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.
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.
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.
Modeling metrology for calibration of OPC models
NASA Astrophysics Data System (ADS)
Mack, Chris A.; Raghunathan, Ananthan; Sturtevant, John; Deng, Yunfei; Zuniga, Christian; Adam, Kostas
2016-03-01
Optical Proximity Correction (OPC) has continually improved in accuracy over the years by adding more physically based models. Here, we further extend OPC modeling by adding the Analytical Linescan Model (ALM) to account for systematic biases in CD-SEM metrology. The ALM was added to a conventional OPC model calibration flow and the accuracy of the calibrated model with the ALM was compared to the standard model without the ALM using validation data. Without using any adjustable parameters in the ALM, OPC validation accuracy was improved by 5%. While very preliminary, these results give hope that modeling metrology could be an important next step in OPC model improvement.
A Method to Test Model Calibration Techniques
Judkoff, Ron; Polly, Ben; Neymark, Joel
2016-08-26
This paper describes a method for testing model calibration techniques. Calibration is commonly used in conjunction with energy retrofit audit models. An audit is conducted to gather information about the building needed to assemble an input file for a building energy modeling tool. A calibration technique is used to reconcile model predictions with utility data, and then the 'calibrated model' is used to predict energy savings from a variety of retrofit measures and combinations thereof. Current standards and guidelines such as BPI-2400 and ASHRAE-14 set criteria for 'goodness of fit' and assume that if the criteria are met, then the calibration technique is acceptable. While it is logical to use the actual performance data of the building to tune the model, it is not certain that a good fit will result in a model that better predicts post-retrofit energy savings. Therefore, the basic idea here is that the simulation program (intended for use with the calibration technique) is used to generate surrogate utility bill data and retrofit energy savings data against which the calibration technique can be tested. This provides three figures of merit for testing a calibration technique, 1) accuracy of the post-retrofit energy savings prediction, 2) closure on the 'true' input parameter values, and 3) goodness of fit to the utility bill data. The paper will also discuss the pros and cons of using this synthetic surrogate data approach versus trying to use real data sets of actual buildings.
Efficient Calibration of Computationally Intensive Hydrological Models
NASA Astrophysics Data System (ADS)
Poulin, A.; Huot, P. L.; Audet, C.; Alarie, S.
2015-12-01
A new hybrid optimization algorithm for the calibration of computationally-intensive hydrological models is introduced. The calibration of hydrological models is a blackbox optimization problem where the only information available to the optimization algorithm is the objective function value. In the case of distributed hydrological models, the calibration process is often known to be hampered by computational efficiency issues. Running a single simulation may take several minutes and since the optimization process may require thousands of model evaluations, the computational time can easily expand to several hours or days. A blackbox optimization algorithm, which can substantially improve the calibration efficiency, has been developed. It merges both the convergence analysis and robust local refinement from the Mesh Adaptive Direct Search (MADS) algorithm, and the global exploration capabilities from the heuristic strategies used by the Dynamically Dimensioned Search (DDS) algorithm. The new algorithm is applied to the calibration of the distributed and computationally-intensive HYDROTEL model on three different river basins located in the province of Quebec (Canada). Two calibration problems are considered: (1) calibration of a 10-parameter version of HYDROTEL, and (2) calibration of a 19-parameter version of the same model. A previous study by the authors had shown that the original version of DDS was the most efficient method for the calibration of HYDROTEL, when compared to the MADS and the very well-known SCEUA algorithms. The computational efficiency of the hybrid DDS-MADS method is therefore compared with the efficiency of the DDS algorithm based on a 2000 model evaluations budget. Results show that the hybrid DDS-MADS method can reduce the total number of model evaluations by 70% for the 10-parameter version of HYDROTEL and by 40% for the 19-parameter version without compromising the quality of the final objective function value.
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...
Autotune Calibrates Models to Building Use Data
2016-08-26
Models of existing buildings are currently unreliable unless calibrated manually by a skilled professional. Autotune, as the name implies, automates this process by calibrating the model of an existing building to measured data, and is now available as open source software. This enables private businesses to incorporate Autotune into their products so that their customers can more effectively estimate cost savings of reduced energy consumption measures in existing buildings.
Autotune Calibrates Models to Building Use Data
None
2016-09-02
Models of existing buildings are currently unreliable unless calibrated manually by a skilled professional. Autotune, as the name implies, automates this process by calibrating the model of an existing building to measured data, and is now available as open source software. This enables private businesses to incorporate Autotune into their products so that their customers can more effectively estimate cost savings of reduced energy consumption measures in existing buildings.
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.
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
Modelling PTB's spatial angle autocollimator calibrator
NASA Astrophysics Data System (ADS)
Kranz, Oliver; Geckeler, Ralf D.; Just, Andreas; Krause, Michael
2013-05-01
The accurate and traceable form measurement of optical surfaces has been greatly advanced by a new generation of surface profilometers which are based on the reflection of light at the surface and the measurement of the reflection angle. For this application, high-resolution electronic autocollimators provide accurate and traceable angle metrology. In recent years, great progress has been made at the Physikalisch-Technische Bundesanstalt (PTB) in autocollimator calibration. For an advanced autocollimator characterisation, a novel calibration device has been built up at PTB: the Spatial Angle Autocollimator Calibrator (SAAC). The system makes use of an innovative Cartesian arrangement of three autocollimators (two reference autocollimators and the autocollimator to be calibrated), which allows a precise measurement of the angular orientation of a reflector cube. Each reference autocollimator is sensitive primarily to changes in one of the two relevant tilt angles, whereas the autocollimator to be calibrated is sensitive to both. The distance between the reflector cube and the autocollimator to be calibrated can be varied flexibly. In this contribution, we present the SAAC and aspects of the mathematical modelling of the system for deriving analytical expressions for the autocollimators' angle responses. These efforts will allow advancing the form measurement substantially with autocollimator-based profilometers and approaching fundamental measurement limits. Additionally, they will help manufacturers of autocollimators to improve their instruments and will provide improved angle measurement methods for precision engineering.
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
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…
Calibrating reaction rates for the CREST model
NASA Astrophysics Data System (ADS)
Handley, Caroline A.; Christie, Michael A.
2017-01-01
The CREST reactive-burn model uses entropy-dependent reaction rates that, until now, have been manually tuned to fit shock-initiation and detonation data in hydrocode simulations. This paper describes the initial development of an automatic method for calibrating CREST reaction-rate coefficients, using particle swarm optimisation. The automatic method is applied to EDC32, to help develop the first CREST model for this conventional high explosive.
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.
Grid based calibration of SWAT hydrological models
NASA Astrophysics Data System (ADS)
Gorgan, D.; Bacu, V.; Mihon, D.; Rodila, D.; Abbaspour, K.; Rouholahnejad, E.
2012-07-01
The calibration and execution of large hydrological models, such as SWAT (soil and water assessment tool), developed for large areas, high resolution, and huge input data, need not only quite a long execution time but also high computation resources. SWAT hydrological model supports studies and predictions of the impact of land management practices on water, sediment, and agricultural chemical yields in complex watersheds. The paper presents the gSWAT application as a web practical solution for environmental specialists to calibrate extensive hydrological models and to run scenarios, by hiding the complex control of processes and heterogeneous resources across the grid based high computation infrastructure. The paper highlights the basic functionalities of the gSWAT platform, and the features of the graphical user interface. The presentation is concerned with the development of working sessions, interactive control of calibration, direct and basic editing of parameters, process monitoring, and graphical and interactive visualization of the results. The experiments performed on different SWAT models and the obtained results argue the benefits brought by the grid parallel and distributed environment as a solution for the processing platform. All the instances of SWAT models used in the reported experiments have been developed through the enviroGRIDS project, targeting the Black Sea catchment area.
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.
Objective calibration of numerical weather prediction models
NASA Astrophysics Data System (ADS)
Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.
2017-07-01
Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.
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.
Process analytical technology case study, part III: calibration monitoring and transfer.
Cogdill, Robert P; Anderson, Carl A; Drennen, James K
2005-10-06
This is the third of a series of articles detailing the development of near-infrared spectroscopy methods for solid dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to develop a system for continuous calibration monitoring and formulate an appropriate strategy for calibration transfer. Indicators of high-flux noise (noise factor level) and wavelength uncertainty were developed. These measurements, in combination with Hotelling's T(2) and Q residual, are used to continuously monitor instrument performance and model relevance. Four calibration transfer techniques were compared. Three established techniques, finite impulse response filtering, generalized least squares weighting, and piecewise direct standardization were evaluated. A fourth technique, baseline subtraction, was the most effective for calibration transfer. Using as few as 15 transfer samples, predictive capability of the analytical method was maintained across multiple instruments and major instrument maintenance.
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, 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.
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
Mortality Probability Model III and Simplified Acute Physiology Score II
Vasilevskis, Eduard E.; Kuzniewicz, Michael W.; Cason, Brian A.; Lane, Rondall K.; Dean, Mitzi L.; Clay, Ted; Rennie, Deborah J.; Vittinghoff, Eric; Dudley, R. Adams
2009-01-01
Background: To develop and compare ICU length-of-stay (LOS) risk-adjustment models using three commonly used mortality or LOS prediction models. Methods: Between 2001 and 2004, we performed a retrospective, observational study of 11,295 ICU patients from 35 hospitals in the California Intensive Care Outcomes Project. We compared the accuracy of the following three LOS models: a recalibrated acute physiology and chronic health evaluation (APACHE) IV-LOS model; and models developed using risk factors in the mortality probability model III at zero hours (MPM0) and the simplified acute physiology score (SAPS) II mortality prediction model. We evaluated models by calculating the following: (1) grouped coefficients of determination; (2) differences between observed and predicted LOS across subgroups; and (3) intraclass correlations of observed/expected LOS ratios between models. Results: The grouped coefficients of determination were APACHE IV with coefficients recalibrated to the LOS values of the study cohort (APACHE IVrecal) [R2 = 0.422], mortality probability model III at zero hours (MPM0 III) [R2 = 0.279], and simplified acute physiology score (SAPS II) [R2 = 0.008]. For each decile of predicted ICU LOS, the mean predicted LOS vs the observed LOS was significantly different (p ≤ 0.05) for three, two, and six deciles using APACHE IVrecal, MPM0 III, and SAPS II, respectively. Plots of the predicted vs the observed LOS ratios of the hospitals revealed a threefold variation in LOS among hospitals with high model correlations. Conclusions: APACHE IV and MPM0 III were more accurate than SAPS II for the prediction of ICU LOS. APACHE IV is the most accurate and best calibrated model. Although it is less accurate, MPM0 III may be a reasonable option if the data collection burden or the treatment effect bias is a consideration. PMID:19363210
Modelling Experimental Procedures for Manipulator Calibration
1991-12-01
AD-A245 603 NAVAL POSTGRADUATE SCHOOL Monterey, California RA D TIC THESIS F-a 1 . MODELLING EXPERIMENTAL PROCEDURES FOR MANIPULATOR CALIBRATION by...William E. Swayze December 1991 Thesis Advisor: Morris R. Driels Approved for public release; distribution is unlimited 92-03143 Uncl ass if ied...2 PERSONAL AUTHORS WILLI.TM E. SWAYZE 13a TYPE OF REPORT 13o TIME COVERED 14. DATE OF REPORT (Year, Mon.th Day) 15 PAGE COUNT Master’s Thesis FROM
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.
Calibrated predictions for multivariate competing risks models.
Gorfine, Malka; Hsu, Li; Zucker, David M; Parmigiani, Giovanni
2014-04-01
Prediction models for time-to-event data play a prominent role in assessing the individual risk of a disease, such as cancer. Accurate disease prediction models provide an efficient tool for identifying individuals at high risk, and provide the groundwork for estimating the population burden and cost of disease and for developing patient care guidelines. We focus on risk prediction of a disease in which family history is an important risk factor that reflects inherited genetic susceptibility, shared environment, and common behavior patterns. In this work family history is accommodated using frailty models, with the main novel feature being allowing for competing risks, such as other diseases or mortality. We show through a simulation study that naively treating competing risks as independent right censoring events results in non-calibrated predictions, with the expected number of events overestimated. Discrimination performance is not affected by ignoring competing risks. Our proposed prediction methodologies correctly account for competing events, are very well calibrated, and easy to implement.
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.
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
Improved Spectrophotometric Calibration of the SDSS-III BOSS Quasar Sample
NASA Astrophysics Data System (ADS)
Margala, Daniel; Kirkby, David; Dawson, Kyle; Bailey, Stephen; Blanton, Michael; Schneider, Donald P.
2016-11-01
We present a model for spectrophotometric calibration errors in observations of quasars from the third generation of the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey (BOSS) and describe the correction procedure we have developed and applied to this sample. Calibration errors are primarily due to atmospheric differential refraction and guiding offsets during each exposure. The corrections potentially reduce the systematics for any studies of BOSS quasars, including the measurement of baryon acoustic oscillations using the Lyα forest. Our model suggests that, on average, the observed quasar flux in BOSS is overestimated by ∼19% at 3600 Å and underestimated by ∼24% at 10,000 Å. Our corrections for the entire BOSS quasar sample are publicly available.
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.
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).
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).
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.
Calibrating historical IR sensors using GEO and AVHRR infrared tropical mean calibration models
NASA Astrophysics Data System (ADS)
Scarino, Benjamin; Doelling, David R.; Minnis, Patrick; Gopalan, Arun; Haney, Conor; Bhatt, Rajendra
2014-09-01
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 bias difference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and
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
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...
Evaluation of “Autotune” calibration against manual calibration of building energy models
Chaudhary, Gaurav; New, Joshua; Sanyal, Jibonananda; ...
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
Distributed calibrating snow models using remotely sensed snow cover information
NASA Astrophysics Data System (ADS)
Li, H.
2015-12-01
Distributed calibrating snow models using remotely sensed snow cover information Hongyi Li1, Tao Che1, Xin Li1, Jian Wang11. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China For improving the simulation accuracy of snow model, remotely sensed snow cover data are used to calibrate spatial parameters of snow model. A physically based snow model is developed and snow parameters including snow surface roughness, new snow density and critical threshold temperature distinguishing snowfall from precipitation, are spatially calibrated in this study. The study region, Babaohe basin, located in northwestern China, have seasonal snow cover and with complex terrain. The results indicates that the spatially calibration of snow model parameters make the simulation results more reasonable, and the simulated snow accumulation days, plot-scale snow depth are more better than lumped calibration.
A Method to Test Model Calibration Techniques: Preprint
Judkoff, Ron; Polly, Ben; Neymark, Joel
2016-09-01
This paper describes a method for testing model calibration techniques. Calibration is commonly used in conjunction with energy retrofit audit models. An audit is conducted to gather information about the building needed to assemble an input file for a building energy modeling tool. A calibration technique is used to reconcile model predictions with utility data, and then the 'calibrated model' is used to predict energy savings from a variety of retrofit measures and combinations thereof. Current standards and guidelines such as BPI-2400 and ASHRAE-14 set criteria for 'goodness of fit' and assume that if the criteria are met, then the calibration technique is acceptable. While it is logical to use the actual performance data of the building to tune the model, it is not certain that a good fit will result in a model that better predicts post-retrofit energy savings. Therefore, the basic idea here is that the simulation program (intended for use with the calibration technique) is used to generate surrogate utility bill data and retrofit energy savings data against which the calibration technique can be tested. This provides three figures of merit for testing a calibration technique, 1) accuracy of the post-retrofit energy savings prediction, 2) closure on the 'true' input parameter values, and 3) goodness of fit to the utility bill data. The paper will also discuss the pros and cons of using this synthetic surrogate data approach versus trying to use real data sets of actual buildings.
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).
Polarimetric PALSAR System Model Assessment and Calibration
NASA Astrophysics Data System (ADS)
Touzi, R.; Shimada, M.
2009-04-01
Polarimetric PALSAR system parameters are assessed using data sets collected over various calibration sites. The data collected over the Amazonian forest permits validating the zero Faraday rotation hypotheses near the equator. The analysis of the Amazonian forest data and the response of the corner reflectors deployed during the PALSAR acquisitions lead to the conclusion that the antenna is highly isolated (better than -35 dB). Theses results are confirmed using data collected over the Sweden and Ottawa calibration sites. The 5-m height trihedrals deployed in the Sweden calibration site by the Chalmers University of technology permits accurate measurement of antenna parameters, and detection of 2-3 degree Faraday rotation during day acquisition, whereas no Faraday rotation was noted during night acquisition. Small Faraday rotation angles (2-3 degree) have been measured using acquisitions over the DLR Oberpfaffenhofen and the Ottawa calibration sites. The presence of small but still significant Faraday rotation (2-3 degree) induces a CR return at the crosspolarization HV and VH that should not be interpreted as the actual antenna cross-talk. PALSAR antenna is highly isolated (better than -35 dB), and diagonal antenna distortion matrices (with zero cross-talk terms) can be used for accurate calibration of PALSAR polarimetric data.
SWAT Model Configuration, Calibration and Validation for Lake Champlain Basin
The Soil and Water Assessment Tool (SWAT) model was used to develop phosphorus loading estimates for sources in the Lake Champlain Basin. This document describes the model setup and parameterization, and presents calibration results.
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.
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.
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.
Assessment of simulation-based calibration of rectangular pulse models
NASA Astrophysics Data System (ADS)
Vanhaute, Willem Jan; Vandenberghe, Sander; Willems, Patrick; Verhoest, Niko E. C.
2013-04-01
The use of stochastic rainfall models has become widespread in many hydrologic applications, especially when historical rainfall records lack in length or quality to be used for practical purposes. Among a variety of models, rectangular pulse models such as the Neyman-scott and Bartlett-Lewis type models are known for their parsimonious nature and relative ease in simulating long rainfall time series. The aforementioned models are often calibrated using the generalized method of moments which fits modeled to observed moments. To ease the computational burden, the expected values of the modeled moments are usually expressed in function of the model parameters through analytical expressions. The derivation of such analytical expressions is considered to be an important bottleneck in the development of these rectangular pulse models. Any adjustment to the model structure must be accompanied by an adjustment of the analytical moments in order to be able to calibrate the adjusted model. To avoid the use of analytical moments during calibration, a simulation-based calibration is needed. The latter would enable the modeler to make and validate adjustments in a more organic matter. However, such simulation-based calibration must be able to account for the randomness of the simulation. As such, ensemble runs must be made for every objective function evaluation, resulting in considerable computational requirements. The presented research investigates how to exploit today's available computational resources in order to enable simulation-based calibration. Once such type of calibration is feasible, it will open doors to implementing adjustments to the model structure (such as the introduction of dependencies between model variables by using copulas) without the need to rely on analytical expressions of the different moments.
Improvement of hydrological model calibration by selecting multiple parameter ranges
NASA Astrophysics Data System (ADS)
Wu, Qiaofeng; Liu, Shuguang; Cai, Yi; Li, Xinjian; Jiang, Yangming
2017-01-01
The parameters of hydrological models are usually calibrated to achieve good performance, owing to the highly non-linear problem of hydrology process modelling. However, parameter calibration efficiency has a direct relation with parameter range. Furthermore, parameter range selection is affected by probability distribution of parameter values, parameter sensitivity, and correlation. A newly proposed method is employed to determine the optimal combination of multi-parameter ranges for improving the calibration of hydrological models. At first, the probability distribution was specified for each parameter of the model based on genetic algorithm (GA) calibration. Then, several ranges were selected for each parameter according to the corresponding probability distribution, and subsequently the optimal range was determined by comparing the model results calibrated with the different selected ranges. Next, parameter correlation and sensibility were evaluated by quantifying two indexes, RC Y, X and SE, which can be used to coordinate with the negatively correlated parameters to specify the optimal combination of ranges of all parameters for calibrating models. It is shown from the investigation that the probability distribution of calibrated values of any particular parameter in a Xinanjiang model approaches a normal or exponential distribution. The multi-parameter optimal range selection method is superior to the single-parameter one for calibrating hydrological models with multiple parameters. The combination of optimal ranges of all parameters is not the optimum inasmuch as some parameters have negative effects on other parameters. The application of the proposed methodology gives rise to an increase of 0.01 in minimum Nash-Sutcliffe efficiency (ENS) compared with that of the pure GA method. The rising of minimum ENS with little change of the maximum may shrink the range of the possible solutions, which can effectively reduce uncertainty of the model performance.
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...
Sediment calibration strategies of Phase 5 Chesapeake Bay watershed model
Wu, J.; Shenk, G.W.; Raffensperger, J.; Moyer, D.; Linker, L.C.; ,
2005-01-01
Sediment is a primary constituent of concern for Chesapeake Bay due to its effect on water clarity. Accurate representation of sediment processes and behavior in Chesapeake Bay watershed model is critical for developing sound load reduction strategies. Sediment calibration remains one of the most difficult components of watershed-scale assessment. This is especially true for Chesapeake Bay watershed model given the size of the watershed being modeled and complexity involved in land and stream simulation processes. To obtain the best calibration, the Chesapeake Bay program has developed four different strategies for sediment calibration of Phase 5 watershed model, including 1) comparing observed and simulated sediment rating curves for different parts of the hydrograph; 2) analyzing change of bed depth over time; 3) relating deposition/scour to total annual sediment loads; and 4) calculating "goodness-of-fit' statistics. These strategies allow a more accurate sediment calibration, and also provide some insightful information on sediment processes and behavior in Chesapeake Bay watershed.
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.
Modelling the arsenic (V) and (III) adsorption
NASA Astrophysics Data System (ADS)
Rau, I.; Meghea, A.; Peleanu, I.; Gonzalo, A.; Valiente, M.; Zaharescu, M.
2003-01-01
Arsenic has gained great notoriety historically for its toxic properties. In aquatic environment, arsenic can exist in several oxidation states, as both inorganic and organometallic species. As (V) is less toxic than As (III). Most research has been directed to the control of arsenic pollution of potable water. Various techniques such as precipitation with iron and aluminium hydroxides, ion exchange, reverse osmosis, and adsorption are used for As (V) removal from surface and waste waters. Because of the easy handling of sludge, its free operation and regeneration capability, the adsorption technique has secured a place as one of the advanced methods of arsenic removal. A study of As (III) and As (V) sorption onto some different adsorbents (Fe (III) — iminodiacetate resin, nanocomposite materials, Fe(III) — forager sponge) referring to kinetic considerations and modelling of the process will be presented. All the systems studied are better described by Freundlich-Langmuir isotherm and the rate constant evaluation shows a sub-unitary order for the adsorption 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.
