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.
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...
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...
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.
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...
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...
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).
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
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.
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.
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...
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
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
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 ...
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.
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...
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.
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.
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
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.
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.
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...
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; 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.
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.
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.
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.
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...
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…
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…
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...
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.
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...
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 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.
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.
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
2016-04-01
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
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
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
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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
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.
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
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.
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...
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
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.
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.
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
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...
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)
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...
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...
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.
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.
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.
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.
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.
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.
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.
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…
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
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.
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
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
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
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.
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
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.
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...
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.
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.
Anh Bui; Nam Dinh; Brian Williams
2013-09-01
In addition to validation data plan, development of advanced techniques for calibration and validation of complex multiscale, multiphysics nuclear reactor simulation codes are a main objective of the CASL VUQ plan. Advanced modeling of LWR systems normally involves a range of physico-chemical models describing multiple interacting phenomena, such as thermal hydraulics, reactor physics, coolant chemistry, etc., which occur over a wide range of spatial and temporal scales. To a large extent, the accuracy of (and uncertainty in) overall model predictions is determined by the correctness of various sub-models, which are not conservation-laws based, but empirically derived from measurement data. Such sub-models normally require extensive calibration before the models can be applied to analysis of real reactor problems. This work demonstrates a case study of calibration of a common model of subcooled flow boiling, which is an important multiscale, multiphysics phenomenon in LWR thermal hydraulics. The calibration process is based on a new strategy of model-data integration, in which, all sub-models are simultaneously analyzed and calibrated using multiple sets of data of different types. Specifically, both data on large-scale distributions of void fraction and fluid temperature and data on small-scale physics of wall evaporation were simultaneously used in this work’s calibration. In a departure from traditional (or common-sense) practice of tuning/calibrating complex models, a modern calibration technique based on statistical modeling and Bayesian inference was employed, which allowed simultaneous calibration of multiple sub-models (and related parameters) using different datasets. Quality of data (relevancy, scalability, and uncertainty) could be taken into consideration in the calibration process. This work presents a step forward in the development and realization of the “CIPS Validation Data Plan” at the Consortium for Advanced Simulation of LWRs to enable
NASA Astrophysics Data System (ADS)
Jepsen, S. M.; Harmon, T. C.; Shi, Y.
2016-04-01
Calibration of watershed models to the shape of the base flow recession curve is a way to capture the important relationship between groundwater discharge and subsurface water storage in a catchment. In some montane Mediterranean regions, such as the midelevation Providence Creek catchment in the southern Sierra Nevada of California (USA), nearly all base flow recession occurs after snowmelt, and during this time evapotranspiration (ET) usually exceeds base flow. We assess the accuracy to which watershed models can be calibrated to ET-dominated base flow recession in Providence Creek, both in terms of fitting a discharge time-series and realistically capturing the observed discharge-storage relationship for the catchment. Model parameters estimated from calibrations to ET-dominated recession are compared to parameters estimated from reference calibrations to base flow recession with ET-effects removed ("potential recession"). We employ the Penn State Integrated Hydrologic Model (PIHM) for simulations of base flow and ET, and methods that are otherwise general in nature. In models calibrated to ET-dominated recession, simulation errors in ET and the targeted relationship for recession (-dQ/dt versus Q) contribute substantially (up to 57% and 46%, respectively) to overestimates in the discharge-storage differential, defined as d(lnQ)/dS, relative to that derived from water flux observations. These errors result in overestimates of deep-subsurface hydraulic conductivity in models calibrated to ET-dominated recession, by up to an order of magnitude, relative to reference calibrations to potential recession. These results illustrate a potential opportunity for improving model representation of discharge-storage dynamics by calibrating to the shape of base flow recession after removing the complicating effects of ET.
20nm CMP model calibration with optimized metrology data and CMP model applications
NASA Astrophysics Data System (ADS)
Katakamsetty, Ushasree; Koli, Dinesh; Yeo, Sky; Hui, Colin; Ghulghazaryan, Ruben; Aytuna, Burak; Wilson, Jeff
2015-03-01
Chemical Mechanical Polishing (CMP) is the essential process for planarization of wafer surface in semiconductor manufacturing. CMP process helps to produce smaller ICs with more electronic circuits improving chip speed and performance. CMP also helps to increase throughput and yield, which results in reduction of IC manufacturer's total production costs. CMP simulation model will help to early predict CMP manufacturing hotspots and minimize the CMP and CMP induced Lithography and Etch defects [2]. In the advanced process nodes, conventional dummy fill insertion for uniform density is not able to address all the CMP short-range, long-range, multi-layer stacking and other effects like pad conditioning, slurry selectivity, etc. In this paper, we present the flow for 20nm CMP modeling using Mentor Graphics CMP modeling tools to build a multilayer Cu-CMP model and study hotspots. We present the inputs required for good CMP model calibration, challenges faced with metrology collections and techniques to optimize the wafer cost. We showcase the CMP model validation results and the model applications to predict multilayer topography accumulation affects for hotspot detection. We provide the flow for early detection of CMP hotspots with Calibre CMPAnalyzer to improve Design-for-Manufacturability (DFM) robustness.
Thornton, Peter E; Wang, Weile; Law, Beverly E.; Nemani, Ramakrishna R
2009-01-01
The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.
NASA Astrophysics Data System (ADS)
Kim, Shaun Sang Ho; Hughes, Justin Douglas; Chen, Jie; Dutta, Dushmanta; Vaze, Jai
2015-11-01
A calibration method is presented that uses a sub-period resampling method to estimate probability distributions of performance for different parameter sets. Where conventional calibration methods implicitly identify the best performing parameterisations on average, the new method looks at the consistency of performance during sub-periods. The method is implemented with the conceptual river reach algorithms within the Australian Water Resources Assessments River (AWRA-R) model in the Murray-Darling Basin, Australia. The new method is tested for 192 reaches in a cross-validation scheme and results are compared to a traditional split-sample calibration-validation implementation. This is done to evaluate the new technique's ability to predict daily streamflow outside the calibration period. The new calibration method produced parameterisations that performed better in validation periods than optimum calibration parameter sets for 103 reaches and produced the same parameterisations for 35 reaches. The method showed a statistically significant improvement to predictive performance and potentially provides more rational flux terms over traditional split-sample calibration methods. Particular strengths of the proposed calibration method is that it avoids extra weighting towards rare periods of good agreement and also prevents compensating biases through time. The method can be used as a diagnostic tool to evaluate stochasticity of modelled systems and used to determine suitable model structures of different time-series models. Although the method is demonstrated using a hydrological model, the method is not limited to the field of hydrology and could be adopted for many different time-series modelling applications.
Calibration of Reduced Dynamic Models of Power Systems using Phasor Measurement Unit (PMU) Data
Zhou, Ning; Lu, Shuai; Singh, Ruchi; Elizondo, Marcelo A.
2011-09-23
Accuracy of a power system dynamic model is essential to the secure and efficient operation of the system. Lower confidence on model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, identification algorithms have been developed to calibrate parameters of individual components using measurement data from staged tests. To facilitate online dynamic studies for large power system interconnections, this paper proposes a model reduction and calibration approach using phasor measurement unit (PMU) data. First, a model reduction method is used to reduce the number of dynamic components. Then, a calibration algorithm is developed to estimate parameters of the reduced model. This approach will help to maintain an accurate dynamic model suitable for online dynamic studies. The performance of the proposed method is verified through simulation studies.
Do internal flow measurements improve the calibration of rainfall-runoff models?
NASA Astrophysics Data System (ADS)
Lerat, J.; AndréAssian, V.; Perrin, C.; Vaze, J.; Perraud, J. M.; Ribstein, P.; Loumagne, C.
2012-02-01
This paper compares four calibration strategies for a daily semidistributed rainfall-runoff model. The model is applied over 187 French catchments where streamflow data are available at the catchment outlet and at internal gauging stations. In the benchmark calibration strategy, the model parameters were optimized against the outlet flow only, with internal points considered as ungauged. In the three multisite alternative strategies, the parameters were optimized against the flow at the outlet and at one internal gauge. On 53 catchments, a second interior gauge was used as an independent validation point. The four methods were compared for their ability to estimate flow at the two internal points and at the catchment outlet, in calibration and validation modes, and considering three performance metrics. The results in validation indicate that interior flow data provided limited improvement in model performance. When the performance was evaluated at the outlet point, multisite calibrations led to nearly identical performance as the single-site calibrations, regardless of the number of calibrated parameters. Unexpectedly, similar results were obtained for most performance statistics when the model was evaluated at interior points. A sensitivity analysis performed on streamflow data confirmed that this conclusion still holds in presence of errors in flow data. Last, the comparison between lumped and semidistributed parameterizations clearly favored the lumped schemes, which show more stable parameters and equivalent performance for the simulation at independent interior points. The finding from this study provides confidence in lumped parameterization schemes, even for predicting the flow at interior gauges in a catchment.
NASA Astrophysics Data System (ADS)
Kunnath-Poovakka, A.; Ryu, D.; Renzullo, L. J.; George, B.
2016-04-01
Calibration of spatially distributed hydrologic models is frequently limited by the availability of ground observations. Remotely sensed (RS) hydrologic information provides an alternative source of observations to inform models and extend modelling capability beyond the limits of ground observations. This study examines the capability of RS evapotranspiration (ET) and soil moisture (SM) in calibrating a hydrologic model and its efficacy to improve streamflow predictions. SM retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and daily ET estimates from the CSIRO MODIS ReScaled potential ET (CMRSET) are used to calibrate a simplified Australian Water Resource Assessment - Landscape model (AWRA-L) for a selection of parameters. The Shuffled Complex Evolution Uncertainty Algorithm (SCE-UA) is employed for parameter estimation at eleven catchments in eastern Australia. A subset of parameters for calibration is selected based on the variance-based Sobol' sensitivity analysis. The efficacy of 15 objective functions for calibration is assessed based on streamflow predictions relative to control cases, and relative merits of each are discussed. Synthetic experiments were conducted to examine the effect of bias in RS ET observations on calibration. The objective function containing the root mean square deviation (RMSD) of ET result in best streamflow predictions and the efficacy is superior for catchments with medium to high average runoff. Synthetic experiments revealed that accurate ET product can improve the streamflow predictions in catchments with low average runoff.
More efficient evolutionary strategies for model calibration with watershed model for demonstration
NASA Astrophysics Data System (ADS)
Baggett, J. S.; Skahill, B. E.
2008-12-01
Evolutionary strategies allow automatic calibration of more complex models than traditional gradient based approaches, but they are more computationally intensive. We present several efficiency enhancements for evolution strategies, many of which are not new, but when combined have been shown to dramatically decrease the number of model runs required for calibration of synthetic problems. To reduce the number of expensive model runs we employ a surrogate objective function for an adaptively determined fraction of the population at each generation (Kern et al., 2006). We demonstrate improvements to the adaptive ranking strategy that increase its efficiency while sacrificing little reliability and further reduce the number of model runs required in densely sampled parts of parameter space. Furthermore, we include a gradient individual in each generation that is usually not selected when the search is in a global phase or when the derivatives are poorly approximated, but when selected near a smooth local minimum can dramatically increase convergence speed (Tahk et al., 2007). Finally, the selection of the gradient individual is used to adapt the size of the population near local minima. We show, by incorporating these enhancements into the Covariance Matrix Adaption Evolution Strategy (CMAES; Hansen, 2006), that their synergetic effect is greater than their individual parts. This hybrid evolutionary strategy exploits smooth structure when it is present but degrades to an ordinary evolutionary strategy, at worst, if smoothness is not present. Calibration of 2D-3D synthetic models with the modified CMAES requires approximately 10%-25% of the model runs of ordinary CMAES. Preliminary demonstration of this hybrid strategy will be shown for watershed model calibration problems. Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review. In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (Eds.). Towards a new evolutionary computation. Advances in estimation of
NASA Astrophysics Data System (ADS)
Matott, L. S.; Rabideau, A. J.
2006-05-01
Nitrate-contaminated groundwater discharge may be a significant source of pollutant loading to impaired water- bodies, and this contribution may be assessed via large-scale regional modeling of subsurface nitrogen transport. Several aspects of large-scale subsurface transport modeling make automated calibration a difficult task. First, the appropriate level of model complexity for a regional subsurface nitrogen transport model is not obvious. Additionally, there are immense computational costs associated with large-scale transport modeling, and these costs are further exacerbated by automated calibration, which can require thousands of model evaluations. Finally, available evidence suggests that highly complex reactive transport models suffer from parameter non-uniqueness, a characteristic that can frustrate traditional regression-based calibration algorithms. These difficulties are the topic of ongoing research at the University at Buffalo, and a preliminary modeling and calibration approach will be presented. The approach is in the early stages of development and is being tested on a 400 square kilometer model that encompasses an agricultural research site in the Neuse River Basin (the Lizzie Research Station), located on an active and privately owned hog farm. Early results highlight the sensitivity of calibrated denitrification rate constants to a variety of secondary processes, including surface complexation of iron and manganese, ion exchange, and the precipitation/dissolution of calcite and metals.
Bayesian calibration for electrochemical thermal model of lithium-ion cells
NASA Astrophysics Data System (ADS)
Tagade, Piyush; Hariharan, Krishnan S.; Basu, Suman; Verma, Mohan Kumar Singh; Kolake, Subramanya Mayya; Song, Taewon; Oh, Dukjin; Yeo, Taejung; Doo, Seokgwang
2016-07-01
Pseudo-two dimensional electrochemical thermal (P2D-ECT) model contains many parameters that are difficult to evaluate experimentally. Estimation of these model parameters is challenging due to computational cost and the transient model. Due to lack of complete physical understanding, this issue gets aggravated at extreme conditions like low temperature (LT) operations. This paper presents a Bayesian calibration framework for estimation of the P2D-ECT model parameters. The framework uses a matrix variate Gaussian process representation to obtain a computationally tractable formulation for calibration of the transient model. Performance of the framework is investigated for calibration of the P2D-ECT model across a range of temperatures (333 Ksbnd 263 K) and operating protocols. In the absence of complete physical understanding, the framework also quantifies structural uncertainty in the calibrated model. This information is used by the framework to test validity of the new physical phenomena before incorporation in the model. This capability is demonstrated by introducing temperature dependence on Bruggeman's coefficient and lithium plating formation at LT. With the incorporation of new physics, the calibrated P2D-ECT model accurately predicts the cell voltage with high confidence. The accurate predictions are used to obtain new insights into the low temperature lithium ion cell behavior.
NASA Astrophysics Data System (ADS)
Trendafiloski, G.; Gaspa Rebull, O.; Ewing, C.; Podlaha, A.; Magee, B.
2012-04-01
Calibration and validation are crucial steps in the production of the catastrophe models for the insurance industry in order to assure the model's reliability and to quantify its uncertainty. Calibration is needed in all components of model development including hazard and vulnerability. Validation is required to ensure that the losses calculated by the model match those observed in past events and which could happen in future. Impact Forecasting, the catastrophe modelling development centre of excellence within Aon Benfield, has recently launched its earthquake model for Algeria as a part of the earthquake model for the Maghreb region. The earthquake model went through a detailed calibration process including: (1) the seismic intensity attenuation model by use of macroseismic observations and maps from past earthquakes in Algeria; (2) calculation of the country-specific vulnerability modifiers by use of past damage observations in the country. The use of Benouar, 1994 ground motion prediction relationship was proven as the most appropriate for our model. Calculation of the regional vulnerability modifiers for the country led to 10% to 40% larger vulnerability indexes for different building types compared to average European indexes. The country specific damage models also included aggregate damage models for residential, commercial and industrial properties considering the description of the buildings stock given by World Housing Encyclopaedia and the local rebuilding cost factors equal to 10% for damage grade 1, 20% for damage grade 2, 35% for damage grade 3, 75% for damage grade 4 and 100% for damage grade 5. The damage grades comply with the European Macroseismic Scale (EMS-1998). The model was validated by use of "as-if" historical scenario simulations of three past earthquake events in Algeria M6.8 2003 Boumerdes, M7.3 1980 El-Asnam and M7.3 1856 Djidjelli earthquake. The calculated return periods of the losses for client market portfolio align with the
Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure
NASA Astrophysics Data System (ADS)
Cheng, Chun-Tian; Zhao, Ming-Yan; Chau, K. W.; Wu, Xin-Yu
2006-01-01
Genetic Algorithm (GA) is globally oriented in searching and thus useful in optimizing multiobjective problems, especially where the objective functions are ill-defined. Conceptual rainfall-runoff models that aim at predicting streamflow from the knowledge of precipitation over a catchment have become a basic tool for flood forecasting. The parameter calibration of a conceptual model usually involves the multiple criteria for judging the performances of observed data. However, it is often difficult to derive all objective functions for the parameter calibration problem of a conceptual model. Thus, a new method to the multiple criteria parameter calibration problem, which combines GA with TOPSIS (technique for order performance by similarity to ideal solution) for Xinanjiang model, is presented. This study is an immediate further development of authors' previous research (Cheng, C.T., Ou, C.P., Chau, K.W., 2002. Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. Journal of Hydrology, 268, 72-86), whose obvious disadvantages are to split the whole procedure into two parts and to become difficult to integrally grasp the best behaviors of model during the calibration procedure. The current method integrates the two parts of Xinanjiang rainfall-runoff model calibration together, simplifying the procedures of model calibration and validation and easily demonstrated the intrinsic phenomenon of observed data in integrity. Comparison of results with two-step procedure shows that the current methodology gives similar results to the previous method, is also feasible and robust, but simpler and easier to apply in practice.
NASA Astrophysics Data System (ADS)
Looper, Jonathan P.; Vieux, Baxter E.; Moreno, Maria A.
2012-02-01
SummaryPhysics-based distributed (PBD) hydrologic models predict runoff throughout a basin using the laws of conservation of mass and momentum, and benefit from more accurate and representative precipitation input. V flo™ is a gridded distributed hydrologic model that predicts runoff and continuously updates soil moisture. As a participating model in the second Distributed Model Intercomparison Project (DMIP2), V flo™ is applied to the Illinois and Blue River basins in Oklahoma. Model parameters are derived from geospatial data for initial setup, and then adjusted to reproduce the observed flow under continuous time-series simulations and on an event basis. Simulation results demonstrate that certain runoff events are governed by saturation excess processes, while in others, infiltration-rate excess processes dominate. Streamflow prediction accuracy is enhanced when multi-sensor precipitation estimates (MPE) are bias corrected through re-analysis of the MPE provided in the DMIP2 experiment, resulting in gauge-corrected precipitation estimates (GCPE). Model calibration identified a set of parameters that minimized objective functions for errors in runoff volume and instantaneous discharge. Simulated streamflow for the Blue and Illinois River basins, have Nash-Sutcliffe efficiency coefficients between 0.61 and 0.68, respectively, for the 1996-2002 period using GCPE. The streamflow prediction accuracy improves by 74% in terms of Nash-Sutcliffe efficiency when GCPE is used during the calibration period. Without model calibration, excellent agreement between hourly simulated and observed discharge is obtained for the Illinois, whereas in the Blue River, adjustment of parameters affecting both saturation and infiltration-rate excess processes were necessary. During the 1996-2002 period, GCPE input was more important than model calibration for the Blue River, while model calibration proved more important for the Illinois River. During the verification period (2002
Modeling the Evolution of Incised Streams: III. Model Application
Technology Transfer Automated Retrieval System (TEKTRAN)
Incision and ensuing widening of alluvial stream channels is widespread in the midsouth and midwestern United States and represents an important form of channel adjustment. Two accompanying papers have presented a robust computational model for simulating the long-term evolution of incised and resto...
NASA Astrophysics Data System (ADS)
Nekouei Shahraki, M.; Haala, N.
2015-09-01
To ensure making valid decisions with high accuracy in machine vision systems such as driver-assistant systems, a primary key factor is to have accurate measurements, which means that we need accurate camera calibration for various optical designs and a very fast approach to analyse the calibration data in real-time. Conventional methods have specific limitations such as limited accuracy, instability by using complex models, difficulties to model the local lens distortions and limitation in real-time calculations that altogether show the necessity to introduce new solutions. We introduce a new model for lens distortion modelling with high accuracies beyond conventional models while yet allowing real-time calculation. The concept is based on Free-Function modelling in a posterior calibration step using the initial distortion estimation and the corresponding residuals on the observations as input information. Free-Function model is the technique of numerically and locally modelling the lens distortion field by assuming unknown functions in our calibration model. This increases the model's flexibility to fit to different optical designs and be able to model the very local lens distortions. Using the Free-Function model one can observe great enhancements in accuracy (in comparison with classical models). Furthermore, by increasing the number of control points and improving their distribution the quality of lens modelling would be improved; a characteristic which is not present in the classical methods.
Calibration of the Variable Infiltration Capacity Model from Hyper-Resolution to the Regional Scale
NASA Astrophysics Data System (ADS)
Uijlenhoet, R.; Melsen, L. A.; Teuling, R.; Torfs, P.; Zappa, M.
2014-12-01
The Variable Infiltration Capacity (VIC, Liang et al., 1994) model has been used for a broad range of applications, in hydrology as well as in the fields of climate and global change. Calibration of the often distributed application of the model is difficult, certainly in the light of the ongoing discussion on applying global models at hyper-resolution (Wood et al., 2011). To improve the calibration procedure for VIC applied at grid resolutions varying from meso-scale catchments to the 1 km 'hyper'resolution now used in several global modeling studies, the parameters of the model are studied in more detail with specific focus on scale effects. A lumped VIC-model was constructed for three nested basins: the Rietholzbach (3.4 km2), Jonschwil (492 km2) and the Thur basin (1700 km2) in Switzerland. With the DELSA sensitivity analysis method (Rakovec et al., 2013) it was shown that parameter sensitivity does not change over scale. Extensive calibration of the lumped models using the DREAM algorithm (Vrugt et al., 2008) revealed that most of the calibrated parameter values of the three basins were within each others uncertainty bound based on the converged part of the posterior. This information was used for calibration of the distributed VIC models, which where constructed for the Thur basin at a grid resolution of 1x1 km, 5x5 km and 10x10 km.
Zhu, Feng; Dong, Liqiang; Jin, Xin; Jiang, Binhui; Kalra, Anil; Shen, Ming; Yang, King H
2015-11-01
Anthropometric test devices (ATDs), such as the Hybrid III crash-test dummy, have been used to simulate lowerextremity responses to military personnel subjected to loading conditions from anti-vehicular (AV) landmine blasts. Numerical simulations [e.g., finite element (FE) analysis] of such high-speed vertical loading on ATD parts require accurate material parameters that are dependent on strain rate. This study presents a combined experimental and computational study to calibrate the rate-dependent properties of three materials on the lower extremities of the Hybrid III dummy. The three materials are heelpad foam, foot skin, and lower-leg flesh, and each has properties that can affect simulation results of forces and moments transferred to the lower extremities. Specifically, the behavior of the heel-pad foam was directly calibrated through standard compression tests, and the properties of the foot skin and lower-leg flesh were calibrated based on an optimization procedure in which the material parameters were adjusted for best fit between the calculated force-deflection responses and least squares of the experimental data. The material models updated with strain-rate effects were then integrated into an ATD full-body FE model (FEM), which was used to simulate vertical impulsive loading responses at different speeds. Results of validations using this model demonstrated basic replication of experimentally obtained response patterns of the tibia. The bending moments matched those calculated from the experimental data 25-40% more accurately than those obtained from the original model, and axial forces were 60-90% more accurate. However, neither the original nor the modified models well captured whole-body response patterns, and further improvements are required. As a generalized approach, the optimization method presented in this paper can be applied to characterize material constants for a wide range of materials. PMID:26660755
NASA Astrophysics Data System (ADS)
Shafii, Mahyar; Tolson, Bryan A.
2015-05-01
The simulated outcome of a calibrated hydrologic model should be hydrologically consistent with the measured response data. Hydrologic modelers typically calibrate models to optimize residual-based goodness-of-fit measures, e.g., the Nash-Sutcliffe efficiency measure, and then evaluate the obtained results with respect to hydrological signatures, e.g., the flow duration curve indices. The literature indicates that the consideration of a large number of hydrologic signatures has not been addressed in a full multiobjective optimization context. This research develops a model calibration methodology to achieve hydrological consistency using goodness-of-fit measures, many hydrological signatures, as well as a level of acceptability for each signature. The proposed framework relies on a scoring method that transforms any hydrological signature to a calibration objective. These scores are used to develop the hydrological consistency metric, which is maximized to obtain hydrologically consistent parameter sets during calibration. This consistency metric is implemented in different signature-based calibration formulations that adapt the sampling according to hydrologic signature values. These formulations are compared with the traditional formulations found in the literature for seven case studies. The results reveal that Pareto dominance-based multiobjective optimization yields the highest level of consistency among all formulations. Furthermore, it is found that the choice of optimization algorithms does not affect the findings of this research.
CALIBRATION AND UNCERTAINTY ANALYSIS OF SWAT MODEL IN A JAPANESE RIVER CATCHMENT
NASA Astrophysics Data System (ADS)
Luo, Pingping; Takara, Kaoru; He, Bin; Cao, Wenqiang; Yamashiki, Yosuke; Nover, Daniel
Calibration and uncertainty analysis is necessary to perform the best estimation and uncertainty identification of hydrological models. This paper uses the Soil and Water Assessment Tool-Calibration and Uncertainly Procedures (SWAT-CUP) model to analyze the uncertainty of SWAT model in a Japanese river catchment. The GLUE and SUFI-2 techniques used in this analysis show quite good results with high value of R2 as 0.98 and 0.95 for monthly simulation. Daily simulation results during calibration and validation are also good with R2 as 0.86 and 0.80. For uncertainty results, the 95% prediction uncertainty (95PPU) brackets very well with the observation. The p-factors of uncertainty analysis for the calibration and validation periods are 92% and 94%. The calibration result by using GLUE shows better than that by using SUFI-2. However, the processing time of the GLUE approach is longer than SUFI-2 approach when they were run in the SWAT-CUP. The uncertainty analysis indicates that the parameters of effective hydraulic conductivity in main channel alluvium (CH_K2) and base-flow alpha factor for bank storage (ALPHA_BNK) play important roles for calibration and validation of SWAT model.
NASA Astrophysics Data System (ADS)
Uddameri, V.; Kuchanur, M.
2007-01-01
Soil moisture balance studies provide a convenient approach to estimate aquifer recharge when only limited site-specific data are available. A monthly mass-balance approach has been utilized in this study to estimate recharge in a small watershed in the coastal bend of South Texas. The developed lumped parameter model employs four adjustable parameters to calibrate model predicted stream runoff to observations at a gaging station. A new procedure was developed to correctly capture the intermittent nature of rainfall. The total monthly rainfall was assigned to a single-equivalent storm whose duration was obtained via calibration. A total of four calibrations were carried out using an evolutionary computing technique called genetic algorithms as well as the conventional gradient descent (GD) technique. Ordinary least squares and the heteroscedastic maximum likelihood error (HMLE) based objective functions were evaluated as part of this study as well. While the genetic algorithm based calibrations were relatively better in capturing the peak runoff events, the GD based calibration did slightly better in capturing the low flow events. Treating the Box-Cox exponent in the HMLE function as a calibration parameter did not yield better estimates and the study corroborates the suggestion made in the literature of fixing this exponent at 0.3. The model outputs were compared against available information and results indicate that the developed modeling approach provides a conservative estimate of recharge.
Calibrating the Johnson-Holmquist Ceramic Model for sic Using Cth
NASA Astrophysics Data System (ADS)
Cazamias, J. U.; Bilyk, S. R.
2009-12-01
The Johnson-Holmquist ceramic material model has been calibrated and successfully applied to numerically simulate ballistic events using the Lagrangian code EPIC. While the majority of the constants are "physics" based, two of the constants for the failed material response are calibrated using ballistic experiments conducted on a confined cylindrical ceramic target. The maximum strength of the failed ceramic is calibrated by matching the penetration velocity. The second refers to the equivalent plastic strain at failure under constant pressure and is calibrated using the dwell time. Use of these two constants in the CTH Eulerian hydrocode does not predict the ballistic response. This difference may be due to the phenomenological nature of the model and the different numerical schemes used by the codes. This paper determines the aforementioned material constants for SiC suitable for simulating ballistic events using CTH.
