able to address one or several aspects of the calibration. We focus on how these methods complete each other in their operational use, and how they help building a coherent set of information that addresses all aspects of in-orbit calibration. Finally, we present the perspectives that the high level of agility of PLEIADES offers for the improvement of its calibration and a better characterization of the calibration sites.

α Centauri A as a potential stellar model calibrator: establishing the nature of its core

Science.gov (United States)

Nsamba, B.; Monteiro, M. J. P. F. G.; Campante, T. L.; Cunha, M. S.; Sousa, S. G.

2018-05-01

Understanding the physical process responsible for the transport of energy in the core of α Centauri A is of the utmost importance if this star is to be used in the calibration of stellar model physics. Adoption of different parallax measurements available in the literature results in differences in the interferometric radius constraints used in stellar modelling. Further, this is at the origin of the different dynamical mass measurements reported for this star. With the goal of reproducing the revised dynamical mass derived by Pourbaix & Boffin, we modelled the star using two stellar grids varying in the adopted nuclear reaction rates. Asteroseismic and spectroscopic observables were complemented with different interferometric radius constraints during the optimisation procedure. Our findings show that best-fit models reproducing the revised dynamical mass favour the existence of a convective core (≳ 70% of best-fit models), a result that is robust against changes to the model physics. If this mass is accurate, then α Centauri A may be used to calibrate stellar model parameters in the presence of a convective core.

Cross-calibration of interferometric SAR data

DEFF Research Database (Denmark)

Dall, Jørgen

2003-01-01

Generation of digital elevation models from interferometric synthetic aperture radar (SAR) data is a well established technique. Achieving a high geometric fidelity calls for a calibration accounting for inaccurate navigation data and system parameters as well as system imperfections. Fully...... automated calibration techniques are preferable, especially for operational mapping. The author presents one such technique, called cross-calibration. Though developed for single-pass interferometry, it may be applicable to multi-pass interferometry, too. Cross-calibration requires stability during mapping...... ground control point is often needed. The paper presents the principles and mathematics of the cross-calibration technique and illustrates its successful application to EMISAR data....

Dataset for: An efficient multi-stage algorithm for full calibration of the hemodynamic model from BOLD signal responses

KAUST Repository

Djellouli, Rabia

2017-01-01

We propose a computational strategy that falls into the category of prediction/correction iterative-type approaches, for calibrating the hemodynamic model introduced by Friston et al. (2000). The proposed method is employed to estimate consecutively the values of the biophysiological system parameters and the external stimulus characteristics of the model. Numerical results corresponding to both synthetic and real functional Magnetic Resonance Imaging (fMRI) measurements for a single stimulus as well as for multiple stimuli are reported to highlight the capability of this computational methodology to fully calibrate the considered hemodynamic model.

Calibration of complex models through Bayesian evidence synthesis: a demonstration and tutorial

Science.gov (United States)

Jackson, Christopher; Jit, Mark; Sharples, Linda; DeAngelis, Daniela

2016-01-01

Summary Decision-analytic models must often be informed using data which are only indirectly related to the main model parameters. The authors outline how to implement a Bayesian synthesis of diverse sources of evidence to calibrate the parameters of a complex model. A graphical model is built to represent how observed data are generated from statistical models with unknown parameters, and how those parameters are related to quantities of interest for decision-making. This forms the basis of an algorithm to estimate a posterior probability distribution, which represents the updated state of evidence for all unknowns given all data and prior beliefs. This process calibrates the quantities of interest against data, and at the same time, propagates all parameter uncertainties to the results used for decision-making. To illustrate these methods, the authors demonstrate how a previously-developed Markov model for the progression of human papillomavirus (HPV16) infection was rebuilt in a Bayesian framework. Transition probabilities between states of disease severity are inferred indirectly from cross-sectional observations of prevalence of HPV16 and HPV16-related disease by age, cervical cancer incidence, and other published information. Previously, a discrete collection of plausible scenarios was identified, but with no further indication of which of these are more plausible. Instead, the authors derive a Bayesian posterior distribution, in which scenarios are implicitly weighted according to how well they are supported by the data. In particular, we emphasise the appropriate choice of prior distributions and checking and comparison of fitted models. PMID:23886677

Approaches to highly parameterized inversion-A guide to using PEST for groundwater-model calibration

Science.gov (United States)

Doherty, John E.; Hunt, Randall J.