Multi-objective model calibration and validation based on runoff and groundwater levels
NASA Astrophysics Data System (ADS)
Beldring, S.
2003-04-01
The multi-objective calibration procedure MOCOM-UA was used to evaluate the validity of a precipitation-runoff model by forcing the model to simulate several observed system responses simultaneously. The model is based on kinematic wave approximations to saturated subsurface flow and saturation overland flow at the hillslope scale in a landcape with a shallow layer of permeable deposits overlying a relatively impermeable bedrock. Data from a catchment with till deposits in the boreal forest zone in south-east Norway were used in this study. The following results were found; (i) The MOCOM-UA method was capable of exploiting information about the physical system contained in the measurement data time series; (ii) The multi-objective calibration procedure provided estimates of the uncertainty associated with model predictions and parameters; (iii) Multi-objective calibration constraining the behaviour of the precipitation-runoff model to observed runoff and groundwater levels reduced the uncertainty of model predictions; (iv) The multi-objective method reduced the uncertainty of the estimates of model parameters; (v) The precipitation-runoff model was able to reproduce several observed system responses simultaneously during both calibration and validation periods; and (vi) Groundwater table depths exerted a major control on the hydrological response of the investigated catchment.
Mask model calibration for MPC applications utilizing shot dose assignment
NASA Astrophysics Data System (ADS)
Bork, Ingo; Buck, Peter; Paninjath, Sankaranarayanan; Mishra, Kushlendra; Bürgel, Christian; Standiford, Keith; Chua, Gek Soon
2014-10-01
Shrinking feature sizes and the need for tighter CD (Critical Dimension) control require the introduction of new technologies in mask making processes. One of those methods is the dose assignment of individual shots on VSB (Variable Shaped Beam) mask writers to compensate CD non-linearity effects and improve dose edge slope. Using increased dose levels only for most critical features, generally only for the smallest CDs on a mask, the change in mask write time is minimal while the increase in image quality can be significant. However, this technology requires accurate modeling of the mask effects, especially the CD/dose dependencies. This paper describes a mask model calibration flow for Mask Process Correction (MPC) applications with shot dose assignment. The first step in the calibration flow is the selection of appropriate test structures. For this work, a combination of linespace patterns as well as a series of contact patterns are used for calibration. Features sizes vary from 34 nm up to several micrometers in order to capture a wide range of CDs and pattern densities. After mask measurements are completed the results are carefully analyzed and measurements very close to the process window limitation and outliers are removed from the data set. One key finding in this study is that by including patterns exposed at various dose levels the simulated contours of the calibrated model very well match the SEM contours even if the calibration was based entirely on gauge based CD values. In the calibration example shown in this paper, only 1D line and space measurements as well as 1D contact measurements are used for calibration. However, those measurements include patterns exposed at dose levels between 75% and 150% of the nominal dose. The best model achieved in this study uses 2 e-beam kernels and 4 kernels for the simulation of development and etch effects. The model error RMS on a large range of CD down to 34 nm line CD is 0.71 nm. The calibrated model is then
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
A calibration model for screen-caged Peltier thermocouple psychrometers
NASA Astrophysics Data System (ADS)
Brown, R. W.; Bartos, D. L.
1982-07-01
A calibration model for screen-caged Peltier thermocouple psychrometers was developed that applies to a water potential range of 0 to 80 bars, over a temperature range of 0 to 40 C, and for cooling times of 15 to 60 seconds. In addition, the model corrects for the effects of temperature gradients over zero-offsets from -60 to +60 microvolts. Complete details of model development are discussed, together with the theory of thermocouple psychrometers, and techniques of calibration and cleaning. Also, information for computer programing and tabular summaries of model characteristics are provided.
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.
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.
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.
Calibration of Disease Simulation Model Using an Engineering Approach
Kong, Chung Yin; McMahon, Pamela M.; Gazelle, G. Scott
2009-01-01
Objectives Calibrating a disease simulation model’s outputs to existing clinical data is vital to generate confidence in the model’s predictive ability. Calibration involves two challenges: 1) defining a total goodness-of-fit score for multiple targets if simultaneous fitting is required; and 2) searching for the optimal parameter set that minimizes the total goodness-of-fit score (i.e., yields the best fit). To address these two prominent challenges, we have applied an engineering approach to calibrate a microsimulation model, the Lung Cancer Policy Model (LCPM). Methods First, eleven targets derived from clinical and epidemiological data were combined into a total goodness-of-fit score by a weighted-sum approach, accounting for the user-defined relative importance of the calibration targets. Second, two automated parameter search algorithms, Simulated Annealing (SA) and Genetic Algorithm (GA), were independently applied to a simultaneous search of 28 natural history parameters to minimize the total goodness-of-fit score. Algorithm performance metrics were defined for speed and model fit. Results Both search algorithms obtained total goodness-of-fit scores below 95 within 1,000 search iterations. Our results show that SA outperformed GA in locating a lower goodness-of-fit. After calibrating our LCPM, the predicted natural history of lung cancer was consistent with other mathematical models of lung cancer development. Conclusion An engineering-based calibration method was able to simultaneously fit LCPM output to multiple calibration targets, with the benefits of fast computational speed and reduced need for human input and its potential bias. PMID:19900254
Tradeoffs among watershed model calibration targets for parameter estimation
NASA Astrophysics Data System (ADS)
Price, Katie; Purucker, S. Thomas; Kraemer, Stephen R.; Babendreier, Justin E.
2012-10-01
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 fit, while modified Nash-Sutcliffe efficiency (MNS) emphasizes lower flows, and the ratio of the simulated to observed standard deviations (RSD) prioritizes flow variability. We investigated tradeoffs of calibrating streamflow on three standard objective functions (NSE, MNS, and RSD), as well as a multiobjective function aggregating these three targets to simultaneously address a range of flow conditions, for calibration of the Soil and Water Assessment Tool (SWAT) daily streamflow simulations in two watersheds. A suite of objective functions was explored to select a minimally redundant set of metrics addressing a range of flow characteristics. After each pass of 2001 simulations, an iterative informal likelihood procedure was used to subset parameter ranges. The ranges from each best-fit simulation set were used for model validation. Values for optimized parameters vary among calibrations using different objective functions, which underscores the importance of linking modeling objectives to calibration target selection. The simulation set approach yielded validated models of similar quality as seen with a single best-fit parameter set, with the added benefit of uncertainty estimations. Our approach represents a novel compromise between equifinality-based approaches and Pareto optimization. Combining the simulation set approach with the multiobjective function was demonstrated to be a practicable and flexible approach for model calibration, which can be readily modified to suit modeling goals, and is not model or location specific.
SEM image contouring for OPC model calibration and verification
NASA Astrophysics Data System (ADS)
Tabery, Cyrus; Morokuma, Hidetoshi; Matsuoka, Ryoichi; Page, Lorena; Bailey, George E.; Kusnadi, Ir; Do, Thuy
2007-03-01
Lithography models for leading-edge OPC and design verification must be calibrated with empirical data, and this data is traditionally collected as a one-dimensional quantification of the features acquired by a CD-SEM. Two-dimensional proximity features such as line-end, bar-to-bar, or bar-to-line are only partially characterized because of the difficulty in transferring the complete information of a SEM image into the OPC model building process. A new method of two-dimensional measurement uses the contouring of large numbers of SEM images acquired within the context of a design based metrology system to drive improvement in the quality of the final calibrated model. Hitachi High-Technologies has continued to develop "full automated EPE measurement and contouring function" based on design layout and detected edges of SEM image. This function can measure edge placement error everywhere in a SEM image and pass the result as a design layout (GDSII) into Mentor Graphics model calibration flow. Classification of the critical design elements using tagging scripts is used to weight the critical contours in the evaluation of model fitness. During process of placement of the detected SEM edges of into the coordinate system of the design, coordinate errors inevitably are introduced because of pattern matching errors. Also, line edge roughness in 2D features introduces noise that is large compared to the model building accuracy requirements of advanced technology nodes. This required the development of contour averaging algorithms. Contours from multiple SEM images are acquired of a feature and averaged before passing into the model calibration. This function has been incorporated into the prototype Calibre Workbench model calibration flow. Based on these methods, experimental data is presented detailing the model accuracy of a 45nm immersion lithography process using traditional 1D calibration only, and a hybrid model calibration using SEM image contours and 1D measurement
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.
Applying Hierarchical Model Calibration to Automatically Generated Items.
ERIC Educational Resources Information Center
Williamson, David M.; Johnson, Matthew S.; Sinharay, Sandip; Bejar, Isaac I.
This study explored the application of hierarchical model calibration as a means of reducing, if not eliminating, the need for pretesting of automatically generated items from a common item model prior to operational use. Ultimately the successful development of automatic item generation (AIG) systems capable of producing items with highly similar…
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.
Challenges of OPC model calibration from SEM contours
NASA Astrophysics Data System (ADS)
Granik, Yuri; Kusnadi, Ir
2008-03-01
Traditionally OPC models are calibrated to match CD measurements from selected test pattern locations. This demand for massive CD data drives advances in metrology. Considerable progress has recently been achieved in complimenting this CD data with SEM contours. Here we propose solutions to some challenges that emerge in calibrating OPC models from the experimental contours. We discuss and state the minimization objective as a measure of the distance between simulation and experimental contours. The main challenge is to correctly process inevitable gaps, discontinuities and roughness of the SEM contours. We discuss standardizing the data interchange formats and procedures between OPC and metrology vendors.
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.
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.
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...
Calibration of hydrological models using flow-duration curves
NASA Astrophysics Data System (ADS)
Westerberg, I. K.; Guerrero, J.-L.; Younger, P. M.; Beven, K. J.; Seibert, J.; Halldin, S.; Freer, J. E.; Xu, C.-Y.
2010-12-01
The degree of belief we have in predictions from hydrologic models depends on how well they can reproduce observations. Calibrations with traditional performance measures such as the Nash-Sutcliffe model efficiency are challenged by problems including: (1) uncertain discharge data, (2) variable importance of the performance with flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. A new calibration method using flow-duration curves (FDCs) was developed which addresses these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) of the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested - based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments without resulting in overpredicted simulated uncertainty. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application e.g. using more/less EPs at high/low flows. While the new method is less sensitive to epistemic input/output errors than the normal use of limits of
Calibration of hydrological models using flow-duration curves
NASA Astrophysics Data System (ADS)
Westerberg, I. K.; Guerrero, J.-L.; Younger, P. M.; Beven, K. J.; Seibert, J.; Halldin, S.; Freer, J. E.; Xu, C.-Y.
2011-07-01
The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1) uncertain discharge data, (2) variable sensitivity of different performance measures to different flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs) to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested - based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e.g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of acceptability applied
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...
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...
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…
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.
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…
Theoretical model atmosphere spectra used for the calibration of infrared instruments
NASA Astrophysics Data System (ADS)
Decin, L.; Eriksson, K.
2007-09-01
Context: One of the key ingredients in establishing the relation between input signal and output flux from a spectrometer is accurate determination of the spectrophotometric calibration. In the case of spectrometers onboard satellites, the accuracy of this part of the calibration pedigree is ultimately linked to the accuracy of the set of reference spectral energy distributions (SEDs) that the spectrophotometric calibration is built on. Aims: In this paper, we deal with the spectrophotometric calibration of infrared (IR) spectrometers onboard satellites in the 2 to 200 μm wavelength range. We aim at comparing the different reference SEDs used for the IR spectrophotometric calibration. The emphasis is on the reference SEDs of stellar standards with spectral type later than A0, with special focus on the theoretical model atmosphere spectra. Methods: Using the MARCS model atmosphere code, spectral reference SEDs were constructed for a set of IR stellar standards (A dwarfs, solar analogs, G9-M0 giants). A detailed error analysis was performed to estimate proper uncertainties on the predicted flux values. Results: It is shown that the uncertainty on the predicted fluxes can be as high as 10%, but in case high-resolution observational optical or near-IR data are available, and IR excess can be excluded, the uncertainty on medium-resolution SEDs can be reduced to 1-2% in the near-IR, to ~3% in the mid-IR, and to ~5% in the far-IR. Moreover, it is argued that theoretical stellar atmosphere spectra are at the moment the best representations for the IR fluxes of cool stellar standards. Conclusions: When aiming at a determination of the spectrophotometric calibration of IR spectrometers better than 3%, effort should be put into constructing an appropriate set of stellar reference SEDs based on theoretical atmosphere spectra for some 15 standard stars with spectral types between A0 V and M0 III.
Calibration of 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.
I-spline Smoothing for Calibrating Predictive Models.
Wu, Yuan; Jiang, Xiaoqian; Kim, Jihoon; Ohno-Machado, Lucila
2012-01-01
We proposed the I-spline Smoothing approach for calibrating predictive models by solving a nonlinear monotone regression problem. We took advantage of I-spline properties to obtain globally optimal solutions while keeping the computational cost low. Numerical studies based on three data sets showed the empirical evidences of I-spline Smoothing in improving calibration (i.e.,1.6x, 1.4x, and 1.4x on the three datasets compared to the average of competitors-Binning, Platt Scaling, Isotonic Regression, Monotone Spline Smoothing, Smooth Isotonic Regression) without deterioration of discrimination.
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.
Calibration of the hydrogeological model of the Baltic Artesian Basin
NASA Astrophysics Data System (ADS)
Virbulis, J.; Klints, I.; Timuhins, A.; Sennikovs, J.; Bethers, U.
2012-04-01
Let us consider the calibration issue for the Baltic Artesian Basin (BAB) which is a complex hydrogeological system in the southeastern Baltic with surface area close to 0.5 million square kilometers. The model of the geological structure contains 42 layers including aquifers and aquitards. The age of sediments varies from Cambrian up to the Quaternary deposits. The finite element method model was developed for the calculation of the steady state three-dimensional groundwater flow with free surface. No-flow boundary conditions were applied on the rock bottom and the side boundaries of BAB, while simple hydrological model is applied on the surface. The level of the lakes, rivers and the sea is fixed as constant hydraulic head. Constant mean value of 70 mm/year was assumed as an infiltration flux elsewhere and adjusted during the automatic calibration process. Averaged long-term water extraction was applied at the water supply wells. The calibration of the hydrogeological model is one of the most important steps during the model development. The knowledge about the parameters of the modeled system is often insufficient, especially for the large regional models, and a lack of geometric and hydraulic conductivity data is typical. The quasi-Newton optimization method L-BFGS-B is used for the calibration of the BAB model. Model is calibrated on the available water level measurements in monitoring wells and level measurements in boreholes during their installation. As the available data is not uniformly distributed over the covered area, weight coefficient is assigned to each borehole in order not to overestimate the clusters of boreholes. The year 2000 is chosen as the reference year for the present time scenario and the data from surrounding years are also taken into account but with smaller weighting coefficients. The objective function to be minimized by the calibration process is the weighted sum of squared differences between observed and modeled piezometric heads
A new selection metric for multiobjective hydrologic model calibration
NASA Astrophysics Data System (ADS)
Asadzadeh, Masoud; Tolson, Bryan A.; Burn, Donald H.
2014-09-01
A novel selection metric called Convex Hull Contribution (CHC) is introduced for solving multiobjective (MO) optimization problems with Pareto fronts that can be accurately approximated by a convex curve. The hydrologic model calibration literature shows that many biobjective calibration problems with a proper setup result in such Pareto fronts. The CHC selection approach identifies a subset of archived nondominated solutions whose map in the objective space forms convex approximation of the Pareto front. The optimization algorithm can sample solely from these solutions to more accurately approximate the convex shape of the Pareto front. It is empirically demonstrated that CHC improves the performance of Pareto Archived Dynamically Dimensioned Search (PA-DDS) when solving MO problems with convex Pareto fronts. This conclusion is based on the results of several benchmark mathematical problems and several hydrologic model calibration problems with two or three objective functions. The impact of CHC on PA-DDS performance is most evident when the computational budget is somewhat limited. It is also demonstrated that 1,000 solution evaluations (limited budget in this study) is sufficient for PA-DDS with CHC-based selection to achieve very high quality calibration results relative to the results achieved after 10,000 solution evaluations.
Calibration and validation of DRAINMOD to model bioretention hydrology
NASA Astrophysics Data System (ADS)
Brown, R. A.; Skaggs, R. W.; Hunt, W. F.
2013-04-01
SummaryPrevious field studies have shown that the hydrologic performance of bioretention cells varies greatly because of factors such as underlying soil type, physiographic region, drainage configuration, surface storage volume, drainage area to bioretention surface area ratio, and media depth. To more accurately describe bioretention hydrologic response, a long-term hydrologic model that generates a water balance is needed. Some current bioretention models lack the ability to perform long-term simulations and others have never been calibrated from field monitored bioretention cells with underdrains. All peer-reviewed models lack the ability to simultaneously perform both of the following functions: (1) model an internal water storage (IWS) zone drainage configuration and (2) account for soil-water content using the soil-water characteristic curve. DRAINMOD, a widely-accepted agricultural drainage model, was used to simulate the hydrologic response of runoff entering a bioretention cell. The concepts of water movement in bioretention cells are very similar to those of agricultural fields with drainage pipes, so many bioretention design specifications corresponded directly to DRAINMOD inputs. Detailed hydrologic measurements were collected from two bioretention field sites in Nashville and Rocky Mount, North Carolina, to calibrate and test the model. Each field site had two sets of bioretention cells with varying media depths, media types, drainage configurations, underlying soil types, and surface storage volumes. After 12 months, one of these characteristics was altered - surface storage volume at Nashville and IWS zone depth at Rocky Mount. At Nashville, during the second year (post-repair period), the Nash-Sutcliffe coefficients for drainage and exfiltration/evapotranspiration (ET) both exceeded 0.8 during the calibration and validation periods. During the first year (pre-repair period), the Nash-Sutcliffe coefficients for drainage, overflow, and exfiltration
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.
Model calibration criteria for estimating ecological flow characteristics
Vis, Marc; Knight, Rodney; Poole, Sandra; Wolfe, William J.; Seibert, Jan; Breuer, Lutz; Kraft, Philipp
2016-01-01
Quantification of streamflow characteristics in ungauged catchments remains a challenge. Hydrological modeling is often used to derive flow time series and to calculate streamflow characteristics for subsequent applications that may differ from those envisioned by the modelers. While the estimation of model parameters for ungauged catchments is a challenging research task in itself, it is important to evaluate whether simulated time series preserve critical aspects of the streamflow hydrograph. To address this question, seven calibration objective functions were evaluated for their ability to preserve ecologically relevant streamflow characteristics of the average annual hydrograph using a runoff model, HBV-light, at 27 catchments in the southeastern United States. Calibration trials were repeated 100 times to reduce parameter uncertainty effects on the results, and 12 ecological flow characteristics were computed for comparison. Our results showed that the most suitable calibration strategy varied according to streamflow characteristic. Combined objective functions generally gave the best results, though a clear underprediction bias was observed. The occurrence of low prediction errors for certain combinations of objective function and flow characteristic suggests that (1) incorporating multiple ecological flow characteristics into a single objective function would increase model accuracy, potentially benefitting decision-making processes; and (2) there may be a need to have different objective functions available to address specific applications of the predicted time series.
Automatic Calibration Method for a Storm Water Runoff Model
NASA Astrophysics Data System (ADS)
Barco, J.; Wong, K. M.; Hogue, T.; Stenstrom, M. K.
2007-12-01
Major metropolitan areas are characterized by continuous increases in imperviousness due to urban development. Increasing imperviousness increases runoff volume and maximum rates of runoff, with generally negative consequences for natural systems. To avoid environmental degradation, new development standards often prohibit increases in total runoff volume and may limit maximum flow rates. Methods to reduce runoff volume and maximum runoff rate are required, and solutions to the problems may benefit from the use of advanced models. In this study the U.S. Storm Water Management Model (SWMM) was adapted and calibrated to the Ballona Creek watershed, a large urban catchment in Southern California. A geographic information system (GIS) was used to process the input data and generate the spatial distribution of precipitation. An optimization procedure using the Complex Method was incorporated to estimate runoff parameters, and ten storms were used for calibration and validation. The calibrated model predicted the observed outputs with reasonable accuracy. A sensitivity analysis showed the impact of the model parameters, and results were most sensitive to imperviousness and impervious depression storage and least sensitive to Manning roughness for surface flow. Optimized imperviousness was greater than imperviousness predicted from landuse information. The results demonstrate that this methodology of integrating GIS and stormwater model with a constrained optimization technique can be applied to large watersheds, and can be a useful tool to evaluate alternative strategies to reduce runoff rate and volume.
Numerical modeling, calibration, and validation of an ultrasonic separator.
Cappon, Hans; Keesman, Karel J
2013-03-01
Our overall goal is to apply acoustic separation technology for the recovery of valuable particulate matter from wastewater in industry. Such large-scale separator systems require detailed design and evaluation to optimize the system performance at the earliest stage possible. Numerical models can facilitate and accelerate the design of this application; therefore, a finite element (FE) model of an ultrasonic particle separator is a prerequisite. In our application, the particle separator consists of a glass resonator chamber with a piezoelectric transducer attached to the glass by means of epoxy adhesive. Separation occurs most efficiently when the system is operated at its main eigenfrequency. The goal of the paper is to calibrate and validate a model of a demonstrator ultrasonic separator, preserving known physical parameters and estimating the remaining unknown or less-certain parameters to allow extrapolation of the model beyond the measured system. A two-step approach was applied to obtain a validated model of the separator. The first step involved the calibration of the piezoelectric transducer. The second step, the subject of this paper, involves the calibration and validation of the entire separator using nonlinear optimization techniques. The results show that the approach lead to a fully calibrated 2-D model of the empty separator, which was validated with experiments on a filled separator chamber. The large sensitivity of the separator to small variations indicated that such a system should either be made and operated within tight specifications to obtain the required performance or the operation of the system should be adaptable to cope with a slightly off-spec system, requiring a feedback controller.
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
Use of Cloud Computing to Calibrate a Highly Parameterized Model
NASA Astrophysics Data System (ADS)
Hayley, K. H.; Schumacher, J.; MacMillan, G.; Boutin, L.
2012-12-01
We present a case study using cloud computing to facilitate the calibration of a complex and highly parameterized model of regional groundwater flow. The calibration dataset consisted of many (~1500) measurements or estimates of static hydraulic head, a high resolution time series of groundwater extraction and disposal rates at 42 locations and pressure monitoring at 147 locations with a total of more than one million raw measurements collected over a ten year pumping history, and base flow estimates at 5 surface water monitoring locations. This modeling project was undertaken to assess the sustainability of groundwater withdrawal and disposal plans for insitu heavy oil extraction in Northeast Alberta, Canada. The geological interpretations used for model construction were based on more than 5,000 wireline logs collected throughout the 30,865 km2 regional study area (RSA), and resulted in a model with 28 slices, and 28 hydro stratigraphic units (average model thickness of 700 m, with aquifers ranging from a depth of 50 to 500 m below ground surface). The finite element FEFLOW model constructed on this geological interpretation had 331,408 nodes and required 265 time steps to simulate the ten year transient calibration period. This numerical model of groundwater flow required 3 hours to run on a on a server with two, 2.8 GHz processers and 16 Gb. RAM. Calibration was completed using PEST. Horizontal and vertical hydraulic conductivity as well as specific storage for each unit were independent parameters. For the recharge and the horizontal hydraulic conductivity in the three aquifers with the most transient groundwater use, a pilot point parameterization was adopted. A 7*7 grid of pilot points was defined over the RSA that defined a spatially variable horizontal hydraulic conductivity or recharge field. A 7*7 grid of multiplier pilot points that perturbed the more regional field was then superimposed over the 3,600 km2 local study area (LSA). The pilot point
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.
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.
Efficient Accommodation of Local Minima in Watershed Model Calibration
2006-02-02
of information if it does not display a currently valid OMB control number. 1. REPORT DATE 2006 2. REPORT TYPE 3. DATES COVERED 00-00-2006 to...should notify the user of this, and of the fact that parameter estimates forthcom- ing from the calibration process are nonunique . Whether or not an...challenges posed by parameter nonuniqueness and local objective function minima will lead to the necessity to carry out more model runs than that
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.
Xenon arc lamp spectral radiance modelling for satellite instrument calibration
NASA Astrophysics Data System (ADS)
Rolt, Stephen; Clark, Paul; Schmoll, Jürgen; Shaw, Benjamin J. R.
2016-07-01
Precise radiometric measurements play a central role in many areas of astronomical and terrestrial observation. We focus on the use of continuum light sources in the absolute radiometric calibration of detectors in an imaging spectrometer for space applications. The application, in this instance, revolves around the ground based calibration of the Sentinel-4/UVN instrument. This imaging spectrometer instrument is expected to be deployed in 2019 and will make spatially resolved spectroscopic measurements of atmospheric chemistry. The instrument, which operates across the UV/VIS and NIR spectrum from 305-775 nm, is designed to measure the absolute spectral radiance of the Earth and compare it with the absolute spectral irradiance of the Sun. Of key importance to the fidelity of these absolute measurements is the ground based calibration campaign. Continuum lamp sources that are temporally stable and are spatially well defined are central to this process. Xenon short arc lamps provide highly intense and efficient continuum illumination in a range extending from the ultra-violet to the infra-red and their spectrum is well matched to this specific application. Despite their widespread commercial use, certain aspects of their performance are not well documented in the literature. One of the important requirements in this calibration application is the delivery of highly uniform, collimated illumination at high radiance. In this process, it cannot be assumed that the xenon arc is a point source; the spatial distribution of the radiance must be characterised accurately. We present here careful measurements that thoroughly characterise the spatial distribution of the spectral radiance of a 1000W xenon lamp. A mathematical model is presented describing the spatial distribution. Temporal stability is another exceptionally important requirement in the calibration process. As such, the paper also describes strategies to re-inforce the temporal stability of the lamp output by
A Robust Bayesian Random Effects Model for Nonlinear Calibration Problems
Fong, Y.; Wakefield, J.; De Rosa, S.; Frahm, N.
2013-01-01
Summary In the context of a bioassay or an immunoassay, calibration means fitting a curve, usually nonlinear, through the observations collected on a set of samples containing known concentrations of a target substance, and then using the fitted curve and observations collected on samples of interest to predict the concentrations of the target substance in these samples. Recent technological advances have greatly improved our ability to quantify minute amounts of substance from a tiny volume of biological sample. This has in turn led to a need to improve statistical methods for calibration. In this paper, we focus on developing calibration methods robust to dependent outliers. We introduce a novel normal mixture model with dependent error terms to model the experimental noise. In addition, we propose a re-parameterization of the five parameter logistic nonlinear regression model that allows us to better incorporate prior information. We examine the performance of our methods with simulation studies and show that they lead to a substantial increase in performance measured in terms of mean squared error of estimation and a measure of the average prediction accuracy. A real data example from the HIV Vaccine Trials Network Laboratory is used to illustrate the methods. PMID:22551415
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.
MODELING NATURAL ATTENUATION OF FUELS WITH BIOPLUME III
A natural attenuation model that simulates the aerobic and anaerobic biodegradation of fuel hydrocarbons was developed. The resulting model, BIOPLUME III, demonstrates the importance of biodegradation in reducing contaminant concentrations in ground water. In hypothetical simulat...
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.
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.
BLOOD FLOW IN THE CIRCLE OF WILLIS: MODELING AND CALIBRATION*
DEVAULT, KRISTEN; GREMAUD, PIERRE A.; NOVAK, VERA; OLUFSEN, METTE S.; VERNIÈRES, GUILLAUME; ZHAO, PENG
2008-01-01
A numerical model based on one-dimensional balance laws and ad hoc zero-dimensional boundary conditions is tested against experimental data. The study concentrates on the circle of Willis, a vital subnetwork of the cerebral vasculature. The main goal is to obtain efficient and reliable numerical tools with predictive capabilities. The flow is assumed to obey the Navier–Stokes equations, while the mechanical reactions of the arterial walls follow a viscoelastic model. Like many previous studies, a dimension reduction is performed through averaging. Unlike most previous work, the resulting model is both calibrated and validated against in vivo data, more precisely transcranial Doppler data of cerebral blood velocity. The network considered has three inflow vessels and six outflow vessels. Inflow conditions come from the data, while outflow conditions are modeled. Parameters in the outflow conditions are calibrated using a subset of the data through ensemble Kalman filtering techniques. The rest of the data is used for validation. The results demonstrate the viability of the proposed approach. PMID:19043621
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
Simple Parametric Model for Intensity Calibration of Cassini Composite Infrared Spectrometer Data
NASA Technical Reports Server (NTRS)
Brasunas, J.; Mamoutkine, A.; Gorius, N.
2016-01-01
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.
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.
Analytical characterization of a Bruderhedral calibration target model
NASA Astrophysics Data System (ADS)
Cremona-Simmons, Peter M.
1996-06-01
The Army Research Laboratory (ARL) has constructed a variation of the bruderhedral calibration and radar cross section (RCS) target model and measured its radar characteristics in the field. A computer version of the same model was generated, and later characterized in both elevation and azimuth for validation. Our goal is to develop a millimeter-wave (MMW) signature generation tool for guidance integrated fuzing (GIF) systems and applications. Before realizing this goal, one must develop a test-bed of tools and approaches upon which to build. ARL has identified approaches to developing generic analytical target-signature models based on some existing electromagnetic scattering codes. A high-frequency RCS and signature prediction software model was selected to perform the radar analysis and provide a mechanism, a synthetic aperture radar (SAR) model, for recognizing prominent scatterers off high-fidelity target models. This method will assist us in creating suitable far- to near-field 3-D transitional models at MMW frequencies. Two target model descriptions were used in the signature prediction model: a flat facet format and a curved surface format. This paper introduces these software models, and some optics and SAR considerations relating to the test wavelength and the size of the target. Also, the simulated azimuthal and elevation response patterns, along with some results from the SAR model, are presented.
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.
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
Model Free Gate Design and Calibration For Superconducting Qubits
NASA Astrophysics Data System (ADS)
Egger, Daniel; Wilhelm, Frank
2014-03-01
Gates for superconducting qubits are realized by time dependent control pulses. The pulse shape for a specific gate depends on the parameters of the superconducting qubits, e.g. frequency and non-linearity. Based on ones knowledge of these parameters and using a specific model the pulse shape is determined either analytically or numerically using optimal control [arXiv:1306.6894, arXiv:1306.2279]. However the performance of the pulse is limited by the accuracy of the model. For a pulse with few parameters this is generally not a problem since it can be ``debugged'' manually. He we present an automated method for calibrating multiparameter pulses. We use the Nelder-Mead simplex method to close the control loop. This scheme uses the experiment as feedback and thus does not need a model. It requires few iterations and circumvents process tomogrophy, therefore making it a fast and versatile tool for gate design.
Mars Entry Atmospheric Data System Modeling, Calibration, and Error Analysis
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.; VanNorman, John; Siemers, Paul M.; Schoenenberger, Mark; Munk, Michelle M.
2014-01-01
The Mars Science Laboratory (MSL) Entry, Descent, and Landing Instrumentation (MEDLI)/Mars Entry Atmospheric Data System (MEADS) project installed seven pressure ports through the MSL Phenolic Impregnated Carbon Ablator (PICA) heatshield to measure heatshield surface pressures during entry. These measured surface pressures are used to generate estimates of atmospheric quantities based on modeled surface pressure distributions. In particular, the quantities to be estimated from the MEADS pressure measurements include the dynamic pressure, angle of attack, and angle of sideslip. This report describes the calibration of the pressure transducers utilized to reconstruct the atmospheric data and associated uncertainty models, pressure modeling and uncertainty analysis, and system performance results. The results indicate that the MEADS pressure measurement system hardware meets the project requirements.
Water Quality Model ROMS-ICM; Development and Calibration
NASA Astrophysics Data System (ADS)
Kim, C. S.; Lim, H.; Cerco, C. F.
2010-12-01
We have developed a three-dimensional water quality model (ROMS-ICM) that consists of hydrodynamic model of ROMS and eutrophication model of CE-QUAL-ICM. The ROMS in structured grid (Kim et al., 2007; Kim and Lim, 2009) has been linked with the unstructured ICM model (Cerco et al., 2010) by using newly coded linkage program. To have more flexibility on computation time and number of cells, the coupling mode has been developed for external link between two models. The ROMS-ICM has been tested for the validation by applying to the Saemangeum tidal lake and coastal waters. The model performance has been tested for the period 2007 - 2009 to validate the annual cycle of major water state variables such as temperature, salinity, chlorophyll, COD, dissolved oxygen, TP, TN etc. Major loadings of nutrients from river flows and controlling points at seawater gates of the tidal lake allow us to estimate the budget of state variables and internally produced loads. The ROMS-ICM is undergoing validation /verification procedure before practical use for the Saemangeum tidal lake and coastal waters in Korea. One of the longest coastal dykes in the world has been constructed in Saenangeum area in the southwest of Korean Peninsula (center location at 126.5E and 35.8N). A 33km-long dyke system connecting a few islands separates the open ocean from the landward water of 401 sq. km area that is planned for reclamation as part of coastal development. The ROMS-ICM has been set up for tidal lake and coastal waters. A observation-based calibration was consucted on the data of year 2009. Observation-based calibration for TN for the year of 2009 at a station in the tidal lake. Computed tidal flows showing the discharge waters.
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.
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
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.
Mathematical modelling to support traceable dynamic calibration of pressure sensors
NASA Astrophysics Data System (ADS)
Matthews, C.; Pennecchi, F.; Eichstädt, S.; Malengo, A.; Esward, T.; Smith, I.; Elster, C.; Knott, A.; Arrhén, F.; Lakka, A.
2014-06-01
This paper focuses on the mathematical modelling required to support the development of new primary standard systems for traceable calibration of dynamic pressure sensors. We address two fundamentally different approaches to realizing primary standards, specifically the shock tube method and the drop-weight method. Focusing on the shock tube method, the paper presents first results of system identification and discusses future experimental work that is required to improve the mathematical and statistical models. We use simulations to identify differences between the shock tube and drop-weight methods, to investigate sources of uncertainty in the system identification process and to assist experimentalists in designing the required measuring systems. We demonstrate the identification method on experimental results and draw conclusions.
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.
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.
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).
Optimizing the lithography model calibration algorithms for NTD process
NASA Astrophysics Data System (ADS)
Hu, C. M.; Lo, Fred; Yang, Elvis; Yang, T. H.; Chen, K. C.
2016-03-01
As patterns shrink to the resolution limits of up-to-date ArF immersion lithography technology, negative tone development (NTD) process has been an increasingly adopted technique to get superior imaging quality through employing bright-field (BF) masks to print the critical dark-field (DF) metal and contact layers. However, from the fundamental materials and process interaction perspectives, several key differences inherently exist between NTD process and the traditional positive tone development (PTD) system, especially the horizontal/vertical resist shrinkage and developer depletion effects, hence the traditional resist parameters developed for the typical PTD process have no longer fit well in NTD process modeling. In order to cope with the inherent differences between PTD and NTD processes accordingly get improvement on NTD modeling accuracy, several NTD models with different combinations of complementary terms were built to account for the NTD-specific resist shrinkage, developer depletion and diffusion, and wafer CD jump induced by sub threshold assistance feature (SRAF) effects. Each new complementary NTD term has its definite aim to deal with the NTD-specific phenomena. In this study, the modeling accuracy is compared among different models for the specific patterning characteristics on various feature types. Multiple complementary NTD terms were finally proposed to address all the NTD-specific behaviors simultaneously and further optimize the NTD modeling accuracy. The new algorithm of multiple complementary NTD term tested on our critical dark-field layers demonstrates consistent model accuracy improvement for both calibration and verification.
Root zone water quality model (RZWQM2): Model use, calibration and validation
Ma, Liwang; Ahuja, Lajpat; Nolan, B.T.; Malone, Robert; Trout, Thomas; Qi, Z.
2012-01-01
The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.
Development and Calibration of Reaction Models for Multilayered Nanocomposites
NASA Astrophysics Data System (ADS)
Vohra, Manav
This dissertation focuses on the development and calibration of reaction models for multilayered nanocomposites. The nanocomposites comprise sputter deposited alternating layers of distinct metallic elements. Specifically, we focus on the equimolar Ni-Al and Zr-Al multilayered systems. Computational models are developed to capture the transient reaction phenomena as well as understand the dependence of reaction properties on the microstructure, composition and geometry of the multilayers. Together with the available experimental data, simulations are used to calibrate the models and enhance the accuracy of their predictions. Recent modeling efforts for the Ni-Al system have investigated the nature of self-propagating reactions in the multilayers. Model fidelity was enhanced by incorporating melting effects due to aluminum [Besnoin et al. (2002)]. Salloum and Knio formulated a reduced model to mitigate computational costs associated with multi-dimensional reaction simulations [Salloum and Knio (2010a)]. However, exist- ing formulations relied on a single Arrhenius correlation for diffusivity, estimated for the self-propagating reactions, and cannot be used to quantify mixing rates at lower temperatures within reasonable accuracy [Fritz (2011)]. We thus develop a thermal model for a multilayer stack comprising a reactive Ni-Al bilayer (nanocalorimeter) and exploit temperature evolution measurements to calibrate the diffusion parameters associated with solid state mixing (≈720 K - 860 K) in the bilayer. The equimolar Zr-Al multilayered system when reacted aerobically is shown to exhibit slow aerobic oxidation of zirconium (in the intermetallic), sustained for about 2-10 seconds after completion of the formation reaction. In a collaborative effort, we aim to exploit the sustained heat release for bio-agent defeat application. A simplified computational model is developed to capture the extended reaction regime characterized by oxidation of Zr-Al multilayers
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.
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.
Finite element model calibration of a nonlinear perforated plate
NASA Astrophysics Data System (ADS)
Ehrhardt, David A.; Allen, Matthew S.; Beberniss, Timothy J.; Neild, Simon A.
2017-03-01
This paper presents a case study in which the finite element model for a curved circular plate is calibrated to reproduce both the linear and nonlinear dynamic response measured from two nominally identical samples. The linear dynamic response is described with the linear natural frequencies and mode shapes identified with a roving hammer test. Due to the uncertainty in the stiffness characteristics from the manufactured perforations, the linear natural frequencies are used to update the effective modulus of elasticity of the full order finite element model (FEM). The nonlinear dynamic response is described with nonlinear normal modes (NNMs) measured using force appropriation and high speed 3D digital image correlation (3D-DIC). The measured NNMs are used to update the boundary conditions of the full order FEM through comparison with NNMs calculated from a nonlinear reduced order model (NLROM). This comparison revealed that the nonlinear behavior could not be captured without accounting for the small curvature of the plate from manufacturing as confirmed in literature. So, 3D-DIC was also used to identify the initial static curvature of each plate and the resulting curvature was included in the full order FEM. The updated models are then used to understand how the stress distribution changes at large response amplitudes providing a possible explanation of failures observed during testing.
Simultaneous Semi-Distributed Model Calibration Guided by ...
Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a solid conceptual classification framework based on our understanding of dominant processes. A Hydrologic Landscape code (5 letter descriptor based on physical and climatic properties) describes each assessment unit area, and these units average area 60km2. The core function of these HL codes is to relate and transfer hydrologically meaningful information between watersheds without the need for streamflow time series. We present a novel approach based on the HL framework to answer the question “How can we calibrate models across separate watersheds simultaneously, guided by our understanding of dominant processes?“. We should be able to apply the same parameterizations to assessment units of common HL codes if 1) the Hydrologic Landscapes contain hydrologic information transferable between watersheds at a sub-watershed-scale and 2) we use a conceptual hydrologic model and parameters that reflect the hydrologic behavior of a watershed. In this study, This work specifically tests the ability or inability to use HL-codes to inform and share model parameters across watersheds in the Pacific Northwest. EPA’s Western Ecology Division has published and is refining a framework for defining la
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
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.
Barañao, P A; Hall, E R
2004-01-01
Activated Sludge Model No 3 (ASM3) was chosen to model an activated sludge system treating effluents from a mechanical pulp and paper mill. The high COD concentration and the high content of readily biodegradable substrates of the wastewater make this model appropriate for this system. ASM3 was calibrated based on batch respirometric tests using fresh wastewater and sludge from the treatment plant, and on analytical measurements of COD, TSS and VSS. The model, developed for municipal wastewater, was found suitable for fitting a variety of respirometric batch tests, performed at different temperatures and food to microorganism ratios (F/M). Therefore, a set of calibrated parameters, as well as the wastewater COD fractions, was estimated for this industrial wastewater. The majority of the calibrated parameters were in the range of those found in the literature.
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
Impact of Spatial Scale on Calibration and Model Output for a Grid-based SWAT Model
NASA Astrophysics Data System (ADS)
Pignotti, G.; Vema, V. K.; Rathjens, H.; Raj, C.; Her, Y.; Chaubey, I.; Crawford, M. M.
2014-12-01
The traditional implementation of the Soil and Water Assessment Tool (SWAT) model utilizes common landscape characteristics known as hydrologic response units (HRUs). Discretization into HRUs provides a simple, computationally efficient framework for simulation, but also represents a significant limitation of the model as spatial connectivity between HRUs is ignored. SWATgrid, a newly developed, distributed version of SWAT, provides modified landscape routing via a grid, overcoming these limitations. However, the current implementation of SWATgrid has significant computational overhead, which effectively precludes traditional calibration and limits the total number of grid cells in a given modeling scenario. Moreover, as SWATgrid is a relatively new modeling approach, it remains largely untested with little understanding of the impact of spatial resolution on model output. The objective of this study was to determine the effects of user-defined input resolution on SWATgrid predictions in the Upper Cedar Creek Watershed (near Auburn, IN, USA). Original input data, nominally at 30 m resolution, was rescaled for a range of resolutions between 30 and 4,000 m. A 30 m traditional SWAT model was developed as the baseline for model comparison. Monthly calibration was performed, and the calibrated parameter set was then transferred to all other SWAT and SWATgrid models to focus the effects of resolution on prediction uncertainty relative to the baseline. Model output was evaluated with respect to stream flow at the outlet and water quality parameters. Additionally, output of SWATgrid models were compared to output of traditional SWAT models at each resolution, utilizing the same scaled input data. A secondary objective considered the effect of scale on calibrated parameter values, where each standard SWAT model was calibrated independently, and parameters were transferred to SWATgrid models at equivalent scales. For each model, computational requirements were evaluated
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.
Modelling and calibration of a ring-shaped electrostatic meter
NASA Astrophysics Data System (ADS)
Zhang, Jianyong; Zhou, Bin; Xu, Chuanlong; Wang, Shimin
2009-02-01
Ring-shaped electrostatic flow meters can provide very useful information on pneumatically transported air-solids mixture. This type of meters are popular in measuring and controlling the pulverized coal flow distribution among conveyors leading to burners in coal-fired power stations, and they have also been used for research purposes, e.g. for the investigation of electrification mechanism of air-solids two-phase flow. In this paper, finite element method (FEM) is employed to analyze the characteristics of ring-shaped electrostatic meters, and a mathematic model has been developed to express the relationship between the meter's voltage output and the motion of charged particles in the sensing volume. The theoretical analysis and the test results using a belt rig demonstrate that the output of the meter depends upon many parameters including the characteristics of conditioning circuitry, the particle velocity vector, the amount and the rate of change of the charge carried by particles, the locations of particles and etc. This paper also introduces a method to optimize the theoretical model via calibration.
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.
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.
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...
NASA Astrophysics Data System (ADS)
Hughes, J. D.; White, J.
2013-12-01
For many numerical hydrologic models it is a challenge to quantitatively demonstrate that complex models are preferable to simpler models. Typically, a decision is made to develop and calibrate a complex model at the beginning of a study. The value of selecting a complex model over simpler models is commonly inferred from use of a model with fewer simplifications of the governing equations because it can be time consuming to develop another numerical code with data processing and parameter estimation functionality. High-level programming languages like Python can greatly reduce the effort required to develop and calibrate simple models that can be used to quantitatively demonstrate the increased value of a complex model. We have developed and calibrated a spatially-distributed surface-water/groundwater flow model for managed basins in southeast Florida, USA, to (1) evaluate the effect of municipal groundwater pumpage on surface-water/groundwater exchange, (2) investigate how the study area will respond to sea-level rise, and (3) explore combinations of these forcing functions. To demonstrate the increased value of this complex model, we developed a two-parameter conceptual-benchmark-discharge model for each basin in the study area. The conceptual-benchmark-discharge model includes seasonal scaling and lag parameters and is driven by basin rainfall. The conceptual-benchmark-discharge models were developed in the Python programming language and used weekly rainfall data. Calibration was implemented with the Broyden-Fletcher-Goldfarb-Shanno method available in the Scientific Python (SciPy) library. Normalized benchmark efficiencies calculated using output from the complex model and the corresponding conceptual-benchmark-discharge model indicate that the complex model has more explanatory power than the simple model driven only by rainfall.
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.
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.
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.
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
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.
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....
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)
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...
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.
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...
ERIC Educational Resources Information Center
Holman, Rebecca; Berger, Martijn P. F.
2001-01-01
Studied calibration designs that maximize the determinants of Fisher's information matrix on the item parameters for sets of polytomously scored items. Analyzed these items using a number of item response theory models. Results show that for the data and models used, a D-optimal calibration design for an answer or set of answers can reduce the…
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
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.
Why Bother to Calibrate? Model Consistency and the Value of Prior Information
NASA Astrophysics Data System (ADS)
Hrachowitz, Markus; Fovet, Ophelie; Ruiz, Laurent; Euser, Tanja; Gharari, Shervan; Nijzink, Remko; Savenije, Hubert; Gascuel-Odoux, Chantal
2015-04-01
Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by 4 calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce 20 hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by using prior information about the system to impose "prior constraints", inferred from expert knowledge and to ensure a model which behaves well with respect to the modeller's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model set-up exhibited increased performance in the independent test period and skill to reproduce all 20 signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if efficiently counter-balanced by available prior constraints, can increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge driven strategy of constraining models.
Why Bother and Calibrate? Model Consistency and the Value of Prior Information.
NASA Astrophysics Data System (ADS)
Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J. E.; Savenije, H.; Gascuel-Odoux, C.
2014-12-01
Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by 4 calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce 20 hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by using prior information about the system to impose "prior constraints", inferred from expert knowledge and to ensure a model which behaves well with respect to the modeller's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model set-up exhibited increased performance in the independent test period and skill to reproduce all 20 signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if efficiently counter-balanced by available prior constraints, can increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge driven strategy of constraining models.
Austin, Peter C; Steyerberg, Ewout W
2014-02-10
Predicting the probability of the occurrence of a binary outcome or condition is important in biomedical research. While assessing discrimination is an essential issue in developing and validating binary prediction models, less attention has been paid to methods for assessing model calibration. Calibration refers to the degree of agreement between observed and predicted probabilities and is often assessed by testing for lack-of-fit. The objective of our study was to examine the ability of graphical methods to assess the calibration of logistic regression models. We examined lack of internal calibration, which was related to misspecification of the logistic regression model, and external calibration, which was related to an overfit model or to shrinkage of the linear predictor. We conducted an extensive set of Monte Carlo simulations with a locally weighted least squares regression smoother (i.e., the loess algorithm) to examine the ability of graphical methods to assess model calibration. We found that loess-based methods were able to provide evidence of moderate departures from linearity and indicate omission of a moderately strong interaction. Misspecification of the link function was harder to detect. Visual patterns were clearer with higher sample sizes, higher incidence of the outcome, or higher discrimination. Loess-based methods were also able to identify the lack of calibration in external validation samples when an overfit regression model had been used. In conclusion, loess-based smoothing methods are adequate tools to graphically assess calibration and merit wider application.
2012-02-01
2007. Calibration of the NEMURO nutrient - phytoplankton -zooplankton food web model to a coastal ecosystem: Evaluation of an automated calibration...Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products . All product names and... product of its use both during and after the parameter estimation process. Another feature is that it is easily adapted by the inclusion of various
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.
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...
NASA Astrophysics Data System (ADS)
Razavi, S.; Tolson, B.
2012-04-01
Sophisticated hydrologic models may require very long run times to simulate for medium-sized and long data periods. With such models in hand, activities like automatic calibration, parameter space exploration, and uncertainty analysis become very computationally intensive as these models are required to repeatedly run hundreds or thousands of times. This study proposes a strategy to improve the computational efficiency of these activities by utilizing a secondary model in conjunction with the original model which works on a medium-sized or long calibration data period. The secondary model is basically the same as the original model but running on a relatively short data period which is a portion of the calibration data period. Certain relationships can be identified to relate the performance of the model on the entire calibration period with the performance of the secondary model on the short data period. Upon establishing such a relationship, the performance of the model for a given parameter set over the entire calibration period can be probabilistically predicted after running the model with the same parameter set over the short data period. The appeal of this strategy is demonstrated in a SWAT hydrologic model automatic calibration case study. A SWAT2000 model of the Cannonsville reservoir watershed in New York, the United States, with 14 parameters is calibrated over a 6-year period. Kriging is used to establish the relationship between the modelling performances for the entire calibration and short periods. Covariance Matrix Adaptation-Evolution Strategy (CMA-ES) is used as the optimizing engine to explore the parameter space during calibration. Numerical results show that the proposed strategy can significantly reduce the computational budget required in automatic calibration practices. Importantly, these efficiency gains are achievable with a minimum level of sacrifice of accuracy. Results also show that through this strategy the parameter space can be
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.
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
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.
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.
Development, Calibration and Application of Runoff Forecasting Models for the Allegheny River Basin
1988-06-01
coefficients are based on calibration with higher flows. The calibrated HECIF models are now in day-to-day use in the Pittsburgh District. As experience is...Interrelated Racords to Simulate TP-2S Digital Simulation of an Existing Water Resources System Streof low TP-29 Cmuter Applications in Continuing Eduacation
Modeling a self-calibrating thermocouple for use in a smart temperature measurement system
Ruppel, F.R. )
1990-12-01
A finite-difference computer-simulation program was developed to explain the thermodynamic behavior of the self-calibrating thermocouple. Based on a literature review and simulation analysis, a method was developed to recognize which point on the time-temperature curve is the calibration point. A description of the model and results of parametric studies are given.
System-Wide Calibration of River System Models: Opportunities and Challenges
NASA Astrophysics Data System (ADS)
Kim, S. S. H.; Hughes, J. D.; Dutta, D.; Vaze, J.
2014-12-01
Semi-distributed river system models are traditionally calibrated using a reach-by-reach calibration approach from that starts from headwater gauges and moves downstream toward the end of the system. Such a calibration method poses a unique problem since errors related to over-fitting, poor gauging data and uncertain physical connection are passed downstream. Reach-by-reach calibration, while efficient, cannot compensate for limited/poor calibration data of some gauges. To overcome the limitations of reach-by-reach calibration, a system calibration approach is proposed in which all the river reaches within a river basin are calibrated together using a global objective function for all stream flow gauges. In this approach, relative weights can be assigned in the global objective function for different gauges based on the magnitude and quality of available data. The system calibration approach was implemented in a river network covering 11 stream flow gauges within Murrumbidgee catchment (Australia). This study optimises flow at the selected gauges within the river network simultaneously (36 calibrated parameters) utilising a process-based semi-distributed river system model. The model includes processes such as routing, localised runoff, irrigation diversion, overbank flow and losses to groundwater. Goodness of fit is evaluated at the 11 gauges and a flow based weighting scheme is employed to find posterior distributions of parameters using an Approximate Bayesian Computation. The method is evaluated against a reach-by-reach calibration scheme. The comparison shows that the system calibration approach provides an overall improved goodness-of-fit by systematically de-valuing poor quality gauges providing an overall improved basin-wide performance. Clusters of viable parameter sets are determined from the posterior distributions and each examined to assess the effects of parameter uncertainty on internal model states. Such a method of calibration provides a lot more
Exploring a Three-Level Model of Calibration Accuracy
ERIC Educational Resources Information Center
Schraw, Gregory; Kuch, Fred; Gutierrez, Antonio P.; Richmond, Aaron S.
2014-01-01
We compared 5 different statistics (i.e., G index, gamma, "d'", sensitivity, specificity) used in the social sciences and medical diagnosis literatures to assess calibration accuracy in order to examine the relationship among them and to explore whether one statistic provided a best fitting general measure of accuracy. College…
A sequential approach to calibrate ecosystem models with multiple time series data
NASA Astrophysics Data System (ADS)
Oliveros-Ramos, Ricardo; Verley, Philippe; Echevin, Vincent; Shin, Yunne-Jai
2017-02-01
When models are aimed to support decision-making, their credibility is essential to consider. Model fitting to observed data is one major criterion to assess such credibility. However, due to the complexity of ecosystem models making their calibration more challenging, the scientific community has given more attention to the exploration of model behavior than to a rigorous comparison to observations. This work highlights some issues related to the comparison of complex ecosystem models to data and proposes a methodology for a sequential multi-phases calibration (or parameter estimation) of ecosystem models. We first propose two criteria to classify the parameters of a model: the model dependency and the time variability of the parameters. Then, these criteria and the availability of approximate initial estimates are used as decision rules to determine which parameters need to be estimated, and their precedence order in the sequential calibration process. The end-to-end (E2E) ecosystem model ROMS-PISCES-OSMOSE applied to the Northern Humboldt Current Ecosystem is used as an illustrative case study. The model is calibrated using an evolutionary algorithm and a likelihood approach to fit time series data of landings, abundance indices and catch at length distributions from 1992 to 2008. Testing different calibration schemes regarding the number of phases, the precedence of the parameters' estimation, and the consideration of time varying parameters, the results show that the multiple-phase calibration conducted under our criteria allowed to improve the model fit.
Calibration of the 7—Equation Transition Model for High Reynolds Flows at Low Mach
NASA Astrophysics Data System (ADS)
Colonia, S.; Leble, V.; Steijl, R.; Barakos, G.
2016-09-01
The numerical simulation of flows over large-scale wind turbine blades without considering the transition from laminar to fully turbulent flow may result in incorrect estimates of the blade loads and performance. Thanks to its relative simplicity and promising results, the Local-Correlation based Transition Modelling concept represents a valid way to include transitional effects into practical CFD simulations. However, the model involves coefficients that need tuning. In this paper, the γ—equation transition model is assessed and calibrated, for a wide range of Reynolds numbers at low Mach, as needed for wind turbine applications. An aerofoil is used to evaluate the original model and calibrate it; while a large scale wind turbine blade is employed to show that the calibrated model can lead to reliable solutions for complex three-dimensional flows. The calibrated model shows promising results for both two-dimensional and three-dimensional flows, even if cross-flow instabilities are neglected.
Regression Model Term Selection for the Analysis of Strain-Gage Balance Calibration Data
NASA Technical Reports Server (NTRS)
Ulbrich, Norbert Manfred; Volden, Thomas R.
2010-01-01
The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.
Matching Images to Models: Camera Calibration for 3-D Surface Reconstruction
NASA Technical Reports Server (NTRS)
Morris, Robin D.; Smelyanskiy, Vadim N.; Cheeseman. Peter C.; Norvig, Peter (Technical Monitor)
2001-01-01
In a previous paper we described a system which recursively recovers a super-resolved three dimensional surface model from a set of images of the surface. In that paper we assumed that the camera calibration for each image was known. In this paper we solve two problems. Firstly, if an estimate of the surface is already known, the problem is to calibrate a new image relative to the existing surface model. Secondly, if no surface estimate is available, the relative camera calibration between the images in the set must be estimated. This will allow an initial surface model to be estimated. Results of both types of estimation are given.
NASA Astrophysics Data System (ADS)
Li, Mingliang; Yang, Dawen; Chen, Jinsong; Hubbard, Susan S.
2012-08-01
In the process of calibrating distributed hydrological models, accounting for input uncertainty is important, yet challenging. In this study, we develop a Bayesian model to estimate parameters associated with a geomorphology-based hydrological model (GBHM). The GBHM model uses geomorphic characteristics to simplify model structure and physically based methods to represent hydrological processes. We divide the observed discharge into low- and high-flow data, and use the first-order autoregressive model to describe their temporal dependence. We consider relative errors in rainfall as spatially distributed variables and estimate them jointly with the GBHM parameters. The joint posterior probability distribution is explored using Markov chain Monte Carlo methods, which include Metropolis-Hastings, delay rejection adaptive Metropolis, and Gibbs sampling methods. We evaluate the Bayesian model using both synthetic and field data sets. The synthetic case study demonstrates that the developed method generally is effective in calibrating GBHM parameters and in estimating their associated uncertainty. The calibration ignoring input errors has lower accuracy and lower reliability compared to the calibration that includes estimation of the input errors, especially under model structure uncertainty. The field case study shows that calibration of GBHM parameters under complex field conditions remains a challenge. Although jointly estimating input errors and GBHM parameters improves the continuous ranked probability score and the consistency of the predictive distribution with the observed data, the improvement is incremental. To better calibrate parameters in a distributed model, such as GBHM here, we need to develop a more complex model and incorporate much more information.
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.
NASA Astrophysics Data System (ADS)
Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael
2014-05-01
Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global
Seismology on a Comet: Calibration Measurements, Modeling and Inversion
NASA Astrophysics Data System (ADS)
Faber, C.; Hoppe, J.; Knapmeyer, M.; Fischer, H.; Seidensticker, K. J.
2011-12-01
The Mission Rosetta was launched to comet 67P/Churyumov-Gerasimenko in 2004. It will finally reach the comet and will deliver the Lander Philae at the surface of the nucleus in November 2014. The Lander carries ten experiments, one of which is the Surface Electric Sounding and Acoustic Monitoring Experiment (SESAME). Part of this experiment is the Comet Acoustic Surface Sounding Experiment (CASSE) housed in the three feet of the lander. The primary goal of CASSE is to determine the elastic parameters of the surface material, like the Young's modulus and the Poisson ratio. Additional goals are the determination of shallow structure, quantification of porosity, and the location of activity spots and thermally and impact caused cometary activity. We conduct calibration measurements with accelerometers identical to the flight model. The goal of these measurements is to develop inversion procedures for travel times and to estimate the expected accuracy that CASSE can achieve in terms of elastic wave velocity, elastic parameters, and source location. The experiments are conducted mainly on sandy soil, in dry, wet or frozen conditions, and apart from buildings with their reflecting walls and artificial noise sources. We expect that natural sources, like thermal cracking at sunrise and sunset, can be located to an accuracy of about 10 degrees in direction and a few decimeters (1σ) in distance if occurring within the sensor triangle and from first arrivals alone. The accuracy of the direction is essentially independent of the distance, whereas distance determination depends critically on the identification of later arrivals. Determination of elastic wave velocities on the comet will be conducted with controlled sources at known positions and are likely to achieve an accuracy of σ=15% for the velocity of the first arriving wave. Limitations are due to the fixed source-receiver geometry and the wavelength emitted by the CASSE piezo-ceramic sources. In addition to the
McFadden, Sam X.; Korellis, John S.; Lee, Kenneth L.; Rogillio, Brendan R.; Hatch, Paul W.
2008-03-01
Experimental data for material plasticity and failure model calibration and validation were obtained from 6061-T651 aluminum, in the form of a 4-in. diameter extruded rod. Model calibration data were taken from smooth tension, notched tension, and shear tests. Model validation data were provided from experiments using thin-walled tube specimens subjected to path-dependent combinations of internal pressure, extension, and torsion.
Weighting observations in the context of calibrating ground-water models
Hill, M.C.; Tiedeman, C.R.
2002-01-01
This paper investigates four issues related to weighting observations in the context of ground-water models calibrated with nonlinear regression: (1) terminology, (2) determining values for the weighting, (3) measurement and model errors, and (4) the effect weighting can have on the accuracy of calibrated models and measures of uncertainty. It is shown that the confusing aspects of weighting can be managed, and are not a practical barrier to using regression methods.
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.
García-Usach, F; Ribes, J; Ferrer, J; Seco, A
2010-10-01
This paper presents the results of an experimental study for the modelling and calibration of denitrifying activity of polyphosphate accumulating organisms (PAOs) in full-scale WWTPs that incorporate simultaneous nitrogen and phosphorus removal. The convenience of using different yields under aerobic and anoxic conditions for modelling biological phosphorus removal processes with the ASM2d has been demonstrated. Thus, parameter η(PAO) in the model is given a physical meaning and represents the fraction of PAOs that are able to follow the DPAO metabolism. Using stoichiometric relationships, which are based on assumed biochemical pathways, the anoxic yields considered in the extended ASM2d can be obtained as a function of their respective aerobic yields. Thus, this modification does not mean an extra calibration effort to obtain the new parameters. In this work, an off-line calibration methodology has been applied to validate the model, where general relationships among stoichiometric parameters are proposed to avoid increasing the number of parameters to calibrate. The results have been validated through a UCT scheme pilot plant that is fed with municipal wastewater. The good concordance obtained between experimental and simulated values validates the use of anoxic yields as well as the calibration methodology. Deterministic modelling approaches, together with off-line calibration methodologies, are proposed to assist in decision-making about further process optimization in biological phosphate removal, since parameter values obtained by off-line calibration give valuable information about the activated sludge process such as the amount of DPAOs in the system.
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.
Neuromusculoskeletal model self-calibration for on-line sequential bayesian moment estimation
NASA Astrophysics Data System (ADS)
Bueno, Diana R.; Montano, L.
2017-04-01
Objective. Neuromusculoskeletal models involve many subject-specific physiological parameters that need to be adjusted to adequately represent muscle properties. Traditionally, neuromusculoskeletal models have been calibrated with a forward-inverse dynamic optimization which is time-consuming and unfeasible for rehabilitation therapy. Non self-calibration algorithms have been applied to these models. To the best of our knowledge, the algorithm proposed in this work is the first on-line calibration algorithm for muscle models that allows a generic model to be adjusted to different subjects in a few steps. Approach. In this paper we propose a reformulation of the traditional muscle models that is able to sequentially estimate the kinetics (net joint moments), and also its full self-calibration (subject-specific internal parameters of the muscle from a set of arbitrary uncalibrated data), based on the unscented Kalman filter. The nonlinearity of the model as well as its calibration problem have obliged us to adopt the sum of Gaussians filter suitable for nonlinear systems. Main results. This sequential Bayesian self-calibration algorithm achieves a complete muscle model calibration using as input only a dataset of uncalibrated sEMG and kinematics data. The approach is validated experimentally using data from the upper limbs of 21 subjects. Significance. The results show the feasibility of neuromusculoskeletal model self-calibration. This study will contribute to a better understanding of the generalization of muscle models for subject-specific rehabilitation therapies. Moreover, this work is very promising for rehabilitation devices such as electromyography-driven exoskeletons or prostheses.
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.
Automated model-based calibration of imaging spectrographs
NASA Astrophysics Data System (ADS)
Kosec, Matjaž; Bürmen, Miran; Tomaževič, Dejan; Pernuš, Franjo; Likar, Boštjan
2012-03-01
Hyper-spectral imaging has gained recognition as an important non-invasive research tool in the field of biomedicine. Among the variety of available hyperspectral imaging systems, systems comprising an imaging spectrograph, lens, wideband illumination source and a corresponding camera stand out for the short acquisition time and good signal to noise ratio. The individual images acquired by imaging spectrograph-based systems contain full spectral information along one spatial dimension. Due to the imperfections in the camera lens and in particular the optical components of the imaging spectrograph, the acquired images are subjected to spatial and spectral distortions, resulting in scene dependent nonlinear spectral degradations and spatial misalignments which need to be corrected. However, the existing correction methods require complex calibration setups and a tedious manual involvement, therefore, the correction of the distortions is often neglected. Such simplified approach can lead to significant errors in the analysis of the acquired hyperspectral images. In this paper, we present a novel fully automated method for correction of the geometric and spectral distortions in the acquired images. The method is based on automated non-rigid registration of the reference and acquired images corresponding to the proposed calibration object incorporating standardized spatial and spectral information. The obtained transformation was successfully used for sub-pixel correction of various hyperspectral images, resulting in significant improvement of the spectral and spatial alignment. It was found that the proposed calibration is highly accurate and suitable for routine use in applications involving either diffuse reflectance or transmittance measurement setups.
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.
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.
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.
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.
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...
NASA Astrophysics Data System (ADS)
Moeck, Christian; Von Freyberg, Jana; Schrimer, Maria
2016-04-01
An important question in recharge impact studies is how model choice, structure and calibration period affect recharge predictions. It is still unclear if a certain model type or structure is less affected by running the model on time periods with different hydrological conditions compared to the calibration period. This aspect, however, is crucial to ensure reliable predictions of groundwater recharge. In this study, we quantify and compare the effect of groundwater recharge model choice, model parametrization and calibration period in a systematic way. This analysis was possible thanks to a unique data set from a large-scale lysimeter in a pre-alpine catchment where daily long-term recharge rates are available. More specifically, the following issues are addressed: We systematically evaluate how the choice of hydrological models influences predictions of recharge. We assess how different parameterizations of models due to parameter non-identifiability affect predictions of recharge by applying a Monte Carlo approach. We systematically assess how the choice of calibration periods influences predictions of recharge within a differential split sample test focusing on the model performance under extreme climatic and hydrological conditions. Results indicate that all applied models (simple lumped to complex physically based models) were able to simulate the observed recharge rates for five different calibration periods. However, there was a marked impact of the calibration period when the complete 20 years validation period was simulated. Both, seasonal and annual differences between simulated and observed daily recharge rates occurred when the hydrological conditions were different to the calibration period. These differences were, however, less distinct for the physically based models, whereas the simpler models over- or underestimate the observed recharge depending on the considered season. It is, however, possible to reduce the differences for the simple models by
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
A Methodology for Calibrating a WATFLOOD Model of the Upper South Saskatchewan River
NASA Astrophysics Data System (ADS)
Dunning, C. F.; Soulis, R. D.; Craig, J. R.
2009-05-01
The upper South Saskatchewan River consists of the Red Deer River, the Bow River, and the Old Man River. With a contributing area of 120,000 km2, these three watersheds flow through a diverse range of land types including mountains, foothills and prairies. Using WATFLOOD, a model has been developed to simulate stream flow in this basin and this model is used as the case study for a straightforward calibration approach. The input for this model is interpolated rainfall data from twenty-three rain gauges throughout the basin, and the model output (stream flow) will be compared to measured stream flow data from thirty stream gauges. The basin is divided into nine land classes and four river classes. Because of the diversity of land types in this basin, proper identification of the parameters for individual land classes and river classes contributes significantly to the accuracy of the model. Critical land class and river class parameters are initially calibrated manually in representative sub-basins (comprised of >90%) of a single land class to determine the effect each parameter has on the system and to determine a reasonable starting estimate of each parameter. Once manual calibration is complete, DDS (Dynamically Dimensioned Search Algorithm) is used to automatically calibrate the model one sub-basin at a time. During this process only the parameters found significant during the manual calibration are altered and focus is on the land classes and river classes that dominate that sub-basin. The process of automated calibration is repeated once more but is done with multiple sub-basins and uses a stream flow weighting method. This is the final step towards a model that is calibrated to represent the diversity of the entire basin. The technique described is intended to be a general method for calibrating a regional scale model with diverse land types. The method is straight forward and allows adjusted parameters to provide relative accuracy over the entire basin.
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.
Modeling, Calibration, and Sensitivity Analysis of Coupled Land-Surface Models
NASA Astrophysics Data System (ADS)
Liu, Y.; Gupta, H. V.; Bastidas, L. A.; Sorooshian, S.
2002-12-01
To better understand various land-surface hydrological processes, it is desirable and pressing to extend land-surface modeling from off-line modes to coupled modes to explore the significance of various land surface-atmospheric interactions in regulating the energy and water balance of the hydrologic cycle. While it is extremely difficult to directly test the parameterizations of a global climate model due to the complexity, a locally coupled single-column model provides a favorable environment for investigations into the complicated interactions between the land surface and the overlying atmosphere. In this research, the off-line NCAR LSM and the coupled NCAR Single-column Community Climate Model (NCAR SCCM) are used. Extensive efforts have been focused on the impacts that the coupling of the two systems may have on the sensitivities of the land-surface model to both land-surface parameters and land-surface parameterizations. Additional efforts are directed to the comparisons of results from off-line and coupled calibration experiments using the optimization algorithm MOCOM-UA and IOP data sets from the Atmosphere Radiation Measurement-Cloud and Radiation Testbed (ARM-CART) project. Possibilities of calibrating some atmospheric parameters in the coupled model are also explored. Preliminary results show that the parameterization of surface energy and water balance is crucial in coupled systems and that the land-atmosphere coupling can significantly affect the estimations of land-surface parameters. In addition, it has been found that solar radiation and precipitation play an extremely important role in a coupled land-surface model by dominating the two-way interactions within the coupled system. This study will also enable us to investigate into the feasibility of applying the parameter estimation methods used for point-validations of LSM over grid-boxes in a coupled environment, and facilitate following studies on the effects that a coupled environment would have
Tian, Hai-Qing; Wang, Chun-Guang; Zhang, Hai-Jun; Yu, Zhi-Hong; Li, Jian-Kang
2012-11-01
Outlier samples strongly influence the precision of the calibration model in soluble solids content measurement of melons using NIR Spectra. According to the possible sources of outlier samples, three methods (predicted concentration residual test; Chauvenet test; leverage and studentized residual test) were used to discriminate these outliers respectively. Nine suspicious outliers were detected from calibration set which including 85 fruit samples. Considering the 9 suspicious outlier samples maybe contain some no-outlier samples, they were reclaimed to the model one by one to see whether they influence the model and prediction precision or not. In this way, 5 samples which were helpful to the model joined in calibration set again, and a new model was developed with the correlation coefficient (r) 0. 889 and root mean square errors for calibration (RMSEC) 0.6010 Brix. For 35 unknown samples, the root mean square errors prediction (RMSEP) was 0.854 degrees Brix. The performance of this model was more better than that developed with non outlier was eliminated from calibration set (r = 0.797, RMSEC= 0.849 degrees Brix, RMSEP = 1.19 degrees Brix), and more representative and stable with all 9 samples were eliminated from calibration set (r = 0.892, RMSEC = 0.605 degrees Brix, RMSEP = 0.862 degrees).
NASA Astrophysics Data System (ADS)
Zhang, Fangkun; Liu, Tao; Wang, Xue Z.; Liu, Jingxiang; Jiang, Xiaobin
2017-02-01
In this paper calibration model building based on using an ATR-FTIR spectroscopy is investigated for in-situ measurement of the solution concentration during a cooling crystallization process. The cooling crystallization of L-glutamic Acid (LGA) as a case is studied here. It was found that using the metastable zone (MSZ) data for model calibration can guarantee the prediction accuracy for monitoring the operating window of cooling crystallization, compared to the usage of undersaturated zone (USZ) spectra for model building as traditionally practiced. Calibration experiments were made for LGA solution under different concentrations. Four candidate calibration models were established using different zone data for comparison, by using a multivariate partial least-squares (PLS) regression algorithm for the collected spectra together with the corresponding temperature values. Experiments under different process conditions including the changes of solution concentration and operating temperature were conducted. The results indicate that using the MSZ spectra for model calibration can give more accurate prediction of the solution concentration during the crystallization process, while maintaining accuracy in changing the operating temperature. The primary reason of prediction error was clarified as spectral nonlinearity for in-situ measurement between USZ and MSZ. In addition, an LGA cooling crystallization experiment was performed to verify the sensitivity of these calibration models for monitoring the crystal growth process.
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...
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
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.
Effects of FRAX(®) model calibration on intervention rates: a simulation study.
Leslie, William D; Lix, Lisa M
2011-01-01
The WHO fracture risk assessment tool (FRAX(®)) estimates an individual's 10-yr major osteoporotic and hip fracture probabilities using a tool customized to the fracture epidemiology of a specific population. Incorrect model calibration could therefore affect performance of the model in clinical practice. The current analysis was undertaken to explore how simulated miscalibration in the FRAX(®) tool would affect the numbers of individuals meeting specific intervention criteria (10-yr major osteoporotic fracture probability ≥20%, 10-yr hip fracture probability ≥3%). The study cohort included 36,730 women and 2873 men aged 50yr and older with FRAX(®) probability estimates using femoral neck bone mineral density. We simulated relative miscalibration error in 10% increments from -50% to +50% relative to a correctly calibrated FRAX(®) model. We found that small changes in model calibration (even on the order of 10%) had large effects on the number of individuals qualifying for treatment. There was a steep gradient in the relationship between relative change in calibration and relative change in intervention rates: for every 1% change in calibration, there was a 2.5% change in intervention rates for women and 4.1% for men. For hip fracture probability, the gradient of the relationship was closer to unity. These results highlight the importance of FRAX(®) model calibration, and speak to the importance of using high-quality fracture epidemiology in constructing FRAX(®) tools.
Nonlinear model calibration of a shear wall building using time and frequency data features
NASA Astrophysics Data System (ADS)
Asgarieh, Eliyar; Moaveni, Babak; Barbosa, Andre R.; Chatzi, Eleni
2017-02-01
This paper investigates the effects of different factors on the performance of nonlinear model updating for a seven-story shear wall building model. The accuracy of calibrated models using different data features and modeling assumptions is studied by comparing the time and frequency responses of the models with the exact simulated ones. Simplified nonlinear finite element models of the shear wall building are calibrated so that the misfit between the considered response data features of the models and the structure is minimized. A refined FE model of the test structure, which was calibrated manually to match the shake table test data, is used instead of the real structure for this performance evaluation study. The simplified parsimonious FE models are composed of simple nonlinear beam-column fiber elements with nonlinearity infused in them by assigning generated hysteretic nonlinear material behaviors to uniaxial stress-strain relationship of the fibers. Four different types of data features and their combinations are used for model calibration: (1) time-varying instantaneous modal parameters, (2) displacement time histories, (3) acceleration time histories, and (4) dissipated hysteretic energy. It has been observed that the calibrated simplified FE models can accurately predict the nonlinear structural response in the absence of significant modeling errors. In the last part of this study, the physics-based models are further simplified for casting into state-space formulation and a real-time identification is performed using an Unscented Kalman filter. It has been shown that the performance of calibrated state-space models can be satisfactory when reasonable modeling assumptions are used.
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)
Athira, P.; Sudheer, K.
2013-12-01
Parameter estimation is one of the major tasks in the application of any physics based distributed model. Generally the calibration does not consider the heterogeneity of the parameters across the basin, and as a result the model simulation conforms to the location for which it has been calibrated for. However, the major advantage of distributed hydrological models is to have reasonably good simulations on various locations in the watershed, including ungauged locations. While multi-site calibration can address this issue to some extent, the availability of more gauge sites in a watershed is always not guaranteed. When single site calibration is performed, generally a uniform variation of the parameters is considered across the basin which does not ensure the true heterogeneity of the parameters in the basin. The primary objective of this study is to compare the effect of uniform variation of the parameter with a procedure that identifies actual heterogeneity of the parameters across the basin, while performing calibration of distributed hydrological models. In order to demonstrate the objective, a case study of two watersheds in the USA using the model, Soil and Water Assessment Tool (SWAT) is presented and discussed. Initially, the SWAT model is calibrated for both the watersheds in the traditional way considering uniform variation of the sensitive parameters during the calibration. Further, the hydrological response units (HRU) delineated in the SWAT are classified into various clusters based the land use, soil type and slope. A random perturbation of the parameters is performed in these clusters during calibration. The rationale behind this approach was to identify plausible parameter values that simulate the hydrological process in these clusters appropriately. The proposed procedure is applied to both the basins. The results indicate that the simulations obtained for upstream ungauged locations (other than that used for calibration) are much better when a
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.
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.
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 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.
Modeling and Calibration of a Novel One-Mirror Galvanometric Laser Scanner
Yu, Chengyi; Chen, Xiaobo; Xi, Juntong
2017-01-01
A laser stripe sensor has limited application when a point cloud of geometric samples on the surface of the object needs to be collected, so a galvanometric laser scanner is designed by using a one-mirror galvanometer element as its mechanical device to drive the laser stripe to sweep along the object. A novel mathematical model is derived for the proposed galvanometer laser scanner without any position assumptions and then a model-driven calibration procedure is proposed. Compared with available model-driven approaches, the influence of machining and assembly errors is considered in the proposed model. Meanwhile, a plane-constraint-based approach is proposed to extract a large number of calibration points effectively and accurately to calibrate the galvanometric laser scanner. Repeatability and accuracy of the galvanometric laser scanner are evaluated on the automobile production line to verify the efficiency and accuracy of the proposed calibration method. Experimental results show that the proposed calibration approach yields similar measurement performance compared with a look-up table calibration method. PMID:28098844
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.
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.
Modeling and Calibration of a Novel One-Mirror Galvanometric Laser Scanner.
Yu, Chengyi; Chen, Xiaobo; Xi, Juntong
2017-01-15
A laser stripe sensor has limited application when a point cloud of geometric samples on the surface of the object needs to be collected, so a galvanometric laser scanner is designed by using a one-mirror galvanometer element as its mechanical device to drive the laser stripe to sweep along the object. A novel mathematical model is derived for the proposed galvanometer laser scanner without any position assumptions and then a model-driven calibration procedure is proposed. Compared with available model-driven approaches, the influence of machining and assembly errors is considered in the proposed model. Meanwhile, a plane-constraint-based approach is proposed to extract a large number of calibration points effectively and accurately to calibrate the galvanometric laser scanner. Repeatability and accuracy of the galvanometric laser scanner are evaluated on the automobile production line to verify the efficiency and accuracy of the proposed calibration method. Experimental results show that the proposed calibration approach yields similar measurement performance compared with a look-up table calibration method.
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
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.
Inaccuracy Determination in Mathematical Model of Labsocs Efficiency Calibration Program
NASA Astrophysics Data System (ADS)
Kuznetsov, M.; Nikishkin, T.; Chursin, S.
2016-08-01
The study of radioactive materials quantitative inaccuracy determination caused by semiconductor detector aging is presented in the article. The study was conducted using a p- type coaxial GC 1518 detector made of a high-purity germanium produced by Canberra Company and LabSOCS mathematical efficiency calibration program. It was discovered that during 8 years of operation the efficiency of the detector had decreased due to increase of the dead layer of the germanium crystal. Increasing the thickness of the dead layer leads to 2 effects, which influence on the efficiency decrease: the shielding effect and the effect of reducing the active volume of the germanium crystal. It is found that the shielding effect contributes at energies below 88 keV. At energies above 88 keV the inaccuracy is connected with the decrease of the germanium crystal active volume, caused by lithium thermal diffusion.
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
NASA Astrophysics Data System (ADS)
Felix, D.; Abgottspon, A.; Albayrak, I.; Boes, R. M.
2016-11-01
At medium- and high-head hydropower plants (HPPs) on sediment-laden rivers, hydro-abrasive erosion on hydraulic turbines is a major economic issue. For optimization of such HPPs, there is an interest in equations to predict erosion depths. Such a semi-empirical equation suitable for engineering practice is proposed in the relevant guideline of the International Electrotechnical Commission (IEC 62364). However, for Pelton turbines no numerical values of the model's calibration parameters have been available yet. In the scope of a research project at the high-head HPP Fieschertal, Switzerland, the particle load and the erosion on the buckets of two hard-coated 32 MW-Pelton runners have been measured since 2012. Based on three years of field data, the numerical values of a group of calibration parameters of the IEC erosion model were determined for five application cases: (i) reduction of splitter height, (ii) increase of splitter width and (iii) increase of cut-out depth due to erosion of mainly base material, as well as erosion of coating on (iv) the splitter crests and (v) inside the buckets. Further laboratory and field investigations are recommended to quantify the effects of individual parameters as well as to improve, generalize and validate erosion models for uncoated and coated Pelton turbines.
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.
Binary Classifier Calibration using an Ensemble of Near Isotonic Regression Models.
Naeini, Mahdi Pakdaman; Cooper, Gregory F
2016-12-01
Learning accurate probabilistic models from data is crucial in many practical tasks in data mining. In this paper we present a new non-parametric calibration method called ensemble of near isotonic regression (ENIR). The method can be considered as an extension of BBQ [20], a recently proposed calibration method, as well as the commonly used calibration method based on isotonic regression (IsoRegC) [27]. ENIR is designed to address the key limitation of IsoRegC which is the monotonicity assumption of the predictions. Similar to BBQ, the method post-processes the output of a binary classifier to obtain calibrated probabilities. Thus it can be used with many existing classification models to generate accurate probabilistic predictions. We demonstrate the performance of ENIR on synthetic and real datasets for commonly applied binary classification models. Experimental results show that the method outperforms several common binary classifier calibration methods. In particular on the real data, ENIR commonly performs statistically significantly better than the other methods, and never worse. It is able to improve the calibration power of classifiers, while retaining their discrimination power. The method is also computationally tractable for large scale datasets, as it is O(N log N) time, where N is the number of samples.
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.
Binary Classifier Calibration using an Ensemble of Near Isotonic Regression Models
Naeini, Mahdi Pakdaman; Cooper, Gregory F.
2017-01-01
Learning accurate probabilistic models from data is crucial in many practical tasks in data mining. In this paper we present a new non-parametric calibration method called ensemble of near isotonic regression (ENIR). The method can be considered as an extension of BBQ [20], a recently proposed calibration method, as well as the commonly used calibration method based on isotonic regression (IsoRegC) [27]. ENIR is designed to address the key limitation of IsoRegC which is the monotonicity assumption of the predictions. Similar to BBQ, the method post-processes the output of a binary classifier to obtain calibrated probabilities. Thus it can be used with many existing classification models to generate accurate probabilistic predictions. We demonstrate the performance of ENIR on synthetic and real datasets for commonly applied binary classification models. Experimental results show that the method outperforms several common binary classifier calibration methods. In particular on the real data, ENIR commonly performs statistically significantly better than the other methods, and never worse. It is able to improve the calibration power of classifiers, while retaining their discrimination power. The method is also computationally tractable for large scale datasets, as it is O(N log N) time, where N is the number of samples. PMID:28316511
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…
Verification and Calibration of an Eddy-Resolving Model of the Gulf of Mexico
1991-05-01
Techniques for verifying and calibrating an eddy-resolving ocean circulation model have been applied to a model of the Gulf of Mexico (GOM). Various...eddy. Although the model can simulate the movement and translation velocities of actual Gulf of Mexico eddies, it does not reproduce the interior flow
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…
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.
Basin-scale geothermal model calibration: experience from the Perth Basin, Australia
NASA Astrophysics Data System (ADS)
Wellmann, Florian; Reid, Lynn
2014-05-01
The calibration of large-scale geothermal models for entire sedimentary basins is challenging as direct measurements of rock properties and subsurface temperatures are commonly scarce and the basal boundary conditions poorly constrained. Instead of the often applied "trial-and-error" manual model calibration, we examine here if we can gain additional insight into parameter sensitivities and model uncertainty with a model analysis and calibration study. Our geothermal model is based on a high-resolution full 3-D geological model, covering an area of more than 100,000 square kilometers and extending to a depth of 55 kilometers. The model contains all major faults (>80 ) and geological units (13) for the entire basin. This geological model is discretised into a rectilinear mesh with a lateral resolution of 500 x 500 m, and a variable resolution at depth. The highest resolution of 25 m is applied to a depth range of 1000-3000 m where most temperature measurements are available. The entire discretised model consists of approximately 50 million cells. The top thermal boundary condition is derived from surface temperature measurements on land and ocean floor. The base of the model extents below the Moho, and we apply the heat flux over the Moho as a basal heat flux boundary condition. Rock properties (thermal conductivity, porosity, and heat production) have been compiled from several existing data sets. The conductive geothermal forward simulation is performed with SHEMAT, and we then use the stand-alone capabilities of iTOUGH2 for sensitivity analysis and model calibration. Simulated temperatures are compared to 130 quality weighted bottom hole temperature measurements. The sensitivity analysis provided a clear insight into the most sensitive parameters and parameter correlations. This proved to be of value as strong correlations, for example between basal heat flux and heat production in deep geological units, can significantly influence the model calibration procedure
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
Calibration of a large-scale semi-distributed hydrological model for the continental United States
NASA Astrophysics Data System (ADS)
Li, S.; Lohmann, D.
2011-12-01
Recent major flood losses raised the awareness of flood risk worldwide. In large-scale (e.g., country) flood simulation, semi-distributed hydrological model shows its advantage in capturing spatial heterogeneity of hydrological characteristics within a basin with relatively low computational cost. However, it is still very challenging to calibrate the model over large scale and a wide variety of hydroclimatic conditions. The objectives of this study are (1) to compare the effectiveness of state-of-the-art evolutionary multiobjective algorithms in calibrating a semi-distributed hydrological model used in the RMS flood loss model; (2) to calibrate the model over the entire continental United States. Firstly, the computational efficiency of the following four algorithms is evaluated: the Non-Dominated Sorted Genetic Algorithm II (NSGAII), the Strength Pareto Evolutionary Algorithm 2 (SPEA2), the Epsilon-Dominance Non-Dominated Sorted Genetic Algorithm II (ɛ-NSGAII), and the Epsilon-Dominance Multi-Objective Evolutionary Algorithm (ɛMOEA). The test was conducted on four river basins with a wide variety of hydro-climatic conditions in US. The optimization objectives include RMSE and high-flow RMSE. Results of the analysis indicate that NSGAII has the best performance in terms of effectiveness and stability. Then we applied the modified version of NSGAII to calibrate the hydrological model over the entire continental US. Comparing with the observation and published data shows the performance of the calibrated model is good overall. This well-calibrated model allows a more accurate modeling of flood risk and loss in the continental United States. Furthermore it will allow underwriters to better manage the exposure.
Development of a univariate calibration model for pharmaceutical analysis based on NIR spectra.
Blanco, M; Cruz, J; Bautista, M
2008-12-01
Near-infrared spectroscopy (NIRS) has been widely used in the pharmaceutical field because of its ability to provide quality information about drugs in near-real time. In practice, however, the NIRS technique requires construction of multivariate models in order to correct collinearity and the typically poor selectivity of NIR spectra. In this work, a new methodology for constructing simple NIR calibration models has been developed, based on the spectrum for the target analyte (usually the active principle ingredient, API), which is compared with that of the sample in order to calculate a correlation coefficient. To this end, calibration samples are prepared spanning an adequate concentration range for the API and their spectra are recorded. The model thus obtained by relating the correlation coefficient to the sample concentration is subjected to least-squares regression. The API concentration in validation samples is predicted by interpolating their correlation coefficients in the straight calibration line previously obtained. The proposed method affords quantitation of API in pharmaceuticals undergoing physical changes during their production process (e.g. granulates, and coated and non-coated tablets). The results obtained with the proposed methodology, based on correlation coefficients, were compared with the predictions of PLS1 calibration models, with which a different model is required for each type of sample. Error values lower than 1-2% were obtained in the analysis of three types of sample using the same model; these errors are similar to those obtained by applying three PLS models for granules, and non-coated and coated samples. Based on the outcome, our methodology is a straightforward choice for constructing calibration models affording expeditious prediction of new samples with varying physical properties. This makes it an effective alternative to multivariate calibration, which requires use of a different model for each type of sample, depending on
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.
When are multiobjective calibration trade-offs in hydrologic models meaningful?
NASA Astrophysics Data System (ADS)
Kollat, J. B.; Reed, P. M.; Wagener, T.
2012-03-01
This paper applies a four-objective calibration strategy focusing on peak flows, low flows, water balance, and flashiness to 392 model parameter estimation experiment (MOPEX) watersheds across the United States. Our analysis explores the influence of model structure by analyzing how the multiobjective calibration trade-offs for two conceptual hydrologic models, the Hydrology Model (HYMOD) and the Hydrologiska Byråns Vattenbalansavdelning (HBV) model, compare for each of the 392 catchments. Our results demonstrate that for modern multiobjective calibration frameworks to identify any meaningful measure of model structural failure, users must be able to carefully control the precision by which they evaluate their trade-offs. Our study demonstrates that the concept of epsilon-dominance provides an effective means of attaining bounded and meaningful hydrologic model calibration trade-offs. When analyzed at an appropriate precision, we found that meaningful multiobjective trade-offs are far less frequent than prior literature has suggested. However, when trade-offs do exist at a meaningful precision, they have significant value for supporting hydrologic model selection, distinguishing core model deficiencies, and identifying hydroclimatic regions where hydrologic model prediction is highly challenging.
Geng, Zongyu; Yang, Feng; Chen, Xi; Wu, Nianqiang
2015-09-01
It remains a challenge to accurately calibrate a sensor subject to environmental drift. The calibration task for such a sensor is to quantify the relationship between the sensor's response and its exposure condition, which is specified by not only the analyte concentration but also the environmental factors such as temperature and humidity. This work developed a Gaussian Process (GP)-based procedure for the efficient calibration of sensors in drifting environments. Adopted as the calibration model, GP is not only able to capture the possibly nonlinear relationship between the sensor responses and the various exposure-condition factors, but also able to provide valid statistical inference for uncertainty quantification of the target estimates (e.g., the estimated analyte concentration of an unknown environment). Built on GP's inference ability, an experimental design method was developed to achieve efficient sampling of calibration data in a batch sequential manner. The resulting calibration procedure, which integrates the GP-based modeling and experimental design, was applied on a simulated chemiresistor sensor to demonstrate its effectiveness and its efficiency over the traditional method.
Caruso, Rosario; Gambino, Grazia Laura; Scordino, Monica; Sabatino, Leonardo; Traulo, Pasqualino; Gagliano, Giacomo
2011-12-01
The influence of the wine distillation process on methanol content has been determined by quantitative analysis using gas chromatographic flame ionization (GC-FID) detection. A comparative study between direct injection of diluted wine and injection of distilled wine was performed. The distillation process does not affect methanol quantification in wines in proportions higher than 10%. While quantification performed on distilled samples gives more reliable results, a screening method for wine injection after a 1:5 water dilution could be employed. The proposed technique was found to be a compromise between the time consuming distillation process and direct wine injection. In the studied calibration range, the stability of the volatile compounds in the reference solution is concentration-dependent. The stability is higher in the less concentrated reference solution. To shorten the operation time, a stronger temperature ramp and carrier flow rate was employed. With these conditions, helium consumption and column thermal stress were increased. However, detection limits, calibration limits, and analytical method performances are not affected substantially by changing from normal to forced GC conditions. Statistical data evaluation were made using both ordinary (OLS) and bivariate least squares (BLS) calibration models. Further confirmation was obtained that limit of detection (LOD) values, calculated according to the 3sigma approach, are lower than the respective Hubaux-Vos (H-V) calculation method. H-V LOD depends upon background noise, calibration parameters and the number of reference standard solutions employed in producing the calibration curve. These remarks are confirmed by both calibration models used.
Geng, Zongyu; Yang, Feng; Chen, Xi; Wu, Nianqiang
2016-01-01
It remains a challenge to accurately calibrate a sensor subject to environmental drift. The calibration task for such a sensor is to quantify the relationship between the sensor’s response and its exposure condition, which is specified by not only the analyte concentration but also the environmental factors such as temperature and humidity. This work developed a Gaussian Process (GP)-based procedure for the efficient calibration of sensors in drifting environments. Adopted as the calibration model, GP is not only able to capture the possibly nonlinear relationship between the sensor responses and the various exposure-condition factors, but also able to provide valid statistical inference for uncertainty quantification of the target estimates (e.g., the estimated analyte concentration of an unknown environment). Built on GP’s inference ability, an experimental design method was developed to achieve efficient sampling of calibration data in a batch sequential manner. The resulting calibration procedure, which integrates the GP-based modeling and experimental design, was applied on a simulated chemiresistor sensor to demonstrate its effectiveness and its efficiency over the traditional method. PMID:26924894
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.
Radiative type III seesaw model and its collider phenomenology
NASA Astrophysics Data System (ADS)
von der Pahlen, Federico; Palacio, Guillermo; Restrepo, Diego; Zapata, Oscar
2016-08-01
We analyze the present bounds of a scotogenic model, the radiative type III seesaw, in which an additional scalar doublet and at least two fermion triplets of S U (2 )L are added to the Standard Model. In the radiative type III seesaw, the new physics (NP) sector is odd under an exact global Z2 symmetry. This symmetry guaranties that the lightest NP neutral particle is stable, providing a natural dark matter candidate, and leads to naturally suppressed neutrino masses generated by a one-loop realization of an effective Weinberg operator. We focus on the region with the highest sensitivity in present and future LHC searches, with light scalar dark matter and at least one NP fermion triplet at the sub-TeV scale. This region allows for significant production cross sections of NP fermion pairs at the LHC. We reinterpret a set of searches for supersymmetric particles at the LHC obtained using the package CheckMATE, to set limits on our model as a function of the masses of the NP particles and their Yukawa interactions. The most sensitive search channel is found to be dileptons plus missing transverse energy. In order to target the case of tau enhanced decays and the case of compressed spectra, we reinterpret the recent slepton and chargino search bounds by ATLAS. For a lightest NP fermion triplet with a maximal branching ratio to either electrons or muons, we exclude NP fermion masses of up to 650 GeV, while this bound is reduced to approximately 400 GeV in the tau-philic case. Allowing for a general flavor structure, we set limits on the Yukawa couplings, which are directly related to the neutrino flavor structure.
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.
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.
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
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.
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.
Tweaking Model Parameters: Manual Adjustment and Self Calibration
NASA Astrophysics Data System (ADS)
Schulz, B.; Tuffs, R. J.; Laureijs, R. J.; Lu, N.; Peschke, S. B.; Gabriel, C.; Khan, I.
2002-12-01
The reduction of P32 data is not always straight forward and the application of the transient model needs tight control by the user. This paper describes how to access the model parameters within the P32Tools software and how to work with the "Inspect signals per pixel" panel, in order to explore the parameter space and improve the model fit.
KINEROS2/AGWA: Model use, calibration, and validation
Technology Transfer Automated Retrieval System (TEKTRAN)
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. Development and improvement of KINEROS continued from the 1960s on a vari...
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.
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)
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
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…
Technology Transfer Automated Retrieval System (TEKTRAN)
Process-based watershed models typically require a large number of parameters to describe complex hydrologic and biogeochemical processes in highly variable environments. Most of such parameters are not directly measured in field and require calibration, in most cases through matching modeled fluxes...
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.
NASA Astrophysics Data System (ADS)
Corbari, Chiara; Manchini, Marco; Li, Jiren; Su, Zhongbo
2013-12-01
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 from satellite remote sensing. This study proposes a methodology for the calibration of distributed hydrological models at basin scale through the constraints on an internal model variable using remote sensing data of land surface temperature. The model (FEST-EWB) algorithm solves the system of energy and mass balances in term of the equilibrium pixel temperature or representative equilibrium temperature that governs the fluxes of energy and mass over the basin domain. This equilibrium surface temperature, which is a critical model state variable, is compared to land surface temperature from MODIS and AATSR. So soil hydraulic parameters and vegetation variables will be calibrated according to the comparison between observed and simulated land surface temperature minimizing the errors. A similar procedure will also be applied performing the traditional calibration using only discharge measurements. These analyses are performed for Upper Yangtze River basin (China) in framework of DRAGON-2 and DRAGON-3 Programme funded by NRSCC and ESA.
A binuclear Fe(III)Dy(III) single molecule magnet. Quantum effects and models.
Ferbinteanu, Marilena; Kajiwara, Takashi; Choi, Kwang-Yong; Nojiri, Hiroyuki; Nakamoto, Akio; Kojima, Norimichi; Cimpoesu, Fanica; Fujimura, Yuichi; Takaishi, Shinya; Yamashita, Masahiro
2006-07-19
The binuclear [FeIII(bpca)(mu-bpca)Dy(NO3)4], having Single Molecule Magnet (SMM) properties, belonging to a series of isostructural FeIIILnIII complexes (Ln = Eu, Gd, Tb, Dy, Ho) and closely related FeIILnIII chain structures, was characterized in concise experimental and theoretical respects. The low temperature magnetization data showed hysteresis and tunneling. The anomalous temperature dependence of Mössbauer spectra is related to the onset of magnetic order, consistent with the magnetization relaxation time scale resulting from AC susceptibility measurements. The advanced ab initio calculations (CASSCF and spin-orbit) revealed the interplay of ligand field, spin-orbit, and exchange effects and probed the effective Ising nature of the lowest states, involved in the SMM and tunneling effects.
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.
Photoionization Models for the Semi-forbidden C III] 1909 Emission in Star-forming Galaxies
NASA Astrophysics Data System (ADS)
Jaskot, A. E.; Ravindranath, S.
2016-12-01
The increasing neutrality of the intergalactic medium at z > 6 suppresses Lyα emission, and spectroscopic confirmation of galaxy redshifts requires the detection of alternative ultraviolet lines. The strong [C iii] λ1907+C iii] λ1909 doublet frequently observed in low-metallicity, actively star-forming galaxies is a promising emission feature. We present CLOUDY photoionization model predictions for C iii] equivalent widths (EWs) and line ratios as a function of starburst age, metallicity, and ionization parameter. Our models include a range of C/O abundances, dust content, and gas density. We also examine the effects of varying the nebular geometry and optical depth. Only the stellar models that incorporate binary interaction effects reproduce the highest observed C iii] EWs. The spectral energy distributions from the binary stellar population models also generate observable C iii] over a longer timescale relative to single-star models. We show that diagnostics using C iii] and nebular He ii λ1640 can separate star-forming regions from shock-ionized gas. We also find that density-bounded systems should exhibit weaker C iii] EWs at a given ionization parameter, and C iii] EWs could, therefore, select candidate Lyman continuum-leaking systems. In almost all models, C iii] is the next strongest line at <2700 Å after Lyα, and C iii] reaches detectable levels for a wide range of conditions at low metallicity. C iii] may therefore serve as an important diagnostic for characterizing galaxies at z > 6.
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.
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
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.
Semi-automated calibration method for modelling of mountain permafrost evolution in Switzerland
NASA Astrophysics Data System (ADS)
Marmy, Antoine; Rajczak, Jan; Delaloye, Reynald; Hilbich, Christin; Hoelzle, Martin; Kotlarski, Sven; Lambiel, Christophe; Noetzli, Jeannette; Phillips, Marcia; Salzmann, Nadine; Staub, Benno; Hauck, Christian
2016-11-01
Permafrost is a widespread phenomenon in mountainous regions of the world such as 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 allow for 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, for large-scale applications, a site-specific model calibration for a multitude of grid points would be very time-consuming. To tackle this issue, this study 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. We show that this semi-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 global and regional climate model (GCM/RCM)-based long-term climate projections under the A1B climate scenario (EU-ENSEMBLES project) specifically downscaled at each borehole site. The projection shows general permafrost degradation with thawing at 10 m, even partially reaching 20 m depth by the end of the century, but with different timing among the sites and with partly considerable uncertainties due to the spread of the applied climatic forcing.
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.
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...
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...
Collis, Joe; Connor, Anthony J; Paczkowski, Marcin; Kannan, Pavitra; Pitt-Francis, Joe; Byrne, Helen M; Hubbard, Matthew E
2017-04-01
In this work, we present a pedagogical tumour growth example, in which we apply calibration and validation techniques to an uncertain, Gompertzian model of tumour spheroid growth. The key contribution of this article is the discussion and application of these methods (that are not commonly employed in the field of cancer modelling) in the context of a simple model, whose deterministic analogue is widely known within the community. In the course of the example, we calibrate the model against experimental data that are subject to measurement errors, and then validate the resulting uncertain model predictions. We then analyse the sensitivity of the model predictions to the underlying measurement model. Finally, we propose an elementary learning approach for tuning a threshold parameter in the validation procedure in order to maximize predictive accuracy of our validated model.
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.
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization
NASA Astrophysics Data System (ADS)
Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan
2017-01-01
Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization
Xi, Maolong; Lu, Dan; Gui, Dongwei; ...
2016-11-27
Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less
Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization
Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan
2016-11-27
Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO_{3}-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.
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.
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.
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.
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.
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...
NASA Astrophysics Data System (ADS)
Mfumu Kihumba, Antoine; Vanclooster, Marnik; Ndembo Longo, Jean
2017-02-01
This study assessed the vulnerability of groundwater against pollution in the Kinshasa region, DR Congo, as a support of a groundwater protection program. The parametric vulnerability model (DRASTIC) was modified and calibrated to predict the intrinsic vulnerability as well as the groundwater pollution risk. The method uses groundwater body specific parameters for the calibration of the factor ratings and weightings of the original DRASTIC model. These groundwater specific parameters are inferred from the statistical relation between the original DRASTIC model and observed nitrate pollution for a specific period. In addition, site-specific land use parameters are integrated into the method. The method is fully embedded in a Geographic Information System (GIS). Following these modifications, the correlation coefficient between groundwater pollution risk and observed nitrate concentrations for the 2013-2014 survey improved from r = 0.42, for the original DRASTIC model, to r = 0.61 for the calibrated model. As a way to validate this pollution risk map, observed nitrate concentrations from another survey (2008) are compared to pollution risk indices showing a good degree of coincidence with r = 0.51. The study shows that a calibration of a vulnerability model is recommended when vulnerability maps are used for groundwater resource management and land use planning at the regional scale and that it is adapted to a specific area.
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.
Calibration of multiple Kinect depth sensors for full surface model reconstruction
NASA Astrophysics Data System (ADS)
Tsui, Kwan Pang; Wong, Kin Hong; Wang, Changling; Kam, Ho Chuen; Yau, Hing Tuen; Yu, Ying Kin
2016-07-01
In this paper, we have investigated different methods to calibrate a 3-D scanning system consisting of multiple Kinect sensors. The main function of the scanning system is for the reconstruction of the full surface model of an object. In this work, we build a four-Kinect system that the Kinect range sensors are positioned around the target object. Each Kinect is responsible for capturing a small local model, and the local models found will be combined to become the full model. To build such a system, calibration of the poses among the Kinects is essential. We have tested a number of methods: using (1) a sphere, (2) a checker board and (3) a cube as the calibration object. After calibration, the results of method (1) and (2) are used in the multiple Kinect system for obtaining the 3-D model of a real object. Results are shown and compared. For method (3) we only performed the simulation test on finding the rotation between two Kinects and the result is promising. This is the first part of a long term project on building a full surface model capturing system. Such a system should be useful in robot vision, scientific research and many other industrial applications.
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
Vogl, Gregory W.; Harper, Kari K.; Payne, Bev
2010-05-28
Piezoelectric shakers have been developed and used at the National Institute of Standards and Technology (NIST) for decades for high-frequency calibration of accelerometers. Recently, NIST researchers built new piezoelectric shakers in the hopes of reducing the uncertainties in the calibrations of accelerometers while extending the calibration frequency range beyond 20 kHz. The ability to build and measure piezoelectric shakers invites modeling of these systems in order to improve their design for increased performance, which includes a sinusoidal motion with lower distortion, lower cross-axial motion, and an increased frequency range. In this paper, we present a model of piezoelectric shakers and match it to experimental data. The equations of motion for all masses are solved along with the coupled state equations for the piezoelectric actuator. Finally, additional electrical elements like inductors, capacitors, and resistors are added to the piezoelectric actuator for matching of experimental and theoretical frequency responses.
The criterion-calibration model of cue interaction in contingency judgments.
Hannah, Samuel D; Allan, Lorraine G
2011-05-01
Siegel, Allan, Hannah, and Crump (2009) demonstrated that cue interaction effects in human contingency judgments reflect processing that occurs after the acquisition of information. This finding is in conflict with a broad class of theories. We present a new postacquisition model, the criterion-calibration model, that describes cue interaction effects as involving shifts in a report criterion. The model accounts for the Siegel et al. data and outperforms the only other postacquisition model of cue interaction, Stout and Miller's (2007) SOCR model. We present new data from an experiment designed to evaluate a prediction of the two models regarding reciprocal cue interaction effects. The new data provide further support for the criterion-calibration model.
Calibration under uncertainty for finite element models of masonry monuments
Atamturktur, Sezer,; Hemez, Francois,; Unal, Cetin
2010-02-01
Historical unreinforced masonry buildings often include features such as load bearing unreinforced masonry vaults and their supporting framework of piers, fill, buttresses, and walls. The masonry vaults of such buildings are among the most vulnerable structural components and certainly among the most challenging to analyze. The versatility of finite element (FE) analyses in incorporating various constitutive laws, as well as practically all geometric configurations, has resulted in the widespread use of the FE method for the analysis of complex unreinforced masonry structures over the last three decades. However, an FE model is only as accurate as its input parameters, and there are two fundamental challenges while defining FE model input parameters: (1) material properties and (2) support conditions. The difficulties in defining these two aspects of the FE model arise from the lack of knowledge in the common engineering understanding of masonry behavior. As a result, engineers are unable to define these FE model input parameters with certainty, and, inevitably, uncertainties are introduced to the FE model.
Meininger, Daniel J; Chee-Garza, Max; Arman, Hadi D; Tonzetich, Zachary J
2016-03-07
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.
Near infrared spectroscopic calibration models for real time monitoring of powder density.
Román-Ospino, Andrés D; Singh, Ravendra; Ierapetritou, Marianthi; Ramachandran, Rohit; Méndez, Rafael; Ortega-Zuñiga, Carlos; Muzzio, Fernando J; Romañach, Rodolfo J
2016-10-15
Near infrared spectroscopic (NIRS) calibration models for real time prediction of powder density (tap, bulk and consolidated) were developed for a pharmaceutical formulation. Powder density is a critical property in the manufacturing of solid oral dosages, related to critical quality attributes such as tablet mass, hardness and dissolution. The establishment of calibration techniques for powder density is highly desired towards the development of control strategies. Three techniques were evaluated to obtain the required variation in powder density for calibration sets: 1) different tap density levels (for a single component), 2) generating different strain levels in powders blends (and as consequence powder density), through a modified shear Couette Cell, and 3) applying normal forces during a compressibility test with a powder rheometer to a pharmaceutical blend. For each variation in powder density, near infrared spectra were acquired to develop partial least squares (PLS) calibration models. Test samples were predicted with a relative standard error of prediction of 0.38%, 7.65% and 0.93% for tap density (single component), shear and rheometer respectively. Spectra obtained in real time in a continuous manufacturing (CM) plant were compared to the spectra from the three approaches used to vary powder density. The calibration based on the application of different strain levels showed the greatest similarity with the blends produced in the CM plant.
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
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.
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.
Siddique, Juned; Crespi, Catherine M; Gibbons, Robert D; Green, Bonnie L
2011-01-30
We present an approach that uses latent variable modeling and multiple imputation to correct rater bias when one group of raters tends to be more lenient in assigning a diagnosis than another. Our method assumes that there exists an unobserved moderate category of patient who is assigned a positive diagnosis by one type of rater and a negative diagnosis by the other type. We present a Bayesian random effects censored ordinal probit model that allows us to calibrate the diagnoses across rater types by identifying and multiply imputing 'case' or 'non-case' status for patients in the moderate category. A Markov chain Monte Carlo algorithm is presented to estimate the posterior distribution of the model parameters and generate multiple imputations. Our method enables the calibrated diagnosis variable to be used in subsequent analyses while also preserving uncertainty in true diagnosis. We apply our model to diagnoses of posttraumatic stress disorder (PTSD) from a depression study where nurse practitioners were twice as likely as clinical psychologists to diagnose PTSD despite the fact that participants were randomly assigned to either a nurse or a psychologist. Our model appears to balance PTSD rates across raters, provides a good fit to the data, and preserves between-rater variability. After calibrating the diagnoses of PTSD across rater types, we perform an analysis looking at the effects of comorbid PTSD on changes in depression scores over time. Results are compared with an analysis that uses the original diagnoses and show that calibrating the PTSD diagnoses can yield different inferences.
SWAT application in intensive irrigation systems: Model modification, calibration and validation
NASA Astrophysics Data System (ADS)
Dechmi, Farida; Burguete, Javier; Skhiri, Ahmed
2012-11-01
SummaryThe Soil and Water Assessment Tool (SWAT) is a well established, distributed, eco-hydrologic model. However, using the study case of an agricultural intensive irrigated watershed, it was shown that all the model versions are not able to appropriately reproduce the total streamflow in such system when the irrigation source is outside the watershed. The objective of this study was to modify the SWAT2005 version for correctly simulating the main hydrological processes. Crop yield, total streamflow, total suspended sediment (TSS) losses and phosphorus load calibration and validation were performed using field survey information and water quantity and quality data recorded during 2008 and 2009 years in Del Reguero irrigated watershed in Spain. The goodness of the calibration and validation results was assessed using five statistical measures, including the Nash-Sutcliffe efficiency (NSE). Results indicated that the average annual crop yield and actual evapotranspiration estimations were quite satisfactory. On a monthly basis, the values of NSE were 0.90 (calibration) and 0.80 (validation) indicating that the modified model could reproduce accurately the observed streamflow. The TSS losses were also satisfactorily estimated (NSE = 0.72 and 0.52 for the calibration and validation steps). The monthly temporal patterns and all the statistical parameters indicated that the modified SWAT-IRRIG model adequately predicted the total phosphorus (TP) loading. Therefore, the model could be used to assess the impacts of different best management practices on nonpoint phosphorus losses in irrigated systems.
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.
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...
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...
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
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.
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.
Guenard, Robert D; Wehlburg, Christine M; Pell, Randy J; Haaland, David M
2007-07-01
This paper reports on the transfer of calibration models between Fourier transform near-infrared (FT-NIR) instruments from four different manufacturers. The piecewise direct standardization (PDS) method is compared with the new hybrid calibration method known as prediction augmented classical least squares/partial least squares (PACLS/PLS). The success of a calibration transfer experiment is judged by prediction error and by the number of samples that are flagged as outliers that would not have been flagged as such if a complete recalibration were performed. Prediction results must be acceptable and the outlier diagnostics capabilities must be preserved for the transfer to be deemed successful. Previous studies have measured the success of a calibration transfer method by comparing only the prediction performance (e.g., the root mean square error of prediction, RMSEP). However, our study emphasizes the need to consider outlier detection performance as well. As our study illustrates, the RMSEP values for a calibration transfer can be within acceptable range; however, statistical analysis of the spectral residuals can show that differences in outlier performance can vary significantly between competing transfer methods. There was no statistically significant difference in the prediction error between the PDS and PACLS/PLS methods when the same subset sample selection method was used for both methods. However, the PACLS/PLS method was better at preserving the outlier detection capabilities and therefore was judged to have performed better than the PDS algorithm when transferring calibrations with the use of a subset of samples to define the transfer function. The method of sample subset selection was found to make a significant difference in the calibration transfer results using the PDS algorithm, while the transfer results were less sensitive to subset selection when the PACLS/PLS method was used.
NASA Astrophysics Data System (ADS)
Pfannerstill, Matthias; Guse, Björn; Haas, Marcelo; Fohrer, Nicola
2015-04-01
Hydrological models are commonly applied for discharge prediction. To achieve reliable reproductions of the discharge and of the hydrological processes for different research questions, a calibration procedure providing reasonable model results is required. Automatic model calibrations of complex hydrological models usually require a large number of model runs. Thus, there is the need to reduce the high computational demand and to increase the information about model reliability in the same model framework that is applied for the automatic model calibration. The calibration of hydrological models is often focused directly or indirectly on special discharge phases (e.g. extreme high flow or extreme low flow) by accepting less satisfying performance of other discharge phases. In this way, the best model calibration runs are selected according to the specific research questions. However, the efficiency of automatic calibration can be increased if the same set of model calibrations can be used for different research questions without recalibration. This is achieved by integrating a flexible evaluation of different discharge phases which depends on the aim of discharge prediction. Our study presents an efficient multi-metric framework that is able to integrate different phases of the hydrograph with corresponding efficiency criteria. The evaluation framework integrates statistical performance metrics for the evaluation of discharge and signature metrics which are focused on the reproduction of segments of the flow duration curve (FDC). In order to consider a fairly balanced evaluation between high and low flow phases, we divided the flow duration curve into segments of high, medium and low flow phases, and additionally into very high and very low flow phases. By integrating all the different segments of the FDC, we make sure that low and high flows are reproduced simultaneously without neglecting a satisfying reproduction of the other phases of the hydrograph. In this
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
NASA Astrophysics Data System (ADS)
Akhtar, T.; Shoemaker, C. A.
2011-12-01
Assessing the sensitivity of calibration results to different calibration criteria can be done through multi objective optimization that considers multiple calibration criteria. This analysis can be extended to uncertainty analysis by comparing the results of simulation of the model with parameter sets from many points along a Pareto Front. In this study we employ multi-objective optimization in order to understand which parameter values should be used for flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville Reservoir in upstate New York. The comprehensive analysis procedure encapsulates identification of suitable objectives, analysis of trade-offs obtained through multi-objective optimization, and the impact of the trade-offs uncertainty. Examples of multiple criteria can include a) quality of the fit in different seasons, b) quality of the fit for high flow events and for low flow events, c) quality of the fit for different constituents (e.g. water versus nutrients). Many distributed watershed models are computationally expensive and include a large number of parameters that are to be calibrated. Efficient optimization algorithms are hence needed to find good solutions to multi-criteria calibration problems in a feasible amount of time. We apply a new algorithm called Gap Optimized Multi-Objective Optimization using Response Surfaces (GOMORS), for efficient multi-criteria optimization of the Cannonsville SWAT watershed calibration problem. GOMORS is a stochastic optimization method, which makes use of Radial Basis Functions for approximation of the computationally expensive objectives. GOMORS performance is also compared against other multi-objective algorithms ParEGO and NSGA-II. ParEGO is a kriging based efficient multi-objective optimization algorithm, whereas NSGA-II is a well-known multi-objective evolutionary optimization algorithm. GOMORS is more efficient than both ParEGO and NSGA-II in providing
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...
Calibration of Model for Tokamak H-mode Pedestal and ELMs
NASA Astrophysics Data System (ADS)
MacDonald, C.; Bateman, G.; Kritz, A. H.; McElhenny, J.; Osborne, T.; Pankin, A. Y.
2004-11-01
Experimental data is used to calibrate a model for the pedestal and Edge Localized Modes (ELMs) implemented in the ASTRA integrated code. The model is calibrated to predict the frequency of the ELMs and the height of the electron and ion temperature pedestals just before an ELM crash. Detailed comparisons are made with experimental data from the DIII-D 98889 discharge, in which the noise in the data is reduced by overlaying the plasma profiles from a sequence of consecutive, nearly identical ELM cycles. The model includes neoclassical transport and transport driven by ion drift modes, resistive ballooning modes, and the electron gradient temperature mode. The criterion for triggering ELM crashes allows for access to second stability. The calibration is carried out by adjusting: (1) The flow shear rates for individual modes of long wavelength turbulent transport; (2) the stability criterion that is used to trigger ELM crashes; and (3) the shapes of the plasma profiles and plasma energy lost after each ELM crash. The calibration is presented as well as the sensitivity to the coefficients in the model.
Barman, Ishan; Kong, Chae-Ryon; Dingari, Narahara Chari; Dasari, Ramachandra R.; Feld, Michael S.
2010-01-01
Sample-to-sample variability has proven to be a major challenge in achieving calibration transfer in quantitative biological Raman spectroscopy. Multiple morphological and optical parameters, such as tissue absorption and scattering, physiological glucose dynamics and skin heterogeneity, vary significantly in a human population introducing non-analyte specific features into the calibration model. In this paper, we show that fluctuations of such parameters in human subjects introduce curved (non-linear) effects in the relationship between the concentrations of the analyte of interest and the mixture Raman spectra. To account for these curved effects, we propose the use of support vector machines (SVM) as a non-linear regression method over conventional linear regression techniques such as partial least squares (PLS). Using transcutaneous blood glucose detection as an example, we demonstrate that application of SVM enables a significant improvement (at least 30%) in cross-validation accuracy over PLS when measurements from multiple human volunteers are employed in the calibration set. Furthermore, using physical tissue models with randomized analyte concentrations and varying turbidities, we show that the fluctuations in turbidity alone causes curved effects which can only be adequately modeled using non-linear regression techniques. The enhanced levels of accuracy obtained with the SVM based calibration models opens up avenues for prospective prediction in humans and thus for clinical translation of the technology. PMID:21050004
Calibrating Charisma: The many-facet Rasch model for leader measurement and automated coaching
NASA Astrophysics Data System (ADS)
Barney, Matt
2016-11-01
No one is a leader unless others follow. Consequently, leadership is fundamentally a social judgment construct, and may be best measured via a Many Facet Rasch Model designed for this purpose. Uniquely, the MFRM allows for objective, accurate and precise estimation of leader attributes, along with identification of rater biases and other distortions of the available information. This presentation will outline a mobile computer-adaptive measurement system that measures and develops charisma, among others. Uniquely, the approach calibrates and mass-personalizes artificially intelligent, Rasch-calibrated electronic coaching that is neither too hard nor too easy but “just right” to help each unique leader develop improved charisma.
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.
Explaining Usutu virus dynamics in Austria: model development and calibration.
Rubel, Franz; Brugger, Katharina; Hantel, Michael; Chvala-Mannsberger, Sonja; Bakonyi, Tamás; Weissenböck, Herbert; Nowotny, Norbert
2008-07-15
Usutu virus (USUV), a flavivirus of the Japanese encephalitis virus complex, was for the first time detected outside Africa in the region around Vienna (Austria) in 2001 by Weissenböck et al. [Weissenböck, H., Kolodziejek, J., Url, A., Lussy, H., Rebel-Bauder, B., Nowotny, N., 2002. Emergence of Usutu virus, an African mosquito-borne flavivirus of the Japanese encephalitis virus group, central Europe. Emerg. Infect. Dis. 8, 652-656]. USUV is an arthropod-borne virus (arbovirus) circulating between arthropod vectors (mainly mosquitoes of the Culex pipiens complex) and avian amplification hosts. Infections of mammalian hosts or humans, as observed for the related West Nile virus (WNV), are rare. However, USUV infection leads to a high mortality in birds, especially blackbirds (Turdus merula), and has similar dynamics with the WNV in North America, which, amongst others, caused mortality in American robins (Turdus migratorius). We hypothesized that the transmission of USUV is determined by an interaction of developing proportion of the avian hosts immune and climatic factors affecting the mosquito population. This mechanism is implemented into the present model that simulates the seasonal cycles of mosquito and bird populations as well as USUV cross-infections. Observed monthly climate data are specified for the temperature-dependent development rates of the mosquitoes as well as the temperature-dependent extrinsic-incubation period. Our model reproduced the observed number of dead birds in Austria between 2001 and 2005, including the peaks in the relevant years. The high number of USUV cases in 2003 seems to be a response to the early beginning of the extraordinary hot summer in that year. The predictions indicate that >70% of the bird population acquired immunity, but also that the percentage would drop rapidly within only a couple of years. We estimated annually averaged basic reproduction numbers between R (0)=0.54 (2004) and 1.35 (2003). Finally, extrapolation
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.
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)
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
Model Independent Approach to the Single Photoelectron Calibration of Photomultiplier Tubes
Saldanha, R.; Grandi, L.; Guardincerri, Y.; Wester, T.
2016-02-09
The accurate calibration of photomultiplier tubes is critical in a wide variety of applications in which it is necessary to know the absolute number of detected photons or precisely determine the resolution of the signal. Conventional calibration methods rely on fitting the photomultiplier response to a low intensity light source with analytical approximations to the single photoelectron distribution, often leading to biased estimates due to the inability to accurately model the full distribution, especially at low charge values. In this paper we present a simple statistical method to extract the relevant single photoelectron calibration parameters without making any assumptions about the underlying single photoelectron distribution. We illustrate the use of this method through the calibration of a Hamamatsu R11410 photomultiplier tube and study the accuracy and precision of the method using Monte Carlo simulations. The method is found to have significantly reduced bias compared to conventional methods and works under a wide range of light intensities, making it suitable for simultaneously calibrating large arrays of photomultiplier tubes.
Calibration 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
2016-09-01
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.
Development of a robust calibration model for nonlinear in-line process data
Despagne; Massart; Chabot
2000-04-01
A comparative study involving a global linear method (partial least squares), a local linear method (locally weighted regression), and a nonlinear method (neural networks) has been performed in order to implement a calibration model on an industrial process. The models were designed to predict the water content in a reactor during a distillation process, using in-line measurements from a near-infrared analyzer. Curved effects due to changes in temperature and variations between the different batches make the problem particularly challenging. The influence of spectral range selection and data preprocessing has been studied. With each calibration method, specific procedures have been applied to promote model robustness. In particular, the use of a monitoring set with neural networks does not always prevent overfitting. Therefore, we developed a model selection criterion based on the determination of the median of monitoring error over replicate trials. The back-propagation neural network models selected were found to outperform the other methods on independent test data.
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.
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.
Sensitivity analysis and calibration of a coupled hydrological/slope stability model (TRIGRS)
NASA Astrophysics Data System (ADS)
Zieher, Thomas; Rutzinger, Martin; Perzl, Frank; Meißl, Gertraud
2014-05-01
Shallow landslides potentially endanger human living in mountain regions worldwide. In order to prevent impacts of such gravitational mass movements it is necessary to fully understand the processes involved. Shallow landslides are usually understood as gravitational mass movements of the translational, slope-parallel type comprising of a mixture of earth and debris with a maximum depth of 1-2 m. Depending on the degree of saturation the initial sliding can turn into a flow-like movement. Numerous approaches for modelling shallow landslide susceptibility with different degrees of complexity exist. Regardless of the modelling approach it is crucial to provide sufficient field data, mainly on regolith characteristics. As for the TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability) model, numerous hydraulic and geotechnical parameters have to be known area-wide. Hence, as spatial interpolation of these input parameters is generally problematic in terms of accuracy, calibrating the model accordingly is a crucial step before conducting any simulations. This study presents a sensitivity analysis and the calibration of the coupled hydrological/slope stability model TRIGRS for a study area in Vorarlberg (Austria). The results of the sensitivity analysis show that in case of the stability model cohesion is the driving parameter while for the hydrological model it is the initial depth of the water table and the saturated hydraulic conductivity. The calibration of the stability model was carried out using a landslide inventory assuming completely saturated conditions. The use of geotechnical parameters extracted from literature for mapped soil types generally lead to unlikely stable conditions. In order to simulate mapped landslide initial areas correctly values for soil cohesion had to be adapted. However, the calibration of the stability model generally supports the assumption of saturated conditions. In absence of meteorological or hydrological
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.
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.
Forest Productivity for Soft Calibration of Soil Parameters in Eco-hydrologic Modeling
NASA Astrophysics Data System (ADS)
Garcia, E.; Tague, C.
2014-12-01
Calibration of soil drainage parameters in hydrologic models is typically achieved using statistics based on streamflow. Models that couple hydrology with ecosystem carbon and nutrient cycling also calculate estimates of carbon and nutrient stores and fluxes. Particularly in water-limited environments, these estimates will be sensitive to soil drainage parameters. We investigate the use of estimates of annual net primary productivity (annNPP) as an additional data source for soil parameter calibration. We combine literature-based estimates of annNPP with streamflow statistics to calibrate for soil parameters in three Western U.S. watersheds using a coupled eco-hydrology model. We show that for all sites, estimates of annNPP vary significantly across soil parameters selected solely using streamflow calibration. In all watersheds streamflow metrics select soil parameters that yield a range of annNPP estimates that can exceed literature-derived bounds for annNPP by 58-77%. Only 1-10% of the original soil parameter sets met both annNPP and streamflow criteria - a substantial reduction when compared to the percentage of acceptable parameter sets selected using annNPP or streamflow separately. Similarly, streamflow performance varies substantially across soil parameters selected based solely on annNPP criteria. Results show that annNPP in combination with streamflow-based metrics can better constrain soil parameters, although the usefulness varies across watersheds.
NASA Astrophysics Data System (ADS)
Sharifi, Amirreza; Lang, Megan W.; McCarty, Gregory W.; Sadeghi, Ali M.; Lee, Sangchul; Yen, Haw; Rabenhorst, Martin C.; Jeong, Jaehak; Yeo, In-Young
2016-10-01
Process based, distributed watershed models possess a large number of parameters that are not directly measured in field and need to be calibrated, in most cases through matching modeled in-stream fluxes with monitored data. Recently, concern has been raised regarding the reliability of this common calibration practice, because models that are deemed to be adequately calibrated based on commonly used metrics (e.g., Nash Sutcliffe efficiency) may not realistically represent intra-watershed responses or fluxes. Such shortcomings stem from the use of an evaluation criteria that only concerns the global in-stream responses of the model without investigating intra-watershed responses. In this study, we introduce a modification to the Soil and Water Assessment Tool (SWAT) model, and a new calibration technique that collectively reduce the chance of misrepresenting intra-watershed responses. The SWAT model was modified to better represent NO3 cycling in soils with various degrees of water holding capacity. The new calibration tool has the capacity to calibrate paired watersheds simultaneously within a single framework. It was found that when both proposed methodologies were applied jointly to two paired watersheds on the Delmarva Peninsula, the performance of the models as judged based on conventional metrics suffered, however, the intra-watershed responses (e.g., mass of NO3 lost to denitrification) in the two models automatically converged to realistic sums. This approach also demonstrates the capacity to spatially distinguish areas of high denitrification potential, an ability that has implications for improved management of prior converted wetlands under crop production and for identifying prominent areas for wetland restoration.
Sin, Gürkan; Vanrolleghem, Peter A
2007-08-01
Recently a model was introduced to interpret the respirometric (OUR) -titrimetric (Hp) data obtained from aerobic oxidation of different carbon sources in view of calibration of Activated Sludge Model No.1 (ASM1). The model requires, among others, the carbon dioxide transfer rate (CTR) to be relatively constant during aerobic experiments. As CTR is an inherently nonlinear process, this assumption may not hold for certain experimental conditions. Hence, we extended the model to describe the nonlinear CTR behavior. A simple calibration procedure of the CO2 model was developed only using titrimetric data. The identifiable parameter subset of this model when using titrimetric data only contained the first equilibrium constant of the CO2 dissociation, pK1, the initial aqueous CO2 concentration, C(Tinit) and the nitrogen content of biomass, i(NBM). The extended model was then successfully applied to interpret typical data obtained from respirometric-titrimetric measurements with a nonlinear CO2 stripping process. The parameter estimation results using titrimetric data were consistent with the results estimated using respirometric data (OUR) alone or combined OUR and Hp data, thereby supporting the validity of the dynamic CO2 model and its calibration approach. The increased range of applicability and accurate utilization of the titrimetric data are expected to contribute particularly to the improvement of calibration of ASM models using batch experiments.
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.
Kinetic modeling of antimony(III) oxidation and sorption in soils.
Cai, Yongbing; Mi, Yuting; Zhang, Hua
2016-10-05
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.
On Inertial Body Tracking in the Presence of Model Calibration Errors.
Miezal, Markus; Taetz, Bertram; Bleser, Gabriele
2016-07-22
In inertial body tracking, the human body is commonly represented as a biomechanical model consisting of rigid segments with known lengths and connecting joints. The model state is then estimated via sensor fusion methods based on data from attached inertial measurement units (IMUs). This requires the relative poses of the IMUs w.r.t. the segments-the IMU-to-segment calibrations, subsequently called I2S calibrations-to be known. Since calibration methods based on static poses, movements and manual measurements are still the most widely used, potentially large human-induced calibration errors have to be expected. This work compares three newly developed/adapted extended Kalman filter (EKF) and optimization-based sensor fusion methods with an existing EKF-based method w.r.t. their segment orientation estimation accuracy in the presence of model calibration errors with and without using magnetometer information. While the existing EKF-based method uses a segment-centered kinematic chain biomechanical model and a constant angular acceleration motion model, the newly developed/adapted methods are all based on a free segments model, where each segment is represented with six degrees of freedom in the global frame. Moreover, these methods differ in the assumed motion model (constant angular acceleration, constant angular velocity, inertial data as control input), the state representation (segment-centered, IMU-centered) and the estimation method (EKF, sliding window optimization). In addition to the free segments representation, the optimization-based method also represents each IMU with six degrees of freedom in the global frame. In the evaluation on simulated and real data from a three segment model (an arm), the optimization-based method showed the smallest mean errors, standard deviations and maximum errors throughout all tests. It also showed the lowest dependency on magnetometer information and motion agility. Moreover, it was insensitive w.r.t. I2S position and
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
NASA Astrophysics Data System (ADS)
Singh, A.; Karsten, A.
2011-06-01
The accuracy of the calibration model for the single and double integrating sphere systems are compared for a white light system. A calibration model is created from a matrix of samples with known absorption and reduced scattering coefficients. In this instance the samples are made using different concentrations of intralipid and black ink. The total and diffuse transmittance and reflectance is measured on both setups and the accuracy of each model compared by evaluating the prediction errors of the calibration model for the different systems. Current results indicate that the single integrating sphere setup is more accurate than the double system method. This is based on the low prediction errors of the model for the single sphere system for a He-Ne laser as well as a white light source. The model still needs to be refined for more absorption factors. Tests on the prediction accuracies were then determined by extracting the optical properties of solid resin based phantoms for each system. When these properties of the phantoms were used as input to the modeling software excellent agreement between measured and simulated data was found for the single sphere systems.
Safta, C.; Ricciuto, Daniel M.; Sargsyan, Khachik; ...
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 employedmore » in the second part of the paper to assess the predictive skill of the model via posterior predictive checks.« less
Liu, Miao; Yang, Shourui; Wang, Zhangying; Huang, Shujun; Liu, Yue; Niu, Zhenqi; Zhang, Xiaoxuan; Zhu, Jigui; Zhang, Zonghua
2016-05-30
Augmented reality system can be applied to provide precise guidance for various kinds of manual works. The adaptability and guiding accuracy of such systems are decided by the computational model and the corresponding calibration method. In this paper, a novel type of augmented reality guiding system and the corresponding designing scheme are proposed. Guided by external positioning equipment, the proposed system can achieve high relative indication accuracy in a large working space. Meanwhile, the proposed system is realized with a digital projector and the general back projection model is derived with geometry relationship between digitized 3D model and the projector in free space. The corresponding calibration method is also designed for the proposed system to obtain the parameters of projector. To validate the proposed back projection model, the coordinate data collected by a 3D positioning equipment is used to calculate and optimize the extrinsic parameters. The final projecting indication accuracy of the system is verified with subpixel pattern projecting technique.
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.
Safta, C.; Ricciuto, Daniel M.; Sargsyan, Khachik; Debusschere, B.; Najm, H. N.; Williams, M.; Thornton, Peter 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)
Chen, R.
2015-12-01
The inter-satellite radiometric calibration technique (also known as XCAL) has been applied with great success between the TRMM Microwave Imager (TMI) -calibration transfer standard- and its constellation imagers, namely, WindSat, AMSR2 and SSMIS. However, while the TRMM mission has now ended, it is now time to change the radiometric transfer standard from the previous TMI to the GPM Microwave Imager (GMI). In this paper, we conduct the inter-calibration between GMI and other imager instruments in its constellation using two different radiative transfer models (RTM), namely XCAL RTM which has been used by XCAL group over the past 10 years, and RSS RTM developed by Remote Sensing Systems (RSS). The main difference between these two RTMs lies in calculating the ocean surface emissivity which is crucial for the measurement of spaceborne microwave radiometers. By comparing the simulated Tb's from two RTMs applied on 9 microwave channels ranging from 10 to 90 GHz, we are able to evaluate the robustness of our XCAL RTM, especially the Elsaesser Ocean Surface Emissivity model that has been used within this model. Besides discussing the reliability of these two RTMs, an XCAL approach known as Double Difference (DD) that has been developed and successfully validated by the Central Florida Remote Sensing Lab will be performed between GMI and its constellation imagers, from which the results will enable us to prescreen the consistency of GMI as the new radiometric transfer standard for imager radiometers as well as assessing the impact of the ocean surface emissivity on radiometric inter-calibration of radiometers at imager channels. Index: Inter-satellite calibration, ocean surface emissivity, radiative transfer model, microwave radiometry
Salter, James M; Williamson, Daniel
2016-12-01
Expensive computer codes, particularly those used for simulating environmental or geological processes, such as climate models, require calibration (sometimes called tuning). When calibrating expensive simulators using uncertainty quantification methods, it is usually necessary to use a statistical model called an emulator in place of the computer code when running the calibration algorithm. Though emulators based on Gaussian processes are typically many orders of magnitude faster to evaluate than the simulator they mimic, many applications have sought to speed up the computations by using regression-only emulators within the calculations instead, arguing that the extra sophistication brought using the Gaussian process is not worth the extra computational power. This was the case for the analysis that produced the UK climate projections in 2009. In this paper, we compare the effectiveness of both emulation approaches upon a multi-wave calibration framework that is becoming popular in the climate modeling community called "history matching." We find that Gaussian processes offer significant benefits to the reduction of parametric uncertainty over regression-only approaches. We find that in a multi-wave experiment, a combination of regression-only emulators initially, followed by Gaussian process emulators for refocussing experiments can be nearly as effective as using Gaussian processes throughout for a fraction of the computational cost. We also discover a number of design and emulator-dependent features of the multi-wave history matching approach that can cause apparent, yet premature, convergence of our estimates of parametric uncertainty. We compare these approaches to calibration in idealized examples and apply it to a well-known geological reservoir model.
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.
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...
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
A New Selection Metric for Multi-Objective Hydrologic Model Calibration
NASA Astrophysics Data System (ADS)
Tolson, B.; Asadzadeh, M.; Burn, D. H.
2014-12-01
A novel selection metric called Convex Hull Contribution (CHC) is introduced for solving multi-objective (MO) optimization problems with Pareto fronts that can be accurately approximated by a convex curve. The hydrologic model calibration literature shows that many bi-objective calibration problems with a proper setup result in such Pareto fronts. The CHC selection approach identifies a subset of archived non-dominated solutions whose map in the objective space forms convex approximation of the Pareto front. The optimization algorithm can sample solely from these solutions to more accurately approximate the convex shape of the Pareto front. It is empirically demonstrated that CHC improves the performance of Pareto Archived Dynamically Dimensioned Search (PA-DDS) when solving MO problems with convex Pareto fronts. This conclusion is based on the results of several benchmark mathematical problems and several hydrologic model calibration problems with two or three objective functions. The impact of CHC on PA-DDS performance is most evident when the computational budget is somewhat limited. It is also demonstrated that 1,000 solution evaluations (limited budget in this study) is sufficient for PA-DDS with CHC-based selection to achieve very high quality calibration results relative to the results achieved after 10,000 solution evaluations.
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.
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.
NASA Astrophysics Data System (ADS)
Walton, Richard S.; Hunter, Heather M.
2009-11-01
SummaryQuantifying relationships between stream water quality and catchment land uses is a major goal of many water quality monitoring programs. This is a challenging task that is rarely achieved through simple analysis of raw data alone. Multiple regression analysis provides one approach, which despite significant limitations, can be successful when very large data sets are available and only annual estimates are required. However, regression techniques have limited application to sub-annual data sets. We present a new method for isolating the water quality responses of different land uses from monitoring data through hydrological model calibration, using a process of simultaneous calibration at several monitoring sites. In addition to model parameters, model algorithm complexity and the number of land-attribute groups are also used as calibration 'parameters'. This helps increase model parameter uniqueness and model predictive certainty. We applied the technique to water quality data from the Johnstone River catchment (1602 km 2) in north-east Australia, using the HSPF model. The data comprised >4000 samples from over five years of monitoring at 16 sites, which drained sub-catchments of differing land area and proportions of each land use. Monitoring occurred at flow gauging sites during high stream flows, and regularly at all sites during non-event periods. Variables modelled included discharge, suspended sediment, and various forms of nitrogen and phosphorus. The calibration process aimed to maximise both goodness-of-fit and parameter sensitivity. We achieved a substantial simplification of HSPF algorithms without appreciable reduction in goodness-of-fit, by a combination of: fixing parameters, tying parameters, and introducing new, simpler equations. Two key calibration tools were reducing the number of land-use groups (by combining land uses) and tying parameters between the three flow paths modelled (surface flow, interflow and base flow). These in turn
Wall, Mark J.
2016-01-01
Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments. NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue
Newton, Adam J H; Wall, Mark J; Richardson, Magnus J E
2017-03-01
Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments.NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue
Calibration and validation of an integrated nitrate transport model within a well capture zone.
Bonton, Alexandre; Bouchard, Christian; Rouleau, Alain; Rodriguez, Manuel J; Therrien, René
2012-02-01
Groundwater contamination by nitrate was investigated in an agricultural area in southern Quebec, Canada, where a municipal well is the local source of drinking water. A network of 38 piezometers was installed within the capture zone of the municipal well to monitor water table levels and nitrate concentrations in the aquifer. Nitrate concentrations were also measured in the municipal well. A Water flow and Nitrate transport Global Model (WNGM) was developed to simulate the impact of agricultural activities on nitrate concentrations in both the aquifer and municipal well. The WNGM first uses the Agriflux model to simulate vertical water and nitrate fluxes below the root zone for each of the seventy agricultural fields located within the capture zone of the municipal well. The WNGM then uses the HydroGeoSphere model to simulate three-dimensional variably-saturated groundwater flow and nitrate transport in the aquifer using water and nitrate fluxes computed with the Agriflux model as the top boundary conditions. The WNGM model was calibrated by reproducing water levels measured from 2005 to 2007 in the network of piezometers and nitrate concentrations measured in the municipal well from 1997 to 2007. The nitrate concentrations measured in the network of piezometers, however, showed greater variability than in the municipal well and could not be reproduced by the calibrated model. After calibration, the model was validated by successfully reproducing the decrease of nitrate concentrations observed in the municipal well in 2006 and 2007. Although it cannot predict nitrate concentrations in individual piezometers, the calibrated and validated WNGM can be used to assess the impact of changes in agricultural practices on global nitrate concentrations in the aquifer and in the municipal well.
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.
Calibration of a hysteretic model for glass fiber reinforced gypsum wall panels
NASA Astrophysics Data System (ADS)
Janardhana, Maganti; Robin Davis, P.; Ravichandran, S. S.; Prasad, A. M.; Menon, D.
2014-06-01
Glass fiber reinforced gypsum (GFRG) wall panels are prefabricated panels with hollow cores, originally developed in Australia and subsequently adopted by India and China for use in buildings. This paper discusses identification and calibration of a suitable hysteretic model for GFRG wall panels filled with reinforced concrete. As considerable pinching was observed in the experimental results, a suitable hysteretic model with pinched hysteretic rule is used to conduct a series of quasi-static as inelastic hysteretic response analyses of GFRG panels with two different widths. The calibration of the pinching model parameters was carried out to approximately match the simulated and experimental responses up to 80% of the peak load in the post peak region. Interestingly, the same values of various parameters (energy dissipation and pinching related parameters) were obtained for all five test specimens.
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.
Lai, Canhai; Xu, Zhijie; Pan, Wenxiao; Sun, Xin; Storlie, Curtis; Marcy, Peter; Dietiker, Jean-François; Li, Tingwen; Spenik, James
2016-01-01
To quantify the predictive confidence of a solid sorbent-based carbon capture design, a hierarchical validation methodology—consisting of basic unit problems with increasing physical complexity coupled with filtered model-based geometric upscaling has been developed and implemented. This paper describes the computational fluid dynamics (CFD) multi-phase reactive flow simulations and the associated data flows among different unit problems performed within the said hierarchical validation approach. The bench-top experiments used in this calibration and validation effort were carefully designed to follow the desired simple-to-complex unit problem hierarchy, with corresponding data acquisition to support model parameters calibrations at each unit problem level. A Bayesian calibration procedure is employed and the posterior model parameter distributions obtained at one unit-problem level are used as prior distributions for the same parameters in the next-tier simulations. Overall, the results have demonstrated that the multiphase reactive flow models within MFIX can be used to capture the bed pressure, temperature, CO2 capture capacity, and kinetics with quantitative accuracy. The CFD modeling methodology and associated uncertainty quantification techniques presented herein offer a solid framework for estimating the predictive confidence in the virtual scale up of a larger carbon capture device.
Calibration of satellite measurements of river discharge using a global hydrology model
NASA Astrophysics Data System (ADS)
Robert Brakenridge, G.; Cohen, Sagy; Kettner, Albert J.; De Groeve, Tom; Nghiem, Son V.; Syvitski, James P. M.; Fekete, Balazs M.
2012-12-01
SummaryMeasurements of river discharge and watershed runoff are essential to water resources management, efficient hydropower generation, accurate flood prediction and control, and improved understanding of the global water cycle. Previous work demonstrates that orbital remote sensing can measure river discharge variation in a manner closely analogous to its measurement at ground stations, and using reach flow surface area instead of stage as the discharge estimator. For international measurements, hydrological modeling can, in principle, be used to provide the needed calibration of sensor data to discharge. The present study tests this approach and investigates the accuracy of the results. We analyze six sites within the US where gauging station, satellite measurements, and WBM model results are all available. Knowledge is thereby gained concerning how accurately satellite sensors can measure discharge, if the signal is calibrated only from global modeling results without any ground-based information. The calibration (rating) equations obtained for the remote sensing signal are similar, whether based on gauging station or on model information: r2 correlation coefficients for least squares fits at one example site (#524; White River, Indiana) are both .66 (n = 144, comparing monthly daily maxima, minima, and mean, 2003-2006). Space-based 4-day mean discharge values for this site when using the model calibration are accurate to within ±67% on the average (n = 1824; largest percent errors occur at low discharges), and annual total runoff is accurate to ±9%, 2003-2008. Comparison of gauging station versus modeled discharge commonly indicates a small positive model bias; the observed errors of satellite-observed annual runoff are also positive and could be improved by bias removal from the rating curves. Also, analysis of a large flood event, along the Indus River in 2010, shows that the model does not capture flood wave attenuation by overbank flow, and thus
Campbell, Kirby R; Campagnola, Paul J
2017-03-02
Extensive remodeling of the extracellular matrix (ECM) occurs in many epithelial cancers. For example, in ovarian cancer, upregulation of collagen isoform type III has been linked to invasive forms of the disease, and this change may be a potential biomarker. To examine this possibility, we implemented wavelength-dependent second harmonic generation circular dichroism (SHG-CD) imaging microscopy to quantitatively determine changes in chirality in ECM models comprised of different Col I/Col III composition. In these models, Col III was varied between 0 and 40%, and we found increasing Col III results in reduced net chirality, consistent with structural biology studies of Col I and III in tissues where the isoforms comingle in the same fibrils. We further examined the wavelength dependence of the SHG-CD to both optimize the response and gain insight into the underlying mechanism. We found using shorter SHG excitation wavelengths resulted in increased SHG-CD sensitivity, where this is consistent with the electric-dipole-coupled oscillator model suggested previously for the nonlinear chirality response from thin films. Moreover, the sensitivity is further consistent with the wavelength dependency of SHG intensity fit to a two-state model of the two-photon absorption in collagen. We also provide experimental calibration protocols to implement the SHG-CD modality on a laser scanning microscope. We last suggest that the technique has broad applicability in probing a wide range of diseased states with changes in collagen molecular structure.
An efficient surrogate-based simulation-optimization method for calibrating a regional MODFLOW model
NASA Astrophysics Data System (ADS)
Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.
2017-01-01
Simulation-optimization method entails a large number of model simulations, which is computationally intensive or even prohibitive if the model simulation is extremely time-consuming. Statistical models have been examined as a surrogate of the high-fidelity physical model during simulation-optimization process to tackle this problem. Among them, Multivariate Adaptive Regression Splines (MARS), a non-parametric adaptive regression method, is superior in overcoming problems of high-dimensions and discontinuities of the data. Furthermore, the stability and accuracy of MARS model can be improved by bootstrap aggregating methods, namely, bagging. In this paper, Bagging MARS (BMARS) method is integrated to a surrogate-based simulation-optimization framework to calibrate a three-dimensional MODFLOW model, which is developed to simulate the groundwater flow in an arid hardrock-alluvium region in northwestern Oman. The physical MODFLOW model is surrogated by the statistical model developed using BMARS algorithm. The surrogate model, which is fitted and validated using training dataset generated by the physical model, can approximate solutions rapidly. An efficient Sobol' method is employed to calculate global sensitivities of head outputs to input parameters, which are used to analyze their importance for the model outputs spatiotemporally. Only sensitive parameters are included in the calibration process to further improve the computational efficiency. Normalized root mean square error (NRMSE) between measured and simulated heads at observation wells is used as the objective function to be minimized during optimization. The reasonable history match between the simulated and observed heads demonstrated feasibility of this high-efficient calibration framework.
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.
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…
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.
Theoretical model for the heat diffusion in an electrically calibrated laser power meter
NASA Astrophysics Data System (ADS)
Sporea, Dan G.; Miron, Nicolae; Dumitru, Gabriel; Timus, Bogdan
1995-09-01
The theoretical model for the heat diffusion in the case of a high power IR electrically calibrated laser powermeter, developed at the Institute for Atomic Physics in Bucharest, is presented. The IR laser beam falls onto a laser detector, a special design copper disc wafer which absorbs the laser beam, heats its center. A daisy-chain of thermocouple elements having one set of junctions thermally connected to the central region of the disc and the other ones to the disc's boundary is used to detect temperature rise induced by the exposure to the laser beam. For calibration, the copper disc is electrically heated and the electric power that produces the same temperature rise as one induced by an incident laser beam, should equal the laser beam power. The electric heater is designed to provide a uniform heating of the copper disc. The solution for heat diffusion equation was searched as a series of Bessel functions of zero order, the cold junction's temperature was imposed as boundary condition and the heat induced by the laser beam in the disc's center was regarded as input data. To find the correct solutions, there must be taken into account the designing elements of the copper disc: termic material's properties (caloric capacity, termic conductibility), laser detector's geometry, copper's density. The electric power for calibration was injected using a precision power injection circuit which allows a stability of the calibration power, better than 0.1%.
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.
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.
Optical modeling and polarization calibration for CMB measurements with ACTPol and Advanced ACTPol
NASA Astrophysics Data System (ADS)
Koopman, Brian; Austermann, Jason; Cho, Hsiao-Mei; Coughlin, Kevin P.; Duff, Shannon M.; Gallardo, Patricio A.; Hasselfield, Matthew; Henderson, Shawn W.; Ho, Shuay-Pwu Patty; Hubmayr, Johannes; Irwin, Kent D.; Li, Dale; McMahon, Jeff; Nati, Federico; Niemack, Michael D.; Newburgh, Laura; Page, Lyman A.; Salatino, Maria; Schillaci, Alessandro; Schmitt, Benjamin L.; Simon, Sara M.; Vavagiakis, Eve M.; Ward, Jonathan T.; Wollack, Edward J.
2016-07-01
The Atacama Cosmology Telescope Polarimeter (ACTPol) is a polarization sensitive upgrade to the Atacama Cosmology Telescope, located at an elevation of 5190 m on Cerro Toco in Chile. ACTPol uses transition edge sensor bolometers coupled to orthomode transducers to measure both the temperature and polarization of the Cosmic Microwave Background (CMB). Calibration of the detector angles is a critical step in producing polarization maps of the CMB. Polarization angle offsets in the detector calibration can cause leakage in polarization from E to B modes and induce a spurious signal in the EB and TB cross correlations, which eliminates our ability to measure potential cosmological sources of EB and TB signals, such as cosmic birefringence. We calibrate the ACTPol detector angles by ray tracing the designed detector angle through the entire optical chain to determine the projection of each detector angle on the sky. The distribution of calibrated detector polarization angles are consistent with a global offset angle from zero when compared to the EB-nulling offset angle, the angle required to null the EB cross-correlation power spectrum. We present the optical modeling process. The detector angles can be cross checked through observations of known polarized sources, whether this be a galactic source or a laboratory reference standard. To cross check the ACTPol detector angles, we use a thin film polarization grid placed in front of the receiver of the telescope, between the receiver and the secondary reflector. Making use of a rapidly rotating half-wave plate (HWP) mount we spin the polarizing grid at a constant speed, polarizing and rotating the incoming atmospheric signal. The resulting sinusoidal signal is used to determine the detector angles. The optical modeling calibration was shown to be consistent with a global offset angle of zero when compared to EB nulling in the first ACTPol results and will continue to be a part of our calibration implementation. The first
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
A calibrated hydrogen-peroxide direct-borohydride fuel cell model
NASA Astrophysics Data System (ADS)
Stroman, Richard O.; Jackson, Gregory S.; Garsany, Yannick; Swider-Lyons, Karen
2014-12-01
A numerical model with global reaction rates is calibrated to measurements from a simple hydrogen-peroxide direct-borohydride fuel cell (H2O2-DBFC), and then used to unravel complex electrochemical and competing parasitic reactions. In this H2O2-DBFC, fuel (1-50 mM NaBH4/2 M NaOH) is oxidized at a Au anode and oxidizer (10-40 mM H2O2/1 M H2SO4) is reduced at a Pd:Ir cathode. Polarization curves and electrode potentials, as functions of fuel and oxidizer feeds support global reaction rate parameter fitting. The measurements and calibrated model showed H2O2 decomposition at the cathode depresses open circuit voltage from 3.01 V theoretical to 1.65 V, and when H2O2 supply is limited, cathode potentials are sufficiently negative to make H+ reduction to H2 thermodynamically favorable. Calibrated model results show that thin concentration boundary layers limit reactant utilization and current density. Decreasing the inlet concentrations, flow rates, and cell voltage slow parasitic reactions and favor desirable charge transfer reactions. Peak conversion efficiency and peak power density coincide because thermodynamic efficiency and parasitic reaction rates decrease (relative to charge transfer reaction rates) with increasing current density. We conclude that the performance of a fuel cell with parasitic side reactions can be predicted through numerical modeling.
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.
Brand, L Arriana; Noon, Barry R; Sisk, Thomas D
2006-06-01
Reliable prediction of the effects of landscape change on species abundance is critical to land managers who must make frequent, rapid decisions with long-term consequences. However, due to inherent temporal and spatial variability in ecological systems, previous attempts to predict species abundance in novel locations and/or time frames have been largely unsuccessful. The Effective Area Model (EAM) uses change in habitat composition and geometry coupled with response of animals to habitat edges to predict change in species abundance at a landscape scale. Our research goals were to validate EAM abundance predictions in new locations and to develop a calibration framework that enables absolute abundance predictions in novel regions or time frames. For model validation, we compared the EAM to a null model excluding edge effects in terms of accurate prediction of species abundance. The EAM outperformed the null model for 83.3% of species (N=12) for which it was possible to discern a difference when considering 50 validation sites. Likewise, the EAM outperformed the null model when considering subsets of validation sites categorized on the basis of four variables (isolation, presence of water, region, and focal habitat). Additionally, we explored a framework for producing calibrated models to decrease prediction error given inherent temporal and spatial variability in abundance. We calibrated the EAM to new locations using linear regression between observed and predicted abundance with and without additional habitat covariates. We found that model adjustments for unexplained variability in time and space, as well as variability that can be explained by incorporating additional covariates, improved EAM predictions. Calibrated EAM abundance estimates with additional site-level variables explained a significant amount of variability (P < 0.05) in observed abundance for 17 of 20 species, with R2 values >25% for 12 species, >48% for six species, and >60% for four species
Wu, Stephen; Angelikopoulos, Panagiotis; Tauriello, Gerardo; Papadimitriou, Costas; Koumoutsakos, Petros
2016-12-28
We propose a hierarchical Bayesian framework to systematically integrate heterogeneous data for the calibration of force fields in Molecular Dynamics (MD) simulations. Our approach enables the fusion of diverse experimental data sets of the physico-chemical properties of a system at different thermodynamic conditions. We demonstrate the value of this framework for the robust calibration of MD force-fields for water using experimental data of its diffusivity, radial distribution function, and density. In order to address the high computational cost associated with the hierarchical Bayesian models, we develop a novel surrogate model based on the empirical interpolation method. Further computational savings are achieved by implementing a highly parallel transitional Markov chain Monte Carlo technique. The present method bypasses possible subjective weightings of the experimental data in identifying MD force-field parameters.
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.
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
NASA Astrophysics Data System (ADS)
Sun, Wenchao; Wang, Yuanyuan; Wang, Guoqiang; Cui, Xingqi; Yu, Jingshan; Zuo, Depeng; Xu, Zongxue
2017-01-01
Physically based distributed hydrological models are widely used for hydrological simulations in various environments. As with conceptual models, they are limited in data-sparse basins by the lack of streamflow data for calibration. Short periods of observational data (less than 1 year) may be obtained from fragmentary historical records of previously existing gauging stations or from temporary gauging during field surveys, which might be of value for model calibration. However, unlike lumped conceptual models, such an approach has not been explored sufficiently for physically based distributed models. This study explored how the use of limited continuous daily streamflow data might support the application of a physically based distributed model in data-sparse basins. The influence of the length of the observation period on the calibration of the widely applied soil and water assessment tool model was evaluated in four Chinese basins with differing climatic and geophysical characteristics. The evaluations were conducted by comparing calibrations based on short periods of data with calibrations based on data from a 3-year period, which were treated as benchmark calibrations of the four basins, respectively. To ensure the differences in the model simulations solely come from differences in the calibration data, the generalized likelihood uncertainty analysis scheme was employed for the automatic calibration and uncertainty analysis. In the four basins, contrary to the common understanding of the need for observations over a period of several years, data records with lengths of less than 1 year were shown to calibrate the model effectively, i.e., performances similar to the benchmark calibrations were achieved. The models of the wet Jinjiang and Donghe basins could be effectively calibrated using a shorter data record (1 month), compared with the dry Heihe and upstream Yalongjiang basins (6 months). Even though the four basins are very different, when using 1-year or
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.
Calibration, characterisation and Monte Carlo modelling of a fast-UNCL
NASA Astrophysics Data System (ADS)
Tagziria, Hamid; