Conroy, Charlie; Gunn, James E.
2010-04-01
Stellar population synthesis (SPS) provides the link between the stellar and dust content of galaxies and their observed spectral energy distributions. In the present work, we perform a comprehensive calibration of our own flexible SPS (FSPS) model against a suite of data. These data include ultraviolet, optical, and near-IR photometry, surface brightness fluctuations, and integrated spectra of star clusters in the Magellanic Clouds (MCs), M87, M31, and the Milky Way (MW), and photometry and spectral indices of both quiescent and post-starburst galaxies at z {approx} 0. Several public SPS models are intercompared, including the models of Bruzual and Charlot (BC03), Maraston (M05), and FSPS. The relative strengths and weaknesses of these models are evaluated, with the following conclusions: (1) the FSPS and BC03 models compare favorably with MC data at all ages, whereas M05 colors are too red and the age dependence is incorrect; (2) all models yield similar optical and near-IR colors for old metal-poor systems, and yet they all provide poor fits to the integrated J - K and V - K colors of both MW and M31 star clusters; (3) FSPS is able to fit all of the ultraviolet data because both the post-asymptotic giant branch (post-AGB) and horizontal branch evolutionary phases are handled flexibly, while the BC03 and M05 models fail in the far-UV, and both far- and near-UV, respectively; (4) all models predict ugr colors too red, D{sub n}4000 strengths too strong, and Hdelta{sub A} strengths too weak compared to massive red sequence galaxies, under the assumption that such galaxies are composed solely of old metal-rich stars; and (5) FSPS and, to a lesser extent, BC03 can reproduce the optical and near-IR colors of post-starburst galaxies, while M05 cannot. Reasons for these discrepancies are explored. The failure at predicting the ugr colors, D{sub n}4000, and Hdelta{sub A} strengths can be explained by some combination of a minority population of metal-poor stars, young
C.F. Ahlers, H.H. Liu
2001-12-18
The purpose of this Analysis/Model Report (AMR) is to document the Calibrated Properties Model that provides calibrated parameter sets for unsaturated zone (UZ) flow and transport process models for the Yucca Mountain Site Characterization Project (YMP). This work was performed in accordance with the AMR Development Plan for U0035 Calibrated Properties Model REV00 (CRWMS M&O 1999c). These calibrated property sets include matrix and fracture parameters for the UZ Flow and Transport Model (UZ Model), drift seepage models, drift-scale and mountain-scale coupled-processes models, and Total System Performance Assessment (TSPA) models as well as Performance Assessment (PA) and other participating national laboratories and government agencies. These process models provide the necessary framework to test conceptual hypotheses of flow and transport at different scales and predict flow and transport behavior under a variety of climatic and thermal-loading conditions.
C. Ahlers; H. Liu
2000-03-12
The purpose of this Analysis/Model Report (AMR) is to document the Calibrated Properties Model that provides calibrated parameter sets for unsaturated zone (UZ) flow and transport process models for the Yucca Mountain Site Characterization Project (YMP). This work was performed in accordance with the ''AMR Development Plan for U0035 Calibrated Properties Model REV00. These calibrated property sets include matrix and fracture parameters for the UZ Flow and Transport Model (UZ Model), drift seepage models, drift-scale and mountain-scale coupled-processes models, and Total System Performance Assessment (TSPA) models as well as Performance Assessment (PA) and other participating national laboratories and government agencies. These process models provide the necessary framework to test conceptual hypotheses of flow and transport at different scales and predict flow and transport behavior under a variety of climatic and thermal-loading conditions.
T. Ghezzehej
2004-10-04
The purpose of this model report is to document the calibrated properties model that provides calibrated property sets for unsaturated zone (UZ) flow and transport process models (UZ models). The calibration of the property sets is performed through inverse modeling. This work followed, and was planned in, ''Technical Work Plan (TWP) for: Unsaturated Zone Flow Analysis and Model Report Integration'' (BSC 2004 [DIRS 169654], Sections 1.2.6 and 2.1.1.6). Direct inputs to this model report were derived from the following upstream analysis and model reports: ''Analysis of Hydrologic Properties Data'' (BSC 2004 [DIRS 170038]); ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004 [DIRS 169855]); ''Simulation of Net Infiltration for Present-Day and Potential Future Climates'' (BSC 2004 [DIRS 170007]); ''Geologic Framework Model'' (GFM2000) (BSC 2004 [DIRS 170029]). Additionally, this model report incorporates errata of the previous version and closure of the Key Technical Issue agreement TSPAI 3.26 (Section 6.2.2 and Appendix B), and it is revised for improved transparency.
H. H. Liu
2003-02-14
This report has documented the methodologies and the data used for developing rock property sets for three infiltration maps. Model calibration is necessary to obtain parameter values appropriate for the scale of the process being modeled. Although some hydrogeologic property data (prior information) are available, these data cannot be directly used to predict flow and transport processes because they were measured on scales smaller than those characterizing property distributions in models used for the prediction. Since model calibrations were done directly on the scales of interest, the upscaling issue was automatically considered. On the other hand, joint use of data and the prior information in inversions can further increase the reliability of the developed parameters compared with those for the prior information. Rock parameter sets were developed for both the mountain and drift scales because of the scale-dependent behavior of fracture permeability. Note that these parameter sets, except those for faults, were determined using the 1-D simulations. Therefore, they cannot be directly used for modeling lateral flow because of perched water in the unsaturated zone (UZ) of Yucca Mountain. Further calibration may be needed for two- and three-dimensional modeling studies. As discussed above in Section 6.4, uncertainties for these calibrated properties are difficult to accurately determine, because of the inaccuracy of simplified methods for this complex problem or the extremely large computational expense of more rigorous methods. One estimate of uncertainty that may be useful to investigators using these properties is the uncertainty used for the prior information. In most cases, the inversions did not change the properties very much with respect to the prior information. The Output DTNs (including the input and output files for all runs) from this study are given in Section 9.4.
Calibrated multi-subband Monte Carlo modeling of tunnel-FETs in silicon and III-V channel materials
NASA Astrophysics Data System (ADS)
Revelant, A.; Palestri, P.; Osgnach, P.; Selmi, L.
2013-10-01
We present a semiclassical model for Tunnel-FET (TFET) devices capable to describe band-to-band tunneling (BtBT) as well as far from equilibrium transport of the generated carriers. BtBT generation is implemented as an add-on into an existing multi-subband Monte Carlo (MSMC) transport simulator that accounts as well for the effects typical to alternative channel materials and high-κ dielectrics. A simple but accurate correction for the calculation of the BtBT generation rate to account for carrier confinement in the subbands is proposed and verified by comparison with full 2D quantum calculation.
Leica Dmc III Calibration and Geometric Sensor Accuracy
NASA Astrophysics Data System (ADS)
Mueller, C.; Neumann, K.
2016-03-01
As an evolution of the successful DMC II digital camera series, Leica Geosystems has introduced the Leica DMC III digital aerial camera using, for the first time in the industry, a large-format CMOS sensor as a panchromatic high-resolution camera head. This paper describes the Leica DMC III calibration and its quality assurance and quality control (QA/QC) procedures. It will explain how calibration was implemented within the production process for the Leica DMC III camera. Based on many years of experience with the DMC and DMC II camera series, it is know that the sensor flatness has a huge influence on the final achievable results. The Leica DMC III panchromatic CMOS sensor with its 100.3mm x 56.9mm size shows remaining errors in a range of 0.1 to 0.2μm for the root mean square and shows maximum values not higher that 1.0μm. The Leica DMC III is calibrated based on a 5cm Ground Sample Distance (GSD) grid pattern flight and evaluated with three different flying heights at 5cm, 8cm and 11cm GSD. The geometric QA/QC has been performed using the calibration field area, as well as using an independent test field. The geometric performance and accuracy is unique and gives ground accuracies far better than the flown GSD.
Bayesian Calibration of Microsimulation Models.
Rutter, Carolyn M; Miglioretti, Diana L; Savarino, James E
2009-12-01
Microsimulation models that describe disease processes synthesize information from multiple sources and can be used to estimate the effects of screening and treatment on cancer incidence and mortality at a population level. These models are characterized by simulation of individual event histories for an idealized population of interest. Microsimulation models are complex and invariably include parameters that are not well informed by existing data. Therefore, a key component of model development is the choice of parameter values. Microsimulation model parameter values are selected to reproduce expected or known results though the process of model calibration. Calibration may be done by perturbing model parameters one at a time or by using a search algorithm. As an alternative, we propose a Bayesian method to calibrate microsimulation models that uses Markov chain Monte Carlo. We show that this approach converges to the target distribution and use a simulation study to demonstrate its finite-sample performance. Although computationally intensive, this approach has several advantages over previously proposed methods, including the use of statistical criteria to select parameter values, simultaneous calibration of multiple parameters to multiple data sources, incorporation of information via prior distributions, description of parameter identifiability, and the ability to obtain interval estimates of model parameters. We develop a microsimulation model for colorectal cancer and use our proposed method to calibrate model parameters. The microsimulation model provides a good fit to the calibration data. We find evidence that some parameters are identified primarily through prior distributions. Our results underscore the need to incorporate multiple sources of variability (i.e., due to calibration data, unknown parameters, and estimated parameters and predicted values) when calibrating and applying microsimulation models. PMID:20076767
Bayesian Calibration of Microsimulation Models
Rutter, Carolyn M.; Miglioretti, Diana L.; Savarino, James E.
2009-01-01
Microsimulation models that describe disease processes synthesize information from multiple sources and can be used to estimate the effects of screening and treatment on cancer incidence and mortality at a population level. These models are characterized by simulation of individual event histories for an idealized population of interest. Microsimulation models are complex and invariably include parameters that are not well informed by existing data. Therefore, a key component of model development is the choice of parameter values. Microsimulation model parameter values are selected to reproduce expected or known results though the process of model calibration. Calibration may be done by perturbing model parameters one at a time or by using a search algorithm. As an alternative, we propose a Bayesian method to calibrate microsimulation models that uses Markov chain Monte Carlo. We show that this approach converges to the target distribution and use a simulation study to demonstrate its finite-sample performance. Although computationally intensive, this approach has several advantages over previously proposed methods, including the use of statistical criteria to select parameter values, simultaneous calibration of multiple parameters to multiple data sources, incorporation of information via prior distributions, description of parameter identifiability, and the ability to obtain interval estimates of model parameters. We develop a microsimulation model for colorectal cancer and use our proposed method to calibrate model parameters. The microsimulation model provides a good fit to the calibration data. We find evidence that some parameters are identified primarily through prior distributions. Our results underscore the need to incorporate multiple sources of variability (i.e., due to calibration data, unknown parameters, and estimated parameters and predicted values) when calibrating and applying microsimulation models. PMID:20076767
NASA Astrophysics Data System (ADS)
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.
Model Calibration in Watershed Hydrology
NASA Technical Reports Server (NTRS)
Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh
2009-01-01
Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.
AUTOMATIC CALIBRATION OF A DISRIBUTED CATCHMENT MODEL
Technology Transfer Automated Retrieval System (TEKTRAN)
Parameters of hydrologic models often are not exactly known and therefore have to be determined by calibration. A manual calibration depends on the subjective assessment of the modeler and can be very time-consuming though. Methods of automatic calibration can improve these shortcomings. Yet, the...
SWAT: Model use, calibration, and validation
Technology Transfer Automated Retrieval System (TEKTRAN)
SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT including manual calibration procedures...
ADAPT model: Model use, calibration and validation
Technology Transfer Automated Retrieval System (TEKTRAN)
This paper presents an overview of the Agricultural Drainage and Pesticide Transport (ADAPT) model and a case study to illustrate the calibration and validation steps for predicting subsurface tile drainage and nitrate-N losses from an agricultural system. The ADAPT model is a daily time step field ...
Parallel computing for automated model calibration
Burke, John S.; Danielson, Gary R.; Schulz, Douglas A.; Vail, Lance W.
2002-07-29
Natural resources model calibration is a significant burden on computing and staff resources in modeling efforts. Most assessments must consider multiple calibration objectives (for example magnitude and timing of stream flow peak). An automated calibration process that allows real time updating of data/models, allowing scientists to focus effort on improving models is needed. We are in the process of building a fully featured multi objective calibration tool capable of processing multiple models cheaply and efficiently using null cycle computing. Our parallel processing and calibration software routines have been generically, but our focus has been on natural resources model calibration. So far, the natural resources models have been friendly to parallel calibration efforts in that they require no inter-process communication, only need a small amount of input data and only output a small amount of statistical information for each calibration run. A typical auto calibration run might involve running a model 10,000 times with a variety of input parameters and summary statistical output. In the past model calibration has been done against individual models for each data set. The individual model runs are relatively fast, ranging from seconds to minutes. The process was run on a single computer using a simple iterative process. We have completed two Auto Calibration prototypes and are currently designing a more feature rich tool. Our prototypes have focused on running the calibration in a distributed computing cross platform environment. They allow incorporation of?smart? calibration parameter generation (using artificial intelligence processing techniques). Null cycle computing similar to SETI@Home has also been a focus of our efforts. This paper details the design of the latest prototype and discusses our plans for the next revision of the software.
Calibration of models using groundwater age
Sanford, W.
2011-01-01
There have been substantial efforts recently by geochemists to determine the age of groundwater (time since water entered the system) and its uncertainty, and by hydrologists to use these data to help calibrate groundwater models. This essay discusses the calibration of models using groundwater age, with conclusions that emphasize what is practical given current limitations rather than theoretical possibilities.
Validation of a watershed model without calibration
NASA Astrophysics Data System (ADS)
Vogel, Richard M.; Sankarasubramanian, A.
2003-10-01
Traditional approaches for the validation of watershed models focus on the "goodness of fit" between model predictions and observations. It is possible for a watershed model to exhibit a "good" fit, yet not accurately represent hydrologic processes; hence "goodness of fit" can be misleading. Instead, we introduce an approach which evaluates the ability of a model to represent the observed covariance structure of the input (climate) and output (streamflow) without ever calibrating the model. An advantage of this approach is that it is not confounded by model error introduced during the calibration process. We illustrate that once a watershed model is calibrated, the unavoidable model error can cloud our ability to validate (or invalidate) the model. We emphasize that model hypothesis testing (validation) should be performed prior to, and independent of, parameter estimation (calibration), contrary to traditional practice in which watershed models are usually validated after calibrating the model. Our approach is tested using two different watershed models at a number of different watersheds in the United States.
Preserving Flow Variability in Watershed Model Calibrations
Background/Question/Methods Although watershed modeling flow calibration techniques often emphasize a specific flow mode, ecological conditions that depend on flow-ecology relationships often emphasize a range of flow conditions. We used informal likelihood methods to investig...
Calibration and verification of environmental models
NASA Technical Reports Server (NTRS)
Lee, S. S.; Sengupta, S.; Weinberg, N.; Hiser, H.
1976-01-01
The problems of calibration and verification of mesoscale models used for investigating power plant discharges are considered. The value of remote sensors for data acquisition is discussed as well as an investigation of Biscayne Bay in southern Florida.
Spectral line position calibration for the SPIRIT III Fourier transform spectrometer
NASA Astrophysics Data System (ADS)
Hansen, Scott M.
1997-11-01
The spatial infrared imaging telescope (SPIRIT III) Fourier transform spectrometer, a Michelson interferometer, contains six IR detectors having independent fields of view and spectral responsivities. The Space Dynamics Laboratory at Utah State University (SDL/USU) designed, built, and calibrated the instrument for the Midcourse Space Experiment (MSX) sponsored by the Ballistic Missile Defense Organization (BMDO). The spectrometer uses a HeNe laser to record the optical path difference introduced by moving one mirror in the spectrometer. Spectral line position errors in the spectrometer were expected as a result of slight deviations in the optical axes of each detector and the reference laser detector relative to the optical axis of the instrument. These spectral line position errors were measured for the spectrometer by comparing measurements of earthlimb radiance to published line position values from the HITRAN database. These errors were fit to a model of the expected optical axis deviations to generate correction factors of the SPIRIT III spectrometer and to infer the approximate effective focal plane location of the reference laser detector relative to the focal plane location of each detector.
A Novel Protocol for Model Calibration in Biological Wastewater Treatment
Zhu, Ao; Guo, Jianhua; Ni, Bing-Jie; Wang, Shuying; Yang, Qing; Peng, Yongzhen
2015-01-01
Activated sludge models (ASMs) have been widely used for process design, operation and optimization in wastewater treatment plants. However, it is still a challenge to achieve an efficient calibration for reliable application by using the conventional approaches. Hereby, we propose a novel calibration protocol, i.e. Numerical Optimal Approaching Procedure (NOAP), for the systematic calibration of ASMs. The NOAP consists of three key steps in an iterative scheme flow: i) global factors sensitivity analysis for factors fixing; ii) pseudo-global parameter correlation analysis for non-identifiable factors detection; and iii) formation of a parameter subset through an estimation by using genetic algorithm. The validity and applicability are confirmed using experimental data obtained from two independent wastewater treatment systems, including a sequencing batch reactor and a continuous stirred-tank reactor. The results indicate that the NOAP can effectively determine the optimal parameter subset and successfully perform model calibration and validation for these two different systems. The proposed NOAP is expected to use for automatic calibration of ASMs and be applied potentially to other ordinary differential equations models. PMID:25682959
A Novel Protocol for Model Calibration in Biological Wastewater Treatment
NASA Astrophysics Data System (ADS)
Zhu, Ao; Guo, Jianhua; Ni, Bing-Jie; Wang, Shuying; Yang, Qing; Peng, Yongzhen
2015-02-01
Activated sludge models (ASMs) have been widely used for process design, operation and optimization in wastewater treatment plants. However, it is still a challenge to achieve an efficient calibration for reliable application by using the conventional approaches. Hereby, we propose a novel calibration protocol, i.e. Numerical Optimal Approaching Procedure (NOAP), for the systematic calibration of ASMs. The NOAP consists of three key steps in an iterative scheme flow: i) global factors sensitivity analysis for factors fixing; ii) pseudo-global parameter correlation analysis for non-identifiable factors detection; and iii) formation of a parameter subset through an estimation by using genetic algorithm. The validity and applicability are confirmed using experimental data obtained from two independent wastewater treatment systems, including a sequencing batch reactor and a continuous stirred-tank reactor. The results indicate that the NOAP can effectively determine the optimal parameter subset and successfully perform model calibration and validation for these two different systems. The proposed NOAP is expected to use for automatic calibration of ASMs and be applied potentially to other ordinary differential equations models.
A novel protocol for model calibration in biological wastewater treatment.
Zhu, Ao; Guo, Jianhua; Ni, Bing-Jie; Wang, Shuying; Yang, Qing; Peng, Yongzhen
2015-01-01
Activated sludge models (ASMs) have been widely used for process design, operation and optimization in wastewater treatment plants. However, it is still a challenge to achieve an efficient calibration for reliable application by using the conventional approaches. Hereby, we propose a novel calibration protocol, i.e. Numerical Optimal Approaching Procedure (NOAP), for the systematic calibration of ASMs. The NOAP consists of three key steps in an iterative scheme flow: i) global factors sensitivity analysis for factors fixing; ii) pseudo-global parameter correlation analysis for non-identifiable factors detection; and iii) formation of a parameter subset through an estimation by using genetic algorithm. The validity and applicability are confirmed using experimental data obtained from two independent wastewater treatment systems, including a sequencing batch reactor and a continuous stirred-tank reactor. The results indicate that the NOAP can effectively determine the optimal parameter subset and successfully perform model calibration and validation for these two different systems. The proposed NOAP is expected to use for automatic calibration of ASMs and be applied potentially to other ordinary differential equations models. PMID:25682959
Simultaneous heat and water model: Model use, calibration and validation
Technology Transfer Automated Retrieval System (TEKTRAN)
A discussion of calibration and validation procedures used for the Simultaneous Heat and Water model is presented. Three calibration approaches are presented and compared for simulating soil water content. Approaches included a stepwise local search methodology, trial-and-error calibration, and an...
Robust calibration of a global aerosol model
NASA Astrophysics Data System (ADS)
Lee, L.; Carslaw, K. S.; Pringle, K. J.; Reddington, C.
2013-12-01
Comparison of models and observations is vital for evaluating how well computer models can simulate real world processes. However, many current methods are lacking in their assessment of the model uncertainty, which introduces questions regarding the robustness of the observationally constrained model. In most cases, models are evaluated against observations using a single baseline simulation considered to represent the models' best estimate. The model is then improved in some way so that its comparison to observations is improved. Continuous adjustments in such a way may result in a model that compares better to observations but there may be many compensating features which make prediction with the newly calibrated model difficult to justify. There may also be some model outputs whose comparison to observations becomes worse in some regions/seasons as others improve. In such cases calibration cannot be considered robust. We present details of the calibration of a global aerosol model, GLOMAP, in which we consider not just a single model setup but a perturbed physics ensemble with 28 uncertain parameters. We first quantify the uncertainty in various model outputs (CCN, CN) for the year 2008 and use statistical emulation to identify which of the 28 parameters contribute most to this uncertainty. We then compare the emulated model simulations in the entire parametric uncertainty space to observations. Regions where the entire ensemble lies outside the error of the observations indicate structural model error or gaps in current knowledge which allows us to target future research areas. Where there is some agreement with the observations we use the information on the sources of the model uncertainty to identify geographical regions in which the important parameters are similar. Identification of regional calibration clusters helps us to use information from observation rich regions to calibrate regions with sparse observations and allow us to make recommendations for
Adaptable Multivariate Calibration Models for Spectral Applications
THOMAS,EDWARD V.
1999-12-20
Multivariate calibration techniques have been used in a wide variety of spectroscopic situations. In many of these situations spectral variation can be partitioned into meaningful classes. For example, suppose that multiple spectra are obtained from each of a number of different objects wherein the level of the analyte of interest varies within each object over time. In such situations the total spectral variation observed across all measurements has two distinct general sources of variation: intra-object and inter-object. One might want to develop a global multivariate calibration model that predicts the analyte of interest accurately both within and across objects, including new objects not involved in developing the calibration model. However, this goal might be hard to realize if the inter-object spectral variation is complex and difficult to model. If the intra-object spectral variation is consistent across objects, an effective alternative approach might be to develop a generic intra-object model that can be adapted to each object separately. This paper contains recommendations for experimental protocols and data analysis in such situations. The approach is illustrated with an example involving the noninvasive measurement of glucose using near-infrared reflectance spectroscopy. Extensions to calibration maintenance and calibration transfer are discussed.
Objective calibration of regional climate models
NASA Astrophysics Data System (ADS)
Bellprat, O.; Kotlarski, S.; Lüthi, D.; SchäR, C.
2012-12-01
Climate models are subject to high parametric uncertainty induced by poorly confined model parameters of parameterized physical processes. Uncertain model parameters are typically calibrated in order to increase the agreement of the model with available observations. The common practice is to adjust uncertain model parameters manually, often referred to as expert tuning, which lacks objectivity and transparency in the use of observations. These shortcomings often haze model inter-comparisons and hinder the implementation of new model parameterizations. Methods which would allow to systematically calibrate model parameters are unfortunately often not applicable to state-of-the-art climate models, due to computational constraints facing the high dimensionality and non-linearity of the problem. Here we present an approach to objectively calibrate a regional climate model, using reanalysis driven simulations and building upon a quadratic metamodel presented by Neelin et al. (2010) that serves as a computationally cheap surrogate of the model. Five model parameters originating from different parameterizations are selected for the optimization according to their influence on the model performance. The metamodel accurately estimates spatial averages of 2 m temperature, precipitation and total cloud cover, with an uncertainty of similar magnitude as the internal variability of the regional climate model. The non-linearities of the parameter perturbations are well captured, such that only a limited number of 20-50 simulations are needed to estimate optimal parameter settings. Parameter interactions are small, which allows to further reduce the number of simulations. In comparison to an ensemble of the same model which has undergone expert tuning, the calibration yields similar optimal model configurations, but leading to an additional reduction of the model error. The performance range captured is much wider than sampled with the expert-tuned ensemble and the presented
Calibration and validation of rockfall models
NASA Astrophysics Data System (ADS)
Frattini, Paolo; Valagussa, Andrea; Zenoni, Stefania; Crosta, Giovanni B.
2013-04-01
Calibrating and validating landslide models is extremely difficult due to the particular characteristic of landslides: limited recurrence in time, relatively low frequency of the events, short durability of post-event traces, poor availability of continuous monitoring data, especially for small landslide and rockfalls. For this reason, most of the rockfall models presented in literature completely lack calibration and validation of the results. In this contribution, we explore different strategies for rockfall model calibration and validation starting from both an historical event and a full-scale field test. The event occurred in 2012 in Courmayeur (Western Alps, Italy), and caused serious damages to quarrying facilities. This event has been studied soon after the occurrence through a field campaign aimed at mapping the blocks arrested along the slope, the shape and location of the detachment area, and the traces of scars associated to impacts of blocks on the slope. The full-scale field test was performed by Geovert Ltd in the Christchurch area (New Zealand) after the 2011 earthquake. During the test, a number of large blocks have been mobilized from the upper part of the slope and filmed with high velocity cameras from different viewpoints. The movies of each released block were analysed to identify the block shape, the propagation path, the location of impacts, the height of the trajectory and the velocity of the block along the path. Both calibration and validation of rockfall models should be based on the optimization of the agreement between the actual trajectories or location of arrested blocks and the simulated ones. A measure that describe this agreement is therefore needed. For calibration purpose, this measure should simple enough to allow trial and error repetitions of the model for parameter optimization. In this contribution we explore different calibration/validation measures: (1) the percentage of simulated blocks arresting within a buffer of the
Evaluation and calibration of a Los Alamos National Laboratory L/sub III/-edge densitometer
McGonnagle, W.J.; Holland, M.K.; Reynolds, C.S.; Trahey, N.M.; Zook, A.C.
1983-07-01
The Department of Energy (DOE), New Brunswick Laboratory (NBL) has evaluated and calibrated an L/sub III/-edge densitometer for the Los Alamos National Laboratory. This prototype instrument was designed for nondestructive on-line measurement of uranium and/or plutonium solutions. The sensitivity was optimized for measuring the uranium and plutonium concentrations in mixed solutions typical of those produced by solvent extraction in the U-Pu fuel cycle. Foil assays were performed on a daily basis to monitor the measurement precision and the stability of the calibration. Traceable reference solutions prepared at NBL were used to calibrate and evaluate the system. For solutions containing approximately 50 grams of uranium and/or plutonium per liter, the relative standard deviation for the L-edge measurements was approximately 0.3%. This experimental evaluation demonstrated that the solution matrix did not influence the results. The instrument performance in a laboratory environment was excellent.
New Method of Calibrating IRT Models.