2010-01-01

Highly parameterized groundwater models can create calibration difficulties. Regularized inversion-the combined use of large numbers of parameters with mathematical approaches for stable parameter estimation-is becoming a common approach to address these difficulties and enhance the transfer of information contained in field measurements to parameters used to model that system. Though commonly used in other industries, regularized inversion is somewhat imperfectly understood in the groundwater field. There is concern that this unfamiliarity can lead to underuse, and misuse, of the methodology. This document is constructed to facilitate the appropriate use of regularized inversion for calibrating highly parameterized groundwater models. The presentation is directed at an intermediate- to advanced-level modeler, and it focuses on the PEST software suite-a frequently used tool for highly parameterized model calibration and one that is widely supported by commercial graphical user interfaces. A brief overview of the regularized inversion approach is provided, and techniques for mathematical regularization offered by PEST are outlined, including Tikhonov, subspace, and hybrid schemes. Guidelines for applying regularized inversion techniques are presented after a logical progression of steps for building suitable PEST input. The discussion starts with use of pilot points as a parameterization device and processing/grouping observations to form multicomponent objective functions. A description of potential parameter solution methodologies and resources available through the PEST software and its supporting utility programs follows. Directing the parameter-estimation process through PEST control variables is then discussed, including guidance for monitoring and optimizing the performance of PEST. Comprehensive listings of PEST control variables, and of the roles performed by PEST utility support programs, are presented in the appendixes.

Three Different Ways of Calibrating Burger's Contact Model for Viscoelastic Model of Asphalt Mixtures by Discrete Element Method

DEFF Research Database (Denmark)

Feng, Huan; Pettinari, Matteo; Stang, Henrik

2016-01-01

modulus. Three different approaches have been used and compared for calibrating the Burger's contact model. Values of the dynamic modulus and phase angle of asphalt mixtures were predicted by conducting DE simulation under dynamic strain control loading. The excellent agreement between the predicted......In this paper the viscoelastic behavior of asphalt mixture was investigated by employing a three-dimensional discrete element method. Combined with Burger's model, three contact models were used for the construction of constitutive asphalt mixture model with viscoelastic properties...

Enhanced Single Seed Trait Predictions in Soybean (Glycine max) and Robust Calibration Model Transfer with Near-Infrared Reflectance Spectroscopy.

Science.gov (United States)

Hacisalihoglu, Gokhan; Gustin, Jeffery L; Louisma, Jean; Armstrong, Paul; Peter, Gary F; Walker, Alejandro R; Settles, A Mark

2016-02-10

Single seed near-infrared reflectance (NIR) spectroscopy predicts soybean (Glycine max) seed quality traits of moisture, oil, and protein. We tested the accuracy of transferring calibrations between different single seed NIR analyzers of the same design by collecting NIR spectra and analytical trait data for globally diverse soybean germplasm. X-ray microcomputed tomography (μCT) was used to collect seed density and shape traits to enhance the number of soybean traits that can be predicted from single seed NIR. Partial least-squares (PLS) regression gave accurate predictive models for oil, weight, volume, protein, and maximal cross-sectional area of the seed. PLS models for width, length, and density were not predictive. Although principal component analysis (PCA) of the NIR spectra showed that black seed coat color had significant signal, excluding black seeds from the calibrations did not impact model accuracies. Calibrations for oil and protein developed in this study as well as earlier calibrations for a separate NIR analyzer of the same design were used to test the ability to transfer PLS regressions between platforms. PLS models built from data collected on one NIR analyzer had minimal differences in accuracy when applied to spectra collected from a sister device. Model transfer was more robust when spectra were trimmed from 910 to 1679 nm to 955-1635 nm due to divergence of edge wavelengths between the two devices. The ability to transfer calibrations between similar single seed NIR spectrometers facilitates broader adoption of this high-throughput, nondestructive, seed phenotyping technology.

Calibrating mechanistic-empirical pavement performance models with an expert matrix

Energy Technology Data Exchange (ETDEWEB)

Tighe, S.; AlAssar, R.; Haas, R. [Waterloo Univ., ON (Canada). Dept. of Civil Engineering; Zhiwei, H. [Stantec Consulting Ltd., Cambridge, ON (Canada)

2001-07-01

Proper management of pavement infrastructure requires pavement performance modelling. For the past 20 years, the Ontario Ministry of Transportation has used the Ontario Pavement Analysis of Costs (OPAC) system for pavement design. Pavement needs, however, have changed substantially during that time. To address this need, a new research contract is underway to enhance the model and verify the predictions, particularly at extreme points such as low and high traffic volume pavement design. This initiative included a complete evaluation of the existing OPAC pavement design method, the construction of a new set of pavement performance prediction models, and the development of the flexible pavement design procedure that incorporates reliability analysis. The design was also expanded to include rigid pavement designs and modification of the existing life cycle cost analysis procedure which includes both the agency cost and road user cost. Performance prediction and life-cycle costs were developed based on several factors, including material properties, traffic loads and climate. Construction and maintenance schedules were also considered. The methodology for the calibration and validation of a mechanistic-empirical flexible pavement performance model was described. Mechanistic-empirical design methods combine theory based design such as calculated stresses, strains or deflections with empirical methods, where a measured response is associated with thickness and pavement performance. Elastic layer analysis was used to determine pavement response to determine the most effective design using cumulative Equivalent Single Axle Loads (ESALs), below grade type and layer thickness.The new mechanistic-empirical model separates the environment and traffic effects on performance. This makes it possible to quantify regional differences between Southern and Northern Ontario. In addition, roughness can be calculated in terms of the International Roughness Index or Riding comfort Index

MODELING OF KINEMATICS OF A PLASTIC SHAPING AT CALIBRATION OF A THIN-WALLED PRECISION PIPE SINKING

Directory of Open Access Journals (Sweden)

E. D. Chertov

2014-01-01

Full Text Available Summary. The mathematical model of kinematics of a plastic shaping at the sinking of a thin-walled precision pipe applied to calibration of the ends of the unified elements of the pipeline of aircraft from titanic alloys and corrosion-resistant steel before assembly to the route by means of automatic argon-arc welding of ring joints is developed. For modeling, the power criterion of stability with use of kinematic possible fields of speeds is applied to receiving the top assessment of effort of deformation. The developed model of kinematics of a plastic current allows to receive power parameters of the main condition of process of calibration by sinking and can be used for the solution of a task on stability of process of deformation by results of comparison of power (power parameters for the main (steady and indignant states. Modeling is made in cylindrical system of coordinates by comparison of options of kinematic possible fields of the speeds of a current meeting a condition of incompressibility and kinematic regional conditions. The result of the modeling was selected discontinuous field of high-speed, in which the decrease outer radius (R occurs only by increasing the thickness of the pipe wall (t. For this option the size of pressure of sinking had the smallest value, therefore the chosen field of speeds closely to the valid. It is established that with increase in a step of giving 1 at calibration by the multisector tool the demanded pressure of sinking of q decreases. At an identical step of giving 1 pipe with the smaller relative thickness of (t/r needs to be calibrated the smaller pressure of sinking. With increase of a limit of fluidity at shift of material of pipe preparation pressure of sinking of (q increases.

Crop physiology calibration in the CLM

Directory of Open Access Journals (Sweden)

I. Bilionis

2015-04-01

scalable and adaptive scheme based on sequential Monte Carlo (SMC. The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.

Lattice modeling and calibration with turn-by-turn orbit data

Directory of Open Access Journals (Sweden)

Xiaobiao Huang

2010-11-01

Full Text Available A new method that explores turn-by-turn beam position monitor (BPM data to calibrate lattice models of accelerators is proposed. The turn-by-turn phase space coordinates at one location of the ring are first established using data from two BPMs separated by a simple section with a known transfer matrix, such as a drift space. The phase space coordinates are then tracked with the model to predict positions at other BPMs, which can be compared to measurements. The model is adjusted to minimize the difference between the measured and predicted orbit data. BPM gains and rolls are included as fitting variables. This technique can be applied to either the entire or a section of the ring. We have tested the method experimentally on a part of the SPEAR3 ring.

Lattice modeling and calibration with turn-by-turn orbit data

Science.gov (United States)

Huang, Xiaobiao; Sebek, Jim; Martin, Don

2010-11-01

A new method that explores turn-by-turn beam position monitor (BPM) data to calibrate lattice models of accelerators is proposed. The turn-by-turn phase space coordinates at one location of the ring are first established using data from two BPMs separated by a simple section with a known transfer matrix, such as a drift space. The phase space coordinates are then tracked with the model to predict positions at other BPMs, which can be compared to measurements. The model is adjusted to minimize the difference between the measured and predicted orbit data. BPM gains and rolls are included as fitting variables. This technique can be applied to either the entire or a section of the ring. We have tested the method experimentally on a part of the SPEAR3 ring.

Sensitivity analysis and development of calibration methodology for near-surface hydrogeology model of Forsmark

International Nuclear Information System (INIS)

Aneljung, Maria; Gustafsson, Lars-Goeran

2007-04-01

The hydrological modelling system MIKE SHE has been used to describe near-surface groundwater flow, transport mechanisms and the contact between ground- and surface water at the Forsmark site. The surface water system at Forsmark is described with the 1D modelling tool MIKE 11, which is fully and dynamically integrated with MIKE SHE. In spring 2007, a new data freeze will be available and a process of updating, rebuilding and calibrating the MIKE SHE model will start, based on the latest data set. Prior to this, it is important to gather as much knowledge as possible on calibration methods and to define critical calibration parameters and areas within the model. In this project, an optimization of the numerical description and an initial calibration of the MIKE SHE model has been made, and an updated base case has been defined. Data from 5 surface water level monitoring stations, 4 surface water discharge monitoring stations and 32 groundwater level monitoring stations (SFM soil boreholes) has been used for model calibration and evaluation. The base case simulations generally show a good agreement between calculated and measured water levels and discharges, indicating that the total runoff from the area is well described by the model. Moreover, with two exceptions (SFM0012 and SFM0022) the base case results show very good agreement between calculated and measured groundwater head elevations for boreholes installed below lakes. The model also shows a reasonably good agreement between calculated and measured groundwater head elevations or depths to phreatic surfaces in many other points. The following major types of calculation-measurement differences can be noted: Differences in groundwater level amplitudes due to transpiration processes. Differences in absolute mean groundwater head, due to differences between borehole casing levels and the interpolated DEM. Differences in absolute mean head elevations, due to local errors in hydraulic conductivity values