Calibrating the Johnson-Holmquist Ceramic Model for SiC using CTH
NASA Astrophysics Data System (ADS)
Cazamias, James
2009-06-01
The Johnson-Holmquist ceramic material model has been calibrated and successfully applied to numerically simulate ballistic events using the Lagrangian code EPIC. While the majority of the constants are ``physics'' based, two of the constants for the failed material response are calibrated using ballistic experiments conducted on a confined cylindrical ceramic target. The maximum strength of the failed ceramic is calibrated by matching the penetration velocity. The second refers to the equivalent plastic strain at failure under constant pressure and is calibrated using the dwell time. Use of these two constants in the CTH Eulerian hydrocode does not predict the ballistic response. This difference may be due to the phenomenological nature of the model and the different numerical schemes used by the codes. This paper determines the afore mentioned material constants for SiC suitable for simulating ballistic events using CTH.
CALIBRATING THE JOHNSON-HOLMQUIST CERAMIC MODEL FOR SIC USING CTH
Cazamias, J. U.; Bilyk, S. R.
2009-12-28
The Johnson-Holmquist ceramic material model has been calibrated and successfully applied to numerically simulate ballistic events using the Lagrangian code EPIC. While the majority of the constants are ''physics'' based, two of the constants for the failed material response are calibrated using ballistic experiments conducted on a confined cylindrical ceramic target. The maximum strength of the failed ceramic is calibrated by matching the penetration velocity. The second refers to the equivalent plastic strain at failure under constant pressure and is calibrated using the dwell time. Use of these two constants in the CTH Eulerian hydrocode does not predict the ballistic response. This difference may be due to the phenomenological nature of the model and the different numerical schemes used by the codes. This paper determines the aforementioned material constants for SiC suitable for simulating ballistic events using CTH.
NASA Technical Reports Server (NTRS)
Scott, W. A.
1984-01-01
The propulsion simulator calibration laboratory (PSCL) in which calibrations can be performed to determine the gross thrust and airflow of propulsion simulators installed in wind tunnel models is described. The preliminary checkout, evaluation and calibration of the PSCL's 3 component force measurement system is reported. Methods and equipment were developed for the alignment and calibration of the force measurement system. The initial alignment of the system demonstrated the need for more efficient means of aligning system's components. The use of precision alignment jigs increases both the speed and accuracy with which the system is aligned. The calibration of the force measurement system shows that the methods and equipment for this procedure can be successful.
Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates
NASA Astrophysics Data System (ADS)
Todorovic, Andrijana; Plavsic, Jasna
2015-04-01
A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters
ATOMIC DATA AND SPECTRAL MODEL FOR Fe III
Bautista, Manuel A.; Ballance, Connor P.; Quinet, Pascal
2010-08-01
We present new atomic data (radiative transitions rates and collision strengths) from large-scale calculations and a non-LTE spectral model for Fe III. This model is in very good agreement with observed astronomical emission spectra, in contrast with previous models that yield large discrepancies in observations. The present atomic computations employ a combination of atomic physics methods, e.g., relativistic Hartree-Fock, the Thomas-Fermi-Dirac potential, and Dirac-Fock computation of A-values and the R-matrix with intermediate coupling frame transformation and the Dirac R-matrix. We study advantages and shortcomings of each method. It is found that the Dirac R-matrix collision strengths yield excellent agreement with observations, much improved over previously available models. By contrast, the transformation of the LS-coupling R-matrix fails to yield accurate effective collision strengths at around 10{sup 4} K, despite using very large configuration expansions, due to the limited treatment of spin-orbit effects in the near-threshold resonances of the collision strengths. The present work demonstrates that accurate atomic data for low-ionization iron-peak species are now within reach.
NASA Astrophysics Data System (ADS)
Keawbunsong, P.; Supanakoon, P.; Promwong, S.
2015-05-01
This article presents Hata's path loss model calibration in order to predict a design of the Digital Terrestrial Television (DTTV) Propagation in an urban area of the south of Thailand through measuring power signal of the network operators’ broadcasting in 4 channels within Haadyai urban area, Songkla Province. The chosen location is a density area, a distance of 2.5-6.5 km. from the broadcasting station. The calibration was conducted through a statistical method of Root Mean Square Error (RMSE) from received power signal and compared with a path loss model from the prediction, followed by looking for relative errors to indicate the efficiency of the calibration model. The RMSE analytical result of CH 26 with the frequency of 514 MHz; CH 42 with the frequency of 642 MHz; CH 46 with the frequency of 674 MHz; CH 54 with the frequency of 738 MHz shows that Hata's path loss model calibration is closer to the measured data than the original and the other model whereas the relative errors are closer to zero than the predicted path loss model. This makes the Hata's path loss model calibration become more accurate in the prediction and subsequently more suitable for use in planning the network design.
Rafique, Rashad; Fienen, Michael N.; Parkin, Timothy B.; Anex, Robert P.
2013-01-01
DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameterized through a traditional “trial and error” approach and has not been calibrated using statistical inverse modelling (i.e. algorithmic parameter estimation). The aim of this study is to establish and demonstrate a procedure for calibration of DayCent to improve estimation of GHG emissions. We coupled DayCent with the parameter estimation (PEST) software for inverse modelling. The PEST software can be used for calibration through regularized inversion as well as model sensitivity and uncertainty analysis. The DayCent model was analysed and calibrated using N2O flux data collected over 2 years at the Iowa State University Agronomy and Agricultural Engineering Research Farms, Boone, IA. Crop year 2003 data were used for model calibration and 2004 data were used for validation. The optimization of DayCent model parameters using PEST significantly reduced model residuals relative to the default DayCent parameter values. Parameter estimation improved the model performance by reducing the sum of weighted squared residual difference between measured and modelled outputs by up to 67 %. For the calibration period, simulation with the default model parameter values underestimated mean daily N2O flux by 98 %. After parameter estimation, the model underestimated the mean daily fluxes by 35 %. During the validation period, the calibrated model reduced sum of weighted squared residuals by 20 % relative to the default simulation. Sensitivity analysis performed provides important insights into the model structure providing guidance for model improvement.
Rebaudo, François; Faye, Emile; Dangles, Olivier
2016-01-01
A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species
Rebaudo, François; Faye, Emile; Dangles, Olivier
2016-01-01
A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species
Spatial calibration and temporal validation of flow for regional scale hydrologic modeling
Technology Transfer Automated Retrieval System (TEKTRAN)
Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validat...
ERIC Educational Resources Information Center
Kubinger, Klaus D.
2005-01-01
This article emphasizes that the Rasch model is not only very useful for psychological test calibration but is also necessary if the number of solved items is to be used as an examinee's score. Simplified proof that the Rasch model implies specific objective parameter comparisons is given. Consequently, a model check per se is possible. For data…
ERIC Educational Resources Information Center
Kubinger, Klaus D.
2005-01-01
In this article, we emphasize that the Rasch model is not only very useful for psychological test calibration but is also necessary if the number of solved items is to be used as an examinee's score. Simplified proof that the Rasch model implies specific objective parameter comparisons is given. Consequently, a model check per se is possible. For…
Maximin Calibration Designs for the Nominal Response Model: An Empirical Evaluation
ERIC Educational Resources Information Center
Passos, Valeria Lima; Berger, Martijn P. F.
2004-01-01
The problem of finding optimal calibration designs for dichotomous item response theory (IRT) models has been extensively studied in the literature. In this study, this problem will be extended to polytomous IRT models. Focus is given to items described by the nominal response model (NRM). The optimizations objective is to minimize the generalized…
Heistand, B.E.; Novak, E.F.
1984-04-01
This report documents the work performed to determine the newly assigned concentrations for the spectral gamma-ray borehole calibration models. Thirty-two models, maintained by the US Department of Energy, are included in this study, and are grouped into eight sets of four models each. The eight sets are located at sites across the United States, and are used to calibrate logging instruments. The assignments are based on in-situ logging data to ensure self-consistency in the assigned concentrations, and on laboratory assays of concrete samples from each model to provide traceability to the New Brunswick Laboratory (NBL) standards. 13 references, 7 figures, 17 tables.
Cui, De-qi; Liao, Ning-fang; Cao, Wei-liang; Tan, Bo-neng; Tian, Li-xun
2011-07-01
All-reflection Fourier transform imaging spectrometer (ARFTIS) is a novel imaging spectrometer. The specialty is not only high spectrum resolution, but also wide band and non-chromatism. It is good for remote sensing field of wide band imaging. Single spectrum calibration, average calibration and weighted average calibration are three common calibration methods. However, they all are limited. Because they cannot meet the demand on both convenience and high precision. In the present paper, the authors propose a novel model for spectrum calibration. It can work in high precision with single spectrum calibration. At the same time, the method is steady, and the average error is less than 5% with multi-bands calibration. It provides a convenient way for the non-professional calibration situation and outer simply calibration work. PMID:21942019
Toward cosmological-model-independent calibrations for the luminosity relations of Gamma-Ray Bursts
NASA Astrophysics Data System (ADS)
Ding, Xuheng; Li, Zhengxiang; Zhu, Zong-Hong
2015-05-01
Gamma-ray bursts (GRBs), have been widely used as distance indicators to measure the cosmic expansion and explore the nature of dark energy. A popular method adopted in previous works is to calibrate the luminosity relations which are responsible for distance estimation of GRBs with more primary (low redshift) cosmic distance ladder objects, type Ia supernovae (SNe Ia). Since distances of SNe Ia in all SN Ia samples used to calibrate GRB luminosity relations were usually derived from the global fit in a specific cosmological model, the distance of GRB at a given redshift calibrated with matching SNe Ia was still cosmological-model-dependent. In this paper, we first directly determine the distances of SNe Ia with the Angular Diameter Distances (ADDs) of galaxy clusters without any assumption for the background of the universe, and then calibrate GRB luminosity relations with our cosmology-independent distances of SNe Ia. The results suggest that, compared to the previous original manner where distances of SNe Ia used as calibrators are determined from the global fit in a particular cosmological model, our treatments proposed here yield almost the same calibrations of GRB luminosity relations and the cosmological implications of them do not suffer any circularity.
Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation
and Ben Polly, Joseph Robertson; Polly, Ben; Collis, Jon
2013-09-01
This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define "explicit" input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.
Evaluation of Automated Model Calibration Techniques for Residential Building Energy Simulation
Robertson, J.; Polly, B.; Collis, J.
2013-09-01
This simulation study adapts and applies the general framework described in BESTEST-EX (Judkoff et al 2010) for self-testing residential building energy model calibration methods. BEopt/DOE-2.2 is used to evaluate four mathematical calibration methods in the context of monthly, daily, and hourly synthetic utility data for a 1960's-era existing home in a cooling-dominated climate. The home's model inputs are assigned probability distributions representing uncertainty ranges, random selections are made from the uncertainty ranges to define 'explicit' input values, and synthetic utility billing data are generated using the explicit input values. The four calibration methods evaluated in this study are: an ASHRAE 1051-RP-based approach (Reddy and Maor 2006), a simplified simulated annealing optimization approach, a regression metamodeling optimization approach, and a simple output ratio calibration approach. The calibration methods are evaluated for monthly, daily, and hourly cases; various retrofit measures are applied to the calibrated models and the methods are evaluated based on the accuracy of predicted savings, computational cost, repeatability, automation, and ease of implementation.
NASA Astrophysics Data System (ADS)
Wright, David; Thyer, Mark; Westra, Seth
2015-04-01
Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this
NASA Astrophysics Data System (ADS)
Aronica, G.; Hankin, B.; Beven, K.
Monte-Carlo simulations of a two-dimensional finite element model of a flood in the southern part of Sicily were used to explore the parameter space of distributed bed-roughness coefficients. For many real-world events specific data are extremely limited so that there is not only fuzziness in the information available to calibrate the model, but fuzziness in the degree of acceptability of model predictions based upon the different parameter values, owing to model structural errors. Here the GLUE procedure is used to compare model predictions and observations for a certain event, coupled with both a fuzzy-rule-based calibration, and a calibration technique based upon normal and heteroscedastic distributions of the predicted residuals. The fuzzy-rule-based calibration is suited to an event of this kind, where the information about the flood is highly uncertain and arises from several different types of observation. The likelihood (relative possibility) distributions predicted by the two calibration techniques are similar, although the fuzzy approach enabled us to constrain the parameter distributions more usefully, to lie within a range which was consistent with the modellers' a priori knowledge of the system.
Calibration of a distributed hydrological model using satellite data of land surface temperature
NASA Astrophysics Data System (ADS)
Corbari, Chiara; Mancini, Marco; Ravazzani, Giovanni
2013-04-01
Calibration and validation of distributed models at basin scale generally refer to external variables, which are integrated catchment model outputs, and usually depend on the comparison between simulated and observed discharges at the available rivers cross sections, which are usually very few. However distributed models allow an internal validation due to their intrinsic structure, so that internal processes and variables of the model can be controlled in each cell of the domain. In particular this work investigates the potentiality to control evapotranspiration and its spatial and temporal variability through the detection of land surface temperature (LST) from satellite remote sensing. This study proposes a methodology for the calibration of distributed hydrological models at basin scale using remote sensing data of land surface temperature. The distributed energy water balance model, Flash-flood Event-based Spatially-distributed rainfall-runoff Transformation - Energy Water Balance model (FEST-EWB) will be calibrated in the Upper Po river basin (Italy) closed at the river cross section of Ponte della Becca with a total catchment area of about 38000 km2. The model algorithm solves the system of energy and mass balances in term of the representative pixel equilibrium temperature (RET) that governs the fluxes of energy and mass over the basin domain. This equilibrium surface temperature, which is a critical model state variable, is comparable to the land surface temperature (LST) from satellite. So a pixel to pixel semi-automatic calibration procedure of soil and vegetation parameter is presented through the comparison between the model internal state variable RET and the remotely observed LST. A similar calibration procedure will also be applied performing the traditional calibration using only discharge measurements. 260 diurnal and nocturne LST MODIS products are compared with FEST-EWB land surface temperature over the 11 years of simulation from 2000 to 2010
Liu, Xianhua; Wang, Lili
2015-01-01
A series of ultraviolet-visible (UV-Vis) spectra from seawater samples collected from sites along the coastline of Tianjin Bohai Bay in China were subjected to multivariate partial least squares (PLS) regression analysis. Calibration models were developed for monitoring chemical oxygen demand (COD) and concentrations of total organic carbon (TOC). Three different PLS models were developed using the spectra from raw samples (Model-1), diluted samples (Model-2), and diluted and raw samples combined (Model-3). Experimental results showed that: (i) possible nonlinearities in the signal concentration relationships were well accounted for by the multivariate PLS model; (ii) the predicted values of COD and TOC fit the analytical values well; the high correlation coefficients and small root mean squared error of cross-validation (RMSECV) showed that this method can be used for seawater quality monitoring; and (iii) compared with Model-1 and Model-2, Model-3 had the highest coefficient of determination (R2) and the lowest number of latent variables. This latter finding suggests that only large data sets that include data representing different combinations of conditions (i.e., various seawater matrices) will produce stable site-specific regressions. The results of this study illustrate the effectiveness of the proposed method and its potential for use as a seawater quality monitoring technique. PMID:26442484
A kinetic model for bacterial Fe(III) oxide reduction in batch cultures
NASA Astrophysics Data System (ADS)
Hacherl, Eric L.; Kosson, David S.; Cowan, Robert M.
2003-04-01
A model has been developed describing the microbial reduction of solid-phase electron acceptors (Fe(III) oxides) as well as dissolved electron acceptors (chelated Fe(III) or organic electron shuttles) in Shewanella alga BrY. The model utilized a multiple-substrate, Monod kinetics formulation. The Monod description of solid Fe(III) reduction requires a normalization of surface Fe concentration to biomass concentration in order to describe the "bioavailable" Fe(III) concentration. The model also contains provisions for irreversible sorption of Fe(II) to Fe(III) oxide surfaces and for the precipitation of Fe(III) carbonates. The loss of bioavailable Fe(III) due to sorption of Fe(II) was found to be minor, even for highly sorptive amorphous Fe(III) oxyhydroxides. However, the final extent of microbial reduction is very sensitive to the rate of siderite precipitation, assuming that siderite precipitation could partially occlude Fe(III) surface sites. The use of a multisubstrate Monod kinetics model enabled an evaluation of the effects of electron shuttles on solid Fe(III) reduction. Because the electron shuttle is recycled, very small additions can greatly increase the overall rate of solid Fe(III) reduction.
Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.
2015-01-01
The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.
Multi-Objective Calibration of Hydrological Model Parameters Using MOSCEM-UA
NASA Astrophysics Data System (ADS)
Wang, Yuhui; Lei, Xiaohui; Jiang, Yunzhong; Wang, Hao
2010-05-01
In the past two decades, many evolutionary algorithms have been adopted in the auto-calibration of hydrological model such as NSGA-II, SCEM, etc., some of which has shown ideal performance. In this article, a detailed hydrological model auto-calibration algorithm Multi-objective Shuffled Complex Evolution Metropolis (MOSCEM-UA) has been introduced to carry out auto-calibration of hydrological model in order to clarify the equilibrium and the uncertainty of model parameters. The development and the implement flow chart of the advanced multi-objective algorithm (MOSCEM-UA) were interpreted in detail. Hymod, a conceptual hydrological model depending on Moore's concept, was then introduced as a lumped Rain-Runoff simulation approach with several principal parameters involved. The five important model parameters subjected to calibration includes maximum storage capacity, spatial variability of the soil moisture capacity, flow distributing factor between slow and quick reservoirs as well as slow tank and quick tank distribution factor. In this study, a test case on the up-stream area of KuanCheng hydrometric station in Haihe basin was studied to verify the performance of calibration. Two objectives including objective for high flow process and objective for low flow process are chosen in the process of calibration. The results emphasized that the interrelationship between objective functions could be described in correlation Pareto Front by using MOSCEM-UA. The Pareto Front can be draw after the iteration. Further more, post range of parameters corresponding to Pareto sets could also be drawn to identify the prediction range of the model. Then a set of balanced parameter was chosen to validate the model and the result showed an ideal prediction. Meanwhile, the correlation among parameters and their effects on the model performance could also be achieved.
NASA Astrophysics Data System (ADS)
Wentworth, Mami Tonoe
Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification
Meininger, Daniel J; Chee-Garza, Max; Arman, Hadi D; Tonzetich, Zachary J
2016-03-01
Gallium(III) tetraphenylporphyrinates (TPP) containing anionic sulfur ligands have been prepared and characterized in the solid state and solution. The complexes serve as structural models for iron(III) heme sites containing sulfur coordination that otherwise prove challenging to synthesize due to the propensity for reduction to iron(II). The compounds prepared include the first well-characterized example of a trivalent metalloporphyrinate containing a terminal hydrosulfide ligand, [Ga(SH)(TPP)], as well as [Ga(SEt)(TPP)], [Ga(SPh)(TPP)], and [Ga(SSi(i)Pr3)(TPP)]. The stability of these compounds toward reduction has permitted an investigation of their solid-state structures and electrochemistry. The structural features and reaction chemistry of the complexes in relation to their iron(III) analogs is discussed. PMID:26872092
Rafique, Rashid; Kumar, Sandeep; Luo, Yiqi; Kiely, Gerard; Asrar, Ghassem R.
2015-02-01
he accurate calibration of complex biogeochemical models is essential for the robust estimation of soil greenhouse gases (GHG) as well as other environmental conditions and parameters that are used in research and policy decisions. DayCent is a popular biogeochemical model used both nationally and internationally for this purpose. Despite DayCent’s popularity, its complex parameter estimation is often based on experts’ knowledge which is somewhat subjective. In this study we used the inverse modelling parameter estimation software (PEST), to calibrate the DayCent model based on sensitivity and identifi- ability analysis. Using previously published N2 O and crop yield data as a basis of our calibration approach, we found that half of the 140 parameters used in this study were the primary drivers of calibration dif- ferences (i.e. the most sensitive) and the remaining parameters could not be identified given the data set and parameter ranges we used in this study. The post calibration results showed improvement over the pre-calibration parameter set based on, a decrease in residual differences 79% for N2O fluxes and 84% for crop yield, and an increase in coefficient of determination 63% for N2O fluxes and 72% for corn yield. The results of our study suggest that future studies need to better characterize germination tem- perature, number of degree-days and temperature dependency of plant growth; these processes were highly sensitive and could not be adequately constrained by the data used in our study. Furthermore, the sensitivity and identifiability analysis was helpful in providing deeper insight for important processes and associated parameters that can lead to further improvement in calibration of DayCent model.
Validation of the predictive power of a calibrated physical stochastic resist model
NASA Astrophysics Data System (ADS)
Robertson, Stewart A.; Biafore, John J.; Smith, Mark D.; Reilly, Michael T.; Wandell, Jerome
2009-12-01
A newly developed stochastic resist model, implemented in a prototype version of the PROLITH lithography simulation software is fitted to experimental data for a commercially available immersion ArF photoresist, EPIC 2013 (Dow Electronic Materials). Calibration is performed only considering the mean CD value through focus and dose for three line/space features of varying pitch (dense, semi-dense and isolated). An unweighted Root Mean Squared Error (RMSE) of approximately 2.0 nm is observed when the calibrated model is compared to the experimental data. Although the model is calibrated only to mean CD values, it is able to accurately predict LER through focus to better than 1.5 nm RMSE and highly accurate CDU distributions at fixed focus and dose conditions. It is also shown how a stochastic model can be used to the describe the bridging behavior often observed at marginal focus and exposure conditions.
Effectiveness of a regional model calibrated to different parts of a flow regime in regionalisation
NASA Astrophysics Data System (ADS)
Kim, H. S.
2015-07-01
The objective of this study was to reduce the parameter uncertainty which has an effect on the identification of the relationship between the catchment characteristics and the catchment response dynamics in ungauged catchments. A water balance model calibrated to represent the rainfall runoff characteristics over long time scales had a potential limitation in the modelling capacity to accurately predict the hydrological effects of non-stationary catchment response dynamics under different climate conditions (distinct wet and dry periods). The accuracy and precision of hydrological modelling predictions was assessed to yield a better understanding for the potential improvement of the model's predictability. In the assessment of model structure suitability to represent the non-stationary catchment response characteristics, there was a flow-dependent bias in the runoff simulations. In particular, over-prediction of the streamflow was dominant for the dry period. The poor model performance during the dry period was associated with the largely different impulse response estimates for the entire period and the dry period. The refined calibration approach was established based on assessment of model deficiencies. The rainfall-runoff models were separately calibrated to different parts of the flow regime, and the calibrated models for the separated time series were used to establish the regional models of relevant parts of the flow regime (i.e. wet and dry periods). The effectiveness of the parameter values for the refined approach in regionalisation was evaluated through investigating the accuracy of predictions of the regional models. The predictability was demonstrated using only the dry period to highlight the improvement in model performance easily veiled by the performance of the model for the whole period. The regional models from the refined calibration approach clearly enhanced the hydrological behaviour by improving the identification of the relationships between
Calibrated Blade-Element/Momentum Theory Aerodynamic Model of the MARIN Stock Wind Turbine: Preprint
Goupee, A.; Kimball, R.; de Ridder, E. J.; Helder, J.; Robertson, A.; Jonkman, J.
2015-04-02
In this paper, a calibrated blade-element/momentum theory aerodynamic model of the MARIN stock wind turbine is developed and documented. The model is created using open-source software and calibrated to closely emulate experimental data obtained by the DeepCwind Consortium using a genetic algorithm optimization routine. The provided model will be useful for those interested in validating interested in validating floating wind turbine numerical simulators that rely on experiments utilizing the MARIN stock wind turbine—for example, the International Energy Agency Wind Task 30’s Offshore Code Comparison Collaboration Continued, with Correlation project.
Hill, M.C.; D'Agnese, F. A.; Faunt, C.C.
2000-01-01
Fourteen guidelines are described which are intended to produce calibrated groundwater models likely to represent the associated real systems more accurately than typically used methods. The 14 guidelines are discussed in the context of the calibration of a regional groundwater flow model of the Death Valley region in the southwestern United States. This groundwater flow system contains two sites of national significance from which the subsurface transport of contaminants could be or is of concern: Yucca Mountain, which is the potential site of the United States high-level nuclear-waste disposal; and the Nevada Test Site, which contains a number of underground nuclear-testing locations. This application of the guidelines demonstrates how they may be used for model calibration and evaluation, and also to direct further model development and data collection.Fourteen guidelines are described which are intended to produce calibrated groundwater models likely to represent the associated real systems more accurately than typically used methods. The 14 guidelines are discussed in the context of the calibration of a regional groundwater flow model of the Death Valley region in the southwestern United States. This groundwater flow system contains two sites of national significance from which the subsurface transport of contaminants could be or is of concern: Yucca Mountain, which is the potential site of the United States high-level nuclear-waste disposal; and the Nevada Test Site, which contains a number of underground nuclear-testing locations. This application of the guidelines demonstrates how they may be used for model calibration and evaluation, and also to direct further model development and data collection.
An approach to identify time consistent model parameters: sub-period calibration
NASA Astrophysics Data System (ADS)
Gharari, S.; Hrachowitz, M.; Fenicia, F.; Savenije, H. H. G.
2013-01-01
Conceptual hydrological models 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 testing 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 applied to a case study in Luxembourg using the HyMod hydrological model as an example.
Sun, Kaiyu; Yan, Da; Hong, Tianzhen; Guo, Siyue
2014-02-28
Overtime is a common phenomenon around the world. Overtime drives both internal heat gains from occupants, lighting and plug-loads, and HVAC operation during overtime periods. Overtime leads to longer occupancy hours and extended operation of building services systems beyond normal working hours, thus overtime impacts total building energy use. Current literature lacks methods to model overtime occupancy because overtime is stochastic in nature and varies by individual occupants and by time. To address this gap in the literature, this study aims to develop a new stochastic model based on the statistical analysis of measured overtime occupancy data from an office building. A binomial distribution is used to represent the total number of occupants working overtime, while an exponential distribution is used to represent the duration of overtime periods. The overtime model is used to generate overtime occupancy schedules as an input to the energy model of a second office building. The measured and simulated cooling energy use during the overtime period is compared in order to validate the overtime model. A hybrid approach to energy model calibration is proposed and tested, which combines ASHRAE Guideline 14 for the calibration of the energy model during normal working hours, and a proposed KS test for the calibration of the energy model during overtime. The developed stochastic overtime model and the hybrid calibration approach can be used in building energy simulations to improve the accuracy of results, and better understand the characteristics of overtime in office buildings.
2014-01-01
Background Traditionally, phase I oncology trials are designed to determine the maximum tolerated dose (MTD), defined as the highest dose with an acceptable probability of dose limiting toxicities(DLT), of a new treatment via a dose escalation study. An alternate approach is to jointly model toxicity and efficacy and allow dose escalation to depend on a pre-specified efficacy/toxicity tradeoff in a phase I-II design. Several phase I-II trial designs have been discussed in the literature; while these model-based designs are attractive in their performance, they are potentially vulnerable to model misspecification. Methods Phase I-II designs often rely on copula models to specify the joint distribution of toxicity and efficacy, which include an additional correlation parameter that can be difficult to estimate. We compare and contrast three models for the joint probability of toxicity and efficacy, including two copula models that have been proposed for use in phase I-II clinical trials and a simple model that assumes the two outcomes are independent. We evaluate the performance of the various models through simulation both when the models are correct and under model misspecification. Results Both models exhibited similar performance, as measured by the probability of correctly identifying the optimal dose and the number of subjects treated at the optimal dose, regardless of whether the data were generated from the correct or incorrect copula, even when there is substantial correlation between the two outcomes. Similar results were observed for a simple model that assumes independence, even in the presence of strong correlation. Further simulation results indicate that estimating the correlation parameter in copula models is difficult with the sample sizes used in Phase I-II clinical trials. Conclusions Our simulation results indicate that the operating characteristics of phase I-II clinical trials are robust to misspecification of the copula model but that a simple
Bayesian calibration of the Unified budburst model in six temperate tree species
NASA Astrophysics Data System (ADS)
Fu, Yongshuo H.; Campioli, Matteo; Demarée, Gaston; Deckmyn, Alex; Hamdi, Rafiq; Janssens, Ivan A.; Deckmyn, Gaby
2012-01-01
Numerous phenology models developed to predict the budburst date of trees have been merged into one Unified model (Chuine, 2000, J. Theor. Biol. 207, 337-347). In this study, we tested a simplified version of the Unified model (Unichill model) on six woody species. Budburst and temperature data were available for five sites across Belgium from 1957 to 1995. We calibrated the Unichill model using a Bayesian calibration procedure, which reduced the uncertainty of the parameter coefficients and quantified the prediction uncertainty. The model performance differed among species. For two species (chestnut and black locust), the model showed good performance when tested against independent data not used for calibration. For the four other species (beech, oak, birch, ash), the model performed poorly. Model performance improved substantially for most species when using site-specific parameter coefficients instead of across-site parameter coefficients. This suggested that budburst is influenced by local environment and/or genetic differences among populations. Chestnut, black locust and birch were found to be temperature-driven species, and we therefore analyzed the sensitivity of budburst date to forcing temperature in those three species. Model results showed that budburst advanced with increasing temperature for 1-3 days °C-1, which agreed with the observed trends. In synthesis, our results suggest that the Unichill model can be successfully applied to chestnut and black locust (with both across-site and site-specific calibration) and to birch (with site-specific calibration). For other species, temperature is not the only determinant of budburst and additional influencing factors will need to be included in the model.