ERIC Educational Resources Information Center
Jiang, Hai; Tang, K. Linda
This discussion of new methods for calibrating item response theory (IRT) models looks into new optimization procedures, such as the Genetic Algorithm (GA) to improve on the use of the Newton-Raphson procedure. The advantages of using a global optimization procedure like GA is that this kind of procedure is not easily affected by local optima and…
Hydrological model calibration for enhancing global flood forecast skill
NASA Astrophysics Data System (ADS)
Hirpa, Feyera A.; Beck, Hylke E.; Salamon, Peter; Thielen-del Pozo, Jutta
2016-04-01
Early warning systems play a key role in flood risk reduction, and their effectiveness is directly linked to streamflow forecast skill. The skill of a streamflow forecast is affected by several factors; among them are (i) model errors due to incomplete representation of physical processes and inaccurate parameterization, (ii) uncertainty in the model initial conditions, and (iii) errors in the meteorological forcing. In macro scale (continental or global) modeling, it is a common practice to use a priori parameter estimates over large river basins or wider regions, resulting in suboptimal streamflow estimations. The aim of this work is to improve flood forecast skill of the Global Flood Awareness System (GloFAS; www.globalfloods.eu), a grid-based forecasting system that produces flood forecast unto 30 days lead, through calibration of the distributed hydrological model parameters. We use a combination of in-situ and satellite-based streamflow data for automatic calibration using a multi-objective genetic algorithm. We will present the calibrated global parameter maps and report the forecast skill improvements achieved. Furthermore, we discuss current challenges and future opportunities with regard to global-scale early flood warning systems.
Stochastic calibration of an orographic percipitation model
Hay, L.E.
1998-01-01
In this study a stochastic approach to calibration of an orographic precipitation model (Rhea, 1978) was applied in the Gunnison River Basin of south-western Colorado. The stochastic approach to model calibration was used to determine: (1) the model parameter uncertainty and sensitivity; (2) the grid-cell resolution to run the model (10 or 5 km grids); (3) the model grid rotation increment; and (4) the basin subdivision by elevation band for parameter definition. Results from the stochastic calibration are location and data dependent. Uncertainty, sensitivity and range in the final parameter sets were found to vary by grid-cell resolution and elevation. Ten km grids were found to be a more robust model configuration than 5 km grids. Grid rotation increment, tested using only 10 km grids, indicated increments of less than 10 degrees to be superior. Basin subdivision into two elevation bands was found to produce 'optimal' results for both 10 and 5 km grids. ?? 1998 John Wiley & Sons, Ltd.
High Accuracy Transistor Compact Model Calibrations
Hembree, Charles E.; Mar, Alan; Robertson, Perry J.
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.
Gradient-based model calibration with proxy-model assistance
NASA Astrophysics Data System (ADS)
Burrows, Wesley; Doherty, John
2016-02-01
Use of a proxy model in gradient-based calibration and uncertainty analysis of a complex groundwater model with large run times and problematic numerical behaviour is described. The methodology is general, and can be used with models of all types. The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation. In enforcing history-matching constraints during the calibration and post-calibration uncertainty analysis processes, the proxy model is run for the purposes of populating the Jacobian matrix, while the original model is run when testing parameter upgrades; the latter process is readily parallelized. Use of a proxy model in this fashion dramatically reduces the computational burden of complex model calibration and uncertainty analysis. At the same time, the effect of model numerical misbehaviour on calculation of local gradients is mitigated, this allowing access to the benefits of gradient-based analysis where lack of integrity in finite-difference derivatives calculation would otherwise have impeded such access. Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.
CALIBRATIONS OF ATMOSPHERIC PARAMETERS OBTAINED FROM THE FIRST YEAR OF SDSS-III APOGEE OBSERVATIONS
Mészáros, Sz.; Allende Prieto, C.; Holtzman, J.; García Pérez, A. E.; Chojnowski, S. D.; Hearty, F. R.; Majewski, S. R.; Schiavon, R. P.; Basu, S.; Bizyaev, D.; Chaplin, W. J.; Elsworth, Y.; Cunha, K.; Epstein, C.; Johnson, J. A.; Frinchaboy, P. M.; García, R. A.; Kallinger, T.; Koesterke, L.; and others
2013-11-01
The Sloan Digital Sky Survey III (SDSS-III) Apache Point Observatory Galactic Evolution Experiment (APOGEE) is a three-year survey that is collecting 10{sup 5} high-resolution spectra in the near-IR across multiple Galactic populations. To derive stellar parameters and chemical compositions from this massive data set, the APOGEE Stellar Parameters and Chemical Abundances Pipeline (ASPCAP) has been developed. Here, we describe empirical calibrations of stellar parameters presented in the first SDSS-III APOGEE data release (DR10). These calibrations were enabled by observations of 559 stars in 20 globular and open clusters. The cluster observations were supplemented by observations of stars in NASA's Kepler field that have well determined surface gravities from asteroseismic analysis. We discuss the accuracy and precision of the derived stellar parameters, considering especially effective temperature, surface gravity, and metallicity; we also briefly discuss the derived results for the abundances of the α-elements, carbon, and nitrogen. Overall, we find that ASPCAP achieves reasonably accurate results for temperature and metallicity, but suffers from systematic errors in surface gravity. We derive calibration relations that bring the raw ASPCAP results into better agreement with independently determined stellar parameters. The internal scatter of ASPCAP parameters within clusters suggests that metallicities are measured with a precision better than 0.1 dex, effective temperatures better than 150 K, and surface gravities better than 0.2 dex. The understanding provided by the clusters and Kepler giants on the current accuracy and precision will be invaluable for future improvements of the pipeline.
NASA Astrophysics Data System (ADS)
Cornic, Philippe; Illoul, Cédric; Cheminet, Adam; Le Besnerais, Guy; Champagnat, Frédéric; Le Sant, Yves; Leclaire, Benjamin
2016-09-01
We address calibration and self-calibration of tomographic PIV experiments within a pinhole model of cameras. A complete and explicit pinhole model of a camera equipped with a 2-tilt angles Scheimpflug adapter is presented. It is then used in a calibration procedure based on a freely moving calibration plate. While the resulting calibrations are accurate enough for Tomo-PIV, we confirm, through a simple experiment, that they are not stable in time, and illustrate how the pinhole framework can be used to provide a quantitative evaluation of geometrical drifts in the setup. We propose an original self-calibration method based on global optimization of the extrinsic parameters of the pinhole model. These methods are successfully applied to the tomographic PIV of an air jet experiment. An unexpected by-product of our work is to show that volume self-calibration induces a change in the world frame coordinates. Provided the calibration drift is small, as generally observed in PIV, the bias on the estimated velocity field is negligible but the absolute location cannot be accurately recovered using standard calibration data.
Seepage Calibration Model and Seepage Testing Data
P. Dixon
2004-02-17
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&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 of
Christchurch field data for rockfall model calibration
NASA Astrophysics Data System (ADS)
Vick, L.; Glover, J.; Davies, T. R.
2013-12-01
The Canterbury earthquake of 2012-2011 triggered devastating rockfalls in the Port Hills in Christchurch, over 8000 boulders resulted in fatalities and severe building damage. There is a requirement for detailed and defensible rockfall hazard analysis to guide planning decisions in response to these rockfall events, most commonly this is performed with the use of a rockfall model. Calibrating a rockfall model requires a robust data set of past rockfall events. Information of rockfall deposit shape and size should be mapped over the affected area, in addition to information on the dynamics of the rockfall events such as jump heights and velocities of rocks. It is often the case that such information is obtained from expensive rock rolling studies; however the dynamics of an event can be estimated from the runout terrain and impact scars. In this study a calibration of a 3D rigid-body rockfall model was performed based on mapped boulder sizes and shapes over the rockfall affected zones of Christchurch, and estimations of boulder velocities gleaned from rock impact scars of individual trajectories and a high resolution digital terrain model produced following the rockfall events. The impact scars were mapped recording their length and depth of penetration into the loess soil cover of the runout zones. Two methods to estimate the boulder velocities have been applied. The first crudely estimates the velocity based on the vertical free fall potential between the rockfall shadow line and the terrain surface, and a velocity correction factor to account for friction. The second uses the impact scars assuming a parabolic trajectory between rock-ground impacts giving an indication of both jump height and velocity. Maximum runout distances produced a shadow angle of 23° in the area. Applying the first method suggests velocities can reach up to ~26 m s-1 and maxima concentrate in gullies and steep terrain. On average the distance between impact scars was 23 m, from which jump
A pelagic ecosystem model calibrated with BATS data
NASA Astrophysics Data System (ADS)
Hurtt, George C.; Armstrong, Robert A.
Mechanistic models of ocean ecosystem dynamics are of fundamental importance to understanding and predicting the role of marine ecosystems in the oceanic uptake of carbon. In this paper, a new pelagic ecosystem model that is descended from the model of Fasham et al. (Journal of Marine Research, 99 (1990) 591-639) (FDM model) is presented. During model development, the FDM model was first simplified to reduce the number of variables unconstrained by data and to reduce the number of parameters to be estimated. Many alternative simplified model formulations were tested in an attempt to fit 1988-1991 Bermuda Atlantic Time-series Study (BATS) data. The model presented here incorporates the changes found to be important. (i) A feature of the FDM physics that gives rise to a troublesome fall bloom was replaced. (ii) A biodiversity effect was added: the addition of larger algal and detrital size classes as phytoplankton and detrital biomasses increase. (iii) A phytoplankton physiological effect was also added: the adjustment of the chlorophyll-to-nitrogen ratio by phytoplankton in response to light and nutrient availabilities. The new model has only four state variables and a total of 11 biological parameters; yet it fits the average annual cycle in BATS data better than the FDM model. The new model also responds reasonably well to interannual variability in physical forcing. Based on the justification for changes (i)--(iii) from empirical studies and the success of this simple model at fitting BATS data, it is argued that these changes may be generally important. It is also shown that two alternative assumptions about ammonium concentrations lead to very different model calibrations, emphasizing the need for time series data on ammonium.
Thematic Mapper. Volume 1: Calibration report flight model, LANDSAT 5
NASA Technical Reports Server (NTRS)
Cooley, R. C.; Lansing, J. C.
1984-01-01
The calibration of the Flight 1 Model Thematic Mapper is discussed. Spectral response, scan profile, coherent noise, line spread profiles and white light leaks, square wave response, radiometric calibration, and commands and telemetry are specifically addressed.
NASA Astrophysics Data System (ADS)
Al-Abed, N. A.; Whiteley, H. R.
2002-11-01
Calibrating a comprehensive, multi-parameter conceptual hydrological model, such as the Hydrological Simulation Program Fortran model, is a major challenge. This paper describes calibration procedures for water-quantity parameters of the HSPF version 10·11 using the automatic-calibration parameter estimator model coupled with a geographical information system (GIS) approach for spatially averaged properties. The study area was the Grand River watershed, located in southern Ontario, Canada, between 79° 30 and 80° 57W longitude and 42° 51 and 44° 31N latitude. The drainage area is 6965 km2. Calibration efforts were directed to those model parameters that produced large changes in model response during sensitivity tests run prior to undertaking calibration. A GIS was used extensively in this study. It was first used in the watershed segmentation process. During calibration, the GIS data were used to establish realistic starting values for the surface and subsurface zone parameters LZSN, UZSN, COVER, and INFILT and physically reasonable ratios of these parameters among watersheds were preserved during calibration with the ratios based on the known properties of the subwatersheds determined using GIS. This calibration procedure produced very satisfactory results; the percentage difference between the simulated and the measured yearly discharge ranged between 4 to 16%, which is classified as good to very good calibration. The average simulated daily discharge for the watershed outlet at Brantford for the years 1981-85 was 67 m3 s-1 and the average measured discharge at Brantford was 70 m3 s-1. The coupling of a GIS with automatice calibration produced a realistic and accurate calibration for the HSPF model with much less effort and subjectivity than would be required for unassisted calibration.
Calibration of hydrological model with programme PEST
NASA Astrophysics Data System (ADS)
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.
The Adaptive Calibration Model of stress responsivity
Ellis, Bruce J.; Shirtcliff, Elizabeth A.
2010-01-01
This paper presents the Adaptive Calibration Model (ACM), an evolutionary-developmental theory of individual differences in the functioning of the stress response system. The stress response system has three main biological functions: (1) to coordinate the organism’s allostatic response to physical and psychosocial challenges; (2) to encode and filter information about the organism’s social and physical environment, mediating the organism’s openness to environmental inputs; and (3) to regulate the organism’s physiology and behavior in a broad range of fitness-relevant areas including defensive behaviors, competitive risk-taking, learning, attachment, affiliation and reproductive functioning. The information encoded by the system during development feeds back on the long-term calibration of the system itself, resulting in adaptive patterns of responsivity and individual differences in behavior. Drawing on evolutionary life history theory, we build a model of the development of stress responsivity across life stages, describe four prototypical responsivity patterns, and discuss the emergence and meaning of sex differences. The ACM extends the theory of biological sensitivity to context (BSC) and provides an integrative framework for future research in the field. PMID:21145350
A Comparison of Two Balance Calibration Model Building Methods
NASA Technical Reports Server (NTRS)
DeLoach, Richard; Ulbrich, Norbert
2007-01-01
Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.
Seepage Calibration Model and Seepage Testing Data
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-Drift to obtain the permeability structure for the seepage model
Lithography process window analysis with calibrated model
NASA Astrophysics Data System (ADS)
Zhou, Wenzhan; Yu, Jin; Lo, James; Liu, Johnson
2004-05-01
As critical-dimension shrink below 0.13 μm, the SPC (Statistical Process Control) based on CD (Critical Dimension) control in lithography process becomes more difficult. Increasing requirements of a shrinking process window have called on the need for more accurate decision of process window center. However in practical fabrication, we found that systematic error introduced by metrology and/or resist process can significantly impact the process window analysis result. Especially, when the simple polynomial functions are used to fit the lithographic data from focus exposure matrix (FEM), the model will fit these systematic errors rather than filter them out. This will definitely impact the process window analysis and determination of the best process condition. In this paper, we proposed to use a calibrated first principle model to do process window analysis. With this method, the systematic metrology error can be filtered out efficiently and give a more reasonable window analysis result.
Rohani Moghadam, Masoud; Haji Shabani, Ali Mohammad; Dadfarnia, Shayessteh
2015-01-25
A solidified floating organic drop microextraction (SFODME) procedure was developed for the simultaneous extraction and preconcentration of Fe(III) and Al(III) from water samples. The method was based on the formation of cationic complexes between Fe(III) and Al(III) and 3,5,7,2',4'-pentahydroxyflavone (morin) which were extracted into 1-undecanol as ion pairs with perchlorate ions. The absorbance of the extracted complexes was then measured in the wavelength range of 300-450 nm. Finally, the concentration of each metal ion was determined by the use of the orthogonal signal correction-partial least squares (OSC-PLS) calibration method. Several experimental parameters that may be affected on the extraction process such as the type and volume of extraction solvent, pH of the aqueous solution, morin and perchlorate concentration and extraction time were optimized. Under the optimum conditions, Fe(III) and Al(III) were determined in the ranges of 0.83-27.00 μg L(-1) (R(2)=0.9985) and 1.00-32.00 μg L(-1) (R(2)=0.9979) of Fe(III) and Al(III), respectively. The relative standard deviations (n=6) at 12.80 μg L(-1) of Fe(III) and 17.00 μg L(-)(1) of Al(III) were 3.2% and 3.5%, respectively. An enhancement factors of 102 and 96 were obtained for Fe(III) and Al(III) ions, respectively. The procedure was successfully applied to determination of iron and aluminum in steam and water samples of thermal power plant; and the accuracy was assessed through the recovery experiments and independent analysis by electrothermal atomic absorption spectroscopy (ETAAS). PMID:25168229
NASA Astrophysics Data System (ADS)
Rohani Moghadam, Masoud; Haji Shabani, Ali Mohammad; Dadfarnia, Shayessteh
2015-01-01
A solidified floating organic drop microextraction (SFODME) procedure was developed for the simultaneous extraction and preconcentration of Fe(III) and Al(III) from water samples. The method was based on the formation of cationic complexes between Fe(III) and Al(III) and 3,5,7,2‧,4‧-pentahydroxyflavone (morin) which were extracted into 1-undecanol as ion pairs with perchlorate ions. The absorbance of the extracted complexes was then measured in the wavelength range of 300-450 nm. Finally, the concentration of each metal ion was determined by the use of the orthogonal signal correction-partial least squares (OSC-PLS) calibration method. Several experimental parameters that may be affected on the extraction process such as the type and volume of extraction solvent, pH of the aqueous solution, morin and perchlorate concentration and extraction time were optimized. Under the optimum conditions, Fe(III) and Al(III) were determined in the ranges of 0.83-27.00 μg L-1 (R2 = 0.9985) and 1.00-32.00 μg L-1 (R2 = 0.9979) of Fe(III) and Al(III), respectively. The relative standard deviations (n = 6) at 12.80 μg L-1 of Fe(III) and 17.00 μg L-1 of Al(III) were 3.2% and 3.5%, respectively. An enhancement factors of 102 and 96 were obtained for Fe(III) and Al(III) ions, respectively. The procedure was successfully applied to determination of iron and aluminum in steam and water samples of thermal power plant; and the accuracy was assessed through the recovery experiments and independent analysis by electrothermal atomic absorption spectroscopy (ETAAS).
Towards automatic calibration of 2-dimensional flood propagation models
NASA Astrophysics Data System (ADS)
Fabio, P.; Aronica, G. T.; Apel, H.
2009-11-01
Hydraulic models for flood propagation description are an essential tool in many fields, e.g. civil engineering, flood hazard and risk assessments, evaluation of flood control measures, etc. Nowadays there are many models of different complexity regarding the mathematical foundation and spatial dimensions available, and most of them are comparatively easy to operate due to sophisticated tools for model setup and control. However, the calibration of these models is still underdeveloped in contrast to other models like e.g. hydrological models or models used in ecosystem analysis. This has basically two reasons: first, the lack of relevant data against the models can be calibrated, because flood events are very rarely monitored due to the disturbances inflicted by them and the lack of appropriate measuring equipment in place. Secondly, especially the two-dimensional models are computationally very demanding and therefore the use of available sophisticated automatic calibration procedures is restricted in many cases. This study takes a well documented flood event in August 2002 at the Mulde River in Germany as an example and investigates the most appropriate calibration strategy for a full 2-D hyperbolic finite element model. The model independent optimiser PEST, that gives the possibility of automatic calibrations, is used. The application of the parallel version of the optimiser to the model and calibration data showed that a) it is possible to use automatic calibration in combination of 2-D hydraulic model, and b) equifinality of model parameterisation can also be caused by a too large number of degrees of freedom in the calibration data in contrast to a too simple model setup. In order to improve model calibration and reduce equifinality a method was developed to identify calibration data with likely errors that obstruct model calibration.
NASA Technical Reports Server (NTRS)
Tripp, John S.; Tcheng, Ping
1999-01-01
Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.
A comparison of alternative multiobjective calibration strategies for hydrological modeling
NASA Astrophysics Data System (ADS)
Fenicia, Fabrizio; Savenije, Hubert H. G.; Matgen, Patrick; Pfister, Laurent
2007-03-01
A conceptual hydrological model structure contains several parameters that have to be estimated through matching observed and modeled watershed behavior in a calibration process. The requirement that a model simulation matches different aspects of system response at the same time has led the calibration problem toward a multiobjective approach. In this work we compare two multiobjective calibration approaches, each of which represents a different calibration philosophy. The first calibration approach is based on the concept of Pareto optimality and consists of calibrating all parameters with respect to a common set of objectives in one calibration stage. This approach results in a set of Pareto-optimal solutions representing the trade-offs between the selected calibration objectives. The second is a stepped calibration approach (SCA), which implies a stepwise calibration of sets of parameters that are associated with specific aspects of the system response. This approach replicates the steps followed by a hydrologist in manual calibration and develops a single solution. The comparison is performed considering the same set of objectives for the two approaches and two model structures of a different level of complexity. The difference in the two approaches, their reciprocal utility, and the practical implications involved in their application are analyzed and discussed using the Hesperange catchment case, an experimental basin in the Alzette River basin in Luxembourg. We show that the two approaches are not necessarily conflicting but can be complementary. The first approach provides useful information about the deficiencies of a model structure and therefore helps the model development, while the second attempts at determining a solution that is consistent with the data available. We also show that with increasing model complexity it becomes possible to reproduce the observations more accurately. As a result, the solutions for the different calibration objectives
Error Modeling and Calibration for Encoded Sun Sensors
Fan, Qiaoyun; Zhang, Guangjun; Li, Jian; Wei, Xinguo; Li, Xiaoyang
2013-01-01
Error factors in the encoded sun sensor (ESS) are analyzed and simulated. Based on the analysis results, an ESS error compensation model containing structural errors and fine-code algorithm errors is established, and the corresponding calibration method for model parameters is proposed. As external parameters, installation deviation between ESS and calibration equipment are introduced to the ESS calibration model, so that the model parameters can be calibrated accurately. The experimental results show that within plus/minus 60 degree of incident angle, the ESS measurement accuracy after compensation is three times higher on average than that before compensation. PMID:23470486
Calibration of a fuel relocation model in BISON
Swiler, L. P.; Williamson, R. L.; Perez, D. M.
2013-07-01
We demonstrate parameter calibration in the context of the BISON nuclear fuels performance analysis code. Specifically, we present the calibration of a parameter governing fuel relocation: the power level at which the relocation model is activated. This relocation activation parameter is a critical value in obtaining reasonable comparison with fuel centerline temperature measurements. It also is the subject of some debate in terms of the optimal values. We show that the optimal value does vary across the calibration to individual rods. We also demonstrate an aggregated calibration, where we calibrate to observations from six rods. (authors)
Residual bias in a multiphase flow model calibration and prediction
Poeter, E.P.; Johnson, R.H.
2002-01-01
When calibrated models produce biased residuals, we assume it is due to an inaccurate conceptual model and revise the model, choosing the most representative model as the one with the best-fit and least biased residuals. However, if the calibration data are biased, we may fail to identify an acceptable model or choose an incorrect model. Conceptual model revision could not eliminate biased residuals during inversion of simulated DNAPL migration under controlled conditions at the Borden Site near Ontario Canada. This paper delineates hypotheses for the source of bias, and explains the evolution of the calibration and resulting model predictions.
Influence of Scale on SWAT Model Calibration for Streamflow
Technology Transfer Automated Retrieval System (TEKTRAN)
The Soil Water Assessment Tool (SWAT) was implemented in the 281,000 ha St. Joseph River Watershed (SJRW) to investigate the influence of multiple scales on stream flow model calibration parameters. The relationship between model calibration parameters and associated hydrological response units (HRU...
METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL
The use of a fitted-parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can l...
Calibration and Sensitivity Analyses of LEACHM Simulation Model
Technology Transfer Automated Retrieval System (TEKTRAN)
Calibration and sensitivity analyses are essential processes in evaluation and application of computer simulation models. Calibration is a process of adjusting model inputs within expected values to minimize the differences between simulated and measured data. The objective of this study was to cali...
Calibrating Historical IR Sensors Using GEO, and AVHRR Infrared Tropical Mean Calibration Models
NASA Technical Reports Server (NTRS)
Scarino, Benjamin; Doelling, David R.; Minnis, Patrick; Gopalan, Arun; Haney, Conor; Bhatt, Rajendra
2014-01-01
Long-term, remote-sensing-based climate data records (CDRs) are highly dependent on having consistent, wellcalibrated satellite instrument measurements of the Earth's radiant energy. Therefore, by making historical satellite calibrations consistent with those of today's imagers, the Earth-observing community can benefit from a CDR that spans a minimum of 30 years. Most operational meteorological satellites rely on an onboard blackbody and space looks to provide on-orbit IR calibration, but neither target is traceable to absolute standards. The IR channels can also be affected by ice on the detector window, angle dependency of the scan mirror emissivity, stray-light, and detector-to-detector striping. Being able to quantify and correct such degradations would mean IR data from any satellite imager could contribute to a CDR. Recent efforts have focused on utilizing well-calibrated modern hyper-spectral sensors to intercalibrate concurrent operational IR imagers to a single reference. In order to consistently calibrate both historical and current IR imagers to the same reference, however, another strategy is needed. Large, well-characterized tropical-domain Earth targets have the potential of providing an Earth-view reference accuracy of within 0.5 K. To that effort, NASA Langley is developing an IR tropical mean calibration model in order to calibrate historical Advanced Very High Resolution Radiometer (AVHRR) instruments. Using Meteosat-9 (Met-9) as a reference, empirical models are built based on spatially/temporally binned Met-9 and AVHRR tropical IR brightness temperatures. By demonstrating the stability of the Met-9 tropical models, NOAA-18 AVHRR can be calibrated to Met-9 by matching the AVHRR monthly histogram averages with the Met-9 model. This method is validated with ray-matched AVHRR and Met-9 biasdifference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and thereby
Evaluation of “Autotune” calibration against manual calibration of building energy models
Chaudhary, Gaurav; New, Joshua; Sanyal, Jibonananda; Im, Piljae; O’Neill, Zheng; Garg, Vishal
2016-08-26
Our paper demonstrates the application of Autotune, a methodology aimed at automatically producing calibrated building energy models using measured data, in two case studies. In the first case, a building model is de-tuned by deliberately injecting faults into more than 60 parameters. This model was then calibrated using Autotune and its accuracy with respect to the original model was evaluated in terms of the industry-standard normalized mean bias error and coefficient of variation of root mean squared error metrics set forth in ASHRAE Guideline 14. In addition to whole-building energy consumption, outputs including lighting, plug load profiles, HVAC energy consumption,more » zone temperatures, and other variables were analyzed. In the second case, Autotune calibration is compared directly to experts’ manual calibration of an emulated-occupancy, full-size residential building with comparable calibration results in much less time. Lastly, our paper concludes with a discussion of the key strengths and weaknesses of auto-calibration approaches.« less
Cook, D A; Joyce, C J; Barnett, R J; Birgan, S P; Playford, H; Cockings, J G L; Hurford, R W
2002-06-01
Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995-1999. PMID:12075637
Automatically calibrating admittances in KATE's autonomous launch operations model
NASA Astrophysics Data System (ADS)
Morgan, Steve
1992-09-01
This report documents a 1000-line Symbolics LISP program that automatically calibrates all 15 fluid admittances in KATE's Autonomous Launch Operations (ALO) model. (KATE is Kennedy Space Center's Knowledge-based Autonomous Test Engineer, a diagnosis and repair expert system created for use on the Space Shuttle's various fluid flow systems.) As a new KATE application, the calibrator described here breaks new ground for KSC's Artificial Intelligence Lab by allowing KATE to both control and measure the hardware she supervises. By automating a formerly manual process, the calibrator: (1) saves the ALO model builder untold amounts of labor; (2) enables quick repairs after workmen accidently adjust ALO's hand valves; and (3) frees the modeler to pursue new KATE applications that previously were too complicated. Also reported are suggestions for enhancing the program: (1) to calibrate ALO's TV cameras, pumps, and sensor tolerances; and (2) to calibrate devices in other KATE models, such as the shuttle's LOX and Environment Control System (ECS).
Automatically calibrating admittances in KATE's autonomous launch operations model
NASA Technical Reports Server (NTRS)
Morgan, Steve
1992-01-01
This report documents a 1000-line Symbolics LISP program that automatically calibrates all 15 fluid admittances in KATE's Autonomous Launch Operations (ALO) model. (KATE is Kennedy Space Center's Knowledge-based Autonomous Test Engineer, a diagnosis and repair expert system created for use on the Space Shuttle's various fluid flow systems.) As a new KATE application, the calibrator described here breaks new ground for KSC's Artificial Intelligence Lab by allowing KATE to both control and measure the hardware she supervises. By automating a formerly manual process, the calibrator: (1) saves the ALO model builder untold amounts of labor; (2) enables quick repairs after workmen accidently adjust ALO's hand valves; and (3) frees the modeler to pursue new KATE applications that previously were too complicated. Also reported are suggestions for enhancing the program: (1) to calibrate ALO's TV cameras, pumps, and sensor tolerances; and (2) to calibrate devices in other KATE models, such as the shuttle's LOX and Environment Control System (ECS).
NASA Technical Reports Server (NTRS)
Koontz, S. L.; Cross, J. B.; Hunton, D.; Lan, E.
1990-01-01
Calibration and characterization of the quadrupole mass spectrometer component of the Evaluation of Oxygen Effects on Materials III (EOIM-III) space-flight experiment are reported in this paper. A high-velocity atom beam system was used to characterize the response of the flight mass spectrometer to high velocity oxygen atoms as well as the reaction/scattering products formed when the atom beam struck a surface. Carbon dioxide, carbon monoxide, and water were observed to form in the mass spectrometer whenever high velocity oxygen atoms were present. The major gaseous products formed from high-velocity atom-beam polymer reactions were easily detected and identified.
NASA Astrophysics Data System (ADS)
Garavaglia, F.; Seyve, E.; Gottardi, F.; Le Lay, M.; Gailhard, J.; Garçon, R.
2014-12-01
MORDOR is a conceptual hydrological model extensively used in Électricité de France (EDF, French electric utility company) operational applications: (i) hydrological forecasting, (ii) flood risk assessment, (iii) water balance and (iv) climate change studies. MORDOR is a lumped, reservoir, elevation based model with hourly or daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt and routing. The model has been intensively used at EDF for more than 20 years, in particular for modeling French mountainous watersheds. In the matter of parameters calibration we propose and test alternative multi-criteria techniques based on two specific approaches: automatic calibration using single-objective functions and a priori parameter calibration founded on hydrological watershed features. The automatic calibration approach uses single-objective functions, based on Kling-Gupta efficiency, to quantify the good agreement between the simulated and observed runoff focusing on four different runoff samples: (i) time-series sample, (I) annual hydrological regime, (iii) monthly cumulative distribution functions and (iv) recession sequences.The primary purpose of this study is to analyze the definition and sensitivity of MORDOR parameters testing different calibration techniques in order to: (i) simplify the model structure, (ii) increase the calibration-validation performance of the model and (iii) reduce the equifinality problem of calibration process. We propose an alternative calibration strategy that reaches these goals. The analysis is illustrated by calibrating MORDOR model to daily data for 50 watersheds located in French mountainous regions.
NASA Astrophysics Data System (ADS)
Kunze, Hans-Joachim
Commercial spectrographic systems are usually supplied with some wave-length calibration, but it is essential that the experimenter performs his own calibration for reliable measurements. A number of sources emitting well-known emission lines are available, and the best values of their wavelengths may be taken from data banks accessible on the internet. Data have been critically evaluated for many decades by the National Institute of Standards and Technology (NIST) of the USA [13], see also p. 3. Special data bases have been established by the astronomy and fusion communities (Appendix B).
Multi-fidelity approach to dynamics model calibration
NASA Astrophysics Data System (ADS)
Absi, Ghina N.; Mahadevan, Sankaran
2016-02-01
This paper investigates the use of structural dynamics computational models with multiple levels of fidelity in the calibration of system parameters. Different types of models may be available for the estimation of unmeasured system properties, with different levels of physics fidelity, mesh resolution and boundary condition assumptions. In order to infer these system properties, Bayesian calibration uses information from multiple sources (including experimental data and prior knowledge), and comprehensively quantifies the uncertainty in the calibration parameters. Estimating the posteriors is done using Markov Chain Monte Carlo sampling, which requires a large number of computations, thus making the use of a high-fidelity model for calibration prohibitively expensive. On the other hand, use of a low-fidelity model could lead to significant error in calibration and prediction. Therefore, this paper develops an approach for model parameter calibration with a low-fidelity model corrected using higher fidelity simulations, and investigates the trade-off between accuracy and computational effort. The methodology is illustrated for a curved panel located in the vicinity of a hypersonic aircraft engine, subjected to acoustic loading. Two models (a frequency response analysis and a full time history analysis) are combined to calibrate the damping characteristics of the panel.
Impact of data quality and quantity and the calibration procedure on crop growth model calibration
NASA Astrophysics Data System (ADS)
Seidel, Sabine J.; Werisch, Stefan
2014-05-01
Crop growth models are a commonly used tool for impact assessment of climate variability and climate change on crop yields and water use. Process-based crop models rely on algorithms that approximate the main physiological plant processes by a set of equations containing several calibration parameters as well as basic underlying assumptions. It is well recognized that model calibration is essential to improve the accuracy and reliability of model predictions. However, model calibration and validation is often hindered by a limited quantity and quality of available data. Recent studies suggest that crop model parameters can only be derived from field experiments in which plant growth and development processes have been measured. To be able to achieve a reliable prediction of crop growth under irrigation or drought stress, the correct characterization of the whole soil-plant-atmosphere system is essential. In this context is the accurate simulation of crop development, yield and the soil water dynamics plays an important role. In this study we aim to investigate the importance of a site and cultivar-specific model calibration based on experimental data using the SVAT model Daisy. We investigate to which extent different data sets and different parameter estimation procedures affect particularly yield estimates, irrigation water demand and the soil water dynamics. The comprehensive experimental data has been derived from an experiment conducted in Germany where five irrigation regimes were imposed on cabbage. Data collection included continuous measurements of soil tension and soil water content in two plots at three depths, weekly measurements of LAI, plant heights, leaf-N-content, stomatal conductivity, biomass partitioning, rooting depth as well as harvested yields and duration of growing period. Three crop growth calibration strategies were compared: (1) manual calibration based on yield and duration of growing period, (2) manual calibration based on yield
Calibration of the Site-Scale Saturated Zone Flow Model
G. A. Zyvoloski
2001-06-28
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&O 1999a).
Bayesian calibration of a flood inundation model using spatial data
NASA Astrophysics Data System (ADS)
Hall, Jim W.; Manning, Lucy J.; Hankin, Robin K. S.
2011-05-01
Bayesian theory of model calibration provides a coherent framework for distinguishing and encoding multiple sources of uncertainty in probabilistic predictions of flooding. This paper demonstrates the use of a Bayesian approach to computer model calibration, where the calibration data are in the form of spatial observations of flood extent. The Bayesian procedure involves generating posterior distributions of the flood model calibration parameters and observation error, as well as a Gaussian model inadequacy function, which represents the discrepancy between the best model predictions and reality. The approach is first illustrated with a simple didactic example and is then applied to a flood model of a reach of the river Thames in the UK. A predictive spatial distribution of flooding is generated for a flood of given severity.
Model Calibration of Exciter and PSS Using Extended Kalman Filter
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.
Finite Element Model Calibration Approach for Ares I-X
NASA Technical Reports Server (NTRS)
Horta, Lucas G.; Reaves, Mercedes C.; Buehrle, Ralph D.; Templeton, Justin D.; Lazor, Daniel R.; Gaspar, James L.; Parks, Russel A.; Bartolotta, Paul A.
2010-01-01
Ares I-X is a pathfinder vehicle concept under development by NASA to demonstrate a new class of launch vehicles. Although this vehicle is essentially a shell of what the Ares I vehicle will be, efforts are underway to model and calibrate the analytical models before its maiden flight. Work reported in this document will summarize the model calibration approach used including uncertainty quantification of vehicle responses and the use of nonconventional boundary conditions during component testing. Since finite element modeling is the primary modeling tool, the calibration process uses these models, often developed by different groups, to assess model deficiencies and to update parameters to reconcile test with predictions. Data for two major component tests and the flight vehicle are presented along with the calibration results. For calibration, sensitivity analysis is conducted using Analysis of Variance (ANOVA). To reduce the computational burden associated with ANOVA calculations, response surface models are used in lieu of computationally intensive finite element solutions. From the sensitivity studies, parameter importance is assessed as a function of frequency. In addition, the work presents an approach to evaluate the probability that a parameter set exists to reconcile test with analysis. Comparisons of pre-test predictions of frequency response uncertainty bounds with measured data, results from the variance-based sensitivity analysis, and results from component test models with calibrated boundary stiffness models are all presented.
Finite Element Model Calibration Approach for Area I-X
NASA Technical Reports Server (NTRS)
Horta, Lucas G.; Reaves, Mercedes C.; Buehrle, Ralph D.; Templeton, Justin D.; Gaspar, James L.; Lazor, Daniel R.; Parks, Russell A.; Bartolotta, Paul A.
2010-01-01
Ares I-X is a pathfinder vehicle concept under development by NASA to demonstrate a new class of launch vehicles. Although this vehicle is essentially a shell of what the Ares I vehicle will be, efforts are underway to model and calibrate the analytical models before its maiden flight. Work reported in this document will summarize the model calibration approach used including uncertainty quantification of vehicle responses and the use of non-conventional boundary conditions during component testing. Since finite element modeling is the primary modeling tool, the calibration process uses these models, often developed by different groups, to assess model deficiencies and to update parameters to reconcile test with predictions. Data for two major component tests and the flight vehicle are presented along with the calibration results. For calibration, sensitivity analysis is conducted using Analysis of Variance (ANOVA). To reduce the computational burden associated with ANOVA calculations, response surface models are used in lieu of computationally intensive finite element solutions. From the sensitivity studies, parameter importance is assessed as a function of frequency. In addition, the work presents an approach to evaluate the probability that a parameter set exists to reconcile test with analysis. Comparisons of pretest predictions of frequency response uncertainty bounds with measured data, results from the variance-based sensitivity analysis, and results from component test models with calibrated boundary stiffness models are all presented.
Experience in calibrating the double-hardening constitutive model Monot
NASA Astrophysics Data System (ADS)
Hicks, M. A.
2003-11-01
The Monot double-hardening soil model has previously been implemented within a general purpose finite element algorithm, and used in the analysis of numerous practical problems. This paper reviews experience gained in calibrating Monot to laboratory data and demonstrates how the calibration process may be simplified without detriment to the range of behaviours modelled. It describes Monot's principal features, important governing equations and various calibration methods, including strategies for overconsolidated, cemented and cohesive soils. Based on a critical review of over 30 previous Monot calibrations, for sands and other geomaterials, trends in parameter values have been identified, enabling parameters to be categorized according to their relative importance. It is shown that, for most practical purposes, a maximum of only 5 parameters is needed; for the remaining parameters, standard default values are suggested. Hence, the advanced stress-strain modelling offered by Monot is attainable with a similar number of parameters as would be needed for some simpler, less versatile, models. Copyright
Tradeoffs among watershed model calibration targets for parameter estimation
Hydrologic models are commonly calibrated by optimizing a single objective function target to compare simulated and observed flows, although individual targets are influenced by specific flow modes. Nash-Sutcliffe efficiency (NSE) emphasizes flood peaks in evaluating simulation f...
Analysis of Sting Balance Calibration Data Using Optimized Regression Models
NASA Technical Reports Server (NTRS)
Ulbrich, N.; Bader, Jon B.
2010-01-01
Calibration data of a wind tunnel sting balance was processed using a candidate math model search algorithm that recommends an optimized regression model for the data analysis. During the calibration the normal force and the moment at the balance moment center were selected as independent calibration variables. The sting balance itself had two moment gages. Therefore, after analyzing the connection between calibration loads and gage outputs, it was decided to choose the difference and the sum of the gage outputs as the two responses that best describe the behavior of the balance. The math model search algorithm was applied to these two responses. An optimized regression model was obtained for each response. Classical strain gage balance load transformations and the equations of the deflection of a cantilever beam under load are used to show that the search algorithm s two optimized regression models are supported by a theoretical analysis of the relationship between the applied calibration loads and the measured gage outputs. The analysis of the sting balance calibration data set is a rare example of a situation when terms of a regression model of a balance can directly be derived from first principles of physics. In addition, it is interesting to note that the search algorithm recommended the correct regression model term combinations using only a set of statistical quality metrics that were applied to the experimental data during the algorithm s term selection process.
Method calibration of the model 13145 infrared target projectors
NASA Astrophysics Data System (ADS)
Huang, Jianxia; Gao, Yuan; Han, Ying
2014-11-01
The SBIR Model 13145 Infrared Target Projectors ( The following abbreviation Evaluation Unit ) used for characterizing the performances of infrared imaging system. Test items: SiTF, MTF, NETD, MRTD, MDTD, NPS. Infrared target projectors includes two area blackbodies, a 12 position target wheel, all reflective collimator. It provide high spatial frequency differential targets, Precision differential targets imaged by infrared imaging system. And by photoelectricity convert on simulate signal or digital signal. Applications software (IR Windows TM 2001) evaluate characterizing the performances of infrared imaging system. With regards to as a whole calibration, first differently calibration for distributed component , According to calibration specification for area blackbody to calibration area blackbody, by means of to amend error factor to calibration of all reflective collimator, radiance calibration of an infrared target projectors using the SR5000 spectral radiometer, and to analyze systematic error. With regards to as parameter of infrared imaging system, need to integrate evaluation method. According to regulation with -GJB2340-1995 General specification for military thermal imaging sets -testing parameters of infrared imaging system, the results compare with results from Optical Calibration Testing Laboratory . As a goal to real calibration performances of the Evaluation Unit.
Groundwater model calibration at Pantex using Data Fusion modeling
1996-04-01
The Pantex plant has operated as one of the Federal government`s key conventional and nuclear weapons facilities since the 1940`s. In recent years, the DOE has expended considerable effort to characterize the nature and extent of groundwater contamination associated with the site. That effort is still on-going with the ultimate aim of determining and implementing appropriate remedial measures. The goal of the study described in this report was to use Data Fusion modeling to calibrate a groundwater model near Zone 12 of Pantex, primarily to define the potential pathways to the Ogallala aquifer. Data Fusion is a new approach for combining different but interrelated types of information from multiple sources into a quantitative analysis of system characteristics and dynamic behavior. The Data Fusion Workstation (DFW) is a patented technique for carrying out Data Fusion analyses using specially developed computer based approaches. The technique results in the development of a calibrated model of a site consistent with the data, first principles, and geostatistical spatial continuity. A more explicit description of the Data Fusion concept and approach is presented.
Finite element model calibration using frequency responses with damping equalization
NASA Astrophysics Data System (ADS)
Abrahamsson, T. J. S.; Kammer, D. C.
2015-10-01
Model calibration is a cornerstone of the finite element verification and validation procedure, in which the credibility of the model is substantiated by positive comparison with test data. The calibration problem, in which the minimum deviation between finite element model data and experimental data is searched for, is normally characterized as being a large scale optimization problem with many model parameters to solve for and with deviation metrics that are nonlinear in these parameters. The calibrated parameters need to be found by iterative procedures, starting from initial estimates. Sometimes these procedures get trapped in local deviation function minima and do not converge to the globally optimal calibration solution that is searched for. The reason for such traps is often the multi-modality of the problem which causes eigenmode crossover problems in the iterative variation of parameter settings. This work presents a calibration formulation which gives a smooth deviation metric with a large radius of convergence to the global minimum. A damping equalization method is suggested to avoid the mode correlation and mode pairing problems that need to be solved in many other model updating procedures. By this method, the modal damping of a test data model and the finite element model is set to be the same fraction of critical modal damping. Mode pairing for mapping of experimentally found damping to the finite element model is thus not needed. The method is combined with model reduction for efficiency and employs the Levenberg-Marquardt minimizer with randomized starts to achieve the calibration solution. The performance of the calibration procedure, including a study of parameter bias and variance under noisy data conditions, is demonstrated by two numerical examples.
Simultaneous calibration of hydrological models in geographical space
NASA Astrophysics Data System (ADS)
Bárdossy, András; Huang, Yingchun; Wagener, Thorsten
2016-07-01
Hydrological models are usually calibrated for selected catchments individually using specific performance criteria. This procedure assumes that the catchments show individual behavior. As a consequence, the transfer of model parameters to other ungauged catchments is problematic. In this paper, the possibility of transferring part of the model parameters was investigated. Three different conceptual hydrological models were considered. The models were restructured by introducing a new parameter η which exclusively controls water balances. This parameter was considered as individual to each catchment. All other parameters, which mainly control the dynamics of the discharge (dynamical parameters), were considered for spatial transfer. Three hydrological models combined with three different performance measures were used in three different numerical experiments to investigate this transferability. The first numerical experiment, involving individual calibration of the models for 15 selected MOPEX catchments, showed that it is difficult to identify which catchments share common dynamical parameters. Parameters of one catchment might be good for another catchment but not the opposite. In the second numerical experiment, a common spatial calibration strategy was used. It was explicitly assumed that the catchments share common dynamical parameters. This strategy leads to parameters which perform well on all catchments. A leave-one-out common calibration showed that in this case a good parameter transfer to ungauged catchments can be achieved. In the third numerical experiment, the common calibration methodology was applied for 96 catchments. Another set of 96 catchments was used to test the transfer of common dynamical parameters. The results show that even a large number of catchments share similar dynamical parameters. The performance is worse than those obtained by individual calibration, but the transfer to ungauged catchments remains possible. The performance of the
Calibrating RZWQM2 model for maize responses to deficit irrigation
Technology Transfer Automated Retrieval System (TEKTRAN)
Calibrating a system model for field research is a challenge and requires collaboration between modelers and experimentalists. In this study, the Root Zone Water Quality Model-DSSAT (RZWQM2) was used for simulating plant water stresses in corn in Eastern Colorado. The experiments were conducted in 2...
Calibrating the ECCO ocean general circulation model using Green's functions
NASA Technical Reports Server (NTRS)
Menemenlis, D.; Fu, L. L.; Lee, T.; Fukumori, I.
2002-01-01
Green's functions provide a simple, yet effective, method to test and calibrate General-Circulation-Model(GCM) parameterizations, to study and quantify model and data errors, to correct model biases and trends, and to blend estimates from different solutions and data products.
NASA Astrophysics Data System (ADS)
Gharari, S.; Hrachowitz, M.; Fenicia, F.; Savenije, H. H. G.
2012-02-01
Conceptual hydrological models often rely on calibration for the identification of their parameters. As these models are typically designed to reflect real catchment processes, a key objective of an appropriate calibration strategy is the determination of parameter sets that reflect a "realistic" model behavior. Previous studies have shown that parameter estimates for different calibration periods can be significantly different. This questions model transposability in time, which is one of the key conditions for the set-up of a "realistic" model. This paper presents a new approach that selects parameter sets that provide a consistent model performance in time. The approach consists of confronting model performance in different periods, and selecting parameter sets that are as close as possible to the optimum of each individual sub-period. While aiding model calibration, the approach is also useful as a diagnostic tool, illustrating tradeoffs in the identification of time consistent parameter sets. The approach is demonstrated in a case study where we illustrate the multi-objective calibration of the HyMod hydrological model to a Luxembourgish catchment.
This report contains complete documentation for the 15 programs and 11 data files of the EPA Atomic Absorption Instrument Automation System. The system incorporates the following major features: (1) multipoint calibration using first, second, or third degree regression or linear ...
Spatiotemporal calibration and resolution refinement of output from deterministic models.
Gilani, Owais; McKay, Lisa A; Gregoire, Timothy G; Guan, Yongtao; Leaderer, Brian P; Holford, Theodore R
2016-06-30
Spatiotemporal calibration of output from deterministic models is an increasingly popular tool to more accurately and efficiently estimate the true distribution of spatial and temporal processes. Current calibration techniques have focused on a single source of data on observed measurements of the process of interest that are both temporally and spatially dense. Additionally, these methods often calibrate deterministic models available in grid-cell format with pixel sizes small enough that the centroid of the pixel closely approximates the measurement for other points within the pixel. We develop a modeling strategy that allows us to simultaneously incorporate information from two sources of data on observed measurements of the process (that differ in their spatial and temporal resolutions) to calibrate estimates from a deterministic model available on a regular grid. This method not only improves estimates of the pollutant at the grid centroids but also refines the spatial resolution of the grid data. The modeling strategy is illustrated by calibrating and spatially refining daily estimates of ambient nitrogen dioxide concentration over Connecticut for 1994 from the Community Multiscale Air Quality model (temporally dense grid-cell estimates on a large pixel size) using observations from an epidemiologic study (spatially dense and temporally sparse) and Environmental Protection Agency monitoring stations (temporally dense and spatially sparse). Copyright © 2016 John Wiley & Sons, Ltd. PMID:26790617
Bayesian calibration of the Community Land Model using surrogates
NASA Astrophysics Data System (ADS)
Ray, J.; Sargsyan, K.; Huang, M.; Hou, Z.
2012-12-01
We present results from a calibration effort of the Community Land Model (CLM) using surrogates. Three parameters, governing subsurface runoff and groundwater dynamics, were targeted and calibrated to observations from the Missouri Ozark Ameriflux tower site (US-Moz) spanning 1996-2004. We adopt a Bayesian approach for calibration where the parameters were estimated as probability distributions to account for the uncertainty due to modelling and observation errors. The model fitting was performed using an adaptive Markov chain Monte Carlo method. Since the sampling-based calibration of CLM could be computationally expensive, we first developed surrogates as alternatives to the CLM. The three-dimensional parameter space was sampled and CLM was used to produce monthly averaged predictions of runoff and latent/sensible heat fluxes. Multiple polynomial "trend" models were proposed, fitted to the CLM simulations via regression, and tested for over-fitting. A quadratic model was ultimately selected and bias-corrected using the universal kriging approach, to produce surrogates with errors less than 10% at any arbitrary point in the parameter-space. This "trend+kriged" model was then used as an inexpensive CLM surrogate, in an MCMC sampler, to solve the calibration problem. Joint densities were developed for the parameters, along with an estimate of the structural error of the surrogates.
Real-data Calibration Experiments On A Distributed Hydrologic Model
NASA Astrophysics Data System (ADS)
Brath, A.; Montanari, A.; Toth, E.
The increasing availability of extended information on the study watersheds does not generally overcome the need for the determination through calibration of at least a part of the parameters of distributed hydrologic models. The complexity of such models, making the computations highly intensive, has often prevented an extensive analysis of calibration issues. The purpose of this study is an evaluation of the validation results of a series of automatic calibration experiments (using the shuffled complex evolu- tion method, Duan et al., 1992) performed with a highly conceptualised, continuously simulating, distributed hydrologic model applied on the real data of a mid-sized Ital- ian watershed. Major flood events occurred in the 1990-2000 decade are simulated with the parameters obtained by the calibration of the model against discharge data observed at the closure section of the watershed and the hydrological features (overall agreement, volumes, peaks and times to peak) of the discharges obtained both in the closure and in an interior stream-gauge are analysed for validation purposes. A first set of calibrations investigates the effect of the variability of the calibration periods, using the data from several single flood events and from longer, continuous periods. Another analysis regards the influence of rainfall input and it is carried out varying the size and distribution of the raingauge network, in order to examine the relation between the spatial pattern of observed rainfall and the variability of modelled runoff. Lastly, a comparison of the hydrographs obtained for the flood events with the model parameterisation resulting when modifying the objective function to be minimised in the automatic calibration procedure is presented.
An Example Multi-Model Analysis: Calibration and Ranking
NASA Astrophysics Data System (ADS)
Ahlmann, M.; James, S. C.; Lowry, T. S.
2007-12-01
Modeling solute transport is a complex process governed by multiple site-specific parameters like porosity and hydraulic conductivity as well as many solute-dependent processes such as diffusion and reaction. Furthermore, it must be determined whether a steady or time-variant model is most appropriate. A problem arises because over-parameterized conceptual models may be easily calibrated to exactly reproduce measured data, even if these data contain measurement noise. During preliminary site investigation stages where available data may be scarce it is often advisable to develop multiple independent conceptual models, but the question immediately arises: which model is best? This work outlines a method for quickly calibrating and ranking multiple models using the parameter estimation code PEST in conjunction with the second-order-bias-corrected Akaike Information Criterion (AICc). The method is demonstrated using the twelve analytical solutions to the one- dimensional convective-dispersive-reactive solute transport equation as the multiple conceptual models (van~Genuchten M. Th. and W. J. Alves, 1982. Analytical solutions of the one-dimensional convective- dispersive solute transport equation, USDA ARS Technical Bulletin Number 1661. U.S. Salinity Laboratory, 4500 Glenwood Drive, Riverside, CA 92501.). Each solution is calibrated to three data sets, each comprising an increasing number of calibration points that represent increased knowledge of the modeled site (calibration points are selected from one of the analytical solutions that provides the "correct" model). The AICc is calculated after each successive calibration to the three data sets yielding model weights that are functions of the sum of the squared, weighted residuals, the number of parameters, and the number of observations (calibration data points) and ultimately indicates which model has the highest likelihood of being correct. The results illustrate how the sparser data sets can be modeled
Stochastic calibration and learning in nonstationary hydroeconomic models
NASA Astrophysics Data System (ADS)
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.
The cost of uniqueness in groundwater model calibration
NASA Astrophysics Data System (ADS)
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
Kelly, J.G.; Griffin, P.J.; Fan, W.C.
1993-08-01
The SPR III bare cavity spectrum and integral parameters have been determined with 24 measured spectrum sensor responses and an independent, detailed, MCNP transport calculation. This environment qualifies as a benchmark field for electronic parts testing.
NONPOINT SOURCE MODEL CALIBRATION IN HONEY CREEK WATERSHED
The U.S. EPA Non-Point Source Model has been applied and calibrated to a fairly large (187 sq. mi.) agricultural watershed in the Lake Erie Drainage basin of north central Ohio. Hydrologic and chemical routing algorithms have been developed. The model is evaluated for suitability...
Cloud-Based Model Calibration Using OpenStudio: Preprint
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.
Calibration and Confirmation in Geophysical Models
NASA Astrophysics Data System (ADS)
Werndl, Charlotte
2016-04-01
For policy decisions the best geophysical models are needed. To evaluate geophysical models, it is essential that the best available methods for confirmation are used. A hotly debated issue on confirmation in climate science (as well as in philosophy) is the requirement of use-novelty (i.e. that data can only confirm models if they have not already been used before. This talk investigates the issue of use-novelty and double-counting for geophysical models. We will see that the conclusions depend on the framework of confirmation and that it is not clear that use-novelty is a valid requirement and that double-counting is illegitimate.
Model calibration and uncertainty analysis in signaling networks.
Heinemann, Tim; Raue, Andreas
2016-06-01
For a long time the biggest challenges in modeling cellular signal transduction networks has been the inference of crucial pathway components and the qualitative description of their interactions. As a result of the emergence of powerful high-throughput experiments, it is now possible to measure data of high temporal and spatial resolution and to analyze signaling dynamics quantitatively. In addition, this increase of high-quality data is the basis for a better understanding of model limitations and their influence on the predictive power of models. We review established approaches in signal transduction network modeling with a focus on ordinary differential equation models as well as related developments in model calibration. As central aspects of the calibration process we discuss possibilities of model adaptation based on data-driven parameter optimization and the concomitant objective of reducing model uncertainties. PMID:27085224
Multi-Dimensional Calibration of Impact Dynamic Models
NASA Technical Reports Server (NTRS)
Horta, Lucas G.; Reaves, Mercedes C.; Annett, Martin S.; Jackson, Karen E.
2011-01-01
NASA Langley, under the Subsonic Rotary Wing Program, recently completed two helicopter tests in support of an in-house effort to study crashworthiness. As part of this effort, work is on-going to investigate model calibration approaches and calibration metrics for impact dynamics models. Model calibration of impact dynamics problems has traditionally assessed model adequacy by comparing time histories from analytical predictions to test at only a few critical locations. Although this approach provides for a direct measure of the model predictive capability, overall system behavior is only qualitatively assessed using full vehicle animations. In order to understand the spatial and temporal relationships of impact loads as they migrate throughout the structure, a more quantitative approach is needed. In this work impact shapes derived from simulated time history data are used to recommend sensor placement and to assess model adequacy using time based metrics and orthogonality multi-dimensional metrics. An approach for model calibration is presented that includes metric definitions, uncertainty bounds, parameter sensitivity, and numerical optimization to estimate parameters to reconcile test with analysis. The process is illustrated using simulated experiment data.
Stepwise calibration procedure for regional coupled hydrological-hydrogeological models
NASA Astrophysics Data System (ADS)
Labarthe, Baptiste; Abasq, Lena; de Fouquet, Chantal; Flipo, Nicolas
2014-05-01
Stream-aquifer interaction is a complex process depending on regional and local processes. Indeed, the groundwater component of hydrosystem and large scale heterogeneities control the regional flows towards the alluvial plains and the rivers. In second instance, the local distribution of the stream bed permeabilities controls the dynamics of stream-aquifer water fluxes within the alluvial plain, and therefore the near-river piezometric head distribution. In order to better understand the water circulation and pollutant transport in watersheds, the integration of these multi-dimensional processes in modelling platform has to be performed. Thus, the nested interfaces concept in continental hydrosystem modelling (where regional fluxes, simulated by large scale models, are imposed at local stream-aquifer interfaces) has been presented in Flipo et al (2014). This concept has been implemented in EauDyssée modelling platform for a large alluvial plain model (900km2) part of a 11000km2 multi-layer aquifer system, located in the Seine basin (France). The hydrosystem modelling platform is composed of four spatially distributed modules (Surface, Sub-surface, River and Groundwater), corresponding to four components of the terrestrial water cycle. Considering the large number of parameters to be inferred simultaneously, the calibration process of coupled models is highly computationally demanding and therefore hardly applicable to a real case study of 10000km2. In order to improve the efficiency of the calibration process, a stepwise calibration procedure is proposed. The stepwise methodology involves determining optimal parameters of all components of the coupled model, to provide a near optimum prior information for the global calibration. It starts with the surface component parameters calibration. The surface parameters are optimised based on the comparison between simulated and observed discharges (or filtered discharges) at various locations. Once the surface parameters
Technical note: Bayesian calibration of dynamic ruminant nutrition models.
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. PMID:27179874
WEPP: Model use, calibration and validation
Technology Transfer Automated Retrieval System (TEKTRAN)
The Water Erosion Prediction Project (WEPP) model is a process-based, continuous simulation, distributed parameter, hydrologic and soil erosion prediction system. It has been developed over the past 25 years to allow for easy application to a large number of land management scenarios. Most general o...
WEPP: Model use, calibration, and validation
Technology Transfer Automated Retrieval System (TEKTRAN)
The Water Erosion Prediction Project (WEPP) model is a process-based, continuous simulation, distributed parameter, hydrologic and soil erosion prediction system. It has been developed over the past 25 years to allow for easy application to a large number of land management scenarios. Most general o...
Bayesian Calibration of the Community Land Model using Surrogates
Ray, Jaideep; Hou, Zhangshuan; Huang, Maoyi; Sargsyan, K.; Swiler, Laura P.
2015-01-01
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, conditioned 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 accurate surrogate models can be created for CLM in most cases. The posterior distributions lead to better prediction 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 potentially be used to identify physical processes that could be contributing to it. While the calibrated CLM has a higher predictive skill, the calibration is under-dispersive.
Bayesian calibration of the Community Land Model using surrogates
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.
Simultaneous calibration of hydrological models in geographical space
NASA Astrophysics Data System (ADS)
Bárdossy, A.; Huang, Y.; Wagener, T.
2015-10-01
Hydrological models are usually calibrated for selected catchments individually using specific performance criteria. This procedure assumes that the catchments show individual behavior. As a consequence, the transfer of model parameters to other ungauged catchments is problematic. In this paper, the possibility of transferring part of the model parameters was investigated. Three different conceptual hydrological models were considered. The models were restructured by introducing a new parameter η which exclusively controls water balances. This parameter was considered as individual to each catchment. All other parameters, which mainly control the dynamics of the discharge (dynamical parameters), were considered for spatial transfer. Three hydrological models combined with three different performance measures were used in four different numerical experiments to investigate this transferability. The first numerical experiment, individual calibration of the models for 15 selected MOPEX catchments, showed that it is difficult to identify which catchments share common dynamical parameters. Parameters of one catchment might be good for another catchment but not reversed. In the second numerical experiment, a common spatial calibration strategy was used. It was explicitly assumed that the catchments share common dynamical parameters. This strategy leads to parameters which perform well on all catchments. A leave one out common calibration showed that in this case a good parameter transfer to ungauged catchments can be achieved. In the third numerical experiment, the common calibration methodology was applied for 96 catchments. Another set of 96 catchments were used to test the transfer of common dynamical parameters. The results show that even a large number of catchments share similar dynamical parameters. The performance is worse than those obtained by individual calibration, but the transfer to ungauged catchments remains possible. The performance of the common
Theoretical model atmosphere spectra used for the calibration of infrared instruments
NASA Astrophysics Data System (ADS)
Decin, L.; Eriksson, K.
2007-09-01
Context: One of the key ingredients in establishing the relation between input signal and output flux from a spectrometer is accurate determination of the spectrophotometric calibration. In the case of spectrometers onboard satellites, the accuracy of this part of the calibration pedigree is ultimately linked to the accuracy of the set of reference spectral energy distributions (SEDs) that the spectrophotometric calibration is built on. Aims: In this paper, we deal with the spectrophotometric calibration of infrared (IR) spectrometers onboard satellites in the 2 to 200 μm wavelength range. We aim at comparing the different reference SEDs used for the IR spectrophotometric calibration. The emphasis is on the reference SEDs of stellar standards with spectral type later than A0, with special focus on the theoretical model atmosphere spectra. Methods: Using the MARCS model atmosphere code, spectral reference SEDs were constructed for a set of IR stellar standards (A dwarfs, solar analogs, G9-M0 giants). A detailed error analysis was performed to estimate proper uncertainties on the predicted flux values. Results: It is shown that the uncertainty on the predicted fluxes can be as high as 10%, but in case high-resolution observational optical or near-IR data are available, and IR excess can be excluded, the uncertainty on medium-resolution SEDs can be reduced to 1-2% in the near-IR, to ~3% in the mid-IR, and to ~5% in the far-IR. Moreover, it is argued that theoretical stellar atmosphere spectra are at the moment the best representations for the IR fluxes of cool stellar standards. Conclusions: When aiming at a determination of the spectrophotometric calibration of IR spectrometers better than 3%, effort should be put into constructing an appropriate set of stellar reference SEDs based on theoretical atmosphere spectra for some 15 standard stars with spectral types between A0 V and M0 III.
Calibration of Automatically Generated Items Using Bayesian Hierarchical Modeling.
ERIC Educational Resources Information Center
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 (2001)…
Hydrologic and water quality models: Use, calibration, and validation
Technology Transfer Automated Retrieval System (TEKTRAN)
This paper introduces a special collection of 22 research articles that present and discuss calibration and validation concepts in detail for hydrologic and water quality models by their developers and presents a broad framework for developing the American Society of Agricultural and Biological Engi...
Hydrologic and water quality models: Key calibration and validation topics
Technology Transfer Automated Retrieval System (TEKTRAN)
As a continuation of efforts to provide a common background and platform for accordant development of calibration and validation (C/V) engineering practices, ASABE members worked to determine critical topics related to model C/V, perform a synthesis of the Moriasi et al. (2012) special collection of...
CALIBRATION OF A PREDICTIVE MODEL FOR INSTANTANEOUSLY DISCHARGED DREDGED MATERIAL
This report describes modifications to a computer model originally developed by R.C.Y. Koh and Y.C. Chang for predicting the physical fate of dredged material instantaneously released into a water column. Changes to the simulation include the calibration and verification of the p...
Calibration of Polytomous Item Families Using Bayesian Hierarchical Modeling
ERIC Educational Resources Information Center
Johnson, Matthew S.; Sinharay, Sandip
2005-01-01
For complex educational assessments, there is an increasing use of item families, which are groups of related items. Calibration or scoring in an assessment involving item families requires models that can take into account the dependence structure inherent among the items that belong to the same item family. This article extends earlier works in…
Robust camera calibration for sport videos using court models
NASA Astrophysics Data System (ADS)
Farin, Dirk; Krabbe, Susanne; de With, Peter H. N.; Effelsberg, Wolfgang
2003-12-01
We propose an automatic camera calibration algorithm for court sports. The obtained camera calibration parameters are required for applications that need to convert positions in the video frame to real-world coordinates or vice versa. Our algorithm uses a model of the arrangement of court lines for calibration. Since the court model can be specified by the user, the algorithm can be applied to a variety of different sports. The algorithm starts with a model initialization step which locates the court in the image without any user assistance or a-priori knowledge about the most probable position. Image pixels are classified as court line pixels if they pass several tests including color and local texture constraints. A Hough transform is applied to extract line elements, forming a set of court line candidates. The subsequent combinatorial search establishes correspondences between lines in the input image and lines from the court model. For the succeeding input frames, an abbreviated calibration algorithm is used, which predicts the camera parameters for the new image and optimizes the parameters using a gradient-descent algorithm. We have conducted experiments on a variety of sport videos (tennis, volleyball, and goal area sequences of soccer games). Video scenes with considerable difficulties were selected to test the robustness of the algorithm. Results show that the algorithm is very robust to occlusions, partial court views, bad lighting conditions, or shadows.
OXYGEN UTILIZATION IN ACTIVATED SLUDGE PLANTS: SIMULATION AND MODEL CALIBRATION
The objective of the research described in the report is to apply recent advances in activated sludge process modeling to the simulation of oxygen utilization rates in full scale activated sludge treatment plants. This is accomplished by calibrating the International Association ...
An Application of the Poisson Race Model to Confidence Calibration
ERIC Educational Resources Information Center
Merkle, Edgar C.; Van Zandt, Trisha
2006-01-01
In tasks as diverse as stock market predictions and jury deliberations, a person's feelings of confidence in the appropriateness of different choices often impact that person's final choice. The current study examines the mathematical modeling of confidence calibration in a simple dual-choice task. Experiments are motivated by an accumulator…
NASA Astrophysics Data System (ADS)
Bowers, C.; Gull, T.; Kimble, R.; Woodgate, B.; Kaiser, M.; Hartig, G.; Valenti, J.; Hood, D.; Sullivan, J.; Standley, C.; Beck, T.; Plait, P.; Sandoval, J.
1996-12-01
The Space Telescope Imaging Spectrograph (STIS) is a versatile, multi-purpose instrument which operates from the ultraviolet to near infrared (115-1000nm) aboard the Hubble Space Telescope (HST). An internal, two mirror relay system replaces COSTAR correcting the spherical aberration and astigmatism present at the STIS field position, about 6 arcminutes from the HST field center. The various STIS modes permit low and medium spectroscopy throughout the spectral range and over the 25 arc-second ultraviolet and 52 arcsecond visible fields. High resolution (30-100,000) echelle spectroscopy capability is provided in the ultraviolet (115-310nm). Broad band imaging is also possible over the complete spectral range and fields and a small selection of narrow and passband filters is available. A wide selection of slits and apertures permits various resolution and spatial scales to be selected in all modes. Coronagraphic stops are provided to permit observations in the visible (310 - 1000nm). On board calibration lamps permit wavelength calibration and flat fields to be obtained. Pre-flight calibration of STIS has been completed. We summarize the optical performance of STIS including measured resolution, scattering and encircled energy characterization in this paper.
Atmospheric drag model calibrations for spacecraft lifetime prediction
NASA Technical Reports Server (NTRS)
Binebrink, A. L.; Radomski, M. S.; Samii, M. V.
1989-01-01
Although solar activity prediction uncertainty normally dominates decay prediction error budget for near-Earth spacecraft, the effect of drag force modeling errors for given levels of solar activity needs to be considered. Two atmospheric density models, the modified Harris-Priester model and the Jacchia-Roberts model, to reproduce the decay histories of the Solar Mesosphere Explorer (SME) and Solar Maximum Mission (SMM) spacecraft in the 490- to 540-kilometer altitude range were analyzed. Historical solar activity data were used in the input to the density computations. For each spacecraft and atmospheric model, a drag scaling adjustment factor was determined for a high-solar-activity year, such that the observed annual decay in the mean semimajor axis was reproduced by an averaged variation-of-parameters (VOP) orbit propagation. The SME (SMM) calibration was performed using calendar year 1983 (1982). The resulting calibration factors differ by 20 to 40 percent from the predictions of the prelaunch ballistic coefficients. The orbit propagations for each spacecraft were extended to the middle of 1988 using the calibrated drag models. For the Jaccia-Roberts density model, the observed decay in the mean semimajor axis of SME (SMM) over the 4.5-year (5.5-year) predictive period was reproduced to within 1.5 (4.4) percent. The corresponding figure for the Harris-Priester model was 8.6 (20.6) percent. Detailed results and conclusions regarding the importance of accurate drag force modeling for lifetime predictions are presented.
Optical model and calibration of a sun tracker
NASA Astrophysics Data System (ADS)
Volkov, Sergei N.; Samokhvalov, Ignatii V.; Cheong, Hai Du; Kim, Dukhyeon
2016-09-01
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.
Calibration of longwavelength exotech model 20-C spectroradiometer
NASA Technical Reports Server (NTRS)
Kumar, R.; Robinson, B.; Silva, L.
1978-01-01
A brief description of the Exotech model 20-C field spectroradiometer which measures the spectral radiance of a target in the wavelength ranges 0.37 to 2.5 microns (short wavelength unit), 2.8 to 5.6 microns and 7.0 to 14 microns (long wavelength unit) is given. Wavelength calibration of long wavelength unit was done by knowing the strong, sharp and accurately known absorption bands of polystyrene, atmospheric carbon dioxide and methyl cyclohexane (liquid) in the infrared wavelength region. The spectral radiance calibration was done by recording spectral scans of the hot and the cold blackbodies and assuming that spectral radiance varies linearly with the signal.
Freire, Ricardo O; da Costa, Nivan B; Rocha, Gerd B; Simas, Alfredo M
2007-07-01
The Sparkle/PM3 model is extended to neodymium(III), promethium(III), and samarium(III) complexes. The unsigned mean error, for all Sparkle/PM3 interatomic distances between the trivalent lanthanide ion and the ligand atoms of the first sphere of coordination, is 0.074 Å for Nd(III); 0.057 Å for Pm(III); and 0.075 Å for Sm(III). These figures are similar to the Sparkle/AM1 ones of 0.076 Å, 0.059 Å, and 0.075 Å, respectively, indicating they are all comparable models. Moreover, their accuracy is similar to what can be obtained by present-day ab initio effective potential calculations on such lanthanide complexes. Hence, the choice of which model to utilize will depend on the assessment of the effect of either AM1 or PM3 on the quantum chemical description of the organic ligands. Finally, we present a preliminary attempt to verify the geometry prediction consistency of Sparkle/PM3. Since lanthanide complexes are usually flexible, we randomly generated 200 different input geometries for the samarium complex QIPQOV which were then fully optimized by Sparkle/PM3. A trend appeared in that, on average, the lower the total energy of the local minima found, the lower the unsigned mean errors, and the higher the accuracy of the model. These preliminary results do indicate that attempting to find, with Sparkle/PM3, a global minimum for the geometry of a given complex, with the understanding that it will tend to be closer to the experimental geometry, appears to be warranted. Therefore, the sparkle model is seemingly a trustworthy semiempirical quantum chemical model for the prediction of lanthanide complexes geometries. PMID:26633229
Residential vertical geothermal heat pump system models: Calibration to data
Thornton, J.W.; McDowell, T.P.; Shonder, J.A.; Hughes, P.J.; Pahud, D.; Hellstroem, G.A.J.
1997-12-31
A detailed component-based simulation model of a geothermal heat pump system has been calibrated to monitored data taken from a family housing unit located at Fort Polk, Louisiana. The simulation model represents the housing unit, geothermal heat pump, ground heat exchanger, thermostat, blower, and ground-loop pump. Each of these component models was tuned to better match the measured data from the site. These tuned models were then interconnected to form the system model. The system model was then exercised in order to demonstrate its capabilities.
Residential Vertical Geothermal Heat Pump System Models: Calibration to Data:
Thornton, Jeff W.; McDowell, T. P.; Shonder, John A; Hughes, Patrick; Pahud, D.; Hellstrom, G.
1997-06-01
A detailed component-based simulation model of a geothermal heat pump system has been calibrated to monitored data taken from a family housing unit located at Fort Polk, Louisiana. The simulation model represents the housing unit, geothermal heat pump, ground heat exchanger, thermostat, blower, and ground-loop pump. Each of these component models was 'tuned' to better match the measured data from the site. These tuned models were then interconnect to form the system model. The system model was then exercised in order to demonatrate its capabilities.
Zhang, Xuesong; Srinivasan, Ragahvan; Arnold, J. G.; Izaurralde, Roberto C.; Bosch, David
2011-04-21
Accurate analysis of water flow pathways from rainfall to streams is critical for simulating water use, climate change impact, and contaminants transport. In this study, we developed a new scheme to simultaneously calibrate surface flow (SF) and baseflow (BF) simulations of soil and water assessment tool (SWAT) by combing evolutionary multi-objective optimization (EMO) and BF separation techniques. The application of this scheme demonstrated pronounced trade-off of SWAT’s performance on SF and BF simulations. The simulated major water fluxes and storages variables (e.g. soil moisture, evapotranspiration, and groundwater) using the multiple parameters from EMO span wide ranges. Uncertainty analysis was conducted by Bayesian model averaging of the Pareto optimal solutions. The 90% confidence interval (CI) estimated using all streamflows substantially overestimate the uncertainty of low flows on BF days while underestimating the uncertainty of high flows on SF days. Despite using statistical criteria calculated based on streamflow for model selection, it is important to conduct diagnostic analysis of the agreement of SWAT behaviour and actual watershed dynamics. The new calibration technique can serve as a useful tool to explore the tradeoff between SF and BF simulations and provide candidates for further diagnostic assessment and model identification.
Analysis of Sting Balance Calibration Data Using Optimized Regression Models
NASA Technical Reports Server (NTRS)
Ulbrich, Norbert; Bader, Jon B.
2009-01-01
Calibration data of a wind tunnel sting balance was processed using a search algorithm that identifies an optimized regression model for the data analysis. The selected sting balance had two moment gages that were mounted forward and aft of the balance moment center. The difference and the sum of the two gage outputs were fitted in the least squares sense using the normal force and the pitching moment at the balance moment center as independent variables. The regression model search algorithm predicted that the difference of the gage outputs should be modeled using the intercept and the normal force. The sum of the two gage outputs, on the other hand, should be modeled using the intercept, the pitching moment, and the square of the pitching moment. Equations of the deflection of a cantilever beam are used to show that the search algorithm s two recommended math models can also be obtained after performing a rigorous theoretical analysis of the deflection of the sting balance under load. The analysis of the sting balance calibration data set is a rare example of a situation when regression models of balance calibration data can directly be derived from first principles of physics and engineering. In addition, it is interesting to see that the search algorithm recommended the same regression models for the data analysis using only a set of statistical quality metrics.
An Expectation-Maximization Method for Calibrating Synchronous Machine Models
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.
Transfer of multivariate calibration models between spectrometers: A progress report
Haaland, D.; Jones, H.; Rohrback, B.
1994-12-31
Multivariate calibration methods are extremely powerful for quantitative spectral analyses and have myriad uses in quality control and process monitoring. However, when analyses are to be completed at multiple sites or when spectrometers drift, recalibration is required. Often a full recalibration of an instrument can be impractical: the problem is particularly acute when the number of calibration standards is large or the standards chemically unstable. Furthermore, simply using Instrument A`s calibration model to predict unknowns on Instrument B can lead to enormous errors. Therefore, a mathematical procedure that would allow for the efficient transfer of a multivariate calibration model from one instrument to others using a small number of transfer standards is highly desirable. In this study, near-infrared spectral data have been collected from two sets of statistically designed round-robin samples on multiple FT-IR and grating spectrometers. One set of samples encompasses a series of dilute aqueous solutions of urea, creatinine, and NaCl while the second set is derived from mixtures of heptane, monochlorobenzene, and toluene. A systematic approach has been used to compare the results from four published transfer algorithms in order to determine parameters that affect the quality of the transfer for each class of sample and each type of spectrometer.
NASA Technical Reports Server (NTRS)
Lokos, William; Miller, Eric; Hudson, Larry; Holguin, Andrew; Neufeld, David; Haraguchi, Ronnie
2015-01-01
This paper describes the design and conduct of the strain gage load calibration ground test of the SubsoniC Research Aircraft Testbed, Gulfstream III aircraft, and the subsequent data analysis and its results. The goal of this effort was to create and validate multi-gage load equations for shear force, bending moment, and torque for two wing measurement stations. For some of the testing the aircraft was supported by three air bags in order to isolate the wing structure from extraneous load inputs through the main landing gear. Thirty-two strain gage bridges were installed on the left wing. Hydraulic loads were applied to the wing lower surface through a total of 16 load zones. Some dead weight load cases were applied to the upper wing surface using shot bags. Maximum applied loads reached 54,000 pounds.
Soybean Physiology Calibration in the Community Land Model
NASA Astrophysics Data System (ADS)
Drewniak, B. A.; Bilionis, I.; Constantinescu, E. M.
2014-12-01
With the large influence of agricultural land use on biophysical and biogeochemical cycles, integrating cultivation into Earth System Models (ESMs) is increasingly important. The Community Land Model (CLM) was augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. However, the strong nonlinearity of ESMs makes parameter fitting a difficult task. In this study, our goal is to calibrate ten of the CLM-Crop parameters for one crop type, soybean, in order to improve model projection of plant development and carbon fluxes. We used measurements of gross primary productivity, net ecosystem exchange, and plant biomass from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). Our scheme can perform model calibration using very few evaluations and, by exploiting parallelism, at a fraction of the time required by plain vanilla Markov Chain Monte Carlo (MCMC). We present the results from a twin experiment (self-validation) and calibration results and validation using real observations from an AmeriFlux tower site in the Midwestern United States, for the soybean crop type. The improved model will help researchers understand how climate affects crop production and resulting carbon fluxes, and additionally, how cultivation impacts climate.
Calibration of two complex ecosystem models with different likelihood functions
NASA Astrophysics Data System (ADS)
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
Computationally efficient calibration of WATCLASS Hydrologic models using surrogate optimization
NASA Astrophysics Data System (ADS)
Kamali, M.; Ponnambalam, K.; Soulis, E. D.
2007-07-01
In this approach, exploration of the cost function space was performed with an inexpensive surrogate function, not the expensive original function. The Design and Analysis of Computer Experiments(DACE) surrogate function, which is one type of approximate models, which takes correlation function for error was employed. The results for Monte Carlo Sampling, Latin Hypercube Sampling and Design and Analysis of Computer Experiments(DACE) approximate model have been compared. The results show that DACE model has a good potential for predicting the trend of simulation results. The case study of this document was WATCLASS hydrologic model calibration on Smokey-River watershed.
A controlled experiment in ground water flow model calibration
Hill, M.C.; Cooley, R.L.; Pollock, D.W.
1998-01-01
Nonlinear regression was introduced to ground water modeling in the 1970s, but has been used very little to calibrate numerical models of complicated ground water systems. Apparently, nonlinear regression is thought by many to be incapable of addressing such complex problems. With what we believe to be the most complicated synthetic test case used for such a study, this work investigates using nonlinear regression in ground water model calibration. Results of the study fall into two categories. First, the study demonstrates how systematic use of a well designed nonlinear regression method can indicate the importance of different types of data and can lead to successive improvement of models and their parameterizations. Our method differs from previous methods presented in the ground water literature in that (1) weighting is more closely related to expected data errors than is usually the case; (2) defined diagnostic statistics allow for more effective evaluation of the available data, the model, and their interaction; and (3) prior information is used more cautiously. Second, our results challenge some commonly held beliefs about model calibration. For the test case considered, we show that (1) field measured values of hydraulic conductivity are not as directly applicable to models as their use in some geostatistical methods imply; (2) a unique model does not necessarily need to be identified to obtain accurate predictions; and (3) in the absence of obvious model bias, model error was normally distributed. The complexity of the test case involved implies that the methods used and conclusions drawn are likely to be powerful in practice.Nonlinear regression was introduced to ground water modeling in the 1970s, but has been used very little to calibrate numerical models of complicated ground water systems. Apparently, nonlinear regression is thought by many to be incapable of addressing such complex problems. With what we believe to be the most complicated synthetic
Design of Experiments, Model Calibration and Data Assimilation
Williams, Brian J.
2014-07-30
This presentation provides an overview of emulation, calibration and experiment design for computer experiments. Emulation refers to building a statistical surrogate from a carefully selected and limited set of model runs to predict unsampled outputs. The standard kriging approach to emulation of complex computer models is presented. Calibration refers to the process of probabilistically constraining uncertain physics/engineering model inputs to be consistent with observed experimental data. An initial probability distribution for these parameters is updated using the experimental information. Markov chain Monte Carlo (MCMC) algorithms are often used to sample the calibrated parameter distribution. Several MCMC algorithms commonly employed in practice are presented, along with a popular diagnostic for evaluating chain behavior. Space-filling approaches to experiment design for selecting model runs to build effective emulators are discussed, including Latin Hypercube Design and extensions based on orthogonal array skeleton designs and imposed symmetry requirements. Optimization criteria that further enforce space-filling, possibly in projections of the input space, are mentioned. Designs to screen for important input variations are summarized and used for variable selection in a nuclear fuels performance application. This is followed by illustration of sequential experiment design strategies for optimization, global prediction, and rare event inference.
Spatial and Temporal Self-Calibration of a Hydroeconomic Model
NASA Astrophysics Data System (ADS)
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
Methane emission modeling with MCMC calibration for a boreal peatland
NASA Astrophysics Data System (ADS)
Raivonen, Maarit; Smolander, Sampo; Susiluoto, Jouni; Backman, Leif; Li, Xuefei; Markkanen, Tiina; Kleinen, Thomas; Makela, Jarmo; Aalto, Tuula; Rinne, Janne; Brovkin, Victor; Vesala, Timo
2016-04-01
Natural wetlands, particularly peatlands of the boreal latitudes, are a significant source of methane (CH4). At the moment, the emission estimates are highly uncertain. These natural emissions respond to climatic variability, so it is necessary to understand their dynamics, in order to be able to predict how they affect the greenhouse gas balance in the future. We have developed a model of CH4 production, oxidation and transport in boreal peatlands. It simulates production of CH4 as a proportion of anaerobic peat respiration, transport of CH4 and oxygen between the soil and the atmosphere via diffusion in aerenchymatous plants and in peat pores (water and air filled), ebullition and oxidation of CH4 by methanotrophic microbes. Ultimately, we aim to add the model functionality to global climate models such as the JSBACH (Reick et al., 2013), the land surface scheme of the MPI Earth System Model. We tested the model with measured methane fluxes (using eddy covariance technique) from the Siikaneva site, an oligotrophic boreal fen in southern Finland (61°49' N, 24°11' E), over years 2005-2011. To give the model estimates regional reliability, we calibrated the model using Markov chain Monte Carlo (MCMC) technique. Although the simulations and the research are still ongoing, preliminary results from the MCMC calibration can be described as very promising considering that the model is still at relatively early stage. We will present the model and its dynamics as well as results from the MCMC calibration and the comparison with Siikaneva flux data.
KINEROS2-AGWA: Model Use, Calibration, and Validation
NASA Technical Reports Server (NTRS)
Goodrich, D C.; Burns, I. S.; Unkrich, C. L.; Semmens, D. J.; Guertin, D. P.; Hernandez, M.; Yatheendradas, S.; Kennedy, J. R.; Levick, L. R..
2013-01-01
KINEROS (KINematic runoff and EROSion) originated in the 1960s as a distributed event-based model that conceptualizes a watershed as a cascade of overland flow model elements that flow into trapezoidal channel model elements. KINEROS was one of the first widely available watershed models that interactively coupled a finite difference approximation of the kinematic overland flow equations to a physically based infiltration model. Development and improvement of KINEROS continued from the 1960s on a variety of projects for a range of purposes, which has resulted in a suite of KINEROS-based modeling tools. This article focuses on KINEROS2 (K2), a spatially distributed, event-based watershed rainfall-runoff and erosion model, and the companion ArcGIS-based Automated Geospatial Watershed Assessment (AGWA) tool. AGWA automates the time-consuming tasks of watershed delineation into distributed model elements and initial parameterization of these elements using commonly available, national GIS data layers. A variety of approaches have been used to calibrate and validate K2 successfully across a relatively broad range of applications (e.g., urbanization, pre- and post-fire, hillslope erosion, erosion from roads, runoff and recharge, and manure transport). The case studies presented in this article (1) compare lumped to stepwise calibration and validation of runoff and sediment at plot, hillslope, and small watershed scales; and (2) demonstrate an uncalibrated application to address relative change in watershed response to wildfire.
Single-sludge nitrogen removal model: Calibration and verification
Argaman, Y.; Papkov, G. ); Ostfeld, A. ); Rubin, D. )
1999-07-01
The objective of this work was to calibrate and verify a modified version of a mathematical model of a single-sludge system for nitrification and denitrification. The new model is based on long-term experimental results, and the main modifications are related to the biological oxygen demand removal kinetics and biomass activity expressions. The model consists of 22 equations with 54 parameters, including 19 kinetic and stoichiometric coefficients. Experiments were performed on four bench-scale units and one pilot plant fed with domestic wastewater. Six sets of runs were carried out under different operational conditions. In the calibration procedure, a mathematical algorithm was implemented, in which an optimal set of coefficients was selected. Several coefficients were directly determined experimentally. Model verification was based on the comparison of experimental results with the values predicted by the mathematical model using a fixed set of model coefficients for each set of runs. From the verification results, the model is considered to be a useful one for the design of a new treatment system and operation of an existing one.
Design driven test patterns for OPC models calibration
NASA Astrophysics Data System (ADS)
Al-Imam, Mohamed
2009-03-01
In the modern photolithography process for manufacturing integrated circuits, geometry dimensions need to be realized on silicon which are much smaller than the exposure wavelength. Thus Resolution Enhancement Techniques have an indispensable role towards the implementation of a successful technology process node. Finding an appropriate RET recipe, that answers the needs of a certain fabrication process, usually involves intensive computational simulations. These simulations have to reflect how different elements in the lithography process under study will behave. In order to achieve this, accurate models are needed that truly represent the transmission of patterns from mask to silicon. A common practice in calibrating lithography models is to collect data for the dimensions of some test structures created on the exposure mask along with the corresponding dimensions of these test structures on silicon after exposure. This data is used to tune the models for good predictions. The models will be guaranteed to accurately predict the test structures that has been used in its tuning. However, real designs might have a much greater variety of structures that might not have been included in the test structures. This paper explores a method for compiling the test structures to be used in the model calibration process using design layouts as an input. The method relies on reducing structures in the design layout to the essential unique structure from the lithography models point of view, and thus ensuring that the test structures represent what the model would actually have to predict during the simulations.
Differences between GPS receiver antenna calibration models and influence on geodetic positioning
NASA Astrophysics Data System (ADS)
Baire, Q.; Bruyninx, C.; Pottiaux, E.; Legrand, J.; Aerts, W.
2012-12-01
Since April 2011, the igs08.atx antenna calibration model is used in the routine IGS (International GNSS Service) data analysis. The model includes mean robot calibrations to correct for the offset and phase center variations of the GNSS receiver antennas. These so-called "type" calibrations are means of the individual calibrations available for a specific antenna/radome combination. The aim of this study is to quantify the offset on the computed station positions when using different receiver antenna calibration models in the analysis. First, type calibrations are compared to individual receiver antenna calibrations. We analyze the observations of the 43 EUREF Permanent Network (EPN) stations equipped with individually calibrated receiver antenna over the period covering 2003 to 2010 using the Precise Point Positioning (PPP) technique. The difference between individual and type calibrations has a larger impact on the vertical component: the position offsets reach 4 mm in the horizontal components and 10 mm in the vertical component. In a second step, the effect of different individual calibration models of the same antenna on the positioning is assessed. For that purpose, data from several GNSS stations equipped with an antenna which has been individually calibrated at two calibration agencies are used. Those agencies are GEO++, performing robot calibrations, and University of Bonn, performing anechoic chamber calibrations, both recognized by the IGS. Initial results show that the position offsets induced by different calibration methods can reach 3 mm in the horizontal components and 7 mm in the vertical component.
Application of variance components estimation to calibrate geoid error models.
Guo, Dong-Mei; Xu, Hou-Ze
2015-01-01
The method of using Global Positioning System-leveling data to obtain orthometric heights has been well studied. A simple formulation for the weighted least squares problem has been presented in an earlier work. This formulation allows one directly employing the errors-in-variables models which completely descript the covariance matrices of the observables. However, an important question that what accuracy level can be achieved has not yet to be satisfactorily solved by this traditional formulation. One of the main reasons for this is the incorrectness of the stochastic models in the adjustment, which in turn allows improving the stochastic models of measurement noises. Therefore the issue of determining the stochastic modeling of observables in the combined adjustment with heterogeneous height types will be a main focus point in this paper. Firstly, the well-known method of variance component estimation is employed to calibrate the errors of heterogeneous height data in a combined least square adjustment of ellipsoidal, orthometric and gravimetric geoid. Specifically, the iterative algorithms of minimum norm quadratic unbiased estimation are used to estimate the variance components for each of heterogeneous observations. Secondly, two different statistical models are presented to illustrate the theory. The first method directly uses the errors-in-variables as a priori covariance matrices and the second method analyzes the biases of variance components and then proposes bias-corrected variance component estimators. Several numerical test results show the capability and effectiveness of the variance components estimation procedure in combined adjustment for calibrating geoid error model. PMID:26306296
Calibrating the Abaqus Crushable Foam Material Model using UNM Data
Schembri, Philip E.; Lewis, Matthew W.
2014-02-27
Triaxial test data from the University of New Mexico and uniaxial test data from W-14 is used to calibrate the Abaqus crushable foam material model to represent the syntactic foam comprised of APO-BMI matrix and carbon microballoons used in the W76. The material model is an elasto-plasticity model in which the yield strength depends on pressure. Both the elastic properties and the yield stress are estimated by fitting a line to the elastic region of each test response. The model parameters are fit to the data (in a non-rigorous way) to provide both a conservative and not-conservative material model. The model is verified to perform as intended by comparing the values of pressure and shear stress at yield, as well as the shear and volumetric stress-strain response, to the test data.
CALIBRATING STELLAR POPULATION MODELS WITH MAGELLANIC CLOUD STAR CLUSTERS
Noeel, N. E. D.; Carollo, C. M.; Greggio, L.; Renzini, A.; Maraston, C.
2013-07-20
Stellar population models are commonly calculated using star clusters as calibrators for those evolutionary stages that depend on free parameters. However, discrepancies exist among different models, even if similar sets of calibration clusters are used. With the aim of understanding these discrepancies, and of improving the calibration procedure, we consider a set of 43 Magellanic Cloud (MC) clusters, taking age and photometric information from the literature. We carefully assign ages to each cluster based on up-to-date determinations, ensuring that these are as homogeneous as possible. To cope with statistical fluctuations, we stack the clusters in five age bins, deriving for each of them integrated luminosities and colors. We find that clusters become abruptly red in optical and optical-infrared colors as they age from {approx}0.6 to {approx}1 Gyr, which we interpret as due to the development of a well-populated thermally pulsing asymptotic giant branch (TP-AGB). We argue that other studies missed this detection because of coarser age binnings. Maraston and Girardi et al. models predict the presence of a populated TP-AGB at {approx}0.6 Gyr, with a correspondingly very red integrated color, at variance with the data; Bruzual and Charlot and Conroy models run within the error bars at all ages. The discrepancy between the synthetic colors of Maraston models and the average colors of MC clusters results from the now obsolete age scale adopted. Finally, our finding that the TP-AGB phase appears to develop between {approx}0.6 and 1 Gyr is dependent on the adopted age scale for the clusters and may have important implications for stellar evolution.
Calibrating Building Energy Models Using Supercomputer Trained Machine Learning Agents
Sanyal, Jibonananda; New, Joshua Ryan; Edwards, Richard; Parker, Lynne Edwards
2014-01-01
Building Energy Modeling (BEM) is an approach to model the energy usage in buildings for design and retrofit purposes. EnergyPlus is the flagship Department of Energy software that performs BEM for different types of buildings. The input to EnergyPlus can often extend in the order of a few thousand parameters which have to be calibrated manually by an expert for realistic energy modeling. This makes it challenging and expensive thereby making building energy modeling unfeasible for smaller projects. In this paper, we describe the Autotune research which employs machine learning algorithms to generate agents for the different kinds of standard reference buildings in the U.S. building stock. The parametric space and the variety of building locations and types make this a challenging computational problem necessitating the use of supercomputers. Millions of EnergyPlus simulations are run on supercomputers which are subsequently used to train machine learning algorithms to generate agents. These agents, once created, can then run in a fraction of the time thereby allowing cost-effective calibration of building models.
Calibration of the crop processes in the climate community model
NASA Astrophysics Data System (ADS)
Constantinescu, E. M.; Drewniak, B. A.; Zeng, X.
2012-12-01
Farming is gaining significant terrestrial ground with increases in population and the expanding use of agriculture for non-nutritional uses such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to refine the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurements of GPP and NEE from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this research we aim to calibrate these parametric forms to provide a faithful projection both in terms of plant development and net carbon exchange. To this end, we propose a new calibration procedure based on a Bayesian approach, which is implemented through a parallel Markov chain Monte Carlo (MCMC) technique. We present the results from a twin experiment (self-validation) and calibration results and validation using real observations from AmeriFlux towers for two sites in the Midwestern U.S., rotating corn and soybean. Data from Bondville, IL and Mead, NE has been collected since the 1990's for GPP, NEE, and plant carbon. The improved model will enhance our understanding of how climate will effect crop production and resulting carbon fluxes and additionally, how cultivation will impact climate.
Calibration of a Groundwater Model of Masaya Volcano, Nicaragua
NASA Astrophysics Data System (ADS)
Sanford, W. E.; MacNeil, R. E.; Connor, C. B.
2005-05-01
Masaya Volcano consists of an active, 400-m-high, 6-km2, composite cone within a large (50-km2) basaltic caldera, and has a history of large phreatomagmatic eruptions. In order to better understand the hydrologic processes in this system, a groundwater model has been developed of the caldera using the USGS model MODFLOW. Transient electromagnetic (TEM) soundings were used to map the water table within the caldera. The water level of Lake Masaya, which occupies the lower one-fifth of the caldera, was used as a calibration point for the soundings. The TEM soundings revealed a water table mound beneath the cone, but not within the more permeable part of the caldera surrounding it. The differences between our estimated water levels inside the caldera and known regional water levels outside strongly suggest that the caldera walls are acting as hydrologic barriers, effectively isolating the groundwater-flow system within the caldera. A total of 29 estimated water levels and two ground-water-flux measurements were used to calibrate the model. The flux measurements were (1) a net flux into Lake Masaya of 1.2 m/yr, calculated from an estimate of lake evaporation and a transient lake-level record during the dry season, and (2) a net steam emission flux of 400 kg/sec from the active vent in Santiago crater. The lake and the steam vents are the only substantial discharges of groundwater within the caldera, each accounting for about half of the annual recharge. The steam discharge is substantially larger than other similar volcanoes in the world, suggesting its origin may be dominantly meteoric. The model calibration revealed that a deep, highly permeable layer must feed the active vent in order for the steam emissions to be maintained at their current levels. Quantifying this type of groundwater-vent interaction could be important to the understanding and prediction of future phreatomagmatic eruptions.
Parameter Calibration of Mini-LEO Hill Slope Model
NASA Astrophysics Data System (ADS)
Siegel, H.
2015-12-01
The mini-LEO hill slope, located at Biosphere 2, is a small-scale catchment model that is used to study the ways landscapes change in response to biological, chemical, and hydrological processes. Previous experiments have shown that soil heterogeneity can develop as a result of groundwater flow; changing the characteristics of the landscape. To determine whether or not flow has caused heterogeneity within the mini-LEO hill slope, numerical models were used to simulate the observed seepage flow, water table height, and storativity. To begin a numerical model of the hill slope was created using CATchment Hydrology (CATHY). The model was then brought to an initial steady state by applying a rainfall event of 5mm/day for 180 days. Then a specific rainfall experiment of alternating intensities was applied to the model. Next, a parameter calibration was conducted, to fit the model to the observed data, by changing soil parameters individually. The parameters of the best fitting calibration were taken to be the most representative of those present within the mini-LEO hill slope. Our model concluded that heterogeneities had indeed arisen as a result of the rainfall event, resulting in a lower hydraulic conductivity downslope. The lower hydraulic conductivity downslope in turn caused in an increased storage of water and a decrease in seepage flow compared to homogeneous models. This shows that the hydraulic processes acting within a landscape can change the very characteristics of the landscape itself, namely the permeability and conductivity of the soil. In the future results from the excavation of soil in mini-LEO can be compared to the models results to improve the model and validate its findings.
Dynamic calibration of agent-based models using data assimilation
Ward, Jonathan A.; Evans, Andrew J.; Malleson, Nicolas S.
2016-01-01
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. PMID:27152214
Dynamic calibration of agent-based models using data assimilation.
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. PMID:27152214
Air pollution modeling and its application III
De Wispelaere, C.
1984-01-01
This book focuses on the Lagrangian modeling of air pollution. Modeling cooling tower and power plant plumes, modeling the dispersion of heavy gases, remote sensing as a tool for air pollution modeling, dispersion modeling including photochemistry, and the evaluation of model performances in practical applications are discussed. Specific topics considered include dispersion in the convective boundary layer, the application of personal computers to Lagrangian modeling, the dynamic interaction of cooling tower and stack plumes, the diffusion of heavy gases, correlation spectrometry as a tool for mesoscale air pollution modeling, Doppler acoustic sounding, tetroon flights, photochemical air quality simulation modeling, acid deposition of photochemical oxidation products, atmospheric diffusion modeling, applications of an integral plume rise model, and the estimation of diffuse hydrocarbon leakages from petrochemical factories. This volume constitutes the proceedings of the Thirteenth International Technical Meeting on Air Pollution Modeling and Its Application held in France in 1982.
Simple parametric model for intensity calibration of Cassini composite infrared spectrometer data.
Brasunas, J; Mamoutkine, A; Gorius, N
2016-06-10
Accurate intensity calibration of a linear Fourier-transform spectrometer typically requires the unknown science target and the two calibration targets to be acquired under identical conditions. We present a simple model suitable for vector calibration that enables accurate calibration via adjustments of measured spectral amplitudes and phases when these three targets are recorded at different detector or optics temperatures. Our model makes calibration more accurate both by minimizing biases due to changing instrument temperatures that are always present at some level and by decreasing estimate variance through incorporating larger averages of science and calibration interferogram scans. PMID:27409028
New NIR Calibration Models Speed Biomass Composition and Reactivity Characterization
2015-09-01
Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. This highlight describes NREL's work to use near-infrared (NIR) spectroscopy and partial least squares multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. This highlight is being developed for the September 2015 Alliance S&T Board meeting.
Recent Improvements to the Calibration Models for RXTE/PCA
NASA Technical Reports Server (NTRS)
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.
NASA Technical Reports Server (NTRS)
Lokos, William A.; Miller, Eric J.; Hudson, Larry D.; Holguin, Andrew C.; Neufeld, David C.; Haraguchi, Ronnie
2015-01-01
This paper describes the design and conduct of the strain-gage load calibration ground test of the SubsoniC Research Aircraft Testbed, Gulfstream III aircraft, and the subsequent data analysis and results. The goal of this effort was to create and validate multi-gage load equations for shear force, bending moment, and torque for two wing measurement stations. For some of the testing the aircraft was supported by three airbags in order to isolate the wing structure from extraneous load inputs through the main landing gear. Thirty-two strain gage bridges were installed on the left wing. Hydraulic loads were applied to the wing lower surface through a total of 16 load zones. Some dead-weight load cases were applied to the upper wing surface using shot bags. Maximum applied loads reached 54,000 lb. Twenty-six load cases were applied with the aircraft resting on its landing gear, and 16 load cases were performed with the aircraft supported by the nose gear and three airbags around the center of gravity. Maximum wing tip deflection reached 17 inches. An assortment of 2, 3, 4, and 5 strain-gage load equations were derived and evaluated against independent check cases. The better load equations had root mean square errors less than 1 percent. Test techniques and lessons learned are discussed.
Optimal calibration method for water distribution water quality model.
Wu, Zheng Yi
2006-01-01
A water quality model is to predict water quality transport and fate throughout a water distribution system. The model is not only a promising alternative for analyzing disinfectant residuals in a cost-effective manner, but also a means of providing enormous engineering insights into the characteristics of water quality variation and constituent reactions. However, a water quality model is a reliable tool only if it predicts what a real system behaves. This paper presents a methodology that enables a modeler to efficiently calibrate a water quality model such that the field observed water quality values match with the model simulated values. The method is formulated to adjust the global water quality parameters and also the element-dependent water quality reaction rates for pipelines and tank storages. A genetic algorithm is applied to optimize the model parameters by minimizing the difference between the model-predicted values and the field-observed values. It is seamlessly integrated with a well-developed hydraulic and water quality modeling system. The approach has provided a generic tool and methodology for engineers to construct the sound water quality model in expedient manner. The method is applied to a real water system and demonstrated that a water quality model can be optimized for managing adequate water supply to public communities. PMID:16854809
Testing calibration routines for LISFLOOD, a distributed hydrological model
NASA Astrophysics Data System (ADS)
Pannemans, B.
2009-04-01
Traditionally hydrological models are considered as difficult to calibrate: their highly non-linearity results in rugged and rough response surfaces were calibration algorithms easily get stuck in local minima. For the calibration of distributed hydrological models two extra factors play an important role: on the one hand they are often costly on computation, thus restricting the feasible number of model runs; on the other hand their distributed nature smooths the response surface, thus facilitating the search for a global minimum. Lisflood is a distributed hydrological model currently used for the European Flood Alert System - EFAS (Van der Knijff et al, 2008). Its upcoming recalibration over more then 200 catchments, each with an average runtime of 2-3 minutes, proved a perfect occasion to put several existing calibration algorithms to the test. The tested routines are Downhill Simplex (DHS, Nelder and Mead, 1965), SCEUA (Duan et Al. 1993), SCEM (Vrugt et al., 2003) and AMALGAM (Vrugt et al., 2008), and they were evaluated on their capability to efficiently converge onto the global minimum and on the spread in the found solutions in repeated runs. The routines were let loose on a simple hyperbolic function, on a Lisflood catchment using model output as observation, and on two Lisflood catchments using real observations (one on the river Inn in the Alps, the other along the downstream stretch of the Elbe). On the mathematical problem and on the catchment with synthetic observations DHS proved to be the fastest and the most efficient in finding a solution. SCEUA and AMALGAM are a slower, but while SCEUA keeps converging on the exact solution, AMALGAM slows down after about 600 runs. For the Lisflood models with real-time observations AMALGAM (hybrid algorithm that combines several other algorithms, we used CMA, PSO and GA) came as fastest out of the tests, and giving comparable results in consecutive runs. However, some more work is needed to tweak the stopping
Empirical calibration of the near-infrared Ca II triplet - III. Fitting functions
NASA Astrophysics Data System (ADS)
Cenarro, A. J.; Gorgas, J.; Cardiel, N.; Vazdekis, A.; Peletier, R. F.
2002-02-01
Using a near-infrared stellar library of 706 stars with a wide coverage of atmospheric parameters, we study the behaviour of the CaII triplet strength in terms of effective temperature, surface gravity and metallicity. Empirical fitting functions for recently defined line-strength indices, namely CaT*, CaT and PaT, are provided. These functions can be easily implemented into stellar population models to provide accurate predictions for integrated CaII strengths. We also present a thorough study of the various error sources and their relation to the residuals of the derived fitting functions. Finally, the derived functional forms and the behaviour of the predicted CaII are compared with those of previous works in the field.
Differential Evolution algorithm applied to FSW model calibration
NASA Astrophysics Data System (ADS)
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.
Model Free Gate Design and Calibration For Superconducting Qubits
NASA Astrophysics Data System (ADS)
Egger, Daniel; Wilhelm, Frank
2014-03-01
Gates for superconducting qubits are realized by time dependent control pulses. The pulse shape for a specific gate depends on the parameters of the superconducting qubits, e.g. frequency and non-linearity. Based on ones knowledge of these parameters and using a specific model the pulse shape is determined either analytically or numerically using optimal control [arXiv:1306.6894, arXiv:1306.2279]. However the performance of the pulse is limited by the accuracy of the model. For a pulse with few parameters this is generally not a problem since it can be ``debugged'' manually. He we present an automated method for calibrating multiparameter pulses. We use the Nelder-Mead simplex method to close the control loop. This scheme uses the experiment as feedback and thus does not need a model. It requires few iterations and circumvents process tomogrophy, therefore making it a fast and versatile tool for gate design.
Mars Entry Atmospheric Data System Modeling, Calibration, and Error Analysis
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.; VanNorman, John; Siemers, Paul M.; Schoenenberger, Mark; Munk, Michelle M.
2014-01-01
The Mars Science Laboratory (MSL) Entry, Descent, and Landing Instrumentation (MEDLI)/Mars Entry Atmospheric Data System (MEADS) project installed seven pressure ports through the MSL Phenolic Impregnated Carbon Ablator (PICA) heatshield to measure heatshield surface pressures during entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. In particular, the quantities to be estimated from the MEADS pressure measurements include the dynamic pressure, angle of attack, and angle of sideslip. This report describes the calibration of the pressure transducers utilized to reconstruct the atmospheric data and associated uncertainty models, pressure modeling and uncertainty analysis, and system performance results. The results indicate that the MEADS pressure measurement system hardware meets the project requirements.
Regional calibration of the Pitman model for the Okavango River
NASA Astrophysics Data System (ADS)
Hughes, Denis A.; Andersson, Lotta; Wilk, Julie; Savenije, Hubert H. G.
2006-11-01
SummaryThis paper reports on the application of a monthly rainfall-runoff model for the Okavango River Basin. Streamflow is mainly generated in Angola where the Cuito and Cubango rivers arise. They then join and cross the Namibia/Angola border, flowing into the Okavango wetland in Botswana. The model is a modified version of the Pitman model, including more explicit ground and surface water interactions. Significant limitations in access to climatological data, and lack of sufficiently long records of observed flow for the eastern sub-basins represent great challenges to model calibration. The majority of the runoff is generated in the wetter headwater tributaries, while the lower sub-basins are dominated by channel loss processes with very little incremental flow contributions, even during wet years. The western tributaries show significantly higher seasonal variation in flow, compared to the baseflow dominated eastern tributaries: observations that are consistent with their geological differences. The basin was sub-divided into 24 sub-basins, of which 18 have gauging stations at their outlet. Satisfactory simulations were achieved with sub-basin parameter value differences that correspond to the spatial variability in basin physiographic characteristics. The limited length of historical rainfall and river discharge data over Angola precluded the use of a split sample calibration/validation test. However, satellite generated rainfall data, revised to reflect the same frequency characteristics as the historical rainfall data, were used to validate the model against the available downstream flow data during the 1990s. The overall conclusion is that the model, in spite of the limited data access, adequately represents the hydrological response of the basin and that it can be used to assess the impact of future development scenarios.
Calibration Modeling Methodology to Optimize Performance for Low Range Applications
NASA Technical Reports Server (NTRS)
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.
A Solvatochromic Model Calibrates Nitriles’ Vibrational Frequencies to Electrostatic Fields
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
Bayesian calibration of hyperelastic constitutive models of soft tissue.
Madireddy, Sandeep; Sista, Bhargava; Vemaganti, Kumar
2016-06-01
There is inherent variability in the experimental response used to characterize the hyperelastic mechanical response of soft tissues. This has to be accounted for while estimating the parameters in the constitutive models to obtain reliable estimates of the quantities of interest. The traditional least squares method of parameter estimation does not give due importance to this variability. We use a Bayesian calibration framework based on nested Monte Carlo sampling to account for the variability in the experimental data and its effect on the estimated parameters through a systematic probability-based treatment. We consider three different constitutive models to represent the hyperelastic nature of soft tissue: Mooney-Rivlin model, exponential model, and Ogden model. Three stress-strain data sets corresponding to the deformation of agarose gel, bovine liver tissue, and porcine brain tissue are considered. Bayesian fits and parameter estimates are compared with the corresponding least squares values. Finally, we propagate the uncertainty in the parameters to a quantity of interest (QoI), namely the force-indentation response, to study the effect of model form on the values of the QoI. Our results show that the quality of the fit alone is insufficient to determine the adequacy of the model, and due importance has to be given to the maximum likelihood value, the landscape of the likelihood distribution, and model complexity. PMID:26751706
Modeling Prairie Pothole Lakes: Linking Satellite Observation and Calibration (Invited)
NASA Astrophysics Data System (ADS)
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
Statistical modeling support for calibration of a multiphysics model of subcooled boiling flows
Bui, A. V.; Dinh, N. T.; Nourgaliev, R. R.; Williams, B. J.