Hydrological processes and model representation: Impact of soft data on calibration
Technology Transfer Automated Retrieval System (TEKTRAN)
Hydrologic and water quality models are increasingly used to determine the environmental impacts of climate variability and land management. Due to differing model objectives and differences in monitored data, there are currently no universally accepted procedures for calibration and validation in ...
Model Calibration Efforts for the International Space Station's Solar Array Mast
NASA Technical Reports Server (NTRS)
Elliott, Kenny B.; Horta, Lucas G.; Templeton, Justin D.; Knight, Norman F., Jr.
2012-01-01
The International Space Station (ISS) relies on sixteen solar-voltaic blankets to provide electrical power to the station. Each pair of blankets is supported by a deployable boom called the Folding Articulated Square Truss Mast (FAST Mast). At certain ISS attitudes, the solar arrays can be positioned in such a way that shadowing of either one or three longerons causes an unexpected asymmetric thermal loading that if unchecked can exceed the operational stability limits of the mast. Work in this paper documents part of an independent NASA Engineering and Safety Center effort to assess the existing operational limits. Because of the complexity of the system, the problem is being worked using a building-block progression from components (longerons), to units (single or multiple bays), to assembly (full mast). The paper presents results from efforts to calibrate the longeron components. The work includes experimental testing of two types of longerons (straight and tapered), development of Finite Element (FE) models, development of parameter uncertainty models, and the establishment of a calibration and validation process to demonstrate adequacy of the models. Models in the context of this paper refer to both FE model and probabilistic parameter models. Results from model calibration of the straight longerons show that the model is capable of predicting the mean load, axial strain, and bending strain. For validation, parameter values obtained from calibration of straight longerons are used to validate experimental results for the tapered longerons.
Examining the Invariance of Rater and Project Calibrations Using a Multi-facet Rasch Model.
ERIC Educational Resources Information Center
O'Neill, Thomas R.; Lunz, Mary E.
To generalize test results beyond the particular test administration, an examinee's ability estimate must be independent of the particular items attempted, and the item difficulty calibrations must be independent of the particular sample of people attempting the items. This stability is a key concept of the Rasch model, a latent trait model of…
NASA Astrophysics Data System (ADS)
Wang, Ling; van Meerveld, Ilja; Seibert, Jan
2016-04-01
Streamflow isotope samples taken during rainfall-runoff events are very useful for multi-criteria model calibration because they can help decrease parameter uncertainty and improve internal model consistency. However, the number of samples that can be collected and analysed is often restricted by practical and financial constraints. It is, therefore, important to choose an appropriate sampling strategy and to obtain samples that have the highest information content for model calibration. We used the Birkenes hydrochemical model and synthetic rainfall, streamflow and isotope data to explore which samples are most informative for model calibration. Starting with error-free observations, we investigated how many samples are needed to obtain a certain model fit. Based on different parameter sets, representing different catchments, and different rainfall events, we also determined which sampling times provide the most informative data for model calibration. Our results show that simulation performance for models calibrated with the isotopic data from two intelligently selected samples was comparable to simulations based on isotopic data for all 100 time steps. The models calibrated with the intelligently selected samples also performed better than the model calibrations with two benchmark sampling strategies (random selection and selection based on hydrologic information). Surprisingly, samples on the rising limb and at the peak were less informative than expected and, generally, samples taken at the end of the event were most informative. The timing of the most informative samples depends on the proportion of different flow components (baseflow, slow response flow, fast response flow and overflow). For events dominated by baseflow and slow response flow, samples taken at the end of the event after the fast response flow has ended were most informative; when the fast response flow was dominant, samples taken near the peak were most informative. However when overflow
NASA Technical Reports Server (NTRS)
Jung, Hahn Chul; Jasinski, Michael; Kim, Jin-Woo; Shum, C. K.; Bates, Paul; Lee, Hgongki; Neal, Jeffrey; Alsdorf, Doug
2012-01-01
Two-dimensional (2D) satellite imagery has been increasingly employed to improve prediction of floodplain inundation models. However, most focus has been on validation of inundation extent, with little attention on the 2D spatial variations of water elevation and slope. The availability of high resolution Interferometric Synthetic Aperture Radar (InSAR) imagery offers unprecedented opportunity for quantitative validation of surface water heights and slopes derived from 2D hydrodynamic models. In this study, the LISFLOOD-ACC hydrodynamic model is applied to the central Atchafalaya River Basin, Louisiana, during high flows typical of spring floods in the Mississippi Delta region, for the purpose of demonstrating the utility of InSAR in coupled 1D/2D model calibration. Two calibration schemes focusing on Manning s roughness are compared. First, the model is calibrated in terms of water elevations at a single in situ gage during a 62 day simulation period from 1 April 2008 to 1 June 2008. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. The best-fit models show that the mean absolute errors are 3.8 cm for a single in situ gage calibration and 5.7 cm/46 days for InSAR water level calibration. The optimum values of Manning's roughness coefficients are 0.024/0.10 for the channel/floodplain, respectively, using a single in situ gage, and 0.028/0.10 for channel/floodplain the using SAR. Based on the calibrated water elevation changes, daily storage changes within the size of approx 230 sq km of the model area are also calculated to be of the order of 107 cubic m/day during high water of the modeled period. This study demonstrates the feasibility of SAR interferometry to support 2D hydrodynamic model calibration and as a tool for improved understanding of complex floodplain hydrodynamics
NASA Astrophysics Data System (ADS)
Camici, Stefania; Tito Aronica, Giuseppe; Tarpanelli, Angelica; Moramarco, Tommaso
2013-04-01
Hydraulic models 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 necessary for the model calibration. Indeed, flood events are very rarely monitored due to the disturbances inflicted by them and the lack of appropriate measuring equipment. The second reason is related to the choice of a suitable performance measures for calibrating and to evaluate model predictions in a credible and consistent way (and to reduce the uncertainty). This study takes a well documented flood event in November 2012 in Paglia river basin (Central Italy). For this area a detailed description of the main channel morphology, obtained from an accurate topographical surveys and by a DEM with spatial resolution of 2 m, and several points within the floodplain areas, in which the maximum water level has been measured, were available for the post-event analysis. On basis of these information two-dimensional inertial finite element hydraulic model was set up and calibrated using different performance measures. Manning roughness coefficients obtained from the different calibrations were then used for the delineation of inundation maps including also uncertainty. The water levels of three hydrometric stations and flooded area extensions, derived by video recording the day after the flood event, have been used for the validation of the model.
NASA Astrophysics Data System (ADS)
WöHling, Thomas; Vrugt, Jasper A.
2008-12-01
Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multiobjective optimization and Bayesian model averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multiobjective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM and used to generate four different model ensembles. These ensembles are postprocessed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multiobjective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.
NASA Technical Reports Server (NTRS)
Jung, Hahn Chul; Jasinski, Michael; Kim, Jin-Woo; Shum, C. K.; Bates, Paul; Neal, Jeffrey; Lee, Hyongki; Alsdorf, Doug
2011-01-01
This study focuses on the feasibility of using SAR interferometry to support 2D hydrodynamic model calibration and provide water storage change in the floodplain. Two-dimensional (2D) flood inundation modeling has been widely studied using storage cell approaches with the availability of high resolution, remotely sensed floodplain topography. The development of coupled 1D/2D flood modeling has shown improved calculation of 2D floodplain inundation as well as channel water elevation. Most floodplain model results have been validated using remote sensing methods for inundation extent. However, few studies show the quantitative validation of spatial variations in floodplain water elevations in the 2D modeling since most of the gauges are located along main river channels and traditional single track satellite altimetry over the floodplain are limited. Synthetic Aperture Radar (SAR) interferometry recently has been proven to be useful for measuring centimeter-scale water elevation changes over the floodplain. In the current study, we apply the LISFLOOD hydrodynamic model to the central Atchafalaya River Basin, Louisiana, during a 62 day period from 1 April to 1 June 2008 using two different calibration schemes for Manning's n. First, the model is calibrated in terms of water elevations from a single in situ gauge that represents a more traditional approach. Due to the gauge location in the channel, the calibration shows more sensitivity to channel roughness relative to floodplain roughness. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. Since SAR interferometry receives strongly scatters in floodplain due to double bounce effect as compared to specular scattering of open water, the calibration shows more dependency to floodplain roughness. An iterative approach is used to determine the best-fit Manning's n for the two
Multispectral scanner flight model (F-1) radiometric calibration and alignment handbook
NASA Technical Reports Server (NTRS)
1981-01-01
This handbook on the calibration of the MSS-D flight model (F-1) provides both the relevant data and a summary description of how the data were obtained for the system radiometric calibration, system relative spectral response, and the filter response characteristics for all 24 channels of the four band MSS-D F-1 scanner. The calibration test procedure and resulting test data required to establish the reference light levels of the MSS-D internal calibration system are discussed. The final set of data ("nominal" calibration wedges for all 24 channels) for the internal calibration system is given. The system relative spectral response measurements for all 24 channels of MSS-D F-1 are included. These data are the spectral response of the complete scanner, which are the composite of the spectral responses of the scan mirror primary and secondary telescope mirrors, fiber optics, optical filters, and detectors. Unit level test data on the measurements of the individual channel optical transmission filters are provided. Measured performance is compared to specification values.
Study of the performance of stereoscopic panomorph systems calibrated with traditional pinhole model
NASA Astrophysics Data System (ADS)
Poulin-Girard, Anne-Sophie; Thibault, Simon; Laurendeau, Denis
2016-06-01
With their large field of view, anamorphosis, and areas of enhanced magnification, panomorph lenses are an interesting choice for navigation systems for mobile robotics in which knowledge of the surroundings is mandatory. However, panomorph lenses special characteristics can be challenging during the calibration process. This study focuses on the calibration of two panomorph stereoscopic systems with a model and technique developed for narrow-angle lenses, the "Camera Calibration Toolbox for MATLAB." In order to assess the performance of the systems, the mean reprojection error (MRE) related to the calibration and the reconstruction error of control points of an object of interest at various locations in the field of view are used. The calibrations were successful and exhibit MREs of less than one pixel in all cases. However, some poorly reconstructed control points illustrate that an acceptable MRE guarantees neither the quality of 3-D reconstruction nor its uniformity in the field of view. In addition, the nonuniformity in the 3-D reconstruction quality indicates that panomorph lenses require a more accurate estimation of the principal point (center of distortion) coordinates to improve the calibration and therefore the 3-D reconstruction.
Calibration of a groundwater model using pattern information from remote sensing data
NASA Astrophysics Data System (ADS)
Li, H. T.; Brunner, P.; Kinzelbach, W.; Li, W. P.; Dong, X. G.
2009-10-01
SummaryDue to the chronic lack of verification data, hydrologic models are notoriously over-parameterized. If a large number of parameters are estimated, while few verification data are available, the calibrated model may have little predictive value. However, recent development in remote sensing (RS) techniques allows generation of spatially distributed data that can be used to construct and verify hydrological models. These additional data reduce the ambiguity of the calibration process and thus increase the predictive value of the model. An example for such remotely sensed data is the spatial distribution of phreatic evaporation. In this modeling approach, we use the spatial distribution of phreatic evaporation obtained by remote sensing images as verification data. Compared to the usual limited amount of head data, the spatial distribution of evaporation data provides a complete areal coverage. However, the absolute values of the evaporation data are uncertain and therefore three ways of using the spatial distribution pattern of evaporation were tested and compared. The first way is to directly use the evaporation pattern defined in a relative manner by dividing the evaporation rate in a pixel by the total evaporation of a selected rectangular area of interest. Alternatively, the discrete fourier transform (DFT) or the discrete wavelet transform (DWT) are applied to the relative evaporation pattern in the space domain defined before. Seven different combinations of using hydraulic head data and/or evaporation pattern data as conditioning information have been tested. The code PEST, based on the least-squares method, was used as an automatic calibration tool. From the calibration results, we can conclude that the evaporation pattern can replace the head data in the model calibration process, independently of the way the evaporation pattern is introduced into the calibration procedure.
Multi-metric calibration of hydrological model to capture overall flow regimes
NASA Astrophysics Data System (ADS)
Zhang, Yongyong; Shao, Quanxi; Zhang, Shifeng; Zhai, Xiaoyan; She, Dunxian
2016-08-01
Flow regimes (e.g., magnitude, frequency, variation, duration, timing and rating of change) play a critical role in water supply and flood control, environmental processes, as well as biodiversity and life history patterns in the aquatic ecosystem. The traditional flow magnitude-oriented calibration of hydrological model was usually inadequate to well capture all the characteristics of observed flow regimes. In this study, we simulated multiple flow regime metrics simultaneously by coupling a distributed hydrological model with an equally weighted multi-objective optimization algorithm. Two headwater watersheds in the arid Hexi Corridor were selected for the case study. Sixteen metrics were selected as optimization objectives, which could represent the major characteristics of flow regimes. Model performance was compared with that of the single objective calibration. Results showed that most metrics were better simulated by the multi-objective approach than those of the single objective calibration, especially the low and high flow magnitudes, frequency and variation, duration, maximum flow timing and rating. However, the model performance of middle flow magnitude was not significantly improved because this metric was usually well captured by single objective calibration. The timing of minimum flow was poorly predicted by both the multi-metric and single calibrations due to the uncertainties in model structure and input data. The sensitive parameter values of the hydrological model changed remarkably and the simulated hydrological processes by the multi-metric calibration became more reliable, because more flow characteristics were considered. The study is expected to provide more detailed flow information by hydrological simulation for the integrated water resources management, and to improve the simulation performances of overall flow regimes.
MCMC-Bayesian Calibration of the Community Land Model for the US-ARM site
NASA Astrophysics Data System (ADS)
Hou, Z.; Ray, J.; Huang, M.
2013-12-01
We present results from the Bayesian calibration of the Community Land Model (CLM) for the US-ARM site. After parameter screening, three most identifiable parameters governing subsurface runoff and groundwater dynamics were chosen for calibration using observations from 1996-2004. The parameters were estimated as probability density functions, which can quantify the uncertainty in the parameter estimates due to limited observations, non-unique relationships between unknown parameters and observable variables, and short-comings of CLM itself. The probability density function for the three parameters was developed using a Markov chain Monte Carlo (MCMC) method, driving surrogates of the CLM. The three-dimensional parameter space was sampled and CLM numerical simulator was used to simulate runoff and latent/sensible heat fluxes for each of the parameter combinations. Surrogate models were then constructed for each month by fitting polynomial trend models to the CLM simulations as a function of the three parameters. The polynomial trend is not sufficiently accurate and the discrepancy between the trend and CLM predictions was spanned by a multivariate Gaussian field. Thus the surrogates are regression-kriged models with a polynomial trend. The surrogates are then used as forward models and integrated with an adaptive MCMC-Bayesian inversion method to estimate the parameters. The monthly errors (combination of measurement and CLM's structural errors) were modeled as independent and identically distributed (i.i.d.) Gaussians with an unknown variance, which was also estimated in the calibration process. Calibrations are done at the US-ARM site, and compared to results at another flux tower site, US-MOz. This also demonstrates the applicability of the calibration approach for different field conditions. The calibrated parameters can significantly improve the CLM predictions during the testing periods. Reduced parameter dimensionality and use of surrogates help make the
EPIC and APEX: Model use, calibration, and validation
Technology Transfer Automated Retrieval System (TEKTRAN)
The Environmental Policy Integrated Climate (EPIC) and Agricultural Policy/Environmental eXtender (APEX) models have been developed to assess a wide variety of agricultural water resource, water quality, and other environmental problems. The EPIC model is designed to be applied at a field-scale leve...
AUTOMATIC CALIBRATION OF A STOCHASTIC-LAGRANGIAN TRANSPORT MODEL (SLAM)
Numerical models are a useful tool in evaluating and designing NAPL remediation systems. Traditional constitutive finite difference and finite element models are complex and expensive to apply. For this reason, this paper presents the application of a simplified stochastic-Lagran...
Self-calibrating models for dynamic monitoring and diagnosis
NASA Technical Reports Server (NTRS)
Kuipers, Benjamin
1994-01-01
The present goal in qualitative reasoning is to develop methods for automatically building qualitative and semiquantitative models of dynamic systems and to use them for monitoring and fault diagnosis. The qualitative approach to modeling provides a guarantee of coverage while our semiquantitative methods support convergence toward a numerical model as observations are accumulated. We have developed and applied methods for automatic creation of qualitative models, developed two methods for obtaining tractable results on problems that were previously intractable for qualitative simulation, and developed more powerful methods for learning semiquantitative models from observations and deriving semiquantitative predictions from them. With these advances, qualitative reasoning comes significantly closer to realizing its aims as a practical engineering method.
Estimating the Health Impact of Climate Change with Calibrated Climate Model Output
Zhou, Jingwen; Chang, Howard H.; Fuentes, Montserrat
2013-01-01
Studies on the health impacts of climate change routinely use climate model output as future exposure projection. Uncertainty quantification, usually in the form of sensitivity analysis, has focused predominantly on the variability arise from different emission scenarios or multi-model ensembles. This paper describes a Bayesian spatial quantile regression approach to calibrate climate model output for examining to the risks of future temperature on adverse health outcomes. Specifically, we first estimate the spatial quantile process for climate model output using nonlinear monotonic regression during a historical period. The quantile process is then calibrated using the quantile functions estimated from the observed monitoring data. Our model also down-scales the gridded climate model output to the point-level for projecting future exposure over a specific geographical region. The quantile regression approach is motivated by the need to better characterize the tails of future temperature distribution where the greatest health impacts are likely to occur. We applied the methodology to calibrate temperature projections from a regional climate model for the period 2041 to 2050. Accounting for calibration uncertainty, we calculated the number of of excess deaths attributed to future temperature for three cities in the US state of Alabama. PMID:24039385
THE EFFECT OF METALLICITY-DEPENDENT T-τ RELATIONS ON CALIBRATED STELLAR MODELS
Tanner, Joel D.; Basu, Sarbani; Demarque, Pierre
2014-04-10
Mixing length theory is the predominant treatment of convection in stellar models today. Usually described by a single free parameter, α, the common practice is to calibrate it using the properties of the Sun, and apply it to all other stellar models as well. Asteroseismic data from Kepler and CoRoT provide precise properties of other stars which can be used to determine α as well, and a recent study of stars in the Kepler field of view found α to vary with metallicity. Interpreting α obtained from calibrated stellar models, however, is complicated by the fact that the value for α depends on the surface boundary condition of the stellar model, or T-τ relation. Calibrated models that use typical T-τ relations, which are static and insensitive to chemical composition, do not include the complete effect of metallicity on α. We use three-dimensional radiation-hydrodynamic simulations to extract metallicity-dependent T-τ relations and use them in calibrated stellar models. We find the previously reported α-metallicity trend to be robust, and not significantly affected by the surface boundary condition of the stellar models.
Comparison of a priori calibration models for respiratory inductance plethysmography during running.
Leutheuser, Heike; Heyde, Christian; Gollhofer, Albert; Eskofier, Bjoern M
2014-01-01
Respiratory inductive plethysmography (RIP) has been introduced as an alternative for measuring ventilation by means of body surface displacement (diameter changes in rib cage and abdomen). Using a posteriori calibration, it has been shown that RIP may provide accurate measurements for ventilatory tidal volume under exercise conditions. Methods for a priori calibration would facilitate the application of RIP. Currently, to the best knowledge of the authors, none of the existing ambulant procedures for RIP calibration can be used a priori for valid subsequent measurements of ventilatory volume under exercise conditions. The purpose of this study is to develop and validate a priori calibration algorithms for ambulant application of RIP data recorded in running exercise. We calculated Volume Motion Coefficients (VMCs) using seven different models on resting data and compared the root mean squared error (RMSE) of each model applied on running data. Least squares approximation (LSQ) without offset of a two-degree-of-freedom model achieved the lowest RMSE value. In this work, we showed that a priori calibration of RIP exercise data is possible using VMCs calculated from 5 min resting phase where RIP and flowmeter measurements were performed simultaneously. The results demonstrate that RIP has the potential for usage in ambulant applications. PMID:25571459
Toward diagnostic model calibration and evaluation: Approximate Bayesian computation
NASA Astrophysics Data System (ADS)
Vrugt, Jasper A.; Sadegh, Mojtaba
2013-07-01
The ever increasing pace of computational power, along with continued advances in measurement technologies and improvements in process understanding has stimulated the development of increasingly complex hydrologic models that simulate soil moisture flow, groundwater recharge, surface runoff, root water uptake, and river discharge at different spatial and temporal scales. Reconciling these high-order system models with perpetually larger volumes of field data is becoming more and more difficult, particularly because classical likelihood-based fitting methods lack the power to detect and pinpoint deficiencies in the model structure. Gupta et al. (2008) has recently proposed steps (amongst others) toward the development of a more robust and powerful method of model evaluation. Their diagnostic approach uses signature behaviors and patterns observed in the input-output data to illuminate to what degree a representation of the real world has been adequately achieved and how the model should be improved for the purpose of learning and scientific discovery. In this paper, we introduce approximate Bayesian computation (ABC) as a vehicle for diagnostic model evaluation. This statistical methodology relaxes the need for an explicit likelihood function in favor of one or multiple different summary statistics rooted in hydrologic theory that together have a clearer and more compelling diagnostic power than some average measure of the size of the error residuals. Two illustrative case studies are used to demonstrate that ABC is relatively easy to implement, and readily employs signature based indices to analyze and pinpoint which part of the model is malfunctioning and in need of further improvement.
Chijimatsu, M.; Borgesson, L.; Fujita, T.; Jussila, P.; Nguyen, S.; Rutqvist, J.; Jing, L.; Hernelind, J.
2009-02-01
In Task A of the international DECOVALEX-THMC project, five research teams study the influence of thermal-hydro-mechanical (THM) coupling on the safety of a hypothetical geological repository for spent fuel. In order to improve the analyses, the teams calibrated their bentonite models with results from laboratory experiments, including swelling pressure tests, water uptake tests, thermally gradient tests, and the CEA mock-up THM experiment. This paper describes the mathematical models used by the teams, and compares the results of their calibrations with the experimental data.
A computer program for calculating relative-transmissivity input arrays to aid model calibration
Weiss, Emanuel
1982-01-01
A program is documented that calculates a transmissivity distribution for input to a digital ground-water flow model. Factors that are taken into account in the calculation are: aquifer thickness, ground-water viscosity and its dependence on temperature and dissolved solids, and permeability and its dependence on overburden pressure. Other factors affecting ground-water flow are indicated. With small changes in the program code, leakance also could be calculated. The purpose of these calculations is to provide a physical basis for efficient calibration, and to extend rational transmissivity trends into areas where model calibration is insensitive to transmissivity values.
Dorado, Antonio David; Gamisans, Xavier; Valderrama, Cesar; Solé, Montse; Lao, Conxita
2014-01-01
Prediction of breakthrough curves for continuous sorption characterization is generally performed by means of simple and simplified equations. These expressions hardly have any physical meaning and, also do not allow extrapolation. A novel and simple approach, based on unsteady state mass balances, is presented herein for the simulation of the adsorption of Cr(III) ions from aqueous onto a low-cost adsorbent (leonardite). The proposed model overcomes the limitations of the commonly used analytical solution-based models without the need for complex mathematical methods. A set of experimental breakthrough curves obtained from lab-scale, fixed-bed columns was used to calibrate and validate the proposed model with a minimum number of parameters to be adjusted. PMID:24171417
NASA Astrophysics Data System (ADS)
de Vos, N. J.; Rientjes, T. H.; Gupta, H. V.
2006-12-01
The forecasting of river discharges and water levels requires models that simulate the transformation of rainfall on a watershed into the runoff. The most popular approach to this complex modeling issue is to use conceptual hydrological models. In recent years, however, data-driven model alternatives have gained significant attention. Such models extract and re-use information that is implicit in hydrological data and do not directly take into account the physical laws that underlie rainfall-runoff processes. In this study, we have made a comparison between a conceptual hydrological model and the popular data-driven approach of Artificial Neural Network (ANN) modeling. ANNs use flexible model structures that simulate rainfall-runoff processes by mapping the transformation from system input and/or system states (e.g., rainfall, evaporation, soil moisture content) to system output (e.g. river discharge). Special attention was paid to the procedure of calibration of both approaches. Singular objective functions based on squared-error-based performance measures, such as the Mean Squared Error (MSE) are commonly used in rainfall-runoff modeling. However, not all differences between modeled and observed hydrograph characteristics can be adequately expressed by a single performance measure. Nowadays it is acknowledged that the calibration of rainfall-runoff models is inherently multi-objective. Therefore, Multi-Objective Evolutionary Algorithms (MOEAs) were tested as alternatives to traditional single-objective algorithms for calibration of both a conceptual and an ANN model for forecasting runoff. The MOEAs compare favorably to traditional single-objective methods in terms of performance, and they shed more light on the trade-offs between various objective functions. Additionally, the distribution of model parameter values gives insights into model parameter uncertainty and model structural deficiencies. Summarizing, the current study presents interesting and promising
Kinetic modeling of antimony(III) oxidation and sorption in soils.
Cai, Yongbing; Mi, Yuting; Zhang, Hua
2016-10-01
Kinetic batch and saturated column experiments were performed to study the oxidation, adsorption and transport of Sb(III) in two soils with contrasting properties. Kinetic and column experiment results clearly demonstrated the extensive oxidation of Sb(III) in soils, and this can in return influence the adsorption and transport of Sb. Both sorption capacity and kinetic oxidation rate were much higher in calcareous Huanjiang soil than in acid red Yingtan soil. The results indicate that soil serve as a catalyst in promoting oxidation of Sb(III) even under anaerobic conditions. A PHREEQC model with kinetic formulations was developed to simulate the oxidation, sorption and transport of Sb(III) in soils. The model successfully described Sb(III) oxidation and sorption data in kinetic batch experiment. It was less successful in simulating the reactive transport of Sb(III) in soil columns. Additional processes such as colloid facilitated transport need to be quantified and considered in the model. PMID:27214003
Value of using remotely sensed evapotranspiration for SWAT model calibration
Technology Transfer Automated Retrieval System (TEKTRAN)
Hydrologic models are useful management tools for assessing water resources solutions and estimating the potential impact of climate variation scenarios. A comprehensive understanding of the water budget components and especially the evapotranspiration (ET) is critical and often overlooked for adeq...
Essa, Mohamed; Sayed, Tarek
2015-11-01
Several studies have investigated the relationship between field-measured conflicts and the conflicts obtained from micro-simulation models using the Surrogate Safety Assessment Model (SSAM). Results from recent studies have shown that while reasonable correlation between simulated and real traffic conflicts can be obtained especially after proper calibration, more work is still needed to confirm that simulated conflicts provide safety measures beyond what can be expected from exposure. As well, the results have emphasized that using micro-simulation model to evaluate safety without proper model calibration should be avoided. The calibration process adjusts relevant simulation parameters to maximize the correlation between field-measured and simulated conflicts. The main objective of this study is to investigate the transferability of calibrated parameters of the traffic simulation model (VISSIM) for safety analysis between different sites. The main purpose is to examine whether the calibrated parameters, when applied to other sites, give reasonable results in terms of the correlation between the field-measured and the simulated conflicts. Eighty-three hours of video data from two signalized intersections in Surrey, BC were used in this study. Automated video-based computer vision techniques were used to extract vehicle trajectories and identify field-measured rear-end conflicts. Calibrated VISSIM parameters obtained from the first intersection which maximized the correlation between simulated and field-observed conflicts were used to estimate traffic conflicts at the second intersection and to compare the results to parameters optimized specifically for the second intersection. The results show that the VISSIM parameters are generally transferable between the two locations as the transferred parameters provided better correlation between simulated and field-measured conflicts than using the default VISSIM parameters. Of the six VISSIM parameters identified as
Calibration of a flood inundation model using a SAR image: influence of acquisition time
NASA Astrophysics Data System (ADS)
Van Wesemael, Alexandra; Gobeyn, Sacha; Neal, Jeffrey; Lievens, Hans; Van Eerdenbrugh, Katrien; De Vleeschouwer, Niels; Schumann, Guy; Vernieuwe, Hilde; Di Baldassarre, Giuliano; De Baets, Bernard; Bates, Paul; Verhoest, Niko
2016-04-01
Flood risk management has always been in a search for effective prediction approaches. As such, the calibration of flood inundation models is continuously improved. In practice, this calibration process consists of finding the optimal roughness parameters, both channel and floodplain Manning coefficients, since these values considerably influence the flood extent in a catchment. In addition, Synthetic Aperture Radar (SAR) images have been proven to be a very useful tool in calibrating the flood extent. These images can distinguish between wet (flooded) and dry (non-flooded) pixels through the intensity of backscattered radio waves. To this date, however, satellite overpass often occurs only once during a flood event. Therefore, this study is specifically concerned with the effect of the timing of the SAR data acquisition on calibration results. In order to model the flood extent, the raster-based inundation model, LISFLOOD-FP, is used together with a high resolution synthetic aperture radar image (ERS-2 SAR) of a flood event of the river Dee, Wales, in December 2006. As only one satellite image of the considered case study is available, a synthetic framework is implemented in order to generate a time series of SAR observations. These synthetic observations are then used to calibrate the model at different time instants. In doing so, the sensitivity of the model output to the channel and floodplain Manning coefficients is studied through time. As results are examined, these suggest that there is a clear difference in the spatial variability to which water is held within the floodplain. Furthermore, these differences seem to be variable through time. Calibration by means of satellite flood observations obtained from the rising or receding limb, would generally lead to more reliable results rather than near peak flow observations.
NASA Astrophysics Data System (ADS)
Khaninezhad, M. R. M.; Jafarpour, B.
2014-12-01
Inference of spatially distributed reservoir and aquifer properties from scattered and spatially limited data poses a poorly constrained nonlinear inverse problem that can have many solutions. In particular, the uncertainty in the geologic continuity model can remarkably degrade the quality of fluid displacement predictions, hence, the efficiency of resource development plans. For model calibration, instead of estimating aquifer properties for each grid cell in the model, the sparse representation of the aquifer properties is estimated from nonlinear production data. The resulting calibration problem can be solved using recent developments in sparse signal processing, widely known as compressed sensing. This novel formulation leads to a sparse data inversion technique that effectively searches for relevant geologic patterns that can explain the available spatiotemporal data. We recently introduced a new model calibration framework by using sparse geologic dictionaries that are constructed from uncertain prior geologic models. Here, we first demonstrate the effectiveness of the proposed sparse geologic dictionaries for flexible and robust model calibration under prior geologic uncertainty. We illustrate the effectiveness of the proposed approach in using limited nonlinear production data to identify a consistent geologic scenario from a number of candidate scenarios, which is usually a challenging problem in geostatistical reservoir characterization. We then evaluate the feasibility of adopting this framework for field application. In particular, we present subsurface field model calibration applications in which sparse geologic dictionaries are learned from uncertain prior information on large-scale reservoir property descriptions. We consider two large-scale field case studies, the Brugges and the Norne field examples. We discuss the construction of geologic dictionaries for large-scale problems and present reduced-order methods to speed up the computational
Calibration of SWAT model for woody plant encroachment using paired experimental watershed data
NASA Astrophysics Data System (ADS)
Qiao, Lei; Zou, Chris B.; Will, Rodney E.; Stebler, Elaine
2015-04-01
Globally, rangeland has been undergoing a transition from herbaceous dominated grasslands into tree or shrub dominated woodlands with great uncertainty of associated changes in water budget. Previous modeling studies simulated the impact of woody plant encroachment on hydrological processes using models calibrated and constrained primarily by historic streamflow from intermediate sized watersheds. In this study, we calibrated the Soil and Water Assessment Tool (SWAT model), a widely used model for cropping and grazing systems, for a prolifically encroaching juniper species, eastern redcedar (Juniperus virginiana), in the south-central Great Plains using species-specific biophysical and hydrological parameters and in situ meteorological forcing from three pairs of experimental watersheds (grassland versus eastern redcedar woodland) for a period of 3-years covering a dry-to-wet cycle. The multiple paired watersheds eliminated the potentially confounding edaphic and topographic influences from changes in hydrological processes related to woody encroachment. The SWAT model was optimized with the Shuffled complexes with Principal component analysis (SP-UCI) algorithm developed from the Shuffled Complexes Evolution (SCE_UA). The mean Nash-Sutcliff coefficient (NSCE) values of the calibrated model for daily and monthly runoff from experimental watersheds reached 0.96 and 0.97 for grassland, respectively, and 0.90 and 0.84 for eastern redcedar woodland, respectively. We then validated the calibrated model with a nearby, larger watershed undergoing rapid eastern redcedar encroachment. The NSCE value for monthly streamflow over a period of 22 years was 0.79. We provide detailed biophysical and hydrological parameters for tallgrass prairie under moderate grazing and eastern redcedar, which can be used to calibrate any model for further validation and application by the hydrologic modeling community.
Liu, Jianchun; Sonnenthal, Eric L; Bodvarsson, Gudmundur S
2003-01-01
In this study, porewater chloride data from Yucca Mountain, NV are analyzed and modeled by three-dimensional chemical transport simulation and analytical methods. The simulation modeling approach is based on a continuum formulation of coupled multiphase fluid flow and tracer transport processes through fractured porous rock using a dual-continuum concept. Infiltration rate calibrations were performed using the porewater chloride data. Model results of chloride distributions were improved in matching the observed data with the calibrated infiltration rates. Statistical analyses of the frequency distribution for overall percolation fluxes and chloride concentration in the unsaturated zone system demonstrate that the use of the calibrated infiltration rates had an insignificant effect on the distribution of simulated percolation fluxes but significantly changed the predicted distribution of simulated chloride concentrations. An analytical method was also applied to model transient chloride transport. The method was verified by three-dimensional simulation results to be capable of capturing major chemical transient behavior and trends. Effects of lateral flow in the Paintbrush nonwelded unit on percolation fluxes and chloride distribution were studied by three-dimensional simulations with increased horizontal permeability. The combined results from these model calibrations furnish important information for the UZ model studies, contributing to performance assessment of the potential repository. PMID:12714292
Using Diverse Data Types to Calibrate a Watershed Model of the Trout Lake Basin, Northern Wisconsin
NASA Astrophysics Data System (ADS)
Hunt, R. J.; Feinstein, D. T.; Pint, C. D.; Anderson, M. P.
2004-12-01
As part of the USGS Water, Energy, and Biogeochemical Budgets project and NSF Long-Term Ecological Research work, a parameter estimation code was used to calibrate a deterministic groundwater flow model of the Trout Lake Basin in northern Wisconsin. Observations included traditional calibration targets (head, lake stage, and baseflow observations) as well as unconventional targets such as groundwater flows to and from lakes, depth of a lake plume, and time of travel. The unconventional data types were important for parameter estimation convergence and allowed the development of a more parameterized model. Independent estimates of groundwater inflow to lakes were most important for constraining lakebed leakance, and the depth of the lake plume was important for determining hydraulic conductivity and conceptual aquifer layering. The most important target, however, was a conventional regional baseflow target that was important for correctly distributing flow between sub-basins and the regional system. The use of parameter estimation: 1) facilitated the calibration process by providing a quantitative assessment of the model's ability to match disparate observed data types; and 2) provided a best fit for the particular model conceptualization. The model calibration required the use of a "universal" parameter estimation code in order to include all types of observations in the objective function. The methods described here help address issues of watershed complexity and non-uniqueness common to deterministic watershed models.
Liu, Jianchun; Sonnenthal, Eric L.; Bodvarsson, Gudmundur S.
2002-09-01
In this study, porewater chloride data from Yucca Mountain, Nevada, are analyzed and modeled by 3-D chemical transport simulations and analytical methods. The simulation modeling approach is based on a continuum formulation of coupled multiphase fluid flow and tracer transport processes through fractured porous rock, using a dual-continuum concept. Infiltration-rate calibrations were using the pore water chloride data. Model results of chloride distributions were improved in matching the observed data with the calibrated infiltration rates. Statistical analyses of the frequency distribution for overall percolation fluxes and chloride concentration in the unsaturated zone system demonstrate that the use of the calibrated infiltration rates had insignificant effect on the distribution of simulated percolation fluxes but significantly changed the predicated distribution of simulated chloride concentrations. An analytical method was also applied to model transient chloride transport. The method was verified by 3-D simulation results as able to capture major chemical transient behavior and trends. Effects of lateral flow in the Paintbrush nonwelded unit on percolation fluxes and chloride distribution were studied by 3-D simulations with increased horizontal permeability. The combined results from these model calibrations furnish important information for the UZ model studies, contributing to performance assessment of the potential repository.
NASA Astrophysics Data System (ADS)
Ye, Yan; Song, Xiaomeng; Zhang, Jianyun; Kong, Fanzhe; Ma, Guangwen
2014-06-01
Practical experience has demonstrated that single objective functions, no matter how carefully chosen, prove to be inadequate in providing proper measurements for all of the characteristics of the observed data. One strategy to circumvent this problem is to define multiple fitting criteria that measure different aspects of system behavior, and to use multi-criteria optimization to identify non-dominated optimal solutions. Unfortunately, these analyses require running original simulation models thousands of times. As such, they demand prohibitively large computational budgets. As a result, surrogate models have been used in combination with a variety of multi-objective optimization algorithms to approximate the true Pareto-front within limited evaluations for the original model. In this study, multi-objective optimization based on surrogate modeling (multivariate adaptive regression splines, MARS) for a conceptual rainfall-runoff model (Xin'anjiang model, XAJ) was proposed. Taking the Yanduhe basin of Three Gorges in the upper stream of the Yangtze River in China as a case study, three evaluation criteria were selected to quantify the goodness-of-fit of observations against calculated values from the simulation model. The three criteria chosen were the Nash-Sutcliffe efficiency coefficient, the relative error of peak flow, and runoff volume (REPF and RERV). The efficacy of this method is demonstrated on the calibration of the XAJ model. Compared to the single objective optimization results, it was indicated that the multi-objective optimization method can infer the most probable parameter set. The results also demonstrate that the use of surrogate-modeling enables optimization that is much more efficient; and the total computational cost is reduced by about 92.5%, compared to optimization without using surrogate modeling. The results obtained with the proposed method support the feasibility of applying parameter optimization to computationally intensive simulation
How Does Knowing Snowpack Distribution Help Model Calibration and Reservoir Management?
NASA Astrophysics Data System (ADS)
Graham, C. B.; Mazurkiewicz, A.; McGurk, B. J.; Painter, T. H.
2014-12-01
Well calibrated hydrologic models are a necessary tool for reservoir managers to meet increasingly complicated regulatory, environmental and consumptive demands on water supply systems. Achieving these objectives is difficult during periods of drought, such as seen in the Sierra Nevada in recent years. This emphasizes the importance of accurate watershed modeling and forecasting of runoff. While basin discharge has traditionally been the main criteria for model calibration, many studies have shown it to be a poor control on model calibration where correct understanding of the subbasin hydrologic processes are required. Additional data sources such as snowpack accumulation and melt are often required to create a reliable model calibration. When allocating resources for monitoring snowpack conditions, water system managers often must choose between monitoring point locations at high temporal resolution (i.e. real time weather and snow monitoring stations) and large spatial surveys (i.e. remote sensing). NASA's Airborne Snow Observatory (ASO) provides a unique opportunity to test the relative value of spatially dense, temporally sparse measurements vs. temporally dense, spatially sparse measurements for hydrologic model calibration. The ASO is a demonstration mission using coupled LiDAR and imaging spectrometer mounted to an aircraft flying at 6100 m to collect high spatial density measurements of snow water content and albedo over the 1189 km2 Tuolumne River Basin. Snow depth and albedo were collected weekly throughout the snowmelt runoff period at 5 m2 resolution during the 2013-2014 snowmelt. We developed an implementation of the USGS Precipitation Runoff Modeling System (PRMS) for the Tuolumne River above Hetch Hetchy Reservoir, the primary water source for San Francisco. The modeled snow accumulation and ablation was calibrated in 2 models using either 2 years of weekly measurements of distributed snow water equivalent from the ASO, or 2 years of 15 minute snow
Cosmological models and gamma-ray bursts calibrated by using Padé method
NASA Astrophysics Data System (ADS)
Liu, Jing; Wei, Hao
2015-11-01
Gamma-ray bursts (GRBs) are among the most powerful sources in the universe. In the recent years, GRBs have been proposed as a complementary probe to type Ia supernovae. However, as is well known, there is a circularity problem in the use of GRBs to study cosmology. In this work, based on the Padé approximant, we propose a new cosmology-independent method to calibrate GRBs. We consider a sample consisting of 138 long Swift GRBs and obtain 79 calibrated long GRBs at high-redshift z>1.4 (named Mayflower sample) which can be used to constrain cosmological models without the circularity problem. Then, we consider the constraints on several cosmological models with these 79 calibrated GRBs and other observational data. We show that GRBs are competent to be a complementary probe to the other well-established cosmological observations.
Calibration of the Sleuth Model Based on the Historic Growth of Houston
NASA Astrophysics Data System (ADS)
Hakan, O.; Klein, A. G.; Srinivasan, R.
The SLEUTH cellular automaton urban growth model was calibrated against historical growth in the Houston-Galveston-Brazoria Consolidated Metropolitan Statistical Area (Houston CMSA) from 1974-2002. The Houston CMSA presents an interesting case study of modeling urban growth using SLEUTH. Houston is perhaps the archetypal Sunbelt city and experienced rapid population growth over the calibration period. Compared to many other United States cities, Houstonxs local governments have a laissez-faire approach to development; in fact Houston is the only major US metropolitan area with no zoning regulations. Calibration of SLEUTH reveals that over the study period urban growth in the Houston CMSA was dominated organic growth, with urban expansion occurring at the urban edges of existing urban centers. Lack of zoning regulations is thought to play an important role on the outward growth of urbanization in Houston.
Calibrating Bayesian Network Representations of Social-Behavioral Models
Whitney, Paul D.; Walsh, Stephen J.
2010-04-08
While human behavior has long been studied, recent and ongoing advances in computational modeling present opportunities for recasting research outcomes in human behavior. In this paper we describe how Bayesian networks can represent outcomes of human behavior research. We demonstrate a Bayesian network that represents political radicalization research – and show a corresponding visual representation of aspects of this research outcome. Since Bayesian networks can be quantitatively compared with external observations, the representation can also be used for empirical assessments of the research which the network summarizes. For a political radicalization model based on published research, we show this empirical comparison with data taken from the Minorities at Risk Organizational Behaviors database.
Stellar models with mixing length and T(τ) relations calibrated on 3D convection simulations
NASA Astrophysics Data System (ADS)
Salaris, Maurizio; Cassisi, Santi
2015-05-01
The calculation of the thermal stratification in the superadiabatic layers of stellar models with convective envelopes is a long-standing problem of stellar astrophysics, and has a major impact on predicted observational properties such as radius and effective temperature. The mixing length theory, almost universally used to model the superadiabatic convective layers, contains one free parameter to be calibrated (αml) whose value controls the resulting effective temperature. Here we present the first self-consistent stellar evolution models calculated by employing the atmospheric temperature stratification, Rosseland opacities, and calibrated variable αml (dependent on effective temperature and surface gravity) from a recently published large suite of three-dimensional radiation hydrodynamics simulations of stellar convective envelopes and atmospheres for solar stellar composition. From our calculations (with the same composition of the radiation hydrodynamics simulations), we find that the effective temperatures of models with the hydro-calibrated variable αml (that ranges between ~1.6 and ~2.0 in the parameter space covered by the simulations) present only minor differences, by at most ~30-50 K, compared to models calculated at constant solar αml (equal to 1.76, as obtained from the same simulations). The depth of the convective regions is essentially the same in both cases. We also analyzed the role played by the hydro-calibrated T(τ) relationships in determining the evolution of the model effective temperatures, when compared to alternative T(τ) relationships often used in stellar model computations. The choice of the T(τ) can have a larger impact than the use of a variable αml compared to a constant solar value. We found that the solar semi-empirical T(τ) by Vernazza et al. (1981, ApJS, 45, 635) provides stellar model effective temperatures that agree quite well with the results with the hydro-calibrated relationships.
NASA Astrophysics Data System (ADS)
liu, li; Solmon, Fabien; Giorgi, Filippo; Vautard, Robert
2014-05-01
Ragweed Ambrosia artemisiifolia L. is a highly allergenic invasive plant. Its pollen can be transported over large distances and has been recognized as a significant cause of hayfever and asthma (D'Amato et al., 2007). In the context of the ATOPICA EU program we are studying the links between climate, land use and ecological changes on the ragweed pollen emissions and concentrations. For this purpose, we implemented a pollen emission/transport module in the RegCM4 regional climate model in collaboration with ATOPICA partners. The Abdus Salam International Centre for Theoretical Physics (ICTP) regional climate model, i.e. RegCM4 was adapted to incorporate the pollen emissions from (ORCHIDEE French) Global Land Surface Model and a pollen tracer model for describing pollen convective transport, turbulent mixing, dry and wet deposition over extensive domains, using consistent assumption regarding the transport of multiple species (Fabien et al., 2008). We performed two families of recent-past simulations on the Euro-Cordex domain (simulation for future condition is been considering). Hindcast simulations (2000~2011) were driven by the ERA-Interim re-analyses and designed to best simulate past periods airborne pollens, which were calibrated with parts of observations and verified by comparison with the additional observations. Historical simulations (1985~2004) were driven by HadGEM CMPI5 and designed to serve as a baseline for comparison with future airborne concentrations as obtained from climate and land-use scenarios. To reduce the uncertainties on the ragweed pollen emission, an assimilation-like method (Rouǐl et al., 2009) was used to calibrate release based on airborne pollen observations. The observations were divided into two groups and used for calibration and validation separately. A wide range of possible calibration coefficients were tested for each calibration station, making the bias between observations and simulations within an admissible value then
Self-calibrating models for dynamic monitoring and diagnosis
NASA Technical Reports Server (NTRS)
Kuipers, Benjamin
1996-01-01
A method for automatically building qualitative and semi-quantitative models of dynamic systems, and using them for monitoring and fault diagnosis, is developed and demonstrated. The qualitative approach and semi-quantitative method are applied to monitoring observation streams, and to design of non-linear control systems.
HYDROLOGIC MODEL CALIBRATION AND UNCERTAINTY IN SCENARIO ANALYSIS
A systematic analysis of model performance during simulations based on
observed land-cover/use change is used to quantify error associated with water-yield
simulations for a series of known landscape conditions over a 24-year period with the
goal of evaluatin...
Remote sensing estimation of evapotranspiration for SWAT Model Calibration
Technology Transfer Automated Retrieval System (TEKTRAN)
Hydrological models are used to assess many water resource problems from water quantity to water quality issues. The accurate assessment of the water budget, primarily the influence of precipitation and evapotranspiration (ET), is a critical first-step evaluation, which is often overlooked in hydro...
Integrating spatial altimetry data into the automatic calibration of hydrological models
NASA Astrophysics Data System (ADS)
Getirana, Augusto C. V.
2010-06-01
SummaryThe automatic calibration of hydrological models has traditionally been performed using gauged data. However, inaccessibility to remote areas and lack of financial support cause data to be lacking in large tropical basins, such as the Amazon basin. Advances in the acquisition, processing and availability of spatially distributed remotely sensed data move the evaluation of computational models easier and more practical. This paper presents the pioneering integration of spatial altimetry data into the automatic calibration of a hydrological model. The study area is the Branco River basin, located in the Northern Amazon basin. An empirical stage × discharge relation is obtained for the Negro River and transposed to the Branco River, which enables the correlation of spatial altimetry data with water discharge derived from the MGB-IPH hydrological model. Six scenarios are created combining two sets of objective functions with three different datasets. Two of them are composed of ENVISAT altimetric data, and the third one is derived from daily gauged discharges. The MOCOM-UA multi-criteria global optimization algorithm is used to optimize the model parameters. The calibration process is validated with gauged discharge at three gauge stations located along the Branco River and two tributaries. Results demonstrate that the combination of virtual stations along the river can provide reasonable parameters. Further, the considerably reduced number of observations provided by the satellite is not a restriction to the automatic calibration, deriving performance coefficients similar to those obtained with the process using daily gauged data.
Calibration of Airframe and Occupant Models for Two Full-Scale Rotorcraft Crash Tests
NASA Technical Reports Server (NTRS)
Annett, Martin S.; Horta, Lucas G.; Polanco, Michael A.
2012-01-01
Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. Accelerations and kinematic data collected from the crash tests were compared to a system integrated finite element model of the test article. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the second full-scale crash test. This combination of heuristic and quantitative methods was used to identify modeling deficiencies, evaluate parameter importance, and propose required model changes. It is shown that the multi-dimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and co-pilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. This approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and test planning guidance. Complete crash simulations with validated finite element models can be used
Prieto, D; Das, T K
2016-03-01
Uncertainty of pandemic influenza viruses continue to cause major preparedness challenges for public health policymakers. Decisions to mitigate influenza outbreaks often involve tradeoff between the social costs of interventions (e.g., school closure) and the cost of uncontrolled spread of the virus. To achieve a balance, policymakers must assess the impact of mitigation strategies once an outbreak begins and the virus characteristics are known. Agent-based (AB) simulation is a useful tool for building highly granular disease spread models incorporating the epidemiological features of the virus as well as the demographic and social behavioral attributes of tens of millions of affected people. Such disease spread models provide excellent basis on which various mitigation strategies can be tested, before they are adopted and implemented by the policymakers. However, to serve as a testbed for the mitigation strategies, the AB simulation models must be operational. A critical requirement for operational AB models is that they are amenable for quick and simple calibration. The calibration process works as follows: the AB model accepts information available from the field and uses those to update its parameters such that some of its outputs in turn replicate the field data. In this paper, we present our epidemiological model based calibration methodology that has a low computational complexity and is easy to interpret. Our model accepts a field estimate of the basic reproduction number, and then uses it to update (calibrate) the infection probabilities in a way that its effect combined with the effects of the given virus epidemiology, demographics, and social behavior results in an infection pattern yielding a similar value of the basic reproduction number. We evaluate the accuracy of the calibration methodology by applying it for an AB simulation model mimicking a regional outbreak in the US. The calibrated model is shown to yield infection patterns closely replicating
Dowding, Kevin J.; Hills, Richard Guy
2005-04-01
Numerical models of complex phenomena often contain approximations due to our inability to fully model the underlying physics, the excessive computational resources required to fully resolve the physics, the need to calibrate constitutive models, or in some cases, our ability to only bound behavior. Here we illustrate the relationship between approximation, calibration, extrapolation, and model validation through a series of examples that use the linear transient convective/dispersion equation to represent the nonlinear behavior of Burgers equation. While the use of these models represents a simplification relative to the types of systems we normally address in engineering and science, the present examples do support the tutorial nature of this document without obscuring the basic issues presented with unnecessarily complex models.
Simulation of sedimentary rock deformation: Lab-scale model calibration and parameterization
NASA Astrophysics Data System (ADS)
Boutt, David F.; McPherson, Brian J. O. L.
2002-02-01
Understanding the mechanical behavior of rock is critical for researchers and decision-makers in fields from petroleum recovery to hazardous waste disposal. Traditional continuum-based numerical models are hampered by inadequate constitutive relationships governing fracture initiation and growth. To overcome limits associated with continuum models we employed a discrete model based on the fundamental laws of contact physics to calibrate triaxial tests. Results from simulations of triaxial compression tests on a suite of sedimentary rocks indicate that the basic physics of rock behavior are clearly captured. Evidence for this conclusion lie in the fact that one set of model parameters describes rock behavior at many confining pressures. The use of both inelastic and elastic parameters for comparison yields insight concerning the uniqueness of these models. These tests will facilitate development and calibration of larger scale discrete element models, which may be applied to a wide range of geological problems.
Bayesian Calibration and Comparison of RANS Turbulence Models for Channel Flow
NASA Astrophysics Data System (ADS)
Oliver, Todd; Moser, Robert
2010-11-01
A set of RANS turbulence models---including Baldwin-Lomax, Spalart-Allmaras, k-ɛ, and v^2-f---are calibrated and compared in the context of fully-developed channel flow. Specifically, a Bayesian calibration procedure is applied to infer the parameter values for each turbulence model from channel flow DNS data. In this process, uncertainty arises both from uncertainty in the data and inadequacies in the turbulence models. Various stochastic models of the turbulence model inadequacy are formulated, and the impacts of different uncertainty modeling choices are examined. The calibrated turbulence models are compared in terms of two items: posterior plausibility and predictions of quantities of interest such as centerline velocity and the location of the maximum Reynolds shear stress. The posterior plausibility indicates which model is preferred by the data according to Bayes' theorem, while the predictions allow assessment of how strongly the model differences impact the quantities of interest. The implications of these comparisons for turbulence model validation will be discussed. This work is supported by the Department of Energy [National Nuclear Security Administration] under Award Number [DE-FC52-08NA28615].
Transducer modeling and compensation in high-pressure dynamic calibration
NASA Astrophysics Data System (ADS)
Gong, Chikun; Li, Yongxin
2005-12-01
When the RBF neural network is used to establish and compensate the transducer model, the numbers of cluster need to be given in advance by using Kohonen algorithm, the RLS algorithm is complicated and the computational burden is much heavier by using it to regulate the output weights. In order to overcome the weakness, a new approach is proposed. The cluster center is decided by the subtractive clustering, and LMS algorithm is used to regulate the output weights. The noise elimination with correlative threshold plus wavelet packet transformation is used to improve the SNR. The study result shows that the network structure is simple and astringency is fast, the modeling and compensation by using the new algorithm is effective to correct the nonlinear dynamic character of transducer, and noise elimination with correlative threshold plus wavelet packet transformation is superior to conventional noise elimination methods.
Stellar model chromospheres. VII - Capella /G5 III +/, Pollux /K0 III/, and Aldebaran /K5 III/
NASA Technical Reports Server (NTRS)
Kelch, W. L.; Chang, S.-H.; Furenlid, I.; Linsky, J. L.; Basri, G. S.; Chiu, H.-Y.; Maran, S. P.
1978-01-01
Data from high-resolution SEC vidicon spectroscopy with a ground-based telescope (for the Ca II K line) and from spectral scans made with the BUSS ultraviolet balloon spectrograph (for the Mg II h and k lines) are used to derive models of the chromospheres and upper photospheres of three G-K giants. The models are based on partial-redistribution analyses of the Ca II K line wings and cores and on the fluxes in the Mg II lines. The photospheres thus computed are hotter than predicted by radiative-equilibrium models. The minimum-to-effective temperature ratio is found to decrease with decreasing effective temperature, while the mass column density at the top of the chromosphere increases with decreasing stellar surface gravity. The computed pressure at the chromosphere top in the primary member of the Capella spectroscopic binary system is 70 times smaller than the transition-region pressure derived by Haisch and Linsky (1976), which suggests that additional terms must be included in the transition-region energy equations for giant stars. Estimates of the Ca II and hydrogen column densities are made for the circumstellar envelope of Aldebaran.
Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data
NASA Astrophysics Data System (ADS)
Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon
2016-04-01
Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model
Calibration of TSI model 3025 ultrafine condensation particle counter
Kesten, J.; Reineking, A.; Porstendoerfer, J. )
1991-01-01
The registration efficiency of the TSI model 3025 ultrafine condensation particle counter for Ag and NaCl particles of between 2 and 20 nm in diameter was determined. Taking into account the different shapes of the input aerosol size distributions entering the differential mobility analyzer (DMA) and the transfer function of the DMA, the counting efficiencies of condensation nucleus counters (CNC) for monodisperse Ag and NaCl particles were estimated. In addition, the dependence of the CNC registration efficiency on the particle concentration was investigated.
Toward improved calibration of watershed models: multisite many objective measures of information
Technology Transfer Automated Retrieval System (TEKTRAN)
This paper presents a computational framework for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. The framework consists of four components: (i) an a-priori characterization of system behavior; (ii) a formal an...
ERIC Educational Resources Information Center
Zhang, Mo; Williamson, David M.; Breyer, F. Jay; Trapani, Catherine
2012-01-01
This article describes two separate, related studies that provide insight into the effectiveness of "e-rater" score calibration methods based on different distributional targets. In the first study, we developed and evaluated a new type of "e-rater" scoring model that was cost-effective and applicable under conditions of absent human rating and…
GROUNDWATER FLOW MODEL CALIBRATION USING WATER LEVEL MEASUREMENTS AT SHORT INTERVALS
Groundwater flow models are usually calibrated with respect to water level measurements collected at intervals of several months or even years. Measurements of these kinds are not sensitive to sudden or short stress conditions, such as impact from stormwater drainage flow or flas...
NASA Astrophysics Data System (ADS)
Tang, Y.; Reed, P.; Wagener, T.
2005-11-01
This study provides a comprehensive assessment of state-of-the-art evolutionary multiobjective optimization (EMO) tools' relative effectiveness in calibrating hydrologic models. The relative computational efficiency, accuracy, and ease-of-use of the following EMO algorithms are tested: Epsilon Dominance Nondominated Sorted Genetic Algorithm-II (ɛ-NSGAII), the Multiobjective Shuffled Complex Evolution Metropolis algorithm (MOSCEM-UA), and the Strength Pareto Evolutionary Algorithm 2 (SPEA2). This study uses three test cases to compare the algorithms' performances: (1) a standardized test function suite from the computer science literature, (2) a benchmark hydrologic calibration test case for the Leaf River near Collins, Mississippi, and (3) a computationally intensive integrated model application in the Shale Hills watershed in Pennsylvania. A challenge and contribution of this work is the development of a methodology for comprehensively comparing EMO algorithms that have different search operators and randomization techniques. Overall, SPEA2 is an excellent benchmark algorithm for multiobjective hydrologic model calibration. SPEA2 attained competitive to superior results for most of the problems tested in this study. ɛ-NSGAII appears to be superior to MOSCEM-UA and competitive with SPEA2 for hydrologic model calibration.
Technology Transfer Automated Retrieval System (TEKTRAN)
The SWAT model is a helpful tool to predict hydrological processes in a study catchment and their impact on the river discharge at the catchment outlet. For reliable discharge predictions, a precise simulation of hydrological processes is required. Therefore, SWAT has to be calibrated accurately to ...
Double-layer parallelization for hydrological model calibration on HPC systems
NASA Astrophysics Data System (ADS)
Zhang, Ang; Li, Tiejian; Si, Yuan; Liu, Ronghua; Shi, Haiyun; Li, Xiang; Li, Jiaye; Wu, Xia
2016-04-01
Large-scale problems that demand high precision have remarkably increased the computational time of numerical simulation models. Therefore, the parallelization of models has been widely implemented in recent years. However, computing time remains a major challenge when a large model is calibrated using optimization techniques. To overcome this difficulty, we proposed a double-layer parallel system for hydrological model calibration using high-performance computing (HPC) systems. The lower-layer parallelism is achieved using a hydrological model, the Digital Yellow River Integrated Model, which was parallelized by decomposing river basins. The upper-layer parallelism is achieved by simultaneous hydrological simulations with different parameter combinations in the same generation of the genetic algorithm and is implemented using the job scheduling functions of an HPC system. The proposed system was applied to the upstream of the Qingjian River basin, a sub-basin of the middle Yellow River, to calibrate the model effectively by making full use of the computing resources in the HPC system and to investigate the model's behavior under various parameter combinations. This approach is applicable to most of the existing hydrology models for many applications.
NASA Astrophysics Data System (ADS)
Finger, David; Vis, Marc; Huss, Matthias; Seibert, Jan
2015-04-01
The assessment of snow, glacier, and rainfall runoff contribution to discharge in mountain streams is of major importance for an adequate water resource management. Such contributions can be estimated via hydrological models, provided that the modeling adequately accounts for snow and glacier melt, as well as rainfall runoff. We present a multiple data set calibration approach to estimate runoff composition using hydrological models with three levels of complexity. For this purpose, the code of the conceptual runoff model HBV-light was enhanced to allow calibration and validation of simulations against glacier mass balances, satellite-derived snow cover area and measured discharge. Three levels of complexity of the model were applied to glacierized catchments in Switzerland, ranging from 39 to 103 km2. The results indicate that all three observational data sets are reproduced adequately by the model, allowing an accurate estimation of the runoff composition in the three mountain streams. However, calibration against only runoff leads to unrealistic snow and glacier melt rates. Based on these results, we recommend using all three observational data sets in order to constrain model parameters and compute snow, glacier, and rain contributions. Finally, based on the comparison of model performance of different complexities, we postulate that the availability and use of different data sets to calibrate hydrological models might be more important than model complexity to achieve realistic estimations of runoff composition.
Automatic TCAD model calibration for multi-cellular Trench-IGBTs
NASA Astrophysics Data System (ADS)
Maresca, Luca; Breglio, Giovanni; Irace, Andrea
2014-01-01
TCAD simulators are a consolidate tool in the field of the semiconductor research because of their predictive capability. However, an accurate calibration of the models is needed in order to get quantitative accurate results. In this work a calibration procedure of the TCAD elementary cell, specific for Trench IGBT with a blocking voltage of 600 V, is presented. It is based on the error minimization between the experimental and the simulated terminal curves of the device at two temperatures. The procedure is applied to a PT-IGBT and a good predictive capability is showed in the simulation of both the short-circuit and turn-off tests.
Calibration models for measuring moisture in unsaturated formations by neutron logging
Engelman, R.E.; Lewis, R.E.; Stromswold, D.C.
1995-10-01
Calibration models containing known amounts of hydrogen have been constructed to simulate unsaturated earth formations for calibrating neutron well logging tools. The models are made of dry mixtures of hydrated alumina (Al(OH){sub 3}) with either silica sand (SiO{sub 2}) or aluminum oxide (Al{sub 2}O{sub 3}). Hydrogen in the hydrated alumina replaces the hydrogen in water for neutron scattering, making it possible to simulate partially saturated formations. The equivalent water contents for the models are 5%, 12%, 20%, and 40% by volume in seven tanks that have a diameter of 1.5 m and a height of 1.8 m. Steel casings of inside diameter 15.4 cm (for three models) and diameter 20.3 cm (for four models) allow logging tool access to simulate logging through cased boreholes.
NASA Astrophysics Data System (ADS)
Junker, Philipp; Hackl, Klaus
2016-06-01
Numerical simulations are a powerful tool to analyze the complex thermo-mechanically coupled material behavior of shape memory alloys during product engineering. The benefit of the simulations strongly depends on the quality of the underlying material model. In this contribution, we discuss a variational approach which is based solely on energetic considerations and demonstrate that unique calibration of such a model is sufficient to predict the material behavior at varying ambient temperature. In the beginning, we recall the necessary equations of the material model and explain the fundamental idea. Afterwards, we focus on the numerical implementation and provide all information that is needed for programing. Then, we show two different ways to calibrate the model and discuss the results. Furthermore, we show how this model is used during real-life industrial product engineering.
Formulation and calibration of a stochastic model form error representation for RANS
NASA Astrophysics Data System (ADS)
Oliver, Todd; Reuter, Bryan; Moser, Robert
2014-11-01
It is well-known that RANS turbulence models fail to accurately represent the effects of turbulence on the mean flow for many important flows. We consider probabilistic representations of this model inadequacy for wall-bounded flows. The particular probabilistic representations considered here take the form of stochastic differential equations that are loosely based on the Reynolds stress transport equations, but include random forcing to represent uncertainty due to the closure problem. This model is disretized using finite elements and a priori uncertainty quantification studies are conducted using Monte Carlo sampling. The results demonstrate that the resulting uncertainties in the mean velocity scale as desired with Reynolds number. In addition to the random forcing, the model contains a number of uncertain parameters. We demonstrate that these can be calibrated using available DNS data. The model is further tested via comparison against additional DNS data outside of the orignal calibration set.
NASA Astrophysics Data System (ADS)
Jackson-Blake, Leah; Helliwell, Rachel
2015-04-01
Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, spanning all hydrochemical conditions. However, regulatory agencies and research organisations generally only sample at a fortnightly or monthly frequency, even in well-studied catchments, often missing peak flow events. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by a process-based, semi-distributed catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the Markov Chain Monte Carlo - DiffeRential Evolution Adaptive Metropolis (MCMC-DREAM) algorithm. Calibration to daily data resulted in improved simulation of peak TDP concentrations and improved model performance statistics. Parameter-related uncertainty in simulated TDP was large when fortnightly data was used for calibration, with a 95% credible interval of 26 μg/l. This uncertainty is comparable in size to the difference between Water Framework Directive (WFD) chemical status classes, and would therefore make it difficult to use this calibration to predict shifts in WFD status. The 95% credible interval reduced markedly with the higher frequency monitoring data, to 6 μg/l. The number of parameters that could be reliably auto-calibrated
Calibration Of 2D Hydraulic Inundation Models In The Floodplain Region Of The Lower Tagus River
NASA Astrophysics Data System (ADS)
Pestanana, R.; Matias, M.; Canelas, R.; Araujo, A.; Roque, D.; Van Zeller, E.; Trigo-Teixeira, A.; Ferreira, R.; Oliveira, R.; Heleno, S.
2013-12-01
In terms of inundated area, the largest floods in Portugal occur in the Lower Tagus River. On average, the river overflows every 2.5 years, at times blocking roads and causing important agricultural damages. This paper focus on the calibration of 2D-horizontal flood simulation models for the floods of 2001 and 2006 on a 70-km stretch of the Lower Tagus River. Flood extent maps, derived from ERS SAR and ENVISAT ASAR imagery were compared with the flood extent maps obtained for each simulation, to calibrate roughness coefficients. The combination of the calibration results from the 2001 and 2006 floods provided a preliminary Manning coefficient map of the study area.
NASA Astrophysics Data System (ADS)
Weiler, M.; Steinbrich, A.
2011-12-01
Predicting the hydrological effect of changes in land-use, whether abrupt (e.g. forest disturbance) or gradual (e.g. urbanization), is still a major challenge, in particular for floods in ungauged watersheds. The application of traditional calibrated rainfall-runoff models is problematic, while the potential of spatially explicit modelling of runoff generation processes to delineate areas with different runoff generation intensity and finally flood hydrographs has not yet been fully explored. We introduce the parsimonious rainfall-runoff model DROGen that is capable of predicting the four major runoff generation mechanisms (infiltration excess, saturation excess, subsurface flow and deep percolation) without parameters to be calibrated. The model incorporates high-resolution GIS data (1m resolution DEM, land-use, impervious surfaces), hydro-geological and pedological data as well as information about the effect of macropores and preferential flow pathways on runoff generation processes. For the State of Baden-Württemberg in Germany we developed guidelines to evaluate the model structure and uncertainty of DROGen. The comprise of the following steps. (1) Field-mapping of runoff generation processes for direct comparison with the simulated pattern of runoff processes for different types of precipitation (high intensity and short duration / low intensity and long duration) as well as for different antecedent moisture conditions. (2) Benchmarking simulated floods with events in a variety of meso-scale watersheds with different physiographic properties and event characteristics. Since a non-calibrated model is applied, input uncertainty as well as model structure uncertainty can be directly evaluated. For example, we could clearly demonstrate a larger uncertainty for floods from convective precipitation events. Another source of uncertainty comes from a missing process representation for strongly layered soil profiles (e.g. podzols). (3) A comparison of the simulated
Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model
NASA Astrophysics Data System (ADS)
Safta, C.; Ricciuto, D. M.; Sargsyan, K.; Najm, H. N.; Debusschere, B.; Thornton, P. E.
2013-12-01
We present uncertainty quantification results for a process-based ecosystem carbon model. The model employs 18 parameters and is driven by meteorological data corresponding to years 1992-2006 at the Harvard Forest site. Daily Net Ecosystem Exchange (NEE) observations were available to calibrate the model parameters and test the performance of the model. Posterior distributions show good predictive capabilities for the calibrated model. A global sensitivity analysis was first performed to determine the important model parameters based on their contribution to the variance of NEE. We then proceed to calibrate the model parameters in a Bayesian framework. The daily discrepancies between measured and predicted NEE values were modeled as independent and identically distributed Gaussians with prescribed daily variance according to the recorded instrument error. All model parameters were assumed to have uninformative priors with bounds set according to expert opinion. The global sensitivity results show that the rate of leaf fall (LEAFALL) is responsible for approximately 25% of the total variance in the average NEE for 1992-2005. A set of 4 other parameters, Nitrogen use efficiency (NUE), base rate for maintenance respiration (BR_MR), growth respiration fraction (RG_FRAC), and allocation to plant stem pool (ASTEM) contribute between 5% and 12% to the variance in average NEE, while the rest of the parameters have smaller contributions. The posterior distributions, sampled with a Markov Chain Monte Carlo algorithm, exhibit significant correlations between model parameters. However LEAFALL, the most important parameter for the average NEE, is not informed by the observational data, while less important parameters show significant updates between their prior and posterior densities. The Fisher information matrix values, indicating which parameters are most informed by the experimental observations, are examined to augment the comparison between the calibration and global
Can hydrodynamic models be implemented and calibrated on the basis of remotely sensed data only?
NASA Astrophysics Data System (ADS)
Domeneghetti, Alessio
2015-04-01
The implementation and calibration of hydrodynamic models are often constrained by the amount of available data (such as topographic and hydraulic data) which may be absent (e.g. in remote areas) or not sufficient to build accurate and trustable models. Nevertheless, the greater availability of remote sensing data (e.g. altimetry data, radar imageries, etc.) stimulates the scientific community to resort to these new data sources for overcoming these limits. The present study analyzes the potential of remotely sensed data, i.e. (i) Shuttle Radar Topography Mission (SRTM; a freely available global Digital Elevation Model with a resolution of 90 m) and (ii) satellite altimetry data (i.e. ERS and ENVISAT data), for a complete implementation and calibration of a one-dimensional (1D) hydrodynamic model. The test site is represented by ~140 km stretch of the Po river (the longest Italian river) where both traditional and remotely sensed topographical and hydrometric data are available. Adopting the SRTM data for representing the riverbed and floodplain morphology, the study investigates the performances of different 1D models in which the geometry of the main channel, which is generally submerged and cannot be remotely surveyed, is reconstructed on the basis of different approaches. The model calibrations are performed referring to long satellite altimetry timeseries (~16 years of observations), while the simulation results are compared with those obtained by means of a quasi-2D model implemented with detailed topographical data (i.e. airborne LiDAR available on the study area). The results of the study are encouraging and show the possibility to implement and calibrate a reliable 1D model referring exclusively to low-resolution DEM (e.g. SRTM) and remotely sensed water surface data (i.e. ERS and ENVISAT). The 1D model is particularly accurate for describing high-flow and flood events (i.e. root mean square error equal to 0.11 m) and comparable with traditionally
Scott, D.T.; Gooseff, M.N.; Bencala, K.E.; Runkel, R.L.
2003-01-01
The hydrologic processes of advection, dispersion, and transient storage are the primary physical mechanisms affecting solute transport in streams. The estimation of parameters for a conservative solute transport model is an essential step to characterize transient storage and other physical features that cannot be directly measured, and often is a preliminary step in the study of reactive solutes. Our study used inverse modeling to estimate parameters of the transient storage model OTIS (One dimensional Transport with Inflow and Storage). Observations from a tracer injection experiment performed on Uvas Creek, California, USA, are used to illustrate the application of automated solute transport model calibration to conservative and nonconservative stream solute transport. A computer code for universal inverse modeling (UCODE) is used for the calibrations. Results of this procedure are compared with a previous study that used a trial-and-error parameter estimation approach. The results demonstrated 1) importance of the proper estimation of discharge and lateral inflow within the stream system; 2) that although the fit of the observations is not much better when transient storage is invoked, a more randomly distributed set of residuals resulted (suggesting non-systematic error), indicating that transient storage is occurring; 3) that inclusion of transient storage for a reactive solute (Sr2+) provided a better fit to the observations, highlighting the importance of robust model parameterization; and 4) that applying an automated calibration inverse modeling estimation approach resulted in a comprehensive understanding of the model results and the limitation of input data.
Khan, Yasin; Mathur, Jyotirmay; Bhandari, Mahabir S
2016-01-01
The paper describes a case study of an information technology office building with a radiant cooling system and a conventional variable air volume (VAV) system installed side by side so that performancecan be compared. First, a 3D model of the building involving architecture, occupancy, and HVAC operation was developed in EnergyPlus, a simulation tool. Second, a different calibration methodology was applied to develop the base case for assessing the energy saving potential. This paper details the calibration of the whole building energy model to the component level, including lighting, equipment, and HVAC components such as chillers, pumps, cooling towers, fans, etc. Also a new methodology for the systematic selection of influence parameter has been developed for the calibration of a simulated model which requires large time for the execution. The error at the whole building level [measured in mean bias error (MBE)] is 0.2%, and the coefficient of variation of root mean square error (CvRMSE) is 3.2%. The total errors in HVAC at the hourly are MBE = 8.7% and CvRMSE = 23.9%, which meet the criteria of ASHRAE 14 (2002) for hourly calibration. Different suggestions have been pointed out to generalize the energy saving of radiant cooling system through the existing building system. So a base case model was developed by using the calibrated model for quantifying the energy saving potential of the radiant cooling system. It was found that a base case radiant cooling system integrated with DOAS can save 28% energy compared with the conventional VAV system.
NASA Astrophysics Data System (ADS)
Tang, Y.; Reed, P.; Wagener, T.
2006-05-01
This study provides a comprehensive assessment of state-of-the-art evolutionary multiobjective optimization (EMO) tools' relative effectiveness in calibrating hydrologic models. The relative computational efficiency, accuracy, and ease-of-use of the following EMO algorithms are tested: Epsilon Dominance Nondominated Sorted Genetic Algorithm-II (ɛ-NSGAII), the Multiobjective Shuffled Complex Evolution Metropolis algorithm (MOSCEM-UA), and the Strength Pareto Evolutionary Algorithm 2 (SPEA2). This study uses three test cases to compare the algorithms' performances: (1) a standardized test function suite from the computer science literature, (2) a benchmark hydrologic calibration test case for the Leaf River near Collins, Mississippi, and (3) a computationally intensive integrated surface-subsurface model application in the Shale Hills watershed in Pennsylvania. One challenge and contribution of this work is the development of a methodology for comprehensively comparing EMO algorithms that have different search operators and randomization techniques. Overall, SPEA2 attained competitive to superior results for most of the problems tested in this study. The primary strengths of the SPEA2 algorithm lie in its search reliability and its diversity preservation operator. The biggest challenge in maximizing the performance of SPEA2 lies in specifying an effective archive size without a priori knowledge of the Pareto set. In practice, this would require significant trial-and-error analysis, which is problematic for more complex, computationally intensive calibration applications. ɛ-NSGAII appears to be superior to MOSCEM-UA and competitive with SPEA2 for hydrologic model calibration. ɛ-NSGAII's primary strength lies in its ease-of-use due to its dynamic population sizing and archiving which lead to rapid convergence to very high quality solutions with minimal user input. MOSCEM-UA is best suited for hydrologic model calibration applications that have small parameter sets
Calibrating Stellar Models with the Pleiades: Resolving the Distance Discrepancy
NASA Astrophysics Data System (ADS)
Soderblom, David
1999-07-01
This is the first phase of a multi-year effort to measure true masses for low-mass dwarfs in the Pleiades and to determine an accurate distance to this fundamental cluster. The goals are: 1} To determine the true distance to the Pleiades to resolve the problem raised by the Hipparcos results for this cluster; The Hipparcos distance for the Pleiades, taken at face value, indicates that solar-composition ZAMS stars are 30% fainter than previously believed. 2} To test ZAMS models of evolution for young solar-type stars by measuring masses of individual stars. 3} To construct a mass-luminosity relation for young low-mass stars with solar composition. The resolution to the Hipparcos distance problem is vital for understanding all the parallaxes that have come from that mission and hence this issue is fundamental to the cosmic distance scale. In this first phase we get several observations of three systems which are already resolved spectroscopically and which have 2 to 3 year orb ital periods, and we examine other Pleiades binaries to ascertain which objects are resolvable pairs with separations suitable for orbit determinations with the FGS. Please note: Most of our targets are bright and near each other, and can therefore be surveyed in TRANS mode in 1/2 an orbit each. Our total orbit request reflects this.
NASA Astrophysics Data System (ADS)
Goldberg, D. N.; Heimbach, P.; Joughin, I.; Smith, B.
2015-12-01
A glacial flow model of Smith, Pope and Kohler Glaciers has been calibrated by means of inverse methods against time-varying, annualy resolved observations of ice height and velocities, covering the period 2002 to 2011. The inversion -- termed ``transient calibration'' -- produces an optimal set of time-mean, spatially varying parameters together with a time-evolving state that accounts for the transient nature of observations and the model dynamics. Serving as an optimal initial condition, the estimated state for 2011 is used, with no additional forcing, for predicting grounded ice volume loss and grounding line retreat over the ensuing 30 years. The transiently calibrated model predicts a near-steady loss of grounded ice volume of approximately 21 km3/a over this period, as well as loss of 33 km2/a grounded area. We contrast this prediction with one obtained following a commonly used ``snapshot'' or steady-state inversion, which does not consider time dependence and assumes all observations to be contemporaneous. Transient calibration is shown to achieve a better fit with observations of thinning and grounding line retreat histories, and yields a quantitatively different projection with respect to ice volume loss and ungrounding. Sensitivity studies suggest large near-future levels of unforced, i.e. committed sea level contribution from these ice streams under reasonable assumptions regarding uncertainties of the unknown parameters.
An initial inverse calibration of the ground-water flow model for the Hanford unconfined aquifer
Jacobson, E.A. . Desert Research Inst.); Freshly, M.D. )
1990-03-01
Large volumes of process cooling water are discharged to the ground form U.S. Department of Energy (DOE) nuclear fuel processing operations in the central portion of the Hanford Site in southeastern Washington. Over the years, these large volumes of waste water have recharged the unconfined aquifer at the Site. This artificial recharge has affected ground-water levels and contaminant movement in the unconfined aquifer. Ground-water flow and contaminant transport models have been applied to assess the impacts of site operations on the rate and direction of ground-water flow and contaminant transport in unconfined aquifer at the Hanford Site. The inverse calibration method developed by Neuman and modified by Jacobson was applied to improve calibration of a ground-water flow model of the unconfined aquifer at the Hanford Site. All information about estimates of hydraulic properties of the aquifer, hydraulic heads, boundary conditions, and discharges to and withdrawals form the aquifer is included in the inverse method to obtain an initial calibration of the ground-water flow model. The purpose of this report is to provide a description of the inverse method, its initial application to the unconfined aquifer at Hanford, and to present results of the initial inverse calibration. 28 refs., 19 figs., 1 tab.
Hidden Connections between Regression Models of Strain-Gage Balance Calibration Data
NASA Technical Reports Server (NTRS)
Ulbrich, Norbert
2013-01-01
Hidden connections between regression models of wind tunnel strain-gage balance calibration data are investigated. These connections become visible whenever balance calibration data is supplied in its design format and both the Iterative and Non-Iterative Method are used to process the data. First, it is shown how the regression coefficients of the fitted balance loads of a force balance can be approximated by using the corresponding regression coefficients of the fitted strain-gage outputs. Then, data from the manual calibration of the Ames MK40 six-component force balance is chosen to illustrate how estimates of the regression coefficients of the fitted balance loads can be obtained from the regression coefficients of the fitted strain-gage outputs. The study illustrates that load predictions obtained by applying the Iterative or the Non-Iterative Method originate from two related regression solutions of the balance calibration data as long as balance loads are given in the design format of the balance, gage outputs behave highly linear, strict statistical quality metrics are used to assess regression models of the data, and regression model term combinations of the fitted loads and gage outputs can be obtained by a simple variable exchange.
Marker-based monitoring of seated spinal posture using a calibrated single-variable threshold model.
Walsh, Pauline; Dunne, Lucy E; Caulfield, Brian; Smyth, Barry
2006-01-01
This work, as part of a larger project developing wearable posture monitors for the work environment, seeks to monitor and model seated posture during computer use. A non-wearable marker-based optoelectronic motion capture system was used to monitor seated posture for ten healthy subjects during a calibration exercise and a typing task. Machine learning techniques were used to select overall spinal sagittal flexion as the best indicator of posture from a set of marker and vector variables. Overall flexion data from the calibration exercise were used to define a threshold model designed to classify posture for each subject, which was then applied to the typing task data. Results of the model were analysed visually by qualified physiotherapists with experience in ergonomics and posture analysis to confirm the accuracy of the calibration. The calibration formula was found to be accurate on 100% subjects. This process will be used as a comparative measure in the evaluation of several wearable posture sensors, and to inform the design of the wearable system. PMID:17946301
Model calibration and validation for OFMSW and sewage sludge co-digestion reactors
Esposito, G.; Frunzo, L.; Panico, A.; Pirozzi, F.
2011-12-15
Highlights: > Disintegration is the limiting step of the anaerobic co-digestion process. > Disintegration kinetic constant does not depend on the waste particle size. > Disintegration kinetic constant depends only on the waste nature and composition. > The model calibration can be performed on organic waste of any particle size. - Abstract: A mathematical model has recently been proposed by the authors to simulate the biochemical processes that prevail in a co-digestion reactor fed with sewage sludge and the organic fraction of municipal solid waste. This model is based on the Anaerobic Digestion Model no. 1 of the International Water Association, which has been extended to include the co-digestion processes, using surface-based kinetics to model the organic waste disintegration and conversion to carbohydrates, proteins and lipids. When organic waste solids are present in the reactor influent, the disintegration process is the rate-limiting step of the overall co-digestion process. The main advantage of the proposed modeling approach is that the kinetic constant of such a process does not depend on the waste particle size distribution (PSD) and rather depends only on the nature and composition of the waste particles. The model calibration aimed to assess the kinetic constant of the disintegration process can therefore be conducted using organic waste samples of any PSD, and the resulting value will be suitable for all the organic wastes of the same nature as the investigated samples, independently of their PSD. This assumption was proven in this study by biomethane potential experiments that were conducted on organic waste samples with different particle sizes. The results of these experiments were used to calibrate and validate the mathematical model, resulting in a good agreement between the simulated and observed data for any investigated particle size of the solid waste. This study confirms the strength of the proposed model and calibration procedure, which can
Calibrating a Rainfall-Runoff and Routing Model for the Continental United States
NASA Astrophysics Data System (ADS)
Jankowfsky, S.; Li, S.; Assteerawatt, A.; Tillmanns, S.; Hilberts, A.
2014-12-01
Catastrophe risk models are widely used in the insurance industry to estimate the cost of risk. The models consist of hazard models linked to vulnerability and financial loss models. In flood risk models, the hazard model generates inundation maps. In order to develop country wide inundation maps for different return periods a rainfall-runoff and routing model is run using stochastic rainfall data. The simulated discharge and runoff is then input to a two dimensional inundation model, which produces the flood maps. In order to get realistic flood maps, the rainfall-runoff and routing models have to be calibrated with observed discharge data. The rainfall-runoff model applied here is a semi-distributed model based on the Topmodel (Beven and Kirkby, 1979) approach which includes additional snowmelt and evapotranspiration models. The routing model is based on the Muskingum-Cunge (Cunge, 1969) approach and includes the simulation of lakes and reservoirs using the linear reservoir approach. Both models were calibrated using the multiobjective NSGA-II (Deb et al., 2002) genetic algorithm with NLDAS forcing data and around 4500 USGS discharge gauges for the period from 1979-2013. Additional gauges having no data after 1979 were calibrated using CPC rainfall data. The model performed well in wetter regions and shows the difficulty of simulating areas with sinks such as karstic areas or dry areas. Beven, K., Kirkby, M., 1979. A physically based, variable contributing area model of basin hydrology. Hydrol. Sci. Bull. 24 (1), 43-69. Cunge, J.A., 1969. On the subject of a flood propagation computation method (Muskingum method), J. Hydr. Research, 7(2), 205-230. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T., 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on evolutionary computation, 6(2), 182-197.
Calibration of inundation models using uncertain SAR-derived maps of flood extent
NASA Astrophysics Data System (ADS)
di Baldassarre, Giuliano; Schumann, Guy; Bates, Paul
2010-05-01
This presentation deals with the calibration of hydraulic models using uncertain inundation maps derived from SAR imagery. The study was performed on a river reach of the Lower Dee, UK, where coarse (ENVISAT ASAR) and high (ERS-2 SAR) resolution imagery were acquired at the same time during the December 2006 flood event. Ten different flood extent maps were derived from the two flood imagery by using five different image processing techniques. These flood extent maps were used to perform a sensitivity analysis of a simple raster-based inundation model (LISFLOOD-FP). Thus, the capability of the two images to calibrate the friction parameters of the model was investigated. The analysis showed that the optimal parameters of the model depend on the type of satellite image used to evaluate the model as well as on the particular procedure used to derive the flood extent map. Then, a methodology is developed to calibrate flood inundation models by comparing the model results to uncertain inundation maps, which are obtained by combining the ten different flood extent maps.
On Inertial Body Tracking in the Presence of Model Calibration Errors.
Miezal, Markus; Taetz, Bertram; Bleser, Gabriele
2016-01-01
In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments-the IMU-to-segment calibrations, subsequently called I2S calibrations-to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and
Technology Transfer Automated Retrieval System (TEKTRAN)
Process based and distributed watershed models possess a large number of parameters that are not directly measured in field and need to be calibrated through matching modeled in-stream fluxes with monitored data. Recently, there have been waves of concern about the reliability of this common practic...
Calibration of the heat balance model for prediction of car climate
NASA Astrophysics Data System (ADS)
Pokorný, Jan; Fišer, Jan; Jícha, Miroslav
2012-04-01
In the paper, the authors refer to development a heat balance model to predict car climate and power heat load. Model is developed in Modelica language using Dymola as interpreter. It is a dynamical system, which describes a heat exchange between car cabin and ambient. Inside a car cabin, there is considered heat exchange between air zone, interior and air-conditioning system. It is considered 1D heat transfer with a heat accumulation and a relative movement Sun respect to the car cabin, whilst car is moving. Measurements of the real operating conditions of gave us data for model calibration. The model was calibrated for Škoda Felicia parking-summer scenarios.
A directional HF noise model: Calibration and validation in the Australian region
NASA Astrophysics Data System (ADS)
Pederick, L. H.; Cervera, M. A.
2016-01-01
The performance of systems using HF (high frequency) radio waves, such as over-the-horizon radars, is strongly dependent on the external noise environment. However, this environment has complex behavior and is known to vary with location, time, season, sunspot number, and radio frequency. It is also highly anisotropic, with the directional variation of noise being very important for the design and development of next generation over-the-horizon radar. By combining global maps of lightning occurrence, raytracing propagation, a model background ionosphere and ionospheric absorption, the behavior of noise at HF may be modeled. This article outlines the principles, techniques, and current progress of the model and calibrates it against a 5 year data set of background noise measurements. The calibrated model is then compared with data at a second site.
NASA Astrophysics Data System (ADS)
Safta, C.; Ricciuto, D. M.; Sargsyan, K.; Debusschere, B.; Najm, H. N.; Williams, M.; Thornton, P. E.
2015-07-01
In this paper we propose a probabilistic framework for an uncertainty quantification (UQ) study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. A global sensitivity analysis (GSA) study indicates the parameters and parameter couplings that are important at different times of the year for quantities of interest (QoIs) obtained with the data assimilation linked ecosystem carbon (DALEC) model. We then employ a Bayesian approach and a statistical model error term to calibrate the parameters of DALEC using net ecosystem exchange (NEE) observations at the Harvard Forest site. The calibration results are employed in the second part of the paper to assess the predictive skill of the model via posterior predictive checks.
NASA Astrophysics Data System (ADS)
Arsenault, Richard; Brissette, François P.; Poulin, Annie; Côté, Pascal; Martel, Jean-Luc
2014-05-01
The process of hydrological model parameter calibration is routinely performed with the help of stochastic optimization algorithms. Many such algorithms have been created and they sometimes provide varying levels of performance (as measured by an efficiency metric such as Nash-Sutcliffe). This is because each algorithm is better suited for one type of optimization problem rather than another. This research project's aim was twofold. First, it was sought upon to find various features in the calibration problem fitness landscapes to map the encountered problem types to the best possible optimization algorithm. Second, the optimal number of model evaluations in order to minimize resources usage and maximize overall model quality was investigated. A total of five stochastic optimization algorithms (SCE-UA, CMAES, DDS, PSO and ASA) were used to calibrate four lumped hydrological models (GR4J, HSAMI, HMETS and MOHYSE) on 421 basins from the US MOPEX database. Each of these combinations was performed using three objective functions (Log(RMSE), NSE, and a metric combining NSE, RMSE and BIAS) to add sufficient diversity to the fitness landscapes. Each run was performed 30 times for statistical analysis. With every parameter set tested during the calibration process, the validation value was taken on a separate period. It was then possible to outline the calibration skill versus the validation skill for the different algorithms. Fitness landscapes were characterized by various metrics, such as the dispersion metric, the mean distance between random points and their respective local minima (found through simple hill-climbing algorithms) and the mean distance between the local minima and the best local optimum found. These metrics were then compared to the calibration score of the various optimization algorithms. Preliminary results tend to show that fitness landscapes presenting a globally convergent structure are more prevalent than other types of landscapes in this
Impact of Land Model Calibration on Coupled Land-Atmosphere Prediction
NASA Technical Reports Server (NTRS)
Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia
2012-01-01
Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry and wet land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystem in NASA's Land Information System (LIS-OPT/UE). The impact of the calibration on the a) spinup of the land surface used as initial conditions, and b) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. Changes in ambient weather and land-atmosphere coupling are evaluated along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Results indicate that the offline calibration leads to systematic improvements in land-PBL fluxes and near-surface temperature and humidity, and in the process provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.
Kay, D; McDonald, A
1983-01-01
This paper reports on the calibration and use of a multiple regression model designed to predict concentrations of Escherichia coli and total coliforms in two upland British impoundments. The multivariate approach has improved predictive capability over previous univariate linear models because it includes predictor variables for the timing and magnitude of hydrological input to the reservoirs and physiochemical parameters of water quality. The significance of these results for catchment management research is considered. PMID:6639016
Wind waves modelling on the water body with coupled WRF and WAVEWATCH III models
NASA Astrophysics Data System (ADS)
Kuznetsova, Alexandra; Troitskaya, Yuliya; Kandaurov, Alexander; Baydakov, Georgy; Vdovin, Maxim; Papko, Vladislav; Sergeev, Daniil
2015-04-01
Simulation of ocean and sea waves is an accepted instrument for the improvement of the weather forecasts. Wave modelling, coupled models modelling is applied to open seas [1] and is less developed for moderate and small inland water reservoirs and lakes, though being of considerable interest for inland navigation. Our goal is to tune the WAVEWATCH III model to the conditions of the inland reservoir and to carry out the simulations of surface wind waves with coupled WRF (Weather Research and Forecasting) and WAVEWATCH III models. Gorky Reservoir, an artificial lake in the central part of the Volga River formed by a hydroelectric dam, was considered as an example of inland reservoir. Comparing to [2] where moderate constant winds (u10 is up to 9 m/s) of different directions blowing steadily all over the surface of the reservoir were considered, here we apply atmospheric model WRF to get wind input to WAVEWATCH III. WRF computations were held on the Yellowstone supercomputer for 4 nested domains with minimum scale of 1 km. WAVEWATCH III model was tuned for the conditions of the Gorky Reservoir. Satellite topographic data on altitudes ranged from 56,6° N to 57,5° N and from 42.9° E to 43.5° E with increments 0,00833 ° in both directions was used. 31 frequencies ranged from 0,2 Hz to 4 Hz and 30 directions were considered. The minimal significant wave height was changed to the lower one. The waves in the model were developing from some initial seeding spectral distribution (Gaussian in frequency and space, cosine in direction). The range of the observed significant wave height in the numerical experiment was from less than 1 cm up to 30 cm. The field experiments were carried out in the south part of the Gorky reservoir from the boat [2, 3]. 1-D spectra of the field experiment were compared with those obtained in the numerical experiments with different parameterizations of flux provided in WAVEWATCH III both with constant wind input and WRF wind input. For all the
Including sugar cane in the agro-ecosystem model ORCHIDEE-STICS: calibration and validation
NASA Astrophysics Data System (ADS)
Valade, A.; Vuichard, N.; Ciais, P.; Viovy, N.
2011-12-01
Sugarcane is currently the most efficient bioenergy crop with regards to the energy produced per hectare. With approximately half the global bioethanol production in 2005, and a devoted land area expected to expand globally in the years to come, sugar cane is at the heart of the biofuel debate. Dynamic global vegetation models coupled with agronomical models are powerful and novel tools to tackle many of the environmental issues related to biofuels if they are carefully calibrated and validated against field observations. Here we adapt the agro-terrestrial model ORCHIDEE-STICS for sugar cane simulations. Observation data of LAI are used to evaluate the sensitivity of the model to parameters of nitrogen absorption and phenology, which are calibrated in a systematic way for six sites in Australia and La Reunion. We find that the optimal set of parameters is highly dependent on the sites' characteristics and that the model can reproduce satisfactorily the evolution of LAI. This careful calibration of ORCHIDEE-STICS for sugar cane biomass production for different locations and technical itineraries provides a strong basis for further analysis of the impacts of bioenergy-related land use change on carbon cycle budgets. As a next step, a sensitivity analysis is carried out to estimate the uncertainty of the model in biomass and carbon flux simulation due to its parameterization.
Sensor modeling, self-calibration and accuracy testing of panoramic cameras and laser scanners
NASA Astrophysics Data System (ADS)
Amiri Parian, Jafar; Gruen, Armin
2010-01-01
Terrestrial Linear Array CCD-based panoramic cameras have been used for purely imaging purposes, but they also have a high potential for use in high accuracy measurement applications. The imaging geometry and the high information content of those images make them suitable candidates for quantitative image analysis. For that a particular sensor model has to be established and the inherent accuracy potential has to be investigated. We developed a sensor model for terrestrial Linear Array-based panoramic cameras by means of a modified bundle adjustment with additional parameters, which models substantial deviations of a real camera from the ideal one. We used 3D straight-line information in addition to tie points to conduct a full calibration and orientation without control point information. Due to the similarity of the operation of laser scanners to panoramic cameras the sensor model of the panoramic cameras was extended for the self-calibration of laser scanners. We present the joint sensor model for panoramic cameras and laser scanners and the results of self-calibration, which indicate a subpixel accuracy level for such highly dynamic systems. Finally we demonstrate the systems' accuracy of two typical panoramic cameras in 3D point positioning, using both a minimal number of control points and a free network adjustment. With these new panoramic imaging devices we have additional powerful sensors for image recording and efficient 3D object modeling.
Parameter Estimation for a crop model: separate and joint calibration of soil and plant parameters
NASA Astrophysics Data System (ADS)
Hildebrandt, A.; Jackisch, C.; Luis, S.
2008-12-01
Vegetation plays a major role both in the atmospheric and terrestrial water cycle. A great deal of vegetation cover in the developed world consists of agricultural used land (i.e. 44 % of the territory of the EU). Therefore, crop models have become increasingly prominent for studying the impact of Global Change both on economic welfare as well as on influence of vegetation on climate, and feedbacks with hydrological processes. By doing so, it is implied that crop models properly reflect the soil water balance and vertical exchange with the atmosphere. Although crop models can be incorporated in Surface Vegetation Atmosphere Transfer Schemes for that purpose, their main focus has traditionally not been on predicting water and energy fluxes, but yield. In this research we use data from two lysimeters in Brandis (Saxony, Germany), which have been planted with the crops of the surrounding farm, to test the capability of the crop model in SWAP. The lysimeters contain different natural soil cores, leading to substantially different yield. This experiment gives the opportunity to test, if the crop model is portable - that is if a calibrated crop can be moved between different locations. When using the default parameters for the respective environment, the model does neither quantitatively nor qualitatively reproduce the difference in yield and LAI for the different lysimeters. The separate calibration of soil and plant parameter was poor compared to the joint calibration of plant and soil parameters. This suggests that the model is not portable, but needs to be calibrated for individual locations, based on measurements or expert knowledge.
Not Available
1981-10-29
This volume contains a description of the software comprising the National Utility Financial Statement Model (NUFS). This is the third of three volumes describing NUFS provided by ICF Incorporated under contract DEAC-01-79EI-10579. The three volumes are entitled: model overview and description, user's guide, and software guide.
Yan, Huiping; Qian, Yun; Lin, Guang; Leung, Lai-Yung R.; Yang, Ben; Fu, Q.
2014-03-25
Convective parameterizations used in weather and climate models all display sensitivity to model resolution and variable skill in different climatic regimes. Although parameters in convective schemes can be calibrated using observations to reduce model errors, it is not clear if the optimal parameters calibrated based on regional data can robustly improve model skill across different model resolutions and climatic regimes. In this study, this issue is investigated using a regional modeling framework based on the Weather Research and Forecasting (WRF) model. To quantify the response and sensitivity of model performance to model parameters, we identified five key input parameters and specified their ranges in the Kain-Fritsch (KF) convection scheme in WRF and calibrated them across different spatial resolutions, climatic regimes, and radiation schemes using observed precipitation data. Results show that the optimal values for the five input parameters in the KF scheme are close and model sensitivity and error exhibit similar dependence on the input parameters for all experiments conducted in this study despite differences in the precipitation climatology. We found that the model overall performances in simulating precipitation are more sensitive to the coefficients of downdraft (Pd) and entrainment (Pe) mass flux and starting height of downdraft (Ph). However, we found that rainfall biases, which are probably more related to structural errors, still exist over some regions in the simulation even with the optimal parameters, suggesting further studies are needed to identify the sources of uncertainties and reduce the model biases or structural errors associated with missed or misrepresented physical processes and/or potential problems with the modeling framework.
J.C. Rowland; D.R. Harp; C.J. Wilson; A.L. Atchley; V.E. Romanovsky; E.T. Coon; S.L. Painter
2016-02-02
This Modeling Archive is in support of an NGEE Arctic publication available at doi:10.5194/tc-10-341-2016. This dataset contains an ensemble of thermal-hydro soil parameters including porosity, thermal conductivity, thermal conductivity shape parameters, and residual saturation of peat and mineral soil. The ensemble was generated using a Null-Space Monte Carlo analysis of parameter uncertainty based on a calibration to soil temperatures collected at the Barrow Environmental Observatory site by the NGEE team. The micro-topography of ice wedge polygons present at the site is included in the analysis using three 1D column models to represent polygon center, rim and trough features. The Arctic Terrestrial Simulator (ATS) was used in the calibration to model multiphase thermal and hydrological processes in the subsurface.
Calibration of a bubble evolution model to observed bubble incidence in divers.
Gault, K A; Tikuisis, P; Nishi, R Y
1995-09-01
The method of maximum likelihood was used to calibrate a probabilistic bubble evolution model against data of bubbles detected in divers. These data were obtained from a diverse set of 2,064 chamber man-dives involving air and heliox with and without oxygen decompression. Bubbles were measured with Doppler ultrasound and graded according to the Kisman-Masurel code from which a single maximum bubble grade (BG) per diver was compared to the maximum bubble radius (Rmax) predicted by the model. This comparison was accomplished using multinomial statistics by relating BG to Rmax through a series of probability functions. The model predicted the formation of the bubble according to the critical radius concept and its evolution was predicted by assuming a linear rate of inert gas exchange across the bubble boundary. Gas exchange between the model compartment and blood was assumed to be perfusion-limited. The most successful calibration of the model was found using a trinomial grouping of BG according to no bubbles, low, and high bubble activity, and by assuming a single tissue compartment. Parameter estimations converge to a tissue volume of 0.00036 cm3, a surface tension of 5.0 dyne.cm-1, respective time constants of 27.9 and 9.3 min for nitrogen and helium, and respective Ostwald tissue solubilities of 0.0438 and 0.0096. Although not part of the calibration algorithm, the predicted evolution of bubble size compares reasonably well with the temporal recordings of BGs. PMID:7580766
ERIC Educational Resources Information Center
Nyasulu, Frazier; Barlag, Rebecca
2011-01-01
The well-known colorimetric determination of the equilibrium constant of the iron(III-thiocyanate complex is simplified by preparing solutions in a cuvette. For the calibration plot, 0.10 mL increments of 0.00100 M KSCN are added to 4.00 mL of 0.200 M Fe(NO[subscript 3])[subscript 3], and for the equilibrium solutions, 0.50 mL increments of…
A model-based approach to the spatial and spectral calibration of NIRSpec onboard JWST
NASA Astrophysics Data System (ADS)
Dorner, B.; Giardino, G.; Ferruit, P.; Alves de Oliveira, C.; Birkmann, S. M.; Böker, T.; De Marchi, G.; Gnata, X.; Köhler, J.; Sirianni, M.; Jakobsen, P.
2016-08-01
Context. The NIRSpec instrument for the James Webb Space Telescope (JWST) can be operated in multiobject spectroscopy (MOS), long-slit, and integral field unit (IFU) mode with spectral resolutions from 100 to 2700. Its MOS mode uses about a quarter of a million individually addressable minislits for object selection, covering a field of view of ~9 arcmin2. Aims: The pipeline used to extract wavelength-calibrated spectra from NIRSpec detector images relies heavily on a model of NIRSpec optical geometry. We demonstrate how dedicated calibration data from a small subset of NIRSpec modes and apertures can be used to optimize this parametric model to the necessary levels of fidelity. Methods: Following an iterative procedure, the initial fiducial values of the model parameters are manually adjusted and then automatically optimized, so that the model predicted location of the images and spectral lines from the fixed slits, the IFU, and a small subset of the MOS apertures matches their measured location in the main optical planes of the instrument. Results: The NIRSpec parametric model is able to reproduce the spatial and spectral position of the input spectra with high fidelity. The intrinsic accuracy (1-sigma, rms) of the model, as measured from the extracted calibration spectra, is better than 1/10 of a pixel along the spatial direction and better than 1/20 of a resolution element in the spectral direction for all of the grating-based spectral modes. This is fully consistent with the corresponding allocation in the spatial and spectral calibration budgets of NIRSpec.
On the behavior of mud floc size distribution: model calibration and model behavior
NASA Astrophysics Data System (ADS)
Mietta, Francesca; Chassagne, Claire; Verney, Romaric; Winterwerp, Johan C.
2011-03-01
In this paper, we study a population balance equation (PBE) where flocs are distributed into classes according to their mass. Each class i contains i primary particles with mass m p and size L p. All differently sized flocs can aggregate, binary breakup into two equally sized flocs is used, and the floc's fractal dimension is d 0 = 2, independently of their size. The collision efficiency is kept constant, and the collision frequency derived by Saffman and Turner (J Fluid Mech 1:16-30, 1956) is used. For the breakup rate, the formulation by Winterwerp (J Hydraul Eng Res 36(3):309-326, 1998), which accounts for the porosity of flocs, is used. We show that the mean floc size computed with the PBE varies with the shear rate as the Kolmogorov microscale, as observed both in laboratory and in situ. Moreover, the equilibrium mean floc size varies linearly with a global parameter P which is proportional to the ratio between the rates of aggregation and breakup. The ratio between the parameters of aggregation and breakup can therefore be estimated analytically from the observed equilibrium floc size. The parameter for aggregation can be calibrated from the temporal evolution of the mean floc size. We calibrate the PBE model using mixing jar flocculation experiments, see Mietta et al. (J Colloid Interface Sci 336(1):134-141, 2009a, Ocean Dyn 59:751-763, 2009b) for details. We show that this model can reproduce the experimental data fairly accurately. The collision efficiency α and the ratio between parameters for aggregation and breakup α and E are shown to decrease linearly with increasing absolute value of the ζ-potential, both for mud and kaolinite suspensions. Suspensions at high pH and different dissolved salt type and concentration have been used. We show that the temporal evolution of the floc size distribution computed with this PBE is very similar to that computed with the PBE developed by Verney et al. (Cont Shelf Res, 2010) where classes are distributed
NASA Astrophysics Data System (ADS)
Han, Feng; Zheng, Yi
2016-02-01
While watershed water quality (WWQ) models have been widely used to support water quality management, their profound modeling uncertainty remains an unaddressed issue. Data assimilation via Bayesian calibration is a promising solution to the uncertainty, but has been rarely practiced for WWQ modeling. This study applied multiple-response Bayesian calibration (MRBC) to SWAT, a classic WWQ model, using the nitrate pollution in the Newport Bay Watershed (southern California, USA) as the study case. How typical input and model structure errors would impact modeling uncertainty, parameter identification and management decision-making was systematically investigated through both synthetic and real-situation modeling cases. The main study findings include: (1) with an efficient sampling scheme, MRBC is applicable to WWQ modeling in characterizing its parametric and predictive uncertainties; (2) incorporating hydrology responses, which are less susceptible to input and model structure errors than water quality responses, can improve the Bayesian calibration results and benefit potential modeling-based management decisions; and (3) the value of MRBC to modeling-based decision-making essentially depends on pollution severity, management objective and decision maker's risk tolerance.
NASA Astrophysics Data System (ADS)
Sueoka, Stacey
2016-05-01
The Daniel K Inouye Solar Telescope (DKIST) will have a suite of first-light polarimetric instrumentation requiring calibration of a complex off-axis optical path. The DKIST polarization calibration process requires modeling and fitting for several optical, thermal and mechanical effects. Three dimensional polarization ray trace codes (PolarisM) allow modeling of polarization errors inherent in assuming a linear retardation as a function of angle of incidence for our calibration retarders at Gregorian and Coudé foci. Stress induced retardation effects from substrate and coating absorption, mechanical mounting stresses, and inherent polishing uniformity tolerances introduce polarization effects at significant levels. These effects require careful characterization and modeling for mitigation during design, construction, calibration and science observations. Modeling efforts, amplitude estimates and mitigation efforts will be presented for the suite of DKIST calibration optics planned for first-light operations.
Automatic Multi-Scale Calibration Procedure for Nested Hydrological-Hydrogeological Regional Models
NASA Astrophysics Data System (ADS)
Labarthe, B.; Abasq, L.; Flipo, N.; de Fouquet, C. D.
2014-12-01
Large hydrosystem modelling and understanding is a complex process depending on regional and local processes. A nested interface concept has been implemented in the hydrosystem modelling platform for a large alluvial plain model (300 km2) part of a 11000 km2 multi-layer aquifer system, included in the Seine basin (65000 km2, France). The platform couples hydrological and hydrogeological processes through four spatially distributed modules (Mass balance, Unsaturated Zone, River and Groundwater). An automatic multi-scale calibration procedure is proposed. Using different data sets from regional scale (117 gauging stations and 183 piezometers over the 65000 km2) to the intermediate scale(dense past piezometric snapshot), it permits the calibration and homogenization of model parameters over scales.The stepwise procedure starts with the optimisation of the water mass balance parameters at regional scale using a conceptual 7 parameters bucket model coupled with the inverse modelling tool PEST. The multi-objective function is derived from river discharges and their de-composition by hydrograph separation. The separation is performed at each gauging station using an automatic procedure based one Chapman filter. Then, the model is run at the regional scale to provide recharge estimate and regional fluxes to the groundwater local model. Another inversion method is then used to determine the local hydrodynamic parameters. This procedure used an initial kriged transmissivity field which is successively updated until the simulated hydraulic head distribution equals a reference one obtained by krigging. Then, the local parameters are upscaled to the regional model by renormalisation procedure.This multi-scale automatic calibration procedure enhances both the local and regional processes representation. Indeed, it permits a better description of local heterogeneities and of the associated processes which are transposed into the regional model, improving the overall performances
Whether generic model works for rapid ERP-based BCI calibration
Jin, Jing; Sellers, Eric W.; Zhang, Yu; Daly, Ian; Wang, Xingyu; Cichocki, Andrzej
2013-01-01
Event-related potential (ERP)-based brain–computer interfacing (BCI) is an effective method of basic communication. However, collecting calibration data, and classifier training, detracts from the amount of time allocated for online communication. Decreasing calibration time can reduce preparation time thereby allowing for additional online use, potentially lower fatigue, and improved performance. Previous studies, using generic online training models which avoid offline calibration, afford more time for online spelling. Such studies have not examined the direct effects of the model on individual performance, and the training sequence exceeded the time reported here. The first goal of this work is to survey whether one generic model works for all subjects and the second goal is to show the performance of a generic model using an online training strategy when participants could use the generic model. The generic model was derived from 10 participant’s data. An additional 11 participants were recruited for the current study. Seven of the participants were able to use the generic model during online training. Moreover, the generic model performed as well as models obtained from participant specific offline data with a mean training time of less than 2 min. However, four of the participants could not use this generic model, which shows that one generic mode is not generic for all subjects. More research on ERPs of subjects with different characteristics should be done, which would be helpful to build generic models for subject groups. This result shows a potential valuable direction for improving the BCI system. PMID:23032116
NASA Astrophysics Data System (ADS)
Xu, Tianfang; Valocchi, Albert J.
2015-11-01
Numerical groundwater flow and solute transport models are usually subject to model structural error due to simplification and/or misrepresentation of the real system, which raises questions regarding the suitability of conventional least squares regression-based (LSR) calibration. We present a new framework that explicitly describes the model structural error statistically in an inductive, data-driven way. We adopt a fully Bayesian approach that integrates Gaussian process error models into the calibration, prediction, and uncertainty analysis of groundwater flow models. We test the usefulness of the fully Bayesian approach with a synthetic case study of the impact of pumping on surface-ground water interaction. We illustrate through this example that the Bayesian parameter posterior distributions differ significantly from parameters estimated by conventional LSR, which does not account for model structural error. For the latter method, parameter compensation for model structural error leads to biased, overconfident prediction under changing pumping condition. In contrast, integrating Gaussian process error models significantly reduces predictive bias and leads to prediction intervals that are more consistent with validation data. Finally, we carry out a generalized LSR recalibration step to assimilate the Bayesian prediction while preserving mass conservation and other physical constraints, using a full error covariance matrix obtained from Bayesian results. It is found that the recalibrated model achieved lower predictive bias compared to the model calibrated using conventional LSR. The results highlight the importance of explicit treatment of model structural error especially in circumstances where subsequent decision-making and risk analysis require accurate prediction and uncertainty quantification.
Semi-automated calibration method for modelling of mountain permafrost evolution in Switzerland
NASA Astrophysics Data System (ADS)
Marmy, A.; Rajczak, J.; Delaloye, R.; Hilbich, C.; Hoelzle, M.; Kotlarski, S.; Lambiel, C.; Noetzli, J.; Phillips, M.; Salzmann, N.; Staub, B.; Hauck, C.
2015-09-01
Permafrost is a widespread phenomenon in the European Alps. Many important topics such as the future evolution of permafrost related to climate change and the detection of permafrost related to potential natural hazards sites are of major concern to our society. Numerical permafrost models are the only tools which facilitate the projection of the future evolution of permafrost. Due to the complexity of the processes involved and the heterogeneity of Alpine terrain, models must be carefully calibrated and results should be compared with observations at the site (borehole) scale. However, a large number of local point data are necessary to obtain a broad overview of the thermal evolution of mountain permafrost over a larger area, such as the Swiss Alps, and the site-specific model calibration of each point would be time-consuming. To face this issue, this paper presents a semi-automated calibration method using the Generalized Likelihood Uncertainty Estimation (GLUE) as implemented in a 1-D soil model (CoupModel) and applies it to six permafrost sites in the Swiss Alps prior to long-term permafrost evolution simulations. We show that this automated calibration method is able to accurately reproduce the main thermal condition characteristics with some limitations at sites with unique conditions such as 3-D air or water circulation, which have to be calibrated manually. The calibration obtained was used for RCM-based long-term simulations under the A1B climate scenario specifically downscaled at each borehole site. The projection shows general permafrost degradation with thawing at 10 m, even partially reaching 20 m depths until the end of the century, but with different timing among the sites. The degradation is more rapid at bedrock sites whereas ice-rich sites with a blocky surface cover showed a reduced sensitivity to climate change. The snow cover duration is expected to be reduced drastically (between -20 to -37 %) impacting the ground thermal regime. However
On Inertial Body Tracking in the Presence of Model Calibration Errors
Miezal, Markus; Taetz, Bertram; Bleser, Gabriele
2016-01-01
In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments—the IMU-to-segment calibrations, subsequently called I2S calibrations—to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and
Towards an effective calibration theory for a broadly applied land surface model (VIC)
NASA Astrophysics Data System (ADS)
Melsen, Lieke; Teuling, Adriaan; Torfs, Paul; Zappa, Massimiliano
2014-05-01
The Variable Infiltration Capacity (VIC, Liang et al., 1994) model has been used for a broad range of applications, in hydrology as well as in the fields of climate and global change. Despite the attention for the model and its output, calibration is often not performed. To improve the calibration procedures for VIC applied at grid resolutions varying from meso-scale catchments to the 1 km 'hyper'resolution now used in several global modeling studies, the parameters of the model are studied in more detail. An earlier sensitivity analysis study on a selection of parameters of the VIC model by Demaria et al (2007) showed that the model is not or hardly sensitive to many of its parameters. With improved sensitivity analysis methods and computational power, this study focuses on a broader spectrum of parameters and with state of the art methods: both the DELSA sensitivity analysis method (Rakovec et al., 2013) and the ABC-method (Vrugt et al., 2013) will be employed parallel to a single cell VIC model of the Rietholzbach in Switzerland (representative of the 1 km hyperresolution), and a single and multiple-cell VIC model of the meso-scale Thur basin in Switzerland. In the latter case, also routing plays an important role. With critically screening the parameters of the model, it is possible to define a frame work for calibration of the model at multiple scales. References Demaria, E., B. Nijssen, and T. Wagener (2007), Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model, J. Geophys. Res., 112, D11,113. Liang, X., D. Lettenmaier, E. Wood, and S. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99 (D7),14,415-14,458. Rakovec, O., M. Hill, M. Clark, A. Weerts, A. Teuling, and R. Uijlenhoet (2013), A new computationally frugal method for sensitivity analysis of environmental models, Water Resour. Res., in press Vrugt, J.A. and M
NASA Astrophysics Data System (ADS)
Sun, Wenbo; Lukashin, Constantine; Baize, Rosemary R.; Goldin, Daniel
2015-01-01
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a high-priority NASA Decadal Survey mission recommended by the National Research Council in 2007. The CLARREO objectives are to conduct highly accurate decadal climate-change observations and to provide an on-orbit inter-calibration standard for relevant Earth observing sensors. The inter-calibration approach is based on providing highly accurate spectral reflectance measurements from the CLARREO Reflected Solar Spectrometer (RSS) as the reference for existing sensors and to monitor and characterize their response function parameters including gain, offset, non-linearity, optics spectral response, and sensitivity to polarization of light. The inter-calibration of instrument sensitivity to polarization requires on-orbit knowledge of polarization state of light as function of observed scene type and viewing geometry. In this study, we validate polarization parameters calculated with the adding-doubling radiative transfer model (ADRTM) for developing the Polarization Distribution Models (PDMs). These model results are compared with observations from the Polarization and Anisotropy of Reflectances for Atmospheric Science instrument coupled with Observations from a Lidar (PARASOL) data. Good agreement between model results and satellite data is shown for both liquid water clouds and ice clouds. Difference between model results and satellite measurements for clear-sky oceans is explained as due to the presence of undetected clouds, that are super-thin or whose spatial and temporal mean optical depth is small, in the PARASOL clear-sky scenes. These results demonstrate that the ADRTM provides a reliable approach for building spectral PDMs for the inter-calibration applications of the CLARREO mission.
Finsterle, S.; Kowalsky, M.B.
2010-10-15
We propose a modification to the Levenberg-Marquardt minimization algorithm for a more robust and more efficient calibration of highly parameterized, strongly nonlinear models of multiphase flow through porous media. The new method combines the advantages of truncated singular value decomposition with those of the classical Levenberg-Marquardt algorithm, thus enabling a more robust solution of underdetermined inverse problems with complex relations between the parameters to be estimated and the observable state variables used for calibration. The truncation limit separating the solution space from the calibration null space is re-evaluated during the iterative calibration process. In between these re-evaluations, fewer forward simulations are required, compared to the standard approach, to calculate the approximate sensitivity matrix. Truncated singular values are used to calculate the Levenberg-Marquardt parameter updates, ensuring that safe small steps along the steepest-descent direction are taken for highly correlated parameters of low sensitivity, whereas efficient quasi-Gauss-Newton steps are taken for independent parameters with high impact. The performance of the proposed scheme is demonstrated for a synthetic data set representing infiltration into a partially saturated, heterogeneous soil, where hydrogeological, petrophysical, and geostatistical parameters are estimated based on the joint inversion of hydrological and geophysical data.
Multimethod evolutionary search for the regional calibration of rainfall-runoff models
NASA Astrophysics Data System (ADS)
Lombardi, Laura; Castiglioni, Simone; Toth, Elena; Castellarin, Attilio; Montanari, Alberto
2010-05-01
The study focuses on regional calibration for a generic rainfall-runoff model. The maximum likelihood function in the spectral domain proposed by Whittle is approximated in the time domain by maximising the simultaneous fit (through a multiobjective optimisation) of selected statistics of streamflow values, with the aim to propose a calibration procedure that can be applied at regional scale. The method may in fact be applied without the availability of actual time series of streamflow observations, since it is based exclusively on the selected statistics, that are here obtained on the basis of the dominant climate and catchment characteristics, through regional regression relationships. The multiobjective optimisation was carried out by using a recently proposed multimethod evolutionary search algorithm (AMALGAM, Vrugt and Robinson, 2007), that runs simultaneously, for population evolution, a set of different optimisation methods (namely NSGA-II, Differential Evolution, Adaptive Metropolis Search and Particle Swarm Optimisation), resulting in a combination of the respective strengths by adaptively updating the weights of these individual methods based on their reproductive success. This ensures a fast, reliable and computationally efficient solution to multiobjective optimisation problems. The proposed technique is applied to the case study of some catchments located in central Italy, which are treated as ungauged and are located in a region where detailed hydrological and geomorfoclimatic information is available. The results obtained with the regional calibration are compared with those provided by a classical least squares calibration in the time domain. The outcomes of the analysis confirm the potentialities of the proposed methodology.
NASA Astrophysics Data System (ADS)
Pasquale, N.; Perona, P.; Wombacher, A.; Burlando, P.
2014-01-01
This paper presents a remote sensing technique for calibrating hydrodynamics models, which is particularly useful when access to the riverbed for a direct measure of flow variables may be precluded. The proposed technique uses terrestrial photography and automatic pattern recognition analysis together with digital mapping and does not require image ortho-rectification. Compared to others invasive or remote sensing calibration, this method is relatively cheap and can be repeated over time, thus allowing calibration over multiple flow rates . We applied this technique to a sequence of high-resolution photographs of the restored reach of the river Thur, near Niederneunforn, Switzerland. In order to calibrate the roughness coefficient, the actual exposed areas of the gravel bar are first computed using the pattern recognition algorithm, and then compared to the ones obtained from numerical hydrodynamic simulations over the entire range of observed flows. Analysis of the minimum error between the observed and the computed exposed areas show that the optimum roughness coefficient is discharge dependent; particularly it decreases as flow rate increases, as expected. The study is completed with an analysis of the root mean square error (RMSE) and mean absolute error (MEA), which allow finding the best fitting roughness coefficient that can be used over a wide range of flow rates, including large floods.
Hydrologic Modeling in the Kenai River Watershed using Event Based Calibration
NASA Astrophysics Data System (ADS)
Wells, B.; Toniolo, H. A.; Stuefer, S. L.
2015-12-01
Understanding hydrologic changes is key for preparing for possible future scenarios. On the Kenai Peninsula in Alaska the yearly salmon runs provide a valuable stimulus to the economy. It is the focus of a large commercial fishing fleet, but also a prime tourist attraction. Modeling of anadromous waters provides a tool that assists in the prediction of future salmon run size. Beaver Creek, in Kenai, Alaska, is a lowlands stream that has been modeled using the Army Corps of Engineers event based modeling package HEC-HMS. With the use of historic precipitation and discharge data, the model was calibrated to observed discharge values. The hydrologic parameters were measured in the field or calculated, while soil parameters were estimated and adjusted during the calibration. With the calibrated parameter for HEC-HMS, discharge estimates can be used by other researches studying the area and help guide communities and officials to make better-educated decisions regarding the changing hydrology in the area and the tied economic drivers.
Calibration and analysis of genome-based models for microbial ecology
Louca, Stilianos; Doebeli, Michael
2015-01-01
Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology. DOI: http://dx.doi.org/10.7554/eLife.08208.001 PMID:26473972
BIOPLUME III is a 2D, finite difference model for simulating the natural attenuation of organic contaminants in groundwater due to the processes of advection, dispersion, sorption, and biodegradation. Biotransformation processes are potentially important in the restoration of aq...
Using Gaussian Processes for the Calibration and Exploration of Complex Computer Models
NASA Astrophysics Data System (ADS)
Coleman-Smith, C. E.
Cutting edge research problems require the use of complicated and computationally expensive computer models. I will present a practical overview of the design and analysis of computer experiments in high energy nuclear and astro phsyics. The aim of these experiments is to infer credible ranges for certain fundamental parameters of the underlying physical processes through the analysis of model output and experimental data. To be truly useful computer models must be calibrated against experimental data. Gaining an understanding of the response of expensive models across the full range of inputs can be a slow and painful process. Gaussian Process emulators can be an efficient and informative surrogate for expensive computer models and prove to be an ideal mechanism for exploring the response of these models to variations in their inputs. A sensitivity analysis can be performed on these model emulators to characterize and quantify the relationship between model input parameters and predicted observable properties. The result of this analysis provides the user with information about which parameters are most important and most likely to affect the prediction of a given observable. Sensitivity analysis allow us to identify what model parameters can be most efficiently constrained by the given observational data set. In this thesis I describe a range of techniques for the calibration and exploration of the complex and expensive computer models so common in modern physics research. These statistical methods are illustrated with examples drawn from the fields of high energy nuclear physics and galaxy formation.
NASA Astrophysics Data System (ADS)
Seibert, Jan
2015-04-01
Simple runoff models with a low number of model parameters are often able to simulated catchment runoff reasonably well, but these models usually rely on model calibration, which makes their use in ungauged basins challenging. Here a dataset of 600+ gauged basins in the US was used to study how good model performances could be achieved when instead of stream flow data only stream level data would be available. The latter obviously is easier to observe and in practice several approaches could be used for such stream level observations: water level loggers have become less expensive and easier to install; stream levels will in the near future be increasingly available from satellite remote sensing resulting in evenly space time series; community-based approaches (e.g., crowdhydrology.org), finally, can offer level observations at irregular time intervals. Here we present a study where a runoff model (the HBV model) was calibrated for the 600+ gauged basins. Pretending that only stream level observations at different time intervals, representing the temporal resolution of the different observation approaches mentioned before, were available, the model was calibrated based on these data subsets. Afterwards the simulations were evaluated on the full observed stream flow record. The results indicate that stream level data alone already can provide surprisingly good model simulation results in humid catchments, whereas in arid catchments some form of quantitative information (stream flow observation or regional average value) is needed to obtain good results. These results are encouraging for hydrological observations in data scarce regions as level observations are much easier to obtain than stream flow observations. Based on runoff modeling it might be possible to derive stream flow series from level observations using loggers, satellites or community-based approaches. The approach presented here also allows comparing the value of different types of observations
Calibration of the k- ɛ model constants for use in CFD applications
NASA Astrophysics Data System (ADS)
Glover, Nina; Guillias, Serge; Malki-Epshtein, Liora
2011-11-01
The k- ɛ turbulence model is a popular choice in CFD modelling due to its robust nature and the fact that it has been well validated. However it has been noted in previous research that the k- ɛ model has problems predicting flow separation as well as unconfined and transient flows. The model contains five empirical model constants whose values were found through data fitting for a wide range of flows (Launder 1972) but ad-hoc adjustments are often made to these values depending on the situation being modeled. Here we use the example of flow within a regular street canyon to perform a Bayesian calibration of the model constants against wind tunnel data. This allows us to assess the sensitivity of the CFD model to changes in these constants, find the most suitable values for the constants as well as quantifying the uncertainty related to the constants and the CFD model as a whole.
NASA Technical Reports Server (NTRS)
Annett, Martin S.; Horta, Lucas G.; Jackson, Karen E.; Polanco, Michael A.; Littell, Justin D.
2012-01-01
Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber (DEA) under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. The presence of this energy absorbing device reduced the peak impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to a system-integrated finite element model of the test article developed in parallel with the test program. In preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests were conducted to evaluate the impact performances of various components and subsystems, including new crush tubes and the DEA blocks. Parameters defined for the system-integrated finite element model were determined from these tests. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the full-scale crash test without the DEA. This combination of heuristic and quantitative methods identified modeling deficiencies, evaluated parameter importance, and proposed required model changes. The multidimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were
Analytical model for calibrating laser intensity in strong-field-ionization experiments
NASA Astrophysics Data System (ADS)
Zhao, Song-Feng; Le, Anh-Thu; Jin, Cheng; Wang, Xu; Lin, C. D.
2016-02-01
The interaction of an intense laser pulse with atoms and molecules depends extremely nonlinearly on the laser intensity. Yet experimentally there still exists no simple reliable methods for determining the peak laser intensity within the focused volume. Here we present a simple method, based on an improved Perelomov-Popov-Terent'ev model, that would allow the calibration of laser intensities from the measured ionization signals of atoms or molecules. The model is first examined by comparing ionization probabilities (or signals) of atoms and several simple diatomic molecules with those from solving the time-dependent Schrödinger equation. We then show the possibility of using this method to calibrate laser intensities for atoms, diatomic molecules as well as large polyatomic molecules, for laser intensities from the multiphoton ionization to tunneling ionization regimes.
Michalas, L. Marcelli, R.; Wang, F.; Brillard, C.; Theron, D.
2015-11-30
This paper presents the full modeling and a methodology for de-embedding the interferometric scanning microwave microscopy measurements by means of dopant profile calibration. A Si calibration sample with different boron-doping level areas is used to that end. The analysis of the experimentally obtained S{sub 11} amplitudes based on the proposed model confirms the validity of the methodology. As a specific finding, changes in the tip radius between new and used tips have been clearly identified, leading to values for the effective tip radius in the range of 45 nm to 85 nm, respectively. Experimental results are also discussed in terms of the effective area concept, taking into consideration details related to the nature of tip-to-sample interaction.
Cole, Charles R.; Bergeron, Marcel P.; Wurstner, Signe K.; Thorne, Paul D.; Orr, Samuel; Mckinley, Mathew I.
2001-05-31
This report describes a new initiative to strengthen the technical defensibility of predictions made with the Hanford site-wide groundwater flow and transport model. The focus is on characterizing major uncertainties in the current model. PNNL will develop and implement a calibration approach and methodology that can be used to evaluate alternative conceptual models of the Hanford aquifer system. The calibration process will involve a three-dimensional transient inverse calibration of each numerical model to historical observations of hydraulic and water quality impacts to the unconfined aquifer system from Hanford operations since the mid-1940s.
Local influence in comparative calibration models under elliptical t-distributions.
Galea, Manuel; Bolfarine, Heleno; Vilca, Filidor
2005-10-01
In this paper we consider applications of local influence (Cook, 1986) to evaluate small perturbations in the model or data set in the context of structural comparative calibration (Bolfarine and Galea, 1995) assuming that the measurements obtained follow a multivariate elliptical distribution. Different perturbation schemes are investigated and an application is considered to a real data set, using the elliptical t-distribution. PMID:16385910
Calibration of mass transfer-based models to predict reference crop evapotranspiration
NASA Astrophysics Data System (ADS)
Valipour, Mohammad
2015-03-01
The present study aims to compare mass transfer-based models to determine the best model under different weather conditions. The results showed that the Penman model estimates reference crop evapotranspiration better than other models in most provinces of Iran (15 provinces). However, the values of R 2 were less than 0.90 for 24 provinces of Iran. Therefore, the models were calibrated, and precision of estimation was increased (the values of R 2 were less than 0.90 for only ten provinces in the modified models). The mass transfer-based models estimated reference crop evapotranspiration in the northern (near the Caspian Sea) and southern (near the Persian Gulf) Iran (annual relative humidity more than 65 %) better than other provinces. The best values of R 2 were 0.96 and 0.98 for the Trabert and Rohwer models in Ardabil (AR) and Mazandaran (MZ) provinces before and after calibration, respectively. Finally, a list of the best performances of each model was presented to use other regions and next studies according to values of mean, maximum, and minimum temperature, relative humidity, and wind speed. The best weather conditions to use mass transfer-based equations are 8-18 °C (with the exception of Ivanov), <25.5 °C, <15 °C, >55 % for mean, maximum, and minimum temperature, and relative humidity, respectively.
Technology Transfer Automated Retrieval System (TEKTRAN)
Robust calibration models were developed to determine protein and amylose contents in rice flour by NIR reflectance spectroscopy. Calibration sample set (n=218) were combined from sample years 1996 (n=90) and 1999 (n=128) to provide a wide range of constituents. Savitzky-Golay method of polynomial c...
A Bayesian, spatially-varying calibration model for the TEX86 proxy
NASA Astrophysics Data System (ADS)
Tierney, Jessica E.; Tingley, Martin P.
2014-02-01
TEX86 is an important proxy for constraining ocean temperatures in the Earth's past. Current calibrations, however, feature structured residuals indicative of a spatially-varying relationship between TEX86 and sea-surface temperatures (SSTs). Here we develop and apply a Bayesian regression approach to the TEX86-SST calibration that explicitly allows for model parameters to smoothly vary as a function of space, and considers uncertainties in the modern SSTs as well as in the TEX86-SST relationship. The spatially-varying model leads to larger uncertainties at locations that are data-poor, while Bayesian inference naturally propagates calibration uncertainty into the uncertainty in the predictions. Applications to both Quaternary and Eocene TEX86 data demonstrate that our approach produces reasonable results, and improves upon previous methods by allowing for probabilistic assessments of past temperatures. The scientific understanding of TEX86 remains imperfect, and the model presented here allows for predictions that implicitly account for the effects of environmental factors other than SSTs that lead to a spatially non-stationary TEX86-SST relationship.
Li, Rui; Ye, Hongfei; Zhang, Weisheng; Ma, Guojun; Su, Yewang
2015-01-01
Spring constant calibration of the atomic force microscope (AFM) cantilever is of fundamental importance for quantifying the force between the AFM cantilever tip and the sample. The calibration within the framework of thin plate theory undoubtedly has a higher accuracy and broader scope than that within the well-established beam theory. However, thin plate theory-based accurate analytic determination of the constant has been perceived as an extremely difficult issue. In this paper, we implement the thin plate theory-based analytic modeling for the static behavior of rectangular AFM cantilevers, which reveals that the three-dimensional effect and Poisson effect play important roles in accurate determination of the spring constants. A quantitative scaling law is found that the normalized spring constant depends only on the Poisson’s ratio, normalized dimension and normalized load coordinate. Both the literature and our refined finite element model validate the present results. The developed model is expected to serve as the benchmark for accurate calibration of rectangular AFM cantilevers. PMID:26510769
Extremely Low-Stress Triaxiality Tests in Calibration of Fracture Models in Metal-Cutting Simulation
NASA Astrophysics Data System (ADS)
Šebek, František; Kubík, Petr; Petruška, Jindřich; Hůlka, Jiří
2016-04-01
The cutting process is now combined with machining, milling, or drilling as one of the widespread manufacturing operations. It is used across various fields of engineering. From an economical point of view, it is desirable to maintain the process in the most effective way in terms of the fracture surface quality or minimizing the burr. It is not possible to manage this experimentally in mass production. Therefore, it is convenient to use numerical computation. To include the crack initiation and propagation in the computations, it is necessary to implement a suitable ductile fracture criterion. Uncoupled ductile fracture models need to be calibrated first from fracture tests when the test selection is crucial. In the present article, there were selected widespread uncoupled ductile fracture models calibrated with, among others, an extremely low-stress triaxiality test realized through the compression of a cylinder with a specific recess. The whole experimental program together with the cutting process experiment were carried out on AISI 1045 carbon steel. After the fracture models were calibrated and the cutting process was simulated with their use, fracture surfaces and force responses from computations were compared with those experimentally obtained and concluding remarks were made.
Li, Rui; Ye, Hongfei; Zhang, Weisheng; Ma, Guojun; Su, Yewang
2015-01-01
Spring constant calibration of the atomic force microscope (AFM) cantilever is of fundamental importance for quantifying the force between the AFM cantilever tip and the sample. The calibration within the framework of thin plate theory undoubtedly has a higher accuracy and broader scope than that within the well-established beam theory. However, thin plate theory-based accurate analytic determination of the constant has been perceived as an extremely difficult issue. In this paper, we implement the thin plate theory-based analytic modeling for the static behavior of rectangular AFM cantilevers, which reveals that the three-dimensional effect and Poisson effect play important roles in accurate determination of the spring constants. A quantitative scaling law is found that the normalized spring constant depends only on the Poisson's ratio, normalized dimension and normalized load coordinate. Both the literature and our refined finite element model validate the present results. The developed model is expected to serve as the benchmark for accurate calibration of rectangular AFM cantilevers. PMID:26510769
NASA Astrophysics Data System (ADS)
Li, Rui; Ye, Hongfei; Zhang, Weisheng; Ma, Guojun; Su, Yewang
2015-10-01
Spring constant calibration of the atomic force microscope (AFM) cantilever is of fundamental importance for quantifying the force between the AFM cantilever tip and the sample. The calibration within the framework of thin plate theory undoubtedly has a higher accuracy and broader scope than that within the well-established beam theory. However, thin plate theory-based accurate analytic determination of the constant has been perceived as an extremely difficult issue. In this paper, we implement the thin plate theory-based analytic modeling for the static behavior of rectangular AFM cantilevers, which reveals that the three-dimensional effect and Poisson effect play important roles in accurate determination of the spring constants. A quantitative scaling law is found that the normalized spring constant depends only on the Poisson’s ratio, normalized dimension and normalized load coordinate. Both the literature and our refined finite element model validate the present results. The developed model is expected to serve as the benchmark for accurate calibration of rectangular AFM cantilevers.
A test of the facultative calibration/reactive heritability model of extraversion
Haysom, Hannah J.; Mitchem, Dorian G.; Lee, Anthony J.; Wright, Margaret J.; Martin, Nicholas G.; Keller, Matthew C.; Zietsch, Brendan P.
2015-01-01
A model proposed by Lukaszewski and Roney (2011) suggests that each individual’s level of extraversion is calibrated to other traits that predict the success of an extraverted behavioural strategy. Under ‘facultative calibration’, extraversion is not directly heritable, but rather exhibits heritability through its calibration to directly heritable traits (“reactive heritability”). The current study uses biometrical modelling of 1659 identical and non-identical twins and their siblings to assess whether the genetic variation in extraversion is calibrated to variation in facial attractiveness, intelligence, height in men and body mass index (BMI) in women. Extraversion was significantly positively correlated with facial attractiveness in both males (r=.11) and females (r=.18), but correlations between extraversion and the other variables were not consistent with predictions. Further, twin modelling revealed that the genetic variation in facial attractiveness did not account for a substantial proportion of the variation in extraversion in either males (2.4%) or females (0.5%). PMID:26880866
Seedling recruitment in forests: Calibrating models to predict patterns of tree seedling dispersion
Ribbens, E.; Silander, J.A. Jr.; Pacala, S.W. )
1994-09-01
Recruitment, the addition of new individuals into a community, is an important factor that can substantially affect community composition and dynamics. We present a method for calibrating spatial models of plant recruitment that does not require identifying the specific parent of each recruitment. This method calibrates seedling recruitment functions by comparing tree seedling distributions with adult distributions via a maximum likelihood analysis. The models obtained from this method can then be used to predict the spatial distributions of seedlings from adult distributions. We calibrated recruitment functions for 10 tree species characteristic of transition oak-northern hardwood forests. Significant differences were found in recruitment abundances and spatial distributions. Predicted seedling recruitment limitation for test stands varied substantially between species, with little recruitment limitation for some species and strong recruitment limitation for others. Recruitment was limited due to low overall recruit production or to restricted recruit dispersion. When these seedling recruitment parameters were incorporated into a spatial, individual-based model of forest dynamics, called SOR-TIE, alterations of recruitment parameters produced substantial changes in species abundance, providing additional support for the potential importance of seedling recruitment processes in community structure and dynamics. 45 refs., 9 figs., 3 tabs.
NASA Astrophysics Data System (ADS)
Soltanzadeh, I.; Azadi, M.; Vakili, G. A.
2011-07-01
Using Bayesian Model Averaging (BMA), an attempt was made to obtain calibrated probabilistic numerical forecasts of 2-m temperature over Iran. The ensemble employs three limited area models (WRF, MM5 and HRM), with WRF used with five different configurations. Initial and boundary conditions for MM5 and WRF are obtained from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and for HRM the initial and boundary conditions come from analysis of Global Model Europe (GME) of the German Weather Service. The resulting ensemble of seven members was run for a period of 6 months (from December 2008 to May 2009) over Iran. The 48-h raw ensemble outputs were calibrated using BMA technique for 120 days using a 40 days training sample of forecasts and relative verification data. The calibrated probabilistic forecasts were assessed using rank histogram and attribute diagrams. Results showed that application of BMA improved the reliability of the raw ensemble. Using the weighted ensemble mean forecast as a deterministic forecast it was found that the deterministic-style BMA forecasts performed usually better than the best member's deterministic forecast.
Calibration of the Multi-Factor HJM Model for Energy Market
NASA Astrophysics Data System (ADS)
Broszkiewicz-Suwaj, E.; Weron, A.
2006-05-01
The purpose of this paper is to show that using the toolkit of interest rate theory, already well known in financial engineering as the HJM model [D. Heath, R. Jarrow, A. Morton, {ITALIC Econometrica} 60, 77 (1992)], it is possible to derive explicite option pricing formula and calibrate the theoretical model to the empirical electricity market. The analysis is illustrated by numerical cases from the European Energy Exchange (EEX) in Leipzig. The multi-factor {ITALIC versus} one-factor HJM models are compared.
Modeling and calibration of pointing errors with alt-az telescope
NASA Astrophysics Data System (ADS)
Huang, Long; Ma, Wenli; Huang, Jinlong
2016-08-01
This paper presents a new model for improving the pointing accuracy of a telescope. The Denavit-Hartenberg (D-H) convention was used to perform an error analysis of the telescope's kinematics. A kinematic model was used to relate pointing errors to mechanical errors and the parameters of the kinematic model were estimated with a statistical model fit using data from two large astronomical telescopes. The model illustrates the geometric errors caused by imprecision in manufacturing and assembly processes and their effects on the pointing accuracy of the telescope. A kinematic model relates pointing error to axis position when certain geometric errors are assumed to be present in a telescope. In the parameter estimation portion, the semi-parametric regression model was introduced to compensate for remaining nonlinear errors. The experimental results indicate that the proposed semi-parametric regression model eliminates both geometric and nonlinear errors, and that the telescope's pointing accuracy significantly improves after this calibration.
NASA Astrophysics Data System (ADS)
Minunno, F.; Peltoniemi, M.; Launiainen, S.; Aurela, M.; Lindroth, A.; Lohila, A.; Mammarella, I.; Minkkinen, K.; Mäkelä, A.
2015-07-01
The problem of model complexity has been lively debated in environmental sciences as well as in the forest modelling community. Simple models are less input demanding and their calibration involves a lower number of parameters, but they might be suitable only at local scale. In this work we calibrated a simplified ecosystem process model (PRELES) to data from multiple sites and we tested if PRELES can be used at regional scale to estimate the carbon and water fluxes of Boreal conifer forests. We compared a multi-site (M-S) with site-specific (S-S) calibrations. Model calibrations and evaluations were carried out by the means of the Bayesian method; Bayesian calibration (BC) and Bayesian model comparison (BMC) were used to quantify the uncertainty in model parameters and model structure. To evaluate model performances BMC results were combined with more classical analysis of model-data mismatch (M-DM). Evapotranspiration (ET) and gross primary production (GPP) measurements collected in 10 sites of Finland and Sweden were used in the study. Calibration results showed that similar estimates were obtained for the parameters at which model outputs are most sensitive. No significant differences were encountered in the predictions of the multi-site and site-specific versions of PRELES with exception of a site with agricultural history (Alkkia). Although PRELES predicted GPP better than evapotranspiration, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. Our analyses underlined also the importance of using long and carefully collected flux datasets in model calibration. In fact, even a single site can provide model calibrations that can be applied at a wider spatial scale, since it covers a wide range of variability in climatic conditions.
NASA Astrophysics Data System (ADS)
Tolley, D. G.; Foglia, L.; Neumann, J.; Harter, T.
2014-12-01
Late summer streamflow for the Scott River in northern California has decreased approximately 50% since the mid 1960's, resulting in increased water temperatures and disconnection of certain portions of the stream which negatively impacts aquatic habitat of fish species such as coho and fall-run Chinook salmon. In collaboration with local stakeholders, the Scott Valley Integrated Hydrologic Model has been developed, which combines a water budget model and a groundwater-surface water model (MODLFOW) of the 200 km2 basin. The goal of the integrated model is to better understand the hydrologic system of the valley and explore effects of different groundwater management scenarios on late summer streamflow. The groundwater model has a quarter-hectare resolution with aggregated monthly stress periods over a 21 year period (1990-2011). The Scott River is represented using either the river (RIV) or streamflow routing (SFR) package. UCODE was used for sensitivity analysis and calibration using head observations for 52 wells in the basin and gain/loss observations for two sections of the river. Of 32 model parameters (hydraulic conductivity, specific storage, riverbed conductance and mountain recharge), 13 were found significantly sensitive to observations. Results from the calibration show excellent agreement between modeled and observed heads and to seasonal and interannual variations in streamflow. The calibrated model was used to evaluate several management scenarios: 1) alternative water budget which takes into account measured irrigation rates in the valley, 2) in-lieu recharge where surface-water instead of groundwater is used to irrigate fields near the river while streamflow is sufficiently high, and 3) managed recharge on agricultural fields in gulches on the eastern side of the valley in the winter months. Preliminary results indicate that alternative water management scenarios (in-lieu and managed recharge) significantly increase late summer streamflow by keeping
Cai, Longyan; He, Hong S.; Wu, Zhiwei; Lewis, Benard L.; Liang, Yu
2014-01-01
Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management. PMID:24714164
Cai, Longyan; He, Hong S; Wu, Zhiwei; Lewis, Benard L; Liang, Yu
2014-01-01
Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management. PMID:24714164
NASA Astrophysics Data System (ADS)
Xu, T.; Valocchi, A. J.
2014-12-01
Effective water resource management typically relies on numerical models to analyse groundwater flow and solute transport processes. These models are usually subject to model structure error due to simplification and/or misrepresentation of the real system. As a result, the model outputs may systematically deviate from measurements, thus violating a key assumption for traditional regression-based calibration and uncertainty analysis. On the other hand, model structure error induced bias can be described statistically in an inductive, data-driven way based on historical model-to-measurement misfit. We adopt a fully Bayesian approach that integrates a Gaussian process error model to account for model structure error to the calibration, prediction and uncertainty analysis of groundwater models. The posterior distributions of parameters of the groundwater model and the Gaussian process error model are jointly inferred using DREAM, an efficient Markov chain Monte Carlo sampler. We test the usefulness of the fully Bayesian approach towards a synthetic case study of surface-ground water interaction under changing pumping conditions. We first illustrate through this example that traditional least squares regression without accounting for model structure error yields biased parameter estimates due to parameter compensation as well as biased predictions. In contrast, the Bayesian approach gives less biased parameter estimates. Moreover, the integration of a Gaussian process error model significantly reduces predictive bias and leads to prediction intervals that are more consistent with observations. The results highlight the importance of explicit treatment of model structure error especially in circumstances where subsequent decision-making and risk analysis require accurate prediction and uncertainty quantification. In addition, the data-driven error modelling approach is capable of extracting more information from observation data than using a groundwater model alone.
Kenoyer, David A.; Anderson, Kurt S.; Myrabo, Leik N.
2008-04-28
A detailed description is provided of the flight dynamics model and development, as well as the procedures used and results obtained in the verification, validation, and calibration of a further refined, flight dynamics system model for a laser lightcraft. The full system model is composed of individual aerodynamic, engine, laser beam, variable vehicle inertial, and 6 DOF dynamics models which have been integrated to represent all major phenomena in a consistent framework. The resulting system level model and associated code was then validated and calibrated using experimental flight information from a 16 flight trajectory data base. This model and code are being developed for the purpose of providing a physics-based predictive tool, which may be used to evaluate the performance of proposed future lightcraft vehicle concepts, engine systems, beam shapes, and active control strategies, thereby aiding in the development of the next generation of laser propelled lightcraft. This paper describes the methods used for isolating the effects of individual component models (e.g. beam, engine, dynamics, etc.) so that the performance of each of these key components could be assessed and adjusted as necessary. As the individual component models were validated, a protocol was developed which permitted the investigators to focus on individual aspects of the system and thereby identify phenomena which explain system behavior, and account for observed deviations between portions of the simulation predictions from experimental flights. These protocols are provided herein, along with physics-based explanations for deviations observed.
A fully Bayesian method for jointly fitting instrumental calibration and X-ray spectral models
Xu, Jin; Yu, Yaming; Van Dyk, David A.; Kashyap, Vinay L.; Siemiginowska, Aneta; Drake, Jeremy; Ratzlaff, Pete; Connors, Alanna; Meng, Xiao-Li E-mail: yamingy@ics.uci.edu E-mail: vkashyap@cfa.harvard.edu E-mail: jdrake@cfa.harvard.edu E-mail: meng@stat.harvard.edu
2014-10-20
Owing to a lack of robust principled methods, systematic instrumental uncertainties have generally been ignored in astrophysical data analysis despite wide recognition of the importance of including them. Ignoring calibration uncertainty can cause bias in the estimation of source model parameters and can lead to underestimation of the variance of these estimates. We previously introduced a pragmatic Bayesian method to address this problem. The method is 'pragmatic' in that it introduced an ad hoc technique that simplified computation by neglecting the potential information in the data for narrowing the uncertainty for the calibration product. Following that work, we use a principal component analysis to efficiently represent the uncertainty of the effective area of an X-ray (or γ-ray) telescope. Here, however, we leverage this representation to enable a principled, fully Bayesian method that coherently accounts for the calibration uncertainty in high-energy spectral analysis. In this setting, the method is compared with standard analysis techniques and the pragmatic Bayesian method. The advantage of the fully Bayesian method is that it allows the data to provide information not only for estimation of the source parameters but also for the calibration product—here the effective area, conditional on the adopted spectral model. In this way, it can yield more accurate and efficient estimates of the source parameters along with valid estimates of their uncertainty. Provided that the source spectrum can be accurately described by a parameterized model, this method allows rigorous inference about the effective area by quantifying which possible curves are most consistent with the data.
Exploring calibration strategies of SEDD model in two olive orchard watersheds
NASA Astrophysics Data System (ADS)
Burguet Marimón, Maria; Taguas, Encarnación V.; Gómez, José A.
2016-04-01
To optimize soil conservation strategies in catchments, an accurate diagnosis of areas contributing to soil erosion using models such as SEDD (Ferro and Minacapilly, 1995) is required. In this study, different calibration strategies of the SEDD model were explored in two commercial olive microcatchments in Spain, Setenil (6.7 ha) and Conchuela (8 ha) monitored for 6 years. The main objectives were to calibrate the model to the study watersheds with different environmental characteristics, soil management ways, and runoff conditions, and to evaluate the temporal variability of the sediment delivery ratio (SDR) at the event and annual scales. The calibration used five different erosivity scenarios with different weights of precipitation components and concentrated flow. To optimize the calibration, biweekly and annual C-RUSLE values and the weight of the travel times of the different watershed morphological units were evaluated. The SEDD model was calibrated successfully in the Conchuela watershed, whereas poor adjustments were found for the Setenil watershed. In Conchuela, the best calibration scenarios were associated with concentrated flow, while the erosivity of Setenil was only rain-dependent. Biweekly C-RUSLE values provided suitable, consistent results in Conchuela where soil moisture over the year. In contrast, there were no appreciable improvements between annual and biweekly C-RUSLE values in Setenil, probably due to the narrower variation interval. The analysis of the SDR function justified the grouping of the different β values according to their sign (positive or negative) as a calibration strategy in Setenil. The medians of these groups of events allowed them to be adjusted (E = 0.7; RMSE = 6.4). In the Conchuela watershed, this variation in the model calibration produced only minor improvements to an adjustment which was already good. The sediment delivery ratios (SDR) in both watersheds indicate very dynamic sediment transport. The mean annual SDR
Monte Carlo modeling provides accurate calibration factors for radionuclide activity meters.
Zagni, F; Cicoria, G; Lucconi, G; Infantino, A; Lodi, F; Marengo, M
2014-12-01
Accurate determination of calibration factors for radionuclide activity meters is crucial for quantitative studies and in the optimization step of radiation protection, as these detectors are widespread in radiopharmacy and nuclear medicine facilities. In this work we developed the Monte Carlo model of a widely used activity meter, using the Geant4 simulation toolkit. More precisely the "PENELOPE" EM physics models were employed. The model was validated by means of several certified sources, traceable to primary activity standards, and other sources locally standardized with spectrometry measurements, plus other experimental tests. Great care was taken in order to accurately reproduce the geometrical details of the gas chamber and the activity sources, each of which is different in shape and enclosed in a unique container. Both relative calibration factors and ionization current obtained with simulations were compared against experimental measurements; further tests were carried out, such as the comparison of the relative response of the chamber for a source placed at different positions. The results showed a satisfactory level of accuracy in the energy range of interest, with the discrepancies lower than 4% for all the tested parameters. This shows that an accurate Monte Carlo modeling of this type of detector is feasible using the low-energy physics models embedded in Geant4. The obtained Monte Carlo model establishes a powerful tool for first instance determination of new calibration factors for non-standard radionuclides, for custom containers, when a reference source is not available. Moreover, the model provides an experimental setup for further research and optimization with regards to materials and geometrical details of the measuring setup, such as the ionization chamber itself or the containers configuration. PMID:25195174
Serrancolí, Gil; Kinney, Allison L; Fregly, Benjamin J; Font-Llagunes, Josep M
2016-08-01
Though walking impairments are prevalent in society, clinical treatments are often ineffective at restoring lost function. For this reason, researchers have begun to explore the use of patient-specific computational walking models to develop more effective treatments. However, the accuracy with which models can predict internal body forces in muscles and across joints depends on how well relevant model parameter values can be calibrated for the patient. This study investigated how knowledge of internal knee contact forces affects calibration of neuromusculoskeletal model parameter values and subsequent prediction of internal knee contact and leg muscle forces during walking. Model calibration was performed using a novel two-level optimization procedure applied to six normal walking trials from the Fourth Grand Challenge Competition to Predict In Vivo Knee Loads. The outer-level optimization adjusted time-invariant model parameter values to minimize passive muscle forces, reserve actuator moments, and model parameter value changes with (Approach A) and without (Approach B) tracking of experimental knee contact forces. Using the current guess for model parameter values but no knee contact force information, the inner-level optimization predicted time-varying muscle activations that were close to experimental muscle synergy patterns and consistent with the experimental inverse dynamic loads (both approaches). For all the six gait trials, Approach A predicted knee contact forces with high accuracy for both compartments (average correlation coefficient r = 0.99 and root mean square error (RMSE) = 52.6 N medial; average r = 0.95 and RMSE = 56.6 N lateral). In contrast, Approach B overpredicted contact force magnitude for both compartments (average RMSE = 323 N medial and 348 N lateral) and poorly matched contact force shape for the lateral compartment (average r = 0.90 medial and -0.10 lateral). Approach B had statistically higher lateral
NASA Technical Reports Server (NTRS)
Lerch, F. J.; Nerem, R. S.; Chinn, D. S.; Chan, J. C.; Patel, G. B.; Klosko, S. M.
1993-01-01
A new method has been developed to provide a direct test of the error calibrations of gravity models based on actual satellite observations. The basic approach projects the error estimates of the gravity model parameters onto satellite observations, and the results of these projections are then compared with data residual computed from the orbital fits. To allow specific testing of the gravity error calibrations, subset solutions are computed based on the data set and data weighting of the gravity model. The approach is demonstrated using GEM-T3 to show that the gravity error estimates are well calibrated and that reliable predictions of orbit accuracies can be achieved for independent orbits.
Calibration of complex models through Bayesian evidence synthesis: a demonstration and tutorial.
Jackson, Christopher H; Jit, Mark; Sharples, Linda D; De Angelis, Daniela
2015-02-01
Decision-analytic models must often be informed using data that are only indirectly related to the main model parameters. The authors outline how to implement a Bayesian synthesis of diverse sources of evidence to calibrate the parameters of a complex model. A graphical model is built to represent how observed data are generated from statistical models with unknown parameters and how those parameters are related to quantities of interest for decision making. This forms the basis of an algorithm to estimate a posterior probability distribution, which represents the updated state of evidence for all unknowns given all data and prior beliefs. This process calibrates the quantities of interest against data and, at the same time, propagates all parameter uncertainties to the results used for decision making. To illustrate these methods, the authors demonstrate how a previously developed Markov model for the progression of human papillomavirus (HPV-16) infection was rebuilt in a Bayesian framework. Transition probabilities between states of disease severity are inferred indirectly from cross-sectional observations of prevalence of HPV-16 and HPV-16-related disease by age, cervical cancer incidence, and other published information. Previously, a discrete collection of plausible scenarios was identified but with no further indication of which of these are more plausible. Instead, the authors derive a Bayesian posterior distribution, in which scenarios are implicitly weighted according to how well they are supported by the data. In particular, we emphasize the appropriate choice of prior distributions and checking and comparison of fitted models. PMID:23886677
NASA Astrophysics Data System (ADS)
Pappenberger, F.; Beven, K. J.; Frodsham, K.; Matgen, P.
2005-12-01
Flood inundation models play an increasingly important role in assessing flood risk. The growth of 2D inundation models that are intimately related to raster maps of floodplains is occurring at the same time as an increase in the availability of 2D remote data (e.g. SAR images and aerial photographs), against which model performancee can be evaluated. This requires new techniques to be explored in order to evaluate model performance in two dimensional space. In this paper we present a fuzzified pattern matching algorithm which compares favorably to a set of traditional measures. However, we further argue that model calibration has to go beyond the comparison of physical properties and should demonstrate how a weighting towards consequences, such as loss of property, can enhance model focus and prediction. Indeed, it will be necessary to abandon a fully spatial comparison in many scenarios to concentrate the model calibration exercise on specific points such as hospitals, police stations or emergency response centers. It can be shown that such point evaluations lead to significantly different flood hazard maps due to the averaging effect of a spatial performance measure. A strategy to balance the different needs (accuracy at certain spatial points and acceptable spatial performance) has to be based in a public and political decision making process.
NASA Astrophysics Data System (ADS)
Asadzadeh, M.; Maclean, A.; Tolson, B. A.; Burn, D. H.
2009-05-01
Hydrologic model calibration aims to find a set of parameters that adequately simulates observations of watershed behavior, such as streamflow, or a state variable, such as snow water equivalent (SWE). There are different metrics for evaluating calibration effectiveness that involve quantifying prediction errors, such as the Nash-Sutcliffe (NS) coefficient and bias evaluated for the entire calibration period, on a seasonal basis, for low flows, or for high flows. Many of these metrics are conflicting such that the set of parameters that maximizes the high flow NS differs from the set of parameters that maximizes the low flow NS. Conflicting objectives are very likely when different calibration objectives are based on different fluxes and/or state variables (e.g., NS based on streamflow versus SWE). One of the most popular ways to balance different metrics is to aggregate them based on their importance and find the set of parameters that optimizes a weighted sum of the efficiency metrics. Comparing alternative hydrologic models (e.g., assessing model improvement when a process or more detail is added to the model) based on the aggregated objective might be misleading since it represents one point on the tradeoff of desired error metrics. To derive a more comprehensive model comparison, we solved a bi-objective calibration problem to estimate the tradeoff between two error metrics for each model. Although this approach is computationally more expensive than the aggregation approach, it results in a better understanding of the effectiveness of selected models at each level of every error metric and therefore provides a better rationale for judging relative model quality. The two alternative models used in this study are two MESH hydrologic models (version 1.2) of the Wolf Creek Research basin that differ in their watershed spatial discretization (a single Grouped Response Unit, GRU, versus multiple GRUs). The MESH model, currently under development by Environment
NASA Astrophysics Data System (ADS)
Saikia, C. K.; Woods, B. B.; Thio, H. K.
- Regional crustal waveguide calibration is essential to the retrieval of source parameters and the location of smaller (M<4.8) seismic events. This path calibration of regional seismic phases is strongly dependent on the accuracy of hypocentral locations of calibration (or master) events. This information can be difficult to obtain, especially for smaller events. Generally, explosion or quarry blast generated travel-time data with known locations and origin times are useful for developing the path calibration parameters, but in many regions such data sets are scanty or do not exist. We present a method which is useful for regional path calibration independent of such data, i.e. with earthquakes, which is applicable for events down to Mw = 4 and which has successfully been applied in India, central Asia, western Mediterranean, North Africa, Tibet and the former Soviet Union. These studies suggest that reliably determining depth is essential to establishing accurate epicentral location and origin time for events. We find that the error in source depth does not necessarily trade-off only with the origin time for events with poor azimuthal coverage, but with the horizontal location as well, thus resulting in poor epicentral locations. For example, hypocenters for some events in central Asia were found to move from their fixed-depth locations by about 20km. Such errors in location and depth will propagate into path calibration parameters, particularly with respect to travel times. The modeling of teleseismic depth phases (pP, sP) yields accurate depths for earthquakes down to magnitude Mw = 4.7. This Mwthreshold can be lowered to four if regional seismograms are used in conjunction with a calibrated velocity structure model to determine depth, with the relative amplitude of the Pnl waves to the surface waves and the interaction of regional sPmP and pPmP phases being good indicators of event depths. We also found that for deep events a seismic phase which follows an S
DOSE-RESPONSE ASSESSMENT FOR DEVELOPMENTAL TOXICITY: III. STATISTICAL MODELS
Although quantitative modeling has been central to cancer risk assessment for years, the concept of dose-response modeling for developmental effects is relatively new. Recently, statistical models appropriate for developmental toxicity testing have been developed and applied (Rai...
Automatic calibration of a global flow routing model in the Amazon basin using virtual SWOT data
NASA Astrophysics Data System (ADS)
Rogel, P. Y.; Mouffe, M.; Getirana, A.; Ricci, S. M.; Lion, C.; Mognard, N. M.; Biancamaria, S.; Boone, A.
2012-12-01
The Surface Water and Ocean Topography (SWOT) wide swath altimetry mission will provide a global coverage of surface water elevation, which will be used to help correct water height and discharge prediction from hydrological models. Here, the aim is to investigate the use of virtually generated SWOT data to improve water height and discharge simulation using calibration of model parameters (like river width, river depth and roughness coefficient). In this work, we use the HyMAP model to estimate water height and discharge on the Amazon catchment area. Before reaching the river network, surface and subsurface runoff are delayed by a set of linear and independent reservoirs. The flow routing is performed by the kinematic wave equation.. Since the SWOT mission has not yet been launched, virtual SWOT data are generated with a set of true parameters for HyMAP as well as measurement errors from a SWOT data simulator (i.e. a twin experiment approach is implemented). These virtual observations are used to calibrate key parameters of HyMAP through the minimization of a cost function defining the difference between the simulated and observed water heights over a one-year simulation period. The automatic calibration procedure is achieved using the MOCOM-UA multicriteria global optimization algorithm as well as the local optimization algorithm BC-DFO that is considered as a computational cost saving alternative. First, to reduce the computational cost of the calibration procedure, each spatially distributed parameter (Manning coefficient, river width and river depth) is corrupted through the multiplication of a spatially uniform factor that is the only factor optimized. In this case, it is shown that, when the measurement errors are small, the true water heights and discharges are easily retrieved. Because of equifinality, the true parameters are not always identified. A spatial correction of the model parameters is then investigated and the domain is divided into 4 regions
Langevin, Christian D.; Hughes, Joseph D.
2010-01-01
A model with a small amount of numerical dispersion was used to represent saltwater 7 intrusion in a homogeneous aquifer for a 10-year historical calibration period with one 8 groundwater withdrawal location followed by a 10-year prediction period with two groundwater 9 withdrawal locations. Time-varying groundwater concentrations at arbitrary locations in this low-10 dispersion model were then used as observations to calibrate a model with a greater amount of 11 numerical dispersion. The low-dispersion model was solved using a Total Variation Diminishing 12 numerical scheme; an implicit finite difference scheme with upstream weighting was used for 13 the calibration simulations. Calibration focused on estimating a three-dimensional hydraulic 14 conductivity field that was parameterized using a regular grid of pilot points in each layer and a 15 smoothness constraint. Other model parameters (dispersivity, porosity, recharge, etc.) were 16 fixed at the known values. The discrepancy between observed and simulated concentrations 17 (due solely to numerical dispersion) was reduced by adjusting hydraulic conductivity through the 18 calibration process. Within the transition zone, hydraulic conductivity tended to be lower than 19 the true value for the calibration runs tested. The calibration process introduced lower hydraulic 20 conductivity values to compensate for numerical dispersion and improve the match between 21 observed and simulated concentration breakthrough curves at monitoring locations. 22 Concentrations were underpredicted at both groundwater withdrawal locations during the 10-23 year prediction period.
NASA Astrophysics Data System (ADS)
Luo, Yue; Ye, Shujun; Wu, Jichun; Wang, Hanmei; Jiao, Xun
2016-05-01
Land-subsidence prediction depends on an appropriate subsidence model and the calibration of its parameter values. A modified inverse procedure is developed and applied to calibrate five parameters in a compacting confined aquifer system using records of field data from vertical extensometers and corresponding hydrographs. The inverse procedure of COMPAC (InvCOMPAC) has been used in the past for calibrating vertical hydraulic conductivity of the aquitards, nonrecoverable and recoverable skeletal specific storages of the aquitards, skeletal specific storage of the aquifers, and initial preconsolidation stress within the aquitards. InvCOMPAC is modified to increase robustness in this study. There are two main differences in the modified InvCOMPAC model (MInvCOMPAC). One is that field data are smoothed before diagram analysis to reduce local oscillation of data and remove abnormal data points. A robust locally weighted regression method is applied to smooth the field data. The other difference is that the Newton-Raphson method, with a variable scale factor, is used to conduct the computer-based inverse adjustment procedure. MInvCOMPAC is then applied to calibrate parameters in a land subsidence model of Shanghai, China. Five parameters of aquifers and aquitards at 15 multiple-extensometer sites are calibrated. Vertical deformation of sedimentary layers can be predicted by the one-dimensional COMPAC model with these calibrated parameters at extensometer sites. These calibrated parameters could also serve as good initial values for parameters of three-dimensional regional land subsidence models of Shanghai.
Calibration of interphase fluorescence in situ hybridization cutoff by mathematical models.
Du, Qinghua; Li, Qingshan; Sun, Daochun; Chen, Xiaoyan; Yu, Bizhen; Ying, Yi
2016-03-01
Fluorescence in situ hybridization (FISH) continues to play an important role in clinical investigations. Laboratories may create their own cutoff, a percentage of positive nuclei to determine whether a specimen is positive or negative, to eliminate false positives that are created by signal overlap in most cases. In some cases, it is difficult to determine the cutoff value because of differences in both the area of nuclei and the number of signals. To address these problems, we established two mathematical models using probability theory. To verify these two models, normal disomy cells from healthy individuals were used to simulate cells with different numbers of signals by hybridization with different probes. We used an X/Y probe to obtain the average distance between two signals and the probability of signal overlap in different nuclei area. Frequencies of all signal patterns were scored and compared with theoretical frequencies, and models were assessed using a goodness of fit test. We used five BCR/ABL1-positive samples, 20 BCR/ABL1-negative samples and two samples with ambiguous results to verify the cutoff calibrated by these two models. The models were in agreement with experimental results. The dynamic cutoff can classify cases in routine analysis correctly, and it can also correct for influences from nuclei area and the number of signals in some ambiguous cases. The probability models can be used to assess the effect of signal overlap and calibrate the cutoff. © 2015 International Society for Advancement of Cytometry. PMID:26580488
Chambers, Robert S.; Tandon, Rajan; Stavig, Mark E.
2015-07-07
In this study, to analyze the stresses and strains generated during the solidification of glass-forming materials, stress and volume relaxation must be predicted accurately. Although the modeling attributes required to depict physical aging in organic glassy thermosets strongly resemble the structural relaxation in inorganic glasses, the historical modeling approaches have been distinctly different. To determine whether a common constitutive framework can be applied to both classes of materials, the nonlinear viscoelastic simplified potential energy clock (SPEC) model, developed originally for glassy thermosets, was calibrated for the Schott 8061 inorganic glass and used to analyze a number of tests. A practical methodology for material characterization and model calibration is discussed, and the structural relaxation mechanism is interpreted in the context of SPEC model constitutive equations. SPEC predictions compared to inorganic glass data collected from thermal strain measurements and creep tests demonstrate the ability to achieve engineering accuracy and make the SPEC model feasible for engineering applications involving a much broader class of glassy materials.
NASA Astrophysics Data System (ADS)
Chanumolu, Anantha; Jones, Damien; Thirupathi, Sivarani
2015-06-01
We present a modelling scheme that predicts the centroids of spectral line features for a high resolution Echelle spectrograph to a high accuracy. Towards this, a computing scheme is used, whereby any astronomical spectrograph can be modelled and controlled without recourse to a ray tracing program. The computations are based on paraxial ray trace and exact corrections added for certain surface types and Buchdahl aberration coefficients for complex modules. The resultant chain of paraxial ray traces and corrections for all relevant components is used to calculate the location of any spectral line on the detector under all normal operating conditions with a high degree of certainty. This will allow a semi-autonomous control using simple in-house, programming modules. The scheme is simple enough to be implemented even in a spreadsheet or in any scripting language. Such a model along with an optimization routine can represent the real time behaviour of the instrument. We present here a case study for Hanle Echelle Spectrograph. We show that our results match well with a popular commercial ray tracing software. The model is further optimized using Thorium Argon calibration lamp exposures taken during the preliminary alignment of the instrument. The model predictions matched the calibration frames at a level of 0.08 pixel. Monte Carlo simulations were performed to show the photon noise effect on the model predictions.
NASA Astrophysics Data System (ADS)
Gilson, L.; Rabet, L.; Imad, A.; Kakogiannis, D.; Coghe, F.
2016-05-01
Among the different material surrogates used to study the effect of small calibre projectiles on the human body, ballistic gelatine is one of the most commonly used because of its specific material properties. For many applications, numerical simulations of this material could give an important added value to understand the different phenomena observed during ballistic testing. However, the material response of gelatine is highly non-linear and complex. Recent developments in this field are available in the literature. Experimental and numerical data on the impact of rigid steel spheres in gelatine available in the literature were considered as a basis for the selection of the best model for further work. For this a comparison of two models for Fackler gelatine has been made. The selected model is afterwards exploited for a real threat consisting of two types of ammunitions: 9 mm and .44 Magnum calibre projectiles. A high-speed camera and a pressure sensor were used in order to measure the velocity decay of the projectiles and the pressure at a given location in the gelatine during penetration of the projectile. The observed instability of the 9 mm bullets was also studied. Four numerical models were developed and solved with LS-DYNA and compared with the experimental data. Good agreement was obtained between the models and the experiments validating the selected gelatine model for future use.
Self-calibration of digital aerial camera using combined orthogonal models
NASA Astrophysics Data System (ADS)
Babapour, Hadi; Mokhtarzade, Mehdi; Valadan Zoej, Mohamad Javad
2016-07-01
The emergence of new digital aerial cameras and the diverse design and technology used in this type of cameras require in-situ calibration. Self-calibration methods, e.g. the Fourier model, are primarily used; however, additional parameters employed in such methods have not yet met the expectations to desirably model the complex multiple distortions existing in the digital aerial cameras. The present study proposes the Chebyshev-Fourier (CHF) and Jacobi-Fourier (JF) combined orthogonal models. The models are evaluated for the multiple distortions using both simulated and real data, the latter being derived from an UltraCam digital camera. The results indicate that the JF model is superior to the other methods where, e.g., in the UltraCam scenario, it improves the planimetric and vertical accuracy over the Fourier model by 18% and 22%, respectively. Furthermore, a 30% and 16% of reduction in external and internal correlation is obtained via this approach which is very promising.
Chambers, Robert S.; Tandon, Rajan; Stavig, Mark E.
2015-07-07
In this study, to analyze the stresses and strains generated during the solidification of glass-forming materials, stress and volume relaxation must be predicted accurately. Although the modeling attributes required to depict physical aging in organic glassy thermosets strongly resemble the structural relaxation in inorganic glasses, the historical modeling approaches have been distinctly different. To determine whether a common constitutive framework can be applied to both classes of materials, the nonlinear viscoelastic simplified potential energy clock (SPEC) model, developed originally for glassy thermosets, was calibrated for the Schott 8061 inorganic glass and used to analyze a number of tests. A practicalmore » methodology for material characterization and model calibration is discussed, and the structural relaxation mechanism is interpreted in the context of SPEC model constitutive equations. SPEC predictions compared to inorganic glass data collected from thermal strain measurements and creep tests demonstrate the ability to achieve engineering accuracy and make the SPEC model feasible for engineering applications involving a much broader class of glassy materials.« less
A generalized grid connectivity-based parameterization for subsurface flow model calibration
NASA Astrophysics Data System (ADS)
Bhark, Eric W.; Jafarpour, Behnam; Datta-Gupta, Akhil
2011-06-01
We develop a novel method of parameterization for spatial hydraulic property characterization to mitigate the challenges associated with the nonlinear