2013-07-01
Nuclear reactor system analyses rely on multiple complex models which describe the physics of reactor neutronics, thermal hydraulics, structural mechanics, coolant physico-chemistry, etc. Such coupled multiphysics models require extensive calibration and validation before they can be used in practical system safety study and/or design/technology optimization. This paper presents an application of statistical modeling and Bayesian inference in calibrating an example multiphysics model of subcooled boiling flows which is widely used in reactor thermal hydraulic analysis. The presence of complex coupling of physics in such a model together with the large number of model inputs, parameters and multidimensional outputs poses significant challenge to the model calibration method. However, the method proposed in this work is shown to be able to overcome these difficulties while allowing data (observation) uncertainty and model inadequacy to be taken into consideration. (authors)
Impact of different individual GNSS receiver antenna calibration models on geodetic positioning
NASA Astrophysics Data System (ADS)
Baire, Q.; Pottiaux, E.; Bruyninx, C.; Defraigne, P.; Aerts, W.; Legrand, J.; Bergeot, N.; Chevalier, J. M.
2012-04-01
Since April 2011, the igs08.atx antenna calibration model is used in the routine IGS (International GNSS Service) data analysis. The model includes mean robot calibrations to correct for the offset and phase center variations of the GNSS receiver antennas. These so-called "type" calibrations are means of the individual calibrations available for a specific antenna/radome combination. The GNSS data analysis performed within the EUREF Permanent Network (EPN) aims at being as consistent as possible with the IGS analysis. This also applies to the receiver antenna calibrations. However, when available, individual antenna calibrations are used within the EPN analysis instead of the "type" calibration. When these individual calibrations are unavailable, then the EPN analysis falls back to (type) calibrations identical as the ones used within the IGS (igs08.atx). The aim of this study is to evaluate the significance of the offset caused by using different receiver antenna calibration models on the station position. Using the PPP (Precise Point Positioning) technique, we first investigate the differences in positioning obtained when switching between individual antenna calibrations and type calibrations. We analyze the observations of the 43 EPN stations equipped with receiver antenna individually calibrated over the period covering from 2003 to 2010 and we show that these differences can reach up to 4 mm in horizontal and 10 mm in vertical. Secondly, we study the accuracy of the individual calibrations models and we evaluate the effect of different sets of individual calibrations on the positioning. For that purpose, we use the data from 6 GNSS stations equipped with an antenna which has been individually calibrated at two calibration facilities recognized by the IGS: GEO++ and Bonn institute.
Development of Metropolitan (CITY III) Model. Final Report.
ERIC Educational Resources Information Center
House, Peter
CITY III, a computer-assisted simulation model to be used in the study of complex interactions and consequences of public and private decision-making in an urban setting, is described in this report. The users of the model, with the help of a computer, become public and private decision-makers in a simulated city and, by interacting with one…
A New Perspective for the Calibration of Computational Predictor Models.
Crespo, Luis Guillermo
2014-11-01
This paper presents a framework for calibrating computational models using data from sev- eral and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncer- tainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of obser- vations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it is a description of the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain (i.e., roll-up and extrapolation).
Calibration of Predictor Models Using Multiple Validation Experiments
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.
2015-01-01
This paper presents a framework for calibrating computational models using data from several and possibly dissimilar validation experiments. The offset between model predictions and observations, which might be caused by measurement noise, model-form uncertainty, and numerical error, drives the process by which uncertainty in the models parameters is characterized. The resulting description of uncertainty along with the computational model constitute a predictor model. Two types of predictor models are studied: Interval Predictor Models (IPMs) and Random Predictor Models (RPMs). IPMs use sets to characterize uncertainty, whereas RPMs use random vectors. The propagation of a set through a model makes the response an interval valued function of the state, whereas the propagation of a random vector yields a random process. Optimization-based strategies for calculating both types of predictor models are proposed. Whereas the formulations used to calculate IPMs target solutions leading to the interval value function of minimal spread containing all observations, those for RPMs seek to maximize the models' ability to reproduce the distribution of observations. Regarding RPMs, we choose a structure for the random vector (i.e., the assignment of probability to points in the parameter space) solely dependent on the prediction error. As such, the probabilistic description of uncertainty is not a subjective assignment of belief, nor is it expected to asymptotically converge to a fixed value, but instead it casts the model's ability to reproduce the experimental data. This framework enables evaluating the spread and distribution of the predicted response of target applications depending on the same parameters beyond the validation domain.
Pseudo-Reaction Zone model calibration for Programmed Burn calculations
NASA Astrophysics Data System (ADS)
Chiquete, Carlos; Meyer, Chad D.; Quirk, James J.; Short, Mark
2015-06-01
The Programmed Burn (PB) engineering methodology for efficiently calculating detonation timing and energy delivery within high explosive (HE) engineering geometries separates the calculation of these two core components. Modern PB approaches utilize Detonation Shock Dynamics (DSD) to provide accurate time-of-arrival information throughout a given geometry, via an experimentally calibrated propagation law relating the surface normal velocity to its local curvature. The Pseudo-Reaction Zone (PRZ) methodology is then used to release the explosive energy in a finite span following the prescribed arrival of the DSD propagated front through a reactive, hydrodynamic calculation. The PRZ energy release rate must be coupled to the local burn velocity set by the DSD surface evolution. In order to synchronize the energy release to the attendant timing calculation, detonation velocity and front shapes resulting from reactive burn simulations utilizing the PRZ rate law and parameters will be fitted to analogues generated via the applied DSD propagation law, thus yielding the PRZ model calibration for the HE.
Application of Extended Kalman Filter Techniques for Dynamic Model Parameter Calibration
Huang, Zhenyu; Du, Pengwei; Kosterev, Dmitry; Yang, Bo
2009-07-26
Abstract -Phasor measurement has previously been used for sub-system model validation, which enables rigorous comparison of model simulation and recorded dynamics and facilitates identification of problematic model components. Recent work extends the sub-system model validation approach with a focus on how model parameters may be calibrated to match recorded dynamics. In this paper, a calibration method using Extended Kalman Filter (EKF) technique is proposed. This paper presents the formulation as well as case studies to show the validity of the EKF-based parameter calibration method. The proposed calibration method is expected to be a cost-effective means complementary to traditional equipment testing for improving dynamic model quality.
Operation and calibration of the Wincharger 450 model SWECS
NASA Astrophysics Data System (ADS)
Bryant, P. J.; Boeh, M.
This paper presents an analysis of the operation of the new 450 model Wincharger. Assembly, testing, output power calibrations and other operational parameters are presented. Techniques of testing are described, including the use of a pickup truck for Controlled Velocity Tests (CVT). The measured output power was just above the rated values when only 12 volts was applied to the generator field. When a separate and constant 15 volt field was applied the output ranged from 46 watts for a 10 mi/h wind speed to 1146 watts for 35 mi/h. At the rated 25 mi/h speed an output of 774 watts was obtained by tuning a resistive load. These values are much greater than the ratings for this unit. However, it is being tested here with a separate field supply and without a voltage regulator.
NASA Astrophysics Data System (ADS)
Ingraham, Patrick; Ruffio, Jean-Baptiste; Perrin, Marshall D.; Wolff, Schuyler G.; Draper, Zachary H.; Maire, Jerome; Marchis, Franck; Fesquet, Vincent
2014-07-01
The newly commissioned Gemini Planet Imager (GPI) combines extreme adaptive optics, an advanced coronagraph, precision wavefront control and a lenslet-based integral field spectrograph (IFS) to measure the spectra of young extrasolar giant planets between 0.9-2.5 μm. Each GPI detector image, when in spectral model, consists of ~37,000 microspectra which are under or critically sampled in the spatial direction. This paper demonstrates how to obtain high-resolution microlens PSFs and discusses their use in enhancing the wavelength calibration, flexure compensation and spectral extraction. This method is generally applicable to any lenslet-based integral field spectrograph including proposed future instrument concepts for space missions.
Interplanetary density models as inferred from solar Type III bursts
NASA Astrophysics Data System (ADS)
Oppeneiger, Lucas; Boudjada, Mohammed Y.; Lammer, Helmut; Lichtenegger, Herbert
2016-04-01
We report on the density models derived from spectral features of solar Type III bursts. They are generated by beams of electrons travelling outward from the Sun along open magnetic field lines. Electrons generate Langmuir waves at the plasma frequency along their ray paths through the corona and the interplanetary medium. A large frequency band is covered by the Type III bursts from several MHz down to few kHz. In this analysis, we consider the previous empirical density models proposed to describe the electron density in the interplanetary medium. We show that those models are mainly based on the analysis of Type III bursts generated in the interplanetary medium and observed by satellites (e.g. RAE, HELIOS, VOYAGER, ULYSSES,WIND). Those models are confronted to stereoscopic observations of Type III bursts recorded by WIND, ULYSSES and CASSINI spacecraft. We discuss the spatial evolution of the electron beam along the interplanetary medium where the trajectory is an Archimedean spiral. We show that the electron beams and the source locations are depending on the choose of the empirical density models.
Technology Transfer Automated Retrieval System (TEKTRAN)
Accurate analysis of water flow pathways from rainfall to streams is critical for simulating water use, climate change impact, and contaminant transport. In this study, we developed a new scheme to simultaneously calibrate surface flow (SF) and baseflow (BF) simulations of Soil and Water Assessment ...
Hotspot detection and design recommendation using silicon calibrated CMP model
NASA Astrophysics Data System (ADS)
Hui, Colin; Wang, Xian Bin; Huang, Haigou; Katakamsetty, Ushasree; Economikos, Laertis; Fayaz, Mohammed; Greco, Stephen; Hua, Xiang; Jayathi, Subramanian; Yuan, Chi-Min; Li, Song; Mehrotra, Vikas; Chen, Kuang Han; Gbondo-Tugbawa, Tamba; Smith, Taber
2009-03-01
Chemical Mechanical Polishing (CMP) has been used in the manufacturing process for copper (Cu) damascene process. It is well known that dishing and erosion occur during CMP process, and they strongly depend on metal density and line width. The inherent thickness and topography variations become an increasing concern for today's designs running through advanced process nodes (sub 65nm). Excessive thickness and topography variations can have major impacts on chip yield and performance; as such they need to be accounted for during the design stage. In this paper, we will demonstrate an accurate physics based CMP model and its application for CMP-related hotspot detection. Model based checking capability is most useful to identify highly environment sensitive layouts that are prone to early process window limitation and hence failure. Model based checking as opposed to rule based checking can identify more accurately the weak points in a design and enable designers to provide improved layout for the areas with highest leverage for manufacturability improvement. Further, CMP modeling has the ability to provide information on interlevel effects such as copper puddling from underlying topography that cannot be captured in Design-for- Manufacturing (DfM) recommended rules. The model has been calibrated against the silicon produced with the 45nm process from Common Platform (IBMChartered- Samsung) technology. It is one of the earliest 45nm CMP models available today. We will show that the CMP-related hotspots can often occur around the spaces between analog macros and digital blocks in the SoC designs. With the help of the CMP model-based prediction, the design, the dummy fill or the placement of the blocks can be modified to improve planarity and eliminate CMP-related hotspots. The CMP model can be used to pass design recommendations to designers to improve chip yield and performance.
Using Runoff Data to Calibrate the Community Land Model
NASA Astrophysics Data System (ADS)
Ray, J.; Hou, Z.; Huang, M.; Swiler, L.
2014-12-01
We present a statistical method for calibrating the Community Land Model (CLM) using streamflow observations collected between 1999 and 2008 at the outlet of two river basins from the Model Parameter Estimation Experiment (MOPEX), Oostanaula River at Resaca GA, and Walnut River at Winfield KS.. The observed streamflow shows variability over a large range of time-scales, none of which significantly dominates the others; consequently, the time-series seems noisy and is difficult to be directly used in model parameter estimation efforts without significant filtering. We perform a multi-resolution wavelet decomposition of the observed streamflow, and use the wavelet power coefficients (WPC) as the tuning data. We construct a mapping (a surrogate model) between WPC and three hydrological parameters of the CLM using a training set of 256 CLM runs. The dependence of WPC on the parameters is complex and cannot be captured using a surrogate unless the parameter combinations yield physically plausible model predictions, i.e., those that are skillful when compared to observations. Retaining only the top quartile of the runs ensures skillfulness, as measured by the RMS error between observations and CLM predictions. This "screening" of the training data yields a region (the "valid" region) in the parameter space where accurate surrogate models can be created. We construct a classifier for the "valid" region, and, in conjunction with the surrogate models for WPC, pose a Bayesian inverse problem for the three hydrological parameters. The inverse problem is solved using an adaptive Markov chain Monte Carlo (MCMC) method to construct a three-dimensional posterior distribution for the hydrological parameters. Posterior predictive tests using the surrogate model reveal that the posterior distribution is more predictive than the nominal values of the parameters, which are used as default values in the current version of CLM. The effectiveness of the inversion is then validated by
Calibration and testing or models of the global carbon cycle
Emanuel, W.R.; Killough, G.G.; Shugart, H.H. Jr.
1980-01-01
A ten-compartment model of the global biogeochemical cycle of carbon is presented. The two less-abundant isotopes of carbon, /sup 13/C and /sup 14/C, as well as total carbon, are considered. The cycling of carbon in the ocean is represented by two well-mixed compartments and in the world's terrestrial ecosystems by seven compartments, five which are dynamic and two with instantaneous transfer. An internally consistent procedure for calibrating this model against an assumed initial steady state is discussed. In particular, the constraint that the average /sup 13/C//sup 12/C ratio in the total flux from the terrestrial component of the model to the atmosphere be equal to that of the steady-state atmosphere is investigated. With this additional constraint, the model provides a more accurate representation of the influence of the terrestrial system on the /sup 13/C//sup 12/C ratio of the atmosphere and provides an improved basis for interpreting records, such as tree rings, reflecting historical changes in this ratio.
NASA Astrophysics Data System (ADS)
Razavi, S.; Anderson, D.; Martin, P.; MacMillan, G.; Tolson, B.; Gabriel, C.; Zhang, B.
2012-12-01
Many sophisticated groundwater models tend to be computationally intensive as they rigorously represent detailed scientific knowledge about the groundwater systems. Calibration (model inversion), which is a vital step of groundwater model development, can require hundreds or thousands of model evaluations (runs) for different sets of parameters and as such demand prohibitively large computational time and resources. One common strategy to circumvent this computational burden is surrogate modelling which is concerned with developing and utilizing fast-to-run surrogates of the original computationally intensive models (also called fine models). Surrogates can be either based on statistical and data-driven models such as kriging and neural networks or simplified physically-based models with lower fidelity to the original system (also called coarse models). Fidelity in this context refers to the degree of the realism of a simulation model. This research initially investigates different strategies for developing lower-fidelity surrogates of a fine groundwater model and their combinations. These strategies include coarsening the fine model, relaxing the numerical convergence criteria, and simplifying the model geological conceptualisation. Trade-offs between model efficiency and fidelity (accuracy) are of special interest. A methodological framework is developed for coordinating the original fine model with its lower-fidelity surrogates with the objective of efficiently calibrating the parameters of the original model. This framework is capable of mapping the original model parameters to the corresponding surrogate model parameters and also mapping the surrogate model response for the given parameters to the original model response. This framework is general in that it can be used with different optimization and/or uncertainty analysis techniques available for groundwater model calibration and parameter/predictive uncertainty assessment. A real-world computationally
A cosmic dust influx model. III
NASA Astrophysics Data System (ADS)
Lebedinets, V. N.; Begkhanov, M.
A model of cosmic dust influx is developed using results of radar and photographic studies of meteors and bolides, micrometeor impact data obtained during space missions, and the available experimental data on dust particles as small as 10 to the -17th g. It is shown, in particular, that particles of all sizes occurring above 30 km are mainly of meteor origin. Above 140 km, the earth atmosphere contains only primary cosmic particles of all sizes whose concentrations are equal to those observed in the interplanetary space but whose flux densities are twice as high. Above 30 km and below 100 km, the atmosphere contains primary micrometeor particles with masses less than 10 to the -8th g and particles of the same mass formed as a result of the fragmentation of large meteoric bodies.
Achleitner, S; Rinderer, M; Kirnbauer, R
2009-01-01
For the Tyrolean part of the river Inn, a hybrid model for flood forecast has been set up and is currently in its test phase. The system is a hybrid system which comprises of a hydraulic 1D model for the river Inn, and the hydrological models HQsim (Rainfall-runoff-discharge model) and the snow and ice melt model SES for modeling the rainfall runoff form non-glaciated and glaciated tributary catchment respectively. Within this paper the focus is put on the hydrological modeling of the totally 49 connected non-glaciated catchments realized with the software HQsim. In the course of model calibration, the identification of the most sensitive parameters is important aiming at an efficient calibration procedure. The indicators used for explaining the parameter sensitivities were chosen specifically for the purpose of flood forecasting. Finally five model parameters could be identified as being sensitive for model calibration when aiming for a well calibrated model for flood conditions. In addition two parameters were identified which are sensitive in situations where the snow line plays an important role. PMID:19759453
View of a five inch standard Mark III model 1 ...
View of a five inch standard Mark III model 1 #39, manufactured in 1916 at the naval gun factory waterveliet, NY; this is the only gun remaining on olympia dating from the period when it was in commission; note ammunition lift at left side of photograph. (p36) - USS Olympia, Penn's Landing, 211 South Columbus Boulevard, Philadelphia, Philadelphia County, PA
Test data sets for calibration of stochastic and fractional stochastic volatility models.
Pospíšil, Jan; Sobotka, Tomáš
2016-09-01
Data for calibration and out-of-sample error testing of option pricing models are provided alongside data obtained from optimization procedures in "On calibration of stochastic and fractional stochastic volatility models" [1]. Firstly we describe testing data sets, further calibration data obtained from combined optimizers is visually depicted - interactive 3d bar plots are provided. The data is suitable for a further comparison of other optimization routines and also to benchmark different pricing models. PMID:27419200
NASA Astrophysics Data System (ADS)
Aggett, Graeme; Spies, Ryan; Szfranski, Bill; Hahn, Claudia; Weil, Page
2016-04-01
An adequate forecasting model may not perform well if it is inadequately calibrated. Model calibration is often constrained by the lack of adequate calibration data, especially for small river basins with high spatial rainfall variability. Rainfall/snow station networks may not be dense enough to accurately estimate the catchment rainfall/SWE. High discharges during flood events are subject to significant error due to flow gauging difficulty. Dynamic changes in catchment conditions (e.g., urbanization; losses in karstic systems) invariably introduce non-homogeneity in the water level and flow data. This presentation will highlight some of the challenges in reliable calibration of National Weather Service (i.e. US) operational flood forecast models, emphasizing the various challenges in different physiographic/climatic domains. It will also highlight the benefit of using various data visualization techniques to transfer information about model calibration to operational forecasters so they may understand the influence of the calibration on model performance under various conditions.
Calibration of visual model for space manipulator with a hybrid LM-GA algorithm
NASA Astrophysics Data System (ADS)
Jiang, Wensong; Wang, Zhongyu
2016-01-01
A hybrid LM-GA algorithm is proposed to calibrate the camera system of space manipulator to improve its locational accuracy. This algorithm can dynamically fuse the Levenberg-Marqurdt (LM) algorithm and Genetic Algorithm (GA) together to minimize the error of nonlinear camera model. LM algorithm is called to optimize the initial camera parameters that are generated by genetic process previously. Iteration should be stopped if the optimized camera parameters meet the accuracy requirements. Otherwise, new populations are generated again by GA and optimized afresh by LM algorithm until the optimal solutions meet the accuracy requirements. A novel measuring machine of space manipulator is designed to on-orbit dynamic simulation and precision test. The camera system of space manipulator, calibrated by hybrid LM-GA algorithm, is used for locational precision test in this measuring instrument. The experimental results show that the mean composite errors are 0.074 mm for hybrid LM-GA camera calibration model, 1.098 mm for LM camera calibration model, and 1.202 mm for GA camera calibration model. Furthermore, the composite standard deviations are 0.103 mm for the hybrid LM-GA camera calibration model, 1.227 mm for LM camera calibration model, and 1.351 mm for GA camera calibration model. The accuracy of hybrid LM-GA camera calibration model is more than 10 times higher than that of other two methods. All in all, the hybrid LM-GA camera calibration model is superior to both the LM camera calibration model and GA camera calibration model.
Yu, Hua; Small, Gary W
2015-02-01
A diagnostic and updating strategy is explored for multivariate calibrations based on near-infrared spectroscopy. For use with calibration models derived from spectral fitting or decomposition techniques, the proposed method constructs models that relate the residual concentrations remaining after a prediction to the residual spectra remaining after the information associated with the calibration model has been extracted. This residual modeling approach is evaluated for use with partial least-squares (PLS) models for predicting physiological levels of glucose in a simulated biological matrix. Residual models are constructed with both PLS and a hybrid technique based on the use of PLS scores as inputs to support vector regression. Calibration and residual models are built with both absorbance and single-beam data collected over 416 days. Effective models for the spectral residuals are built with both types of data and demonstrate the ability to diagnose and correct deviations in performance of the calibration model with time. PMID:25473807
Dong, Ren G.; Welcome, Daniel E.; McDowell, Thomas W.; Wu, John Z.
2015-01-01
While simulations of the measured biodynamic responses of the whole human body or body segments to vibration are conventionally interpreted as summaries of biodynamic measurements, and the resulting models are considered quantitative, this study looked at these simulations from a different angle: model calibration. The specific aims of this study are to review and clarify the theoretical basis for model calibration, to help formulate the criteria for calibration validation, and to help appropriately select and apply calibration methods. In addition to established vibration theory, a novel theorem of mechanical vibration is also used to enhance the understanding of the mathematical and physical principles of the calibration. Based on this enhanced understanding, a set of criteria was proposed and used to systematically examine the calibration methods. Besides theoretical analyses, a numerical testing method is also used in the examination. This study identified the basic requirements for each calibration method to obtain a unique calibration solution. This study also confirmed that the solution becomes more robust if more than sufficient calibration references are provided. Practically, however, as more references are used, more inconsistencies can arise among the measured data for representing the biodynamic properties. To help account for the relative reliabilities of the references, a baseline weighting scheme is proposed. The analyses suggest that the best choice of calibration method depends on the modeling purpose, the model structure, and the availability and reliability of representative reference data. PMID:26740726
NASA Astrophysics Data System (ADS)
Dong, Ren G.; Welcome, Daniel E.; McDowell, Thomas W.; Wu, John Z.
2015-11-01
While simulations of the measured biodynamic responses of the whole human body or body segments to vibration are conventionally interpreted as summaries of biodynamic measurements, and the resulting models are considered quantitative, this study looked at these simulations from a different angle: model calibration. The specific aims of this study are to review and clarify the theoretical basis for model calibration, to help formulate the criteria for calibration validation, and to help appropriately select and apply calibration methods. In addition to established vibration theory, a novel theorem of mechanical vibration is also used to enhance the understanding of the mathematical and physical principles of the calibration. Based on this enhanced understanding, a set of criteria was proposed and used to systematically examine the calibration methods. Besides theoretical analyses, a numerical testing method is also used in the examination. This study identified the basic requirements for each calibration method to obtain a unique calibration solution. This study also confirmed that the solution becomes more robust if more than sufficient calibration references are provided. Practically, however, as more references are used, more inconsistencies can arise among the measured data for representing the biodynamic properties. To help account for the relative reliabilities of the references, a baseline weighting scheme is proposed. The analyses suggest that the best choice of calibration method depends on the modeling purpose, the model structure, and the availability and reliability of representative reference data.
The impact of asynchronicity on event-flow estimation in basin-scale hydrologic model calibration
Technology Transfer Automated Retrieval System (TEKTRAN)
The calibration of basin-scale hydrologic models consists of adjusting parameters such that simulated values closely match observed values. However, due to inevitable inaccuracies in models and model inputs, simulated response hydrographs for multi-year calibrations will not be perfectly synchroniz...
Lee, Kenneth L.; Korellis, John S.; McFadden, Sam X.
2006-01-01
Experimental data for material plasticity and failure model calibration and validation were obtained from 304L stainless steel. Model calibration data were taken from smooth tension, notched tension, and compression tests. Model validation data were provided from experiments using thin-walled tube specimens subjected to path dependent combinations of internal pressure, extension, and torsion.
NSLS-II: Nonlinear Model Calibration for Synchrotrons
Bengtsson, J.
2010-10-08
This tech note is essentially a summary of a lecture we delivered to the Acc. Phys. Journal Club Apr, 2010. However, since the estimated accuracy of these methods has been naive and misleading in the field of particle accelerators, i.e., ignores the impact of noise, we will elaborate on this in some detail. A prerequisite for a calibration of the nonlinear Hamiltonian is that the quadratic part has been understood, i.e., that the linear optics for the real accelerator has been calibrated. For synchrotron light source operations, this problem has been solved by the interactive LOCO technique/tool (Linear Optics from Closed Orbits). Before that, in the context of hadron accelerators, it has been done by signal processing of turn-by-turn BPM data. We have outlined how to make a basic calibration of the nonlinear model for synchrotrons. In particular, we have shown how this was done for LEAR, CERN (antiprotons) in the mid-80s. Specifically, our accuracy for frequency estimation was {approx} 1 x 10{sup -5} for 1024 turns (to calibrate the linear optics) and {approx} 1 x 10{sup -4} for 256 turns for tune footprint and betatron spectrum. For a comparison, the estimated tune footprint for stable beam for NSLS-II is {approx}0.1. Since the transverse damping time is {approx}20 msec, i.e., {approx}4,000 turns. There is no fundamental difference for: antiprotons, protons, and electrons in this case. Because the estimated accuracy for these methods in the field of particle accelerators has been naive, i.e., ignoring the impact of noise, we have also derived explicit formula, from first principles, for a quantitative statement. For e.g. N = 256 and 5% noise we obtain {delta}{nu} {approx} 1 x 10{sup -5}. A comparison with the state-of-the-arts in e.g. telecomm and electrical engineering since the 60s is quite revealing. For example, Kalman filter (1960), crucial for the: Ranger, Mariner, and Apollo (including the Lunar Module) missions during the 60s. Or Claude Shannon et al
Calibrating a Magnetotail Model for Storm/Substorm Forecasting
NASA Astrophysics Data System (ADS)
Horton, W.; Siebert, S.; Mithaiwala, M.; Doxas, I.
2003-12-01
The physics network model called WINDMI for the solar WIND driven Magnetosphere-Ionosphere weather system is calibrated on substorm databases [1] using a genetic algorithm. We report on the use of the network as a digital filter to classify the substorms into three types; a process traditionally performed individual inspection. We then turn to using the filter on the seven Geospace Environmental Modeling (GEM) Storms designated for community wide study. These storms cover periods of days and contain many substorms. First the WINDMI model is run with the 14 parameters set from the study based on the Blanchard-McPherron database of 117 isolated substorms with 80% of the data having the AL below -500nT. In contrast, the GEM storms have long periods with AL in the range of -1000nT. The prediction error measured with the average-relative variance (ARV) is of approximately unity. Reapplying the genetic algorithm the parameters shift such that the one long storm has an ARV=0.59. Physics modifications of the basic WINDMI model including the injection of sheet plasma into the ring current are being evaluated in terms of their impact on the ARV and comparisons with non-physics based signal processing prediction filters. Ensembles of initial conditions are run with 700MHz G3 CPU run times of order 17 sec per orbit per day of real data. The AMD AthlonXP 1700+ processor takes 5sec per orbit per day. The IBM SP-2 speed will be reported. With such speeds it is possible to run balls of initial conditions. Substrom Classification with the WINDMI Model, W. Horton, R.S. Weigel, D. Vassiliadis, and I. Doxas, Nonlinear Processes in Geophysics, 1-9, 2003. This work was supported by the National Science Foundation Grant ATM-0229863.
Calibration of a COTS Integration Cost Model Using Local Project Data
NASA Technical Reports Server (NTRS)
Boland, Dillard; Coon, Richard; Byers, Kathryn; Levitt, David
1997-01-01
The software measures and estimation techniques appropriate to a Commercial Off the Shelf (COTS) integration project differ from those commonly used for custom software development. Labor and schedule estimation tools that model COTS integration are available. Like all estimation tools, they must be calibrated with the organization's local project data. This paper describes the calibration of a commercial model using data collected by the Flight Dynamics Division (FDD) of the NASA Goddard Spaceflight Center (GSFC). The model calibrated is SLIM Release 4.0 from Quantitative Software Management (QSM). By adopting the SLIM reuse model and by treating configuration parameters as lines of code, we were able to establish a consistent calibration for COTS integration projects. The paper summarizes the metrics, the calibration process and results, and the validation of the calibration.
Technology Transfer Automated Retrieval System (TEKTRAN)
In this paper, the Genetic Algorithms (GA) and Bayesian model averaging (BMA) were combined to simultaneously conduct calibration and uncertainty analysis for the Soil and Water Assessment Tool (SWAT). In this hybrid method, several SWAT models with different structures are first selected; next GA i...
The value of subsidence data in ground water model calibration.
Yan, Tingting; Burbey, Thomas J
2008-01-01
The accurate estimation of aquifer parameters such as transmissivity and specific storage is often an important objective during a ground water modeling investigation or aquifer resource evaluation. Parameter estimation is often accomplished with changes in hydraulic head data as the key and most abundant type of observation. The availability and accessibility of global positioning system and interferometric synthetic aperture radar data in heavily pumped alluvial basins can provide important subsidence observations that can greatly aid parameter estimation. The aim of this investigation is to evaluate the value of spatial and temporal subsidence data for automatically estimating parameters with and without observation error using UCODE-2005 and MODFLOW-2000. A synthetic conceptual model (24 separate cases) containing seven transmissivity zones and three zones each for elastic and inelastic skeletal specific storage was used to simulate subsidence and drawdown in an aquifer with variably thick interbeds with delayed drainage. Five pumping wells of variable rates were used to stress the system for up to 15 years. Calibration results indicate that (1) the inverse of the square of the observation values is a reasonable way to weight the observations, (2) spatially abundant subsidence data typically produce superior parameter estimates under constant pumping even with observation error, (3) only a small number of subsidence observations are required to achieve accurate parameter estimates, and (4) for seasonal pumping, accurate parameter estimates for elastic skeletal specific storage values are largely dependent on the quantity of temporal observational data and less on the quantity of available spatial data. PMID:18384595
Optimization of measurement campaigns for calibration of a conceptual sewer model.
Kleidorfer, M; Möderl, M; Fach, S; Rauch, W
2009-01-01
To simulate hydrological models of combined sewer systems an accurate calibration is indispensable. In addition to all sources of uncertainties in data collection due to the measurement methods itself, it is a key question which data has to be collected to calibrate a hydrological model, how long measurement campaigns should last and where that data has to be collected in a spatial distributed system as it is neither possible nor sensible to measure the complete system characteristics. In this paper we address this question by means of stochastic modelling. Using Monte Carlo Simulation different calibration strategies (selection of measurement sites, selection of rainfall-events) and different calibration parameters (overflow volume, number of overflows) are tested, in order to evaluate the influence on predicting the total overflow volume of the entire system. This methodology is applied in a case study with the aim to calculate the combined sewer overflow (CSO) efficiency. It can be shown that a distributed hydrological model can be calibrated sufficiently when calibration is done on 30% of all existing CSOs based on long-term observation. Event based calibration is limited possible to a limited extend when calibration events are selected carefully as wrong selection of calibration events can result in a complete failure of the calibration exercise. PMID:19403965
Model Robust Calibration: Method and Application to Electronically-Scanned Pressure Transducers
NASA Technical Reports Server (NTRS)
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.
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.
Calibration of model constants in a biological reaction model for sewage treatment plants.
Amano, Ken; Kageyama, Kohji; Watanabe, Shoji; Takemoto, Takeshi
2002-02-01
Various biological reaction models have been proposed which estimate concentrations of soluble and insoluble components in effluent of sewage treatment plants. These models should be effective to develop a better operation system and plant design, but their formulas consist of nonlinear equations, and there are many model constants, which are not easy to calibrate. A technique has been proposed to decide the model constants by precise experiments, but it is not practical for design engineers or process operators to perform these experiments regularly. Other approaches which calibrate the model constants by mathematical techniques should be used. In this paper, the optimal regulator method of modern control theory is applied as a mathematical technique to calibrate the model constants. This method is applied in a small sewage treatment testing facility. Calibration of the model constants is examined to decrease the deviations between calculated and measured concentrations. Results show that calculated values of component concentrations approach measured values and the method is useful for actual plants. PMID:11848341
Thermal Modeling Method Improvements for SAGE III on ISS
NASA Technical Reports Server (NTRS)
Liles, Kaitlin; Amundsen, Ruth; Davis, Warren; McLeod, Shawn
2015-01-01
The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III will be delivered to the International Space Station (ISS) via the SpaceX Dragon vehicle. A detailed thermal model of the SAGE III payload, which consists of multiple subsystems, has been developed in Thermal Desktop (TD). Many innovative analysis methods have been used in developing this model; these will be described in the paper. This paper builds on a paper presented at TFAWS 2013, which described some of the initial developments of efficient methods for SAGE III. The current paper describes additional improvements that have been made since that time. To expedite the correlation of the model to thermal vacuum (TVAC) testing, the chambers and GSE for both TVAC chambers at Langley used to test the payload were incorporated within the thermal model. This allowed the runs of TVAC predictions and correlations to be run within the flight model, thus eliminating the need for separate models for TVAC. In one TVAC test, radiant lamps were used which necessitated shooting rays from the lamps, and running in both solar and IR wavebands. A new Dragon model was incorporated which entailed a change in orientation; that change was made using an assembly, so that any potential additional new Dragon orbits could be added in the future without modification of the model. The Earth orbit parameters such as albedo and Earth infrared flux were incorporated as time-varying values that change over the course of the orbit; despite being required in one of the ISS documents, this had not been done before by any previous payload. All parameters such as initial temperature, heater voltage, and location of the payload are defined based on the case definition. For one component, testing was performed in both air and vacuum; incorporating the air convection in a submodel that was
Using the cloud to speed-up calibration of watershed-scale hydrologic models (Invited)
NASA Astrophysics Data System (ADS)
Goodall, J. L.; Ercan, M. B.; Castronova, A. M.; Humphrey, M.; Beekwilder, N.; Steele, J.; Kim, I.
2013-12-01
This research focuses on using the cloud to address computational challenges associated with hydrologic modeling. One example is calibration of a watershed-scale hydrologic model, which can take days of execution time on typical computers. While parallel algorithms for model calibration exist and some researchers have used multi-core computers or clusters to run these algorithms, these solutions do not fully address the challenge because (i) calibration can still be too time consuming even on multicore personal computers and (ii) few in the community have the time and expertise needed to manage a compute cluster. Given this, another option for addressing this challenge that we are exploring through this work is the use of the cloud for speeding-up calibration of watershed-scale hydrologic models. The cloud used in this capacity provides a means for renting a specific number and type of machines for only the time needed to perform a calibration model run. The cloud allows one to precisely balance the duration of the calibration with the financial costs so that, if the budget allows, the calibration can be performed more quickly by renting more machines. Focusing specifically on the SWAT hydrologic model and a parallel version of the DDS calibration algorithm, we show significant speed-up time across a range of watershed sizes using up to 256 cores to perform a model calibration. The tool provides a simple web-based user interface and the ability to monitor the calibration job submission process during the calibration process. Finally this talk concludes with initial work to leverage the cloud for other tasks associated with hydrologic modeling including tasks related to preparing inputs for constructing place-based hydrologic models.
Calibration models for density borehole logging - construction report
Engelmann, R.E.; Lewis, R.E.; Stromswold, D.C.
1995-10-01
Two machined blocks of magnesium and aluminum alloys form the basis for Hanford`s density models. The blocks provide known densities of 1.780 {plus_minus} 0.002 g/cm{sup 3} and 2.804 {plus_minus} 0.002 g/cm{sup 3} for calibrating borehole logging tools that measure density based on gamma-ray scattering from a source in the tool. Each block is approximately 33 x 58 x 91 cm (13 x 23 x 36 in.) with cylindrical grooves cut into the sides of the blocks to hold steel casings of inner diameter 15 cm (6 in.) and 20 cm (8 in.). Spacers that can be inserted between the blocks and casings can create air gaps of thickness 0.64, 1.3, 1.9, and 2.5 cm (0.25, 0.5, 0.75 and 1.0 in.), simulating air gaps that can occur in actual wells from hole enlargements behind the casing.
Kalivas, John H; Héberger, Károly; Andries, Erik
2015-04-15
Most multivariate calibration methods require selection of tuning parameters, such as partial least squares (PLS) or the Tikhonov regularization variant ridge regression (RR). Tuning parameter values determine the direction and magnitude of respective model vectors thereby setting the resultant predication abilities of the model vectors. Simultaneously, tuning parameter values establish the corresponding bias/variance and the underlying selectivity/sensitivity tradeoffs. Selection of the final tuning parameter is often accomplished through some form of cross-validation and the resultant root mean square error of cross-validation (RMSECV) values are evaluated. However, selection of a "good" tuning parameter with this one model evaluation merit is almost impossible. Including additional model merits assists tuning parameter selection to provide better balanced models as well as allowing for a reasonable comparison between calibration methods. Using multiple merits requires decisions to be made on how to combine and weight the merits into an information criterion. An abundance of options are possible. Presented in this paper is the sum of ranking differences (SRD) to ensemble a collection of model evaluation merits varying across tuning parameters. It is shown that the SRD consensus ranking of model tuning parameters allows automatic selection of the final model, or a collection of models if so desired. Essentially, the user's preference for the degree of balance between bias and variance ultimately decides the merits used in SRD and hence, the tuning parameter values ranked lowest by SRD for automatic selection. The SRD process is also shown to allow simultaneous comparison of different calibration methods for a particular data set in conjunction with tuning parameter selection. Because SRD evaluates consistency across multiple merits, decisions on how to combine and weight merits are avoided. To demonstrate the utility of SRD, a near infrared spectral data set and a
Automated calibration of a three-dimensional ground water flow model
Baker, F.G.; Guo, X.; Zigich, D.
1996-12-31
A three-dimensional ground water flow model was developed and calibrated for use as a quantitative tool for the evaluation of several potential ground water remedial alternatives during the On-Post Feasibility Study for the Rocky Mountain Arsenal. The USGS MODFLOW code was implemented and calibrated for steady-state conditions over the entire model area and for transient conditions where local pumping test data were available. Strict modeling goals and calibration criteria were established before modeling was initiated and formed a basis to guide the modeling process as it proceeded. The modeling effort utilized a non-traditional optimization technique to assist in model calibration. During calibration, this practical and systematic parameter adjustment procedure was used where parameter change was tightly constrained by preset geologic and hydrogeologic conditions. Hydraulic conductivity parameter was adjusted based on frequent comparison of calculated head to observed head conditions. The driving parameter was adjusted within limits until the calibration criteria achieved predetermined calibration targets. The paper presents the calibration approach and discusses the model application for evaluation of alternatives.
Technology Transfer Automated Retrieval System (TEKTRAN)
Availability of continuous long-term measured data for model calibration and validation is limited due to time and resources constraints. As a result, hydrologic and water quality models are calibrated and, if possible, validated when measured data is available. Past work reported on the impact of t...
Technology Transfer Automated Retrieval System (TEKTRAN)
Watershed simulation models can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of detailed outputs that some of the calibrated models may not reflect summative actual watershed behavior. Thus, it is necessary to use “soft data” (i....
Evaluation of impact of length of calibration time period on the APEX model streamflow simulation
Technology Transfer Automated Retrieval System (TEKTRAN)
Due to resource constraints, continuous long-term measured data for model calibration and validation (C/V) are rare. As a result, most hydrologic and water quality models are calibrated and, if possible, validated using limited available measured data. However, little research has been carried out t...
Technology Transfer Automated Retrieval System (TEKTRAN)
This is a review of the book “Calibration and Reliability in Groundwater Modeling: From Uncertainty to Decision Making” edited by M. F. P. Bierkens, J. C. Gehrels and K. Kovar. It is a collection of selected papers that dealt with advances in groundwater modeling, calibration techniques, and potenti...
Technology Transfer Automated Retrieval System (TEKTRAN)
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...
HRMA calibration handbook: EKC gravity compensated XRCF models
NASA Technical Reports Server (NTRS)
Tananbaum, H. D.; Jerius, D.; Hughes, J.
1994-01-01
This document, consisting of hardcopy printout of explanatory text, figures, and tables, represents one incarnation of the AXAF high resolution mirror assembly (HRMA) Calibration Handbook. However, as we have envisioned it, the handbook also consists of electronic versions of this hardcopy printout (in the form of postscript files), the individual scripts which produced the various figures and the associated input data, the model raytrace files, and all scripts, parameter files, and input data necessary to generate the raytraces. These data are all available electronically as either ASCII or FITS files. The handbook is intended to be a living document and will be updated as new information and/or fabrication data on the HRMA are obtained, or when the need for additional results are indicated. The SAO Mission Support Team (MST) is developing a high fidelity HRMA model, consisting of analytical and numerical calculations, computer software, and databases of fundamental physical constants, laboratory measurements, configuration data, finite element models, AXAF assembly data, and so on. This model serves as the basis for the simulations presented in the handbook. The 'core' of the model is the raytrace package OSAC, which we have substantially modified and now refer to as SAOsac. One major structural modification to the software has been to utilize the UNIX binary pipe data transport mechanism for passing rays between program modules. This change has made it possible to simulate rays which are distributed randomly over the entrance aperture of the telescope. It has also resulted in a highly efficient system for tracing large numbers of rays. In one application to date (the analysis of VETA-I ring focus data) we have employed 2 x 10(exp 7) rays, a substantial improvement over the limit of 1 x 10(exp 4) rays in the original OSAC module. A second major modification is the manner in which SAOsac incorporates low spatial frequency surface errors into the geometric raytrace
Automation of sample plan creation for process model calibration
NASA Astrophysics Data System (ADS)
Oberschmidt, James; Abdo, Amr; Desouky, Tamer; Al-Imam, Mohamed; Krasnoperova, Azalia; Viswanathan, Ramya
2010-04-01
The process of preparing a sample plan for optical and resist model calibration has always been tedious. Not only because it is required to accurately represent full chip designs with countless combinations of widths, spaces and environments, but also because of the constraints imposed by metrology which may result in limiting the number of structures to be measured. Also, there are other limits on the types of these structures, and this is mainly due to the accuracy variation across different types of geometries. For instance, pitch measurements are normally more accurate than corner rounding. Thus, only certain geometrical shapes are mostly considered to create a sample plan. In addition, the time factor is becoming very crucial as we migrate from a technology node to another due to the increase in the number of development and production nodes, and the process is getting more complicated if process window aware models are to be developed in a reasonable time frame, thus there is a need for reliable methods to choose sample plans which also help reduce cycle time. In this context, an automated flow is proposed for sample plan creation. Once the illumination and film stack are defined, all the errors in the input data are fixed and sites are centered. Then, bad sites are excluded. Afterwards, the clean data are reduced based on geometrical resemblance. Also, an editable database of measurement-reliable and critical structures are provided, and their percentage in the final sample plan as well as the total number of 1D/2D samples can be predefined. It has the advantage of eliminating manual selection or filtering techniques, and it provides powerful tools for customizing the final plan, and the time needed to generate these plans is greatly reduced.
NASA Technical Reports Server (NTRS)
Hovenac, Edward A.; Lock, James A.
1993-01-01
Scattering calculations using a more detailed model of the multimode laser beam in the forward-scattering spectrometer probe (FSSP) were carried out by using a recently developed extension to Mie scattering theory. From this model, new calibration curves for the FSSP were calculated. The difference between the old calibration curves and the new ones is small for droplet diameters less than 10 micrometers, but the difference increases to approximately 10% at diameters of 50 micrometers. When using glass beads to calibrate the FSSP, calibration errors can be minimized, by using glass beads of many different diameters, over the entire range of the FSSP. If the FSSP is calibrated using one-diameter glass beads, then the new formalism is necessary to extrapolate the calibration over the entire range.
NASA Technical Reports Server (NTRS)
Hovenac, Edward A.; Lock, James A.
1993-01-01
Scattering calculations using a detailed model of the multimode laser beam in the forward-scattering spectrometer probe (FSSP) were carried out using a recently developed extension to Mie scattering theory. From this model, new calibration curves for the FSSP were calculated. The difference between the old calibration curves and the new ones is small for droplet diameters less than 10 microns, but the difference increases to approximately 10 percent at diameters of 50 microns. When using glass beads to calibrate the FSSP, calibration errors can be minimized by using glass beads of many different diameters, over the entire range of the FSSP. If the FSSP is calibrated using one-diameter glass beads, then the new formalism is necessary to extrapolate the calibration over the entire range.
Calibration and uncertainty issues of a hydrological model (SWAT) applied to West Africa
NASA Astrophysics Data System (ADS)
Schuol, J.; Abbaspour, K. C.
2006-09-01
Distributed hydrological models like SWAT (Soil and Water Assessment Tool) are often highly over-parameterized, making parameter specification and parameter estimation inevitable steps in model calibration. Manual calibration is almost infeasible due to the complexity of large-scale models with many objectives. Therefore we used a multi-site semi-automated inverse modelling routine (SUFI-2) for calibration and uncertainty analysis. Nevertheless, the question of when a model is sufficiently calibrated remains open, and requires a project dependent definition. Due to the non-uniqueness of effective parameter sets, parameter calibration and prediction uncertainty of a model are intimately related. We address some calibration and uncertainty issues using SWAT to model a four million km2 area in West Africa, including mainly the basins of the river Niger, Volta and Senegal. This model is a case study in a larger project with the goal of quantifying the amount of global country-based available freshwater. Annual and monthly simulations with the "calibrated" model for West Africa show promising results in respect of the freshwater quantification but also point out the importance of evaluating the conceptual model uncertainty as well as the parameter uncertainty.
Automatic Calibration of a Semi-Distributed Hydrologic Model Using Particle Swarm Optimization
NASA Astrophysics Data System (ADS)
Bekele, E. G.; Nicklow, J. W.
2005-12-01
Hydrologic simulation models need to be calibrated and validated before using them for operational predictions. Spatially-distributed hydrologic models generally have a large number of parameters to capture the various physical characteristics of a hydrologic system. Manual calibration of such models is a very tedious and daunting task, and its success depends on the subjective assessment of a particular modeler, which includes knowledge of the basic approaches and interactions in the model. In order to alleviate these shortcomings, an automatic calibration model, which employs an evolutionary optimization technique known as Particle Swarm Optimizer (PSO) for parameter estimation, is developed. PSO is a heuristic search algorithm that is inspired by social behavior of bird flocking or fish schooling. The newly-developed calibration model is integrated to the U.S. Department of Agriculture's Soil and Water Assessment Tool (SWAT). SWAT is a physically-based, semi-distributed hydrologic model that was developed to predict the long term impacts of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use, and management conditions. SWAT was calibrated for streamflow and sediment concentration. The calibration process involves parameter specification, whereby sensitive model parameters are identified, and parameter estimation. In order to reduce the number of parameters to be calibrated, parameterization was performed. The methodology is applied to a demonstration watershed known as Big Creek, which is located in southern Illinois. Application results show the effectiveness of the approach and model predictions are significantly improved.
Technology Transfer Automated Retrieval System (TEKTRAN)
Watershed simulation models are used extensively to investigate hydrologic processes, landuse and climate change impacts, pollutant load assessments and best management practices (BMPs). Developing, calibrating and validating these models require a number of critical decisions that will influence t...
Dr. Carl Stern; Dr. Martin Lee
1999-06-28
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.
Model of selective growth of III-V nanowires
NASA Astrophysics Data System (ADS)
Dubrovskii, V. G.
2015-12-01
A kinetic model of growth of nanowires of III-V semiconductor compounds (including nitride ones) in the absence of metal catalyst is proposed; these conditions correspond to the methods of selective epitaxy or self-induced growth. A stationary solution for the nanowire growth rate is obtained, which indicates that the growth can be limited by not only the kinetics of III-group element with allowance for the surface diffusion (as was suggested earlier), but also the flow of the V-group element. Different modes are characterized by radically different dependences of the growth rate on the nanowire radius. Under arsenicenriched conditions, a typical dependence with a maximum and decay at large radii (limited by the gallium adatom diffusion) is observed. Under gallium-enriched conditions, there is a transition to the growth rate that is practically independent of the radius and linearly increases with an increase in the arsenic flow.
Reaction-based reactive transport modeling of Fe(III)
Kemner, K.M.; Kelly, S.D.; Burgos, Bill; Roden, Eric
2006-06-01
This research project (started Fall 2004) was funded by a grant to Argonne National Laboratory, The Pennsylvania State University, and The University of Alabama in the Integrative Studies Element of the NABIR Program (DE-FG04-ER63914/63915/63196). Dr. Eric Roden, formerly at The University of Alabama, is now at the University of Wisconsin, Madison. Our project focuses on the development of a mechanistic understanding and quantitative models of coupled Fe(III)/U(VI) reduction in FRC Area 2 sediments. This work builds on our previous studies of microbial Fe(III) and U(VI) reduction, and is directly aligned with the Scheibe et al. NABIR FRC Field Project at Area 2.
Comparison of global optimization approaches for robust calibration of hydrologic model parameters
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Klostermann, U. K.; Mülders, T.; Schmöller, T.; Lorusso, G. F.; Hendrickx, E.
2010-04-01
In this paper, we discuss the performance of EUV resist models in terms of predictive accuracy, and we assess the readiness of the corresponding model calibration methodology. The study is done on an extensive OPC data set collected at IMEC for the ShinEtsu resist SEVR-59 on the ASML EUV Alpha Demo Tool (ADT), with the data set including more than thousand CD values. We address practical aspects such as the speed of calibration and selection of calibration patterns. The model is calibrated on 12 process window data series varying in pattern width (32, 36, 40 nm), orientation (H, V) and pitch (dense, isolated). The minimum measured feature size at nominal process condition is a 32 nm CD at a dense pitch of 64 nm. Mask metrology is applied to verify and eventually correct nominal width of the drawn CD. Cross-sectional SEM information is included in the calibration to tune the simulated resist loss and sidewall angle. The achieved calibration RMS is ~ 1.0 nm. We show what elements are important to obtain a well calibrated model. We discuss the impact of 3D mask effects on the Bossung tilt. We demonstrate that a correct representation of the flare level during the calibration is important to achieve a high predictability at various flare conditions. Although the model calibration is performed on a limited subset of the measurement data (one dimensional structures only), its accuracy is validated based on a large number of OPC patterns (at nominal dose and focus conditions) not included in the calibration; validation RMS results as small as 1 nm can be reached. Furthermore, we study the model's extendibility to two-dimensional end of line (EOL) structures. Finally, we correlate the experimentally observed fingerprint of the CD uniformity to a model, where EUV tool specific signatures are taken into account.
Can satellite-derived water surface changes be used to calibrate a hydrodynamic model?
NASA Astrophysics Data System (ADS)
Revilla-Romero, Beatriz; Beck, Hylke; Salamon, Peter; Burek, Peter; de Roo, Ad; Thielen, Jutta
2015-04-01
The limited availability of recent ground observational data is one of the main challenges for validation of hydrodynamic models. This is especially relevant for real-time global applications such as flood forecasting models. In this study, we aim to use remotely-sensed data from the Global Flood Detection System (GFDS) as a proxy of river discharge time series and test its value through calibration of the hydrological model LISFLOOD. This was carried out for the time period 1998-2010 at 40 sites in Africa, Europe, North America and South America by calibrating the parameters that control the flow routing and groundwater processes. We compared the performance of the calibrated simulated discharge time series that used satellite-derived data with the ground discharge time series. Furthermore, we compared it with the independent calibrated run that used ground data and also, to the non-calibrated simulated discharge time series. The non-calibrated set up used a set of parameters which values were predefined by expert-knowledge. This is currently being used by the LISFLOOD set up model embedded in the pre-operational Global Flood Awareness System (GloFAS). The results of this study showed that the satellite surface water changes from the Global Flood Detection System can be used as a proxy of river discharge data, through the demonstration of its added value for model calibration and validation. Using satellite-derived data, the skill scores obtained by the calibrated simulated model discharge improved when comparing to non-calibrated simulated time series. Calibration, post-processing and data assimilation strategies of satellite data as a proxy for streamflow data within the global hydrological model are outlined and discussed.
Calibration of hydrological models using TOPEX/Poseidon radar altimetry observations
NASA Astrophysics Data System (ADS)
Sun, W.; Song, H.; Cheng, T.; Yu, J.
2015-05-01
This paper describes an approach for calibrating hydrological models using satellite radar altimetric observations of river water level at the basin outlet, aiming at providing a new direction for solving the calibration problem in ungauged basins where streamflow observations are unavailable. The methodology is illustrated by a case study in the Upper Mississippi basin. The water level data are derived from the TOPEX/Poseidon (T/P) satellite. The Generalized Likelihood Uncertainty Estimation (GLUE) method is employed for model calibration and uncertainty analysis. The Nash-Sutcliffe efficiency of averaged simulated streamflow by behavioural parameter sets is 64.50%. And the uncertainty bounds of the ensemble simulation embrace about 65% of daily streamflow. These results indicate that the hydrological model has been calibrated effectively. At the same time, comparison with traditional calibration using streamflow data illustrates that the proposed method is only valuable for applications in ungauged basins.
Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity
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.
Towards automatic calibration of hydrodynamic models - evaluation of gradient based optimisers
NASA Astrophysics Data System (ADS)
Fabio, Pamela; Apel, Heiko; Aronica, Giuseppe T.
2010-05-01
The calibration of two-dimensional hydraulic models is still underdeveloped in the present survey of scientific research. They are computationally very demanding and therefore the use of available sophisticated automatic calibration procedures is restricted in many cases. Moreover, the lack of relevant data against the models can be calibrated has ever to be accounted. The present study considers a serious and well documented flood event that occurred on August 2002 on the river Mulde in the city of Eilenburg in Saxony, Germany. The application of the parallel version of the model gradient-based optimiser PEST, that gives the possibility of automatic and model independent calibrations, is here presented, and different calibration strategies, adopting different aggregation levels of the spatially distributed surface roughness parameters, are compared. Gradient-based methods are often criticized because they can be sensitive to the initial parameter values and might get trapped in a local minimum of objective functions. But on the other hand they are computational very efficient and may be the only possibility to automatically calibrate CPU time demanding models like 2D hydraulic models. In order to test the performance of the gradient based optimiser the optimisation results were compared with a sensitivity analysis testing the whole parameters space through a Latin hypercube sampling, thus emulating a global optimiser. The results show that it is possible to use automatic calibration in combination of 2D hydraulic model, and that equifinality of model parameterisation can also be caused by a too large number of degrees of freedom in the calibration data in contrast to a too simple model setup. Also the sensitivity analysis showed that the gradient based optimiser was always able to find the global minimum. Based on these first results it can be concluded that a gradient based optimiser appears to be a viable and appropriate choice for automatic calibration of
Wolfrum, E. J.; Sluiter, A. D.
2009-01-01
We have studied rapid calibration models to predict the composition of a variety of biomass feedstocks by correlating near-infrared (NIR) spectroscopic data to compositional data produced using traditional wet chemical analysis techniques. The rapid calibration models are developed using multivariate statistical analysis of the spectroscopic and wet chemical data. This work discusses the latest versions of the NIR calibration models for corn stover feedstock and dilute-acid pretreated corn stover. Measures of the calibration precision and uncertainty are presented. No statistically significant differences (p = 0.05) are seen between NIR calibration models built using different mathematical pretreatments. Finally, two common algorithms for building NIR calibration models are compared; no statistically significant differences (p = 0.05) are seen for the major constituents glucan, xylan, and lignin, but the algorithms did produce different predictions for total extractives. A single calibration model combining the corn stover feedstock and dilute-acid pretreated corn stover samples gave less satisfactory predictions than the separate models.
System-Wide Calibration of River System Models: Opportunities and Challenges
NASA Astrophysics Data System (ADS)
Kim, S. S. H.; Hughes, J. D.; Dutta, D.; Vaze, J.
2014-12-01
Semi-distributed river system models are traditionally calibrated using a reach-by-reach calibration approach from that starts from headwater gauges and moves downstream toward the end of the system. Such a calibration method poses a unique problem since errors related to over-fitting, poor gauging data and uncertain physical connection are passed downstream. Reach-by-reach calibration, while efficient, cannot compensate for limited/poor calibration data of some gauges. To overcome the limitations of reach-by-reach calibration, a system calibration approach is proposed in which all the river reaches within a river basin are calibrated together using a global objective function for all stream flow gauges. In this approach, relative weights can be assigned in the global objective function for different gauges based on the magnitude and quality of available data. The system calibration approach was implemented in a river network covering 11 stream flow gauges within Murrumbidgee catchment (Australia). This study optimises flow at the selected gauges within the river network simultaneously (36 calibrated parameters) utilising a process-based semi-distributed river system model. The model includes processes such as routing, localised runoff, irrigation diversion, overbank flow and losses to groundwater. Goodness of fit is evaluated at the 11 gauges and a flow based weighting scheme is employed to find posterior distributions of parameters using an Approximate Bayesian Computation. The method is evaluated against a reach-by-reach calibration scheme. The comparison shows that the system calibration approach provides an overall improved goodness-of-fit by systematically de-valuing poor quality gauges providing an overall improved basin-wide performance. Clusters of viable parameter sets are determined from the posterior distributions and each examined to assess the effects of parameter uncertainty on internal model states. Such a method of calibration provides a lot more
Exploring a Three-Level Model of Calibration Accuracy
ERIC Educational Resources Information Center
Schraw, Gregory; Kuch, Fred; Gutierrez, Antonio P.; Richmond, Aaron S.
2014-01-01
We compared 5 different statistics (i.e., G index, gamma, "d'", sensitivity, specificity) used in the social sciences and medical diagnosis literatures to assess calibration accuracy in order to examine the relationship among them and to explore whether one statistic provided a best fitting general measure of accuracy. College…
Calibration Methods Used in Cancer Simulation Models and Suggested Reporting Guidelines
Stout, Natasha K.; Knudsen, Amy B.; Kong, Chung Yin (Joey); McMahon, Pamela M.; Gazelle, G. Scott
2009-01-01
Background Increasingly, computer simulation models are used for economic and policy evaluation in cancer prevention and control. A model’s predictions of key outcomes such as screening effectiveness depends on the values of unobservable natural history parameters. Calibration is the process of determining the values of unobservable parameters by constraining model output to replicate observed data. Because there are many approaches for model calibration and little consensus on best practices, we surveyed the literature to catalogue the use and reporting of these methods in cancer simulation models. Methods We conducted a MEDLINE search (1980 through 2006) for articles on cancer screening models and supplemented search results with articles from our personal reference databases. For each article, two authors independently abstracted pre-determined items using a standard form. Data items included cancer site, model type, methods used for determination of unobservable parameter values, and description of any calibration protocol. All authors reached consensus on items of disagreement. Reviews and non-cancer models were excluded. Articles describing analytical models which estimate parameters with statistical approaches (e.g., maximum likelihood) were catalogued separately. Models that included unobservable parameters were analyzed and classified by whether calibration methods were reported and if so, the methods used. Results The review process yielded 154 articles that met our inclusion criteria and of these, we concluded that 131 may have used calibration methods to determine model parameters. Although the term “calibration” was not always used, descriptions of calibration or “model fitting” were found in 50% (n=66) of the articles with an additional 16% (n=21) providing a reference to methods. Calibration target data were identified in nearly all of these articles. Other methodologic details such as the goodness-of-fit metric were discussed in 54% (n=47
NASA Astrophysics Data System (ADS)
McGurk, B. J.; Painter, T. H.
2014-12-01
Deterministic snow accumulation and ablation simulation models are widely used by runoff managers throughout the world to predict runoff quantities and timing. Model fitting is typically based on matching modeled runoff volumes and timing with observed flow time series at a few points in the basin. In recent decades, sparse networks of point measurements of the mountain snowpacks have been available to compare with modeled snowpack, but the comparability of results from a snow sensor or course to model polygons of 5 to 50 sq. km is suspect. However, snowpack extent, depth, and derived snow water equivalent have been produced by the NASA/JPL Airborne Snow Observatory (ASO) mission for spring of 20013 and 2014 in the Tuolumne River basin above Hetch Hetchy Reservoir. These high-resolution snowpack data have exposed the weakness in a model calibration based on runoff alone. The U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) calibration that was based on 30-years of inflow to Hetch Hetchy produces reasonable inflow results, but modeled spatial snowpack location and water quantity diverged significantly from the weekly measurements made by ASO during the two ablation seasons. The reason is that the PRMS model has many flow paths, storages, and water transfer equations, and a calibrated outflow time series can be right for many wrong reasons. The addition of a detailed knowledge of snow extent and water content constrains the model so that it is a better representation of the actual watershed hydrology. The mechanics of recalibrating PRMS to the ASO measurements will be described, and comparisons in observed versus modeled flow for both a small subbasin and the entire Hetch Hetchy basin will be shown. The recalibrated model provided a bitter fit to the snowmelt recession, a key factor for water managers as they balance declining inflows with demand for power generation and ecosystem releases during the final months of snow melt runoff.
NASA Astrophysics Data System (ADS)
Chegwidden, O.; Xiao, M.; Rupp, D. E.; Stumbaugh, M. R.; Hamman, J.; Pan, M.; Nijssen, B.
2015-12-01
Hydrologic models are often calibrated to streamflow observations at discrete points along a river network. Even if the area contributing to each flow location is discretized into multiple model elements, the calibration parameters are typically adjusted uniformly, either by setting them to the same value or transforming them in the same way (for example, multiply each parameter value by a given factor). Such a procedure typically results in sharp gradients in calibrated parameters between neighboring subbasins and disregards parameter heterogeneity at the subbasin scale. Here we apply a streamflow disaggregation procedure to develop daily, spatially-distributed runoff fields at the same resolution as the model application. We then use these fields to calibrate selected model parameters for each model grid cell independently. We have implemented two hydrologic models (the Variable Infiltration Capacity model and the Precipitation Runoff Modeling System) across the Columbia River Basin plus the coastal drainages in Oregon and Washington at a subdaily timestep and a spatial resolution of 1/16 degree or ~6km, resulting in 23,929 individual model grid cells. All model grid cells are calibrated independently to the distributed runoff fields using the shuffled complex evolution method and the Kling-Gupta Efficiency (KGE) as the objective function. The KGE was calculated on a weekly time step to minimize the effects of timing errors in the disaggregated runoff fields. We will present calibrated parameter fields and then discuss their structure (or lack thereof), which can provide important insight into parameter identifiability and uncertainty.
Matching Images to Models: Camera Calibration for 3-D Surface Reconstruction
NASA Technical Reports Server (NTRS)
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.
NASA Astrophysics Data System (ADS)
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
Seismology on a Comet: Calibration Measurements, Modeling and Inversion
NASA Astrophysics Data System (ADS)
Faber, C.; Hoppe, J.; Knapmeyer, M.; Fischer, H.; Seidensticker, K. J.
2011-12-01
The Mission Rosetta was launched to comet 67P/Churyumov-Gerasimenko in 2004. It will finally reach the comet and will deliver the Lander Philae at the surface of the nucleus in November 2014. The Lander carries ten experiments, one of which is the Surface Electric Sounding and Acoustic Monitoring Experiment (SESAME). Part of this experiment is the Comet Acoustic Surface Sounding Experiment (CASSE) housed in the three feet of the lander. The primary goal of CASSE is to determine the elastic parameters of the surface material, like the Young's modulus and the Poisson ratio. Additional goals are the determination of shallow structure, quantification of porosity, and the location of activity spots and thermally and impact caused cometary activity. We conduct calibration measurements with accelerometers identical to the flight model. The goal of these measurements is to develop inversion procedures for travel times and to estimate the expected accuracy that CASSE can achieve in terms of elastic wave velocity, elastic parameters, and source location. The experiments are conducted mainly on sandy soil, in dry, wet or frozen conditions, and apart from buildings with their reflecting walls and artificial noise sources. We expect that natural sources, like thermal cracking at sunrise and sunset, can be located to an accuracy of about 10 degrees in direction and a few decimeters (1σ) in distance if occurring within the sensor triangle and from first arrivals alone. The accuracy of the direction is essentially independent of the distance, whereas distance determination depends critically on the identification of later arrivals. Determination of elastic wave velocities on the comet will be conducted with controlled sources at known positions and are likely to achieve an accuracy of σ=15% for the velocity of the first arriving wave. Limitations are due to the fixed source-receiver geometry and the wavelength emitted by the CASSE piezo-ceramic sources. In addition to the
Sparkle/AM1 Parameters for the Modeling of Samarium(III) and Promethium(III) Complexes.
Freire, Ricardo O; da Costa, Nivan B; Rocha, Gerd B; Simas, Alfredo M
2006-01-01
The Sparkle/AM1 model is extended to samarium(III) and promethium(III) complexes. A set of 15 structures of high crystallographic quality (R factor < 0.05 Å), with ligands chosen to be representative of all samarium complexes in the Cambridge Crystallographic Database 2004, CSD, with nitrogen or oxygen directly bonded to the samarium ion, was used as a training set. In the validation procedure, we used a set of 42 other complexes, also of high crystallographic quality. The results show that this parametrization for the Sm(III) ion is similar in accuracy to the previous parametrizations for Eu(III), Gd(III), and Tb(III). On the other hand, promethium is an artificial radioactive element with no stable isotope. So far, there are no promethium complex crystallographic structures in CSD. To circumvent this, we confirmed our previous result that RHF/STO-3G/ECP, with the MWB effective core potential (ECP), appears to be the most efficient ab initio model chemistry in terms of coordination polyhedron crystallographic geometry predictions from isolated lanthanide complex ion calculations. We thus generated a set of 15 RHF/STO-3G/ECP promethium complex structures with ligands chosen to be representative of complexes available in the CSD for all other trivalent lanthanide cations, with nitrogen or oxygen directly bonded to the lanthanide ion. For the 42 samarium(III) complexes and 15 promethium(III) complexes considered, the Sparkle/AM1 unsigned mean error, for all interatomic distances between the Ln(III) ion and the ligand atoms of the first sphere of coordination, is 0.07 and 0.06 Å, respectively, a level of accuracy comparable to present day ab initio/ECP geometries, while being hundreds of times faster. PMID:26626380
Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin
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.
NASA Astrophysics Data System (ADS)
Madsen, Henrik
A consistent framework for parameter estimation in distributed hydrological catchment modelling using automatic calibration is formulated. The framework focuses on the different steps in the estimation process from model parameterisation and selection of calibration parameters, formulation of calibration criteria, and choice of optimisation algorithm. The calibration problem is formulated in a general multi-objective context in which different objective functions that measure individual process descriptions can be optimised simultaneously. Within this framework it is possible to tailor the model calibration to the specific objectives of the model application being considered. A test example is presented that illustrates the use of the calibration framework for parameter estimation in the MIKE SHE integrated and distributed hydrological modelling system. A significant trade-off between the performance of the groundwater level simulations and the catchment runoff is observed in this case, defining a Pareto front with a very sharp structure. The Pareto optimum solution corresponding to a proposed balanced aggregated objective function is seen to provide a proper balance between the two objectives. Compared to a manual expert calibration, the balanced Pareto optimum solution provides generally better simulation of the runoff, whereas virtually similar performance is obtained for the groundwater level simulations.
Calibrating corneal material model parameters using only inflation data: an ill-posed problem.
Kok, S; Botha, N; Inglis, H M
2014-12-01
Goldmann applanation tonometry (GAT) is a method used to estimate the intraocular pressure by measuring the indentation resistance of the cornea. A popular approach to investigate the sensitivity of GAT results to material and geometry variations 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, the underlying material constitutive behaviour is inferred from the measured macroscopic response (chamber pressure versus apical displacement). In this study, a biomechanically motivated elastic fibre-reinforced corneal material model is chosen. The inverse problem of calibrating the corneal material model parameters using only experimental inflation data is demonstrated to be ill-posed, with small variations in the experimental data leading to large differences in the calibrated model parameters. This can result in different groups of researchers, calibrating their material model with the same inflation test data, drawing vastly different conclusions about the effect of material parameters on GAT results. It is further demonstrated that multiple loading scenarios, such as inflation as well as bending, would be required to reliably calibrate such a corneal material model. PMID:25112972
Technology Transfer Automated Retrieval System (TEKTRAN)
The importance of uncertainty inherent in measured calibration/validation data is frequently stated in literature, but it is not often considered in calibrating and evaluating hydrologic and water quality models. This is due to the limited amount of data available to support relevant research and t...
NASA Astrophysics Data System (ADS)
Lin, Z.; Radcliffe, D. E.; Doherty, J.
2004-12-01
Automatic calibration has been applied to conceptual rainfall-runoff models for more than three decades, usually to lumped models. Even when a (semi-)distributed model that allows spatial variability of parameters is calibrated using an automated process, the parameters of the model are often lumped over space so that the model is simplified as a lumped model. Our objective was to develop a two-stage routine for automatically calibrating the Soil Water Assessment Tool (SWAT, a semi-distributed watershed model) that would find the optimal values for the model parameters, preserve the spatial variability in essential parameters, and lead to a measure of the model prediction uncertainty. In the first stage of this proposed calibration scheme, a global search method, namely, the Shuffled Complex Evolution (SCE-UA) method, was employed to find the ``best'' values for the lumped model parameters. That is, in order to limit the number of the calibrated parameters, the model parameters were assumed to be invariant over different subbasins and hydrologic response units (HRU, the basic calculation unit in the SWAT model). However, in the second stage, the spatial variability of the original model parameters was restored and the number of the calibrated parameters was dramatically increased (from a few to near a hundred). Hence, a local search method, namely, a variation of Levenberg-Marquart method, was preferred to find the more distributed set of parameters using the results of the previous stage as starting values. Furthermore, in order to prevent the parameters from taking extreme values, a strategy called ``regularization'' was adopted, through which the distributed parameters were constrained to vary as little as possible from the initial values of the lumped parameters. We calibrated the stream flow in the Etowah River measured at Canton, GA (a watershed area of 1,580 km2) for the years 1983-1992 and used the years 1993-2001 for validation. Calibration for daily and
NASA Astrophysics Data System (ADS)
Bolisetti, T.; Datta, A. R.; Balachandar, R.
2009-05-01
Studies on impact assessment and the corresponding uncertainties in hydrologic regime predictions is of paramount in developing water resources management plans under climate change scenarios,. The variability in hydrologic model parameters is one of the major sources of uncertainties associated with climate change impact on streamflow. Uncertainty in hydrologic model parameters may arise from the choice of model calibration technique, model calibration period, model structure and response variables. The recent studies show that consideration of uncertainties in input variables (precipitation, evapotranspiration etc.) during calibration of a hydrologic model has resulted in decrease in prediction uncertainty. The present study has examined the significance of input uncertainty in hydrologic model calibration for climate change impact studies. A physically distributed hydrologic model, Soil and Water Assessment Tool (SWAT), is calibrated considering uncertainties in (i) model parameters only, and (ii) both model parameters and precipitation input. The Markov chain Monte Carlo algorithm is used to estimate the posterior probability density function of hydrologic model parameters. The observed daily precipitation and streamflow data of the Canard River watershed of Essex region, Ontario, Canada are used as input and output variables, respectively, during calibration. The parameter sets of the 100 most skillful hydrologic model simulations obtained from each calibration technique are used for predicting streamflow by 2070s under climate change conditions. In each run, the climate predictions of the Canadian Regional Climate Model (CRCM) for SRES scenario A2 are used as input to the hydrologic model for streamflow prediction. The paper presents the results of uncertainty in seasonal and annual streamflow prediction. The outcome of the study is expected to contribute to the assessment of uncertainty in climate change impact studies and better management of available
Efficient calibration of a distributed pde-based hydrological model using grid coarsening
NASA Astrophysics Data System (ADS)
von Gunten, D.; Wöhling, T.; Haslauer, C.; Merchán, D.; Causapé, J.; Cirpka, O. A.
2014-11-01
Partial-differential-equation based integrated hydrological models are now regularly used at catchment scale. They rely on the shallow water equations for surface flow and on the Richards' equations for subsurface flow, allowing a spatially explicit representation of properties and states. However, these models usually come at high computational costs, which limit their accessibility to state-of-the-art methods of parameter estimation and uncertainty quantification, because these methods require a large number of model evaluations. In this study, we present an efficient model calibration strategy, based on a hierarchy of grid resolutions, each of them resolving the same zonation of subsurface and land-surface units. We first analyze which model outputs show the highest similarities between the original model and two differently coarsened grids. Then we calibrate the coarser models by comparing these similar outputs to the measurements. We finish the calibration using the fully resolved model, taking the result of the preliminary calibration as starting point. We apply the proposed approach to the well monitored Lerma catchment in North-East Spain, using the model HydroGeoSphere. The original model grid with 80,000 finite elements was complemented with two other model variants with approximately 16,000 and 10,000 elements, respectively. Comparing the model results for these different grids, we observe differences in peak discharge, evapotranspiration, and near-surface saturation. Hydraulic heads and low flow, however, are very similar for all tested parameter sets, which allows the use of these variables to calibrate our model. The calibration results are satisfactory and the duration of the calibration has been greatly decreased by using different model grid resolutions.
Visible spectroscopy calibration transfer model in determining pH of Sala mangoes
NASA Astrophysics Data System (ADS)
Yahaya, O. K. M.; MatJafri, M. Z.; Aziz, A. A.; Omar, A. F.
2015-05-01
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 R2 = 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 R2 = 0.839 and RMSEP = 0.16 pH.
Role of Imaging Specrometer Data for Model-based Cross-calibration of Imaging Sensors
NASA Technical Reports Server (NTRS)
Thome, Kurtis John
2014-01-01
Site characterization benefits from imaging spectrometry to determine spectral bi-directional reflectance of a well-understood surface. Cross calibration approaches, uncertainties, role of imaging spectrometry, model-based site characterization, and application to product validation.
NASA Astrophysics Data System (ADS)
Merino, J.; Cera, E.; Bruno, J.; Quiñones, J.; Casas, I.; Clarens, F.; Giménez, J.; de Pablo, J.; Rovira, M.; Martínez-Esparza, A.
2005-11-01
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 rad 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.
In this study, the calibration of subsurface batch and reactive-transport models involving complex biogeochemical processes was systematically evaluated. Two hypothetical nitrate biodegradation scenarios were developed and simulated in numerical experiments to evaluate the perfor...
Evaluation of different validation strategies and long term effects in NIR calibration models.
Sileoni, Valeria; Marconi, Ombretta; Perretti, Giuseppe; Fantozzi, Paolo
2013-12-01
Stable and reliable NIR calibration models for the barley malt quality assessment were developed and exhaustively evaluated. The measured parameters are: fine extract, fermentability, pH, soluble nitrogen, viscosity, friability and free-amino nitrogen. The reliability of the developed calibration models was evaluated comparing the classic leave-one-out internal validation with a more challenging one exploiting re-sampling scheme. The long-term effects, intended as possible alterations of the NIR method predictive power, due to the variation between samples collected in different years, were evaluated through an external validation which demonstrated the stability of the developed calibration models. Finally, the accuracy and the precision of the developed calibration models were evaluated in comparison with the reference methods. This exhaustive evaluation offers a realistic idea of the developed NIR methods predictive power for future unknown samples and their application in the beer industry. PMID:23871006
Predictive sensor based x-ray calibration using a physical model
Fuente, Matias de la; Lutz, Peter; Wirtz, Dieter C.; Radermacher, Klaus
2007-04-15
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 of a Hydrologic Model via Densely Distributed Soil Moisture Observations
NASA Astrophysics Data System (ADS)
Thorstensen, A. R.; Nguyen, P.; Hsu, K. L.; Sorooshian, S.
2014-12-01
The complexity of a catchment's physical heterogeneities is often addressed through calibration via observed streamflow. As hydrologic models move from lumped to distributed, and Earth observations increase in number and variety, the question is raised as to whether or not such distributed observations can be used to satisfy the possibly heterogenic calibration needs of a catchment. The goal of this study is to examine if calibration of a distributed hydrologic model using soil moisture observations can improve simulated streamflow. The NWS's Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) is used in this study. HL-RDHM uses the Sacramento Heat Transfer with enhanced Evapotranspiration for rainfall-runoff production and can convert conceptual storages to soil layers. This allows for calibration of conceptual parameters based on observed soil moisture profiles. HL-RDHM is calibrated using scalar multipliers of a-priori grids derived from soil surveys, with the premise that heterogeneity of these grids is correct. This assumption is relaxed to study the benefit of distributed calibration. Soil moisture measurements in the Turkey River Basin, which was equipped with 20 in-situ soil moisture sites for the Iowa Flood Studies campaign, were used for calibration of parameters related to soil moisture (i.e. storage and release parameters). The Shuffled Complex Evolution method was used to calibrate pixels collocated with in-situ probes based on soil moisture RMSE at point scale. Methods to allocate calibrated parameter values to remaining pixels include an averaging method, spatial interpolation, and a similarity method. Calibration was done for spring 2013, and validation for 2009 and 2011. Results show that calibration using stream gauges remains the superior method, especially for correlation. This is because calibration based on streamflow can correct peak timing by adjusting routing parameters. Such adjustments using soil moisture cannot be done
Ecologically-focused Calibration of Hydrological Models for Environmental Flow Applications
NASA Astrophysics Data System (ADS)
Adams, S. K.; Bledsoe, B. P.
2015-12-01
Hydrologic alteration resulting from watershed urbanization is a common cause of aquatic ecosystem degradation. Developing environmental flow criteria for urbanizing watersheds requires quantitative flow-ecology relationships that describe biological responses to streamflow alteration. Ideally, gaged flow data are used to develop flow-ecology relationships; however, biological monitoring sites are frequently ungaged. For these ungaged locations, hydrologic models must be used to predict streamflow characteristics through calibration and testing at gaged sites, followed by extrapolation to ungaged sites. Physically-based modeling of rainfall-runoff response has frequently utilized "best overall fit" calibration criteria, such as the Nash-Sutcliffe Efficiency (NSE), that do not necessarily focus on specific aspects of the flow regime relevant to biota of interest. This study investigates the utility of employing flow characteristics known a priori to influence regional biological endpoints as "ecologically-focused" calibration criteria compared to traditional, "best overall fit" criteria. For this study, 19 continuous HEC-HMS 4.0 models were created in coastal southern California and calibrated to hourly USGS streamflow gages with nearby biological monitoring sites using one "best overall fit" and three "ecologically-focused" criteria: NSE, Richards-Baker Flashiness Index (RBI), percent of time when the flow is < 1 cfs (%<1), and a Combined Calibration (RBI and %<1). Calibrated models were compared using calibration accuracy, environmental flow metric reproducibility, and the strength of flow-ecology relationships. Results indicate that "ecologically-focused" criteria can be calibrated with high accuracy and may provide stronger flow-ecology relationships than "best overall fit" criteria, especially when multiple "ecologically-focused" criteria are used in concert, despite inabilities to accurately reproduce additional types of ecological flow metrics to which the
Multivariate Calibration Models for Sorghum Composition using Near-Infrared Spectroscopy
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.
Strain gage balance for half models 302-6. Calibration report
NASA Astrophysics Data System (ADS)
Blaettler, Heinz
1986-02-01
A six-component strain gage balance for half models 302-6 for the transonic wind tunnel was developed and calibrated. The calibration was executed with a special lever, so that forces and moments could be loaded at the point of attack of the model. Point 8 (for recording buffering) was also measured. The balance is conceived for: X = +/- 100 (N); Mx = +/- 200 (Nm); Y = +/- 200 (N); My = +/- 35 (Nm); Z = +/- 1000 (N); and Mz = +/- 30 (Nm).
Model Calibration and Optics Correction Using Orbit Response Matrix in the Fermilab Booster
Lebedev, V.A.; Prebys, E.; Petrenko, A.V.; Kopp, S.E.; McAteer, M.J.; /Texas U.
2012-05-01
We have calibrated the lattice model and measured the beta and dispersion functions in Fermilab's fast-ramping Booster synchrotron using the Linear Optics from Closed Orbit (LOCO) method. We used the calibrated model to implement ramped coupling, dispersion, and beta-beating corrections throughout the acceleration cycle, reducing horizontal beta beating from its initial magnitude of {approx}30% to {approx}10%, and essentially eliminating vertical beta-beating and transverse coupling.
The report gives results of activities relating to the Advanced Utility Simulation Model (AUSM): sensitivity testing. comparison with a mature electric utility model, and calibration to historical emissions. The activities were aimed at demonstrating AUSM's validity over input va...
Impacts of Hydraulic Variables on Groundwater Model Calibration for Long Island, New York
NASA Astrophysics Data System (ADS)
Chesebrough, E. G.; Gorokhovich, Y.
2014-12-01
Groundwater is the largest source of readily available freshwater on our planet. Aquifers are vulnerable to climate change and require new groundwater management plans to account for changing precipitation patterns and sea level rise, among other factors. Building a three dimensional groundwater model as framework for evaluating these changes is fundamental. Ultimately this model will be coupled with the output from several Global Circulation Models and used as a predictive model to determine the impact of climate change on Long Island, New York. This research looks at the process of modeling the physical elements of the groundwater hydrology of Long Island, New York. The model accounts for the unconfined and confined aquifers, as well as the confining zones. Calibration of the model includes visual comparisons with HA-709, a groundwater model built by the USGS in 1989, to illustrate similarities in the model foundation. The model is then calibrated by calculating the root mean square error between historic USGS groundwater data to the models simulated groundwater heads. Looking at how changes in the model impact the calibration process provides insight into model accuracy and modelers' choices. In this research we show how various combinations of model cell sizes, horizontal hydraulic conductivity, recharge, and drains impact model calibration, and ultimately the model that will be used during the research process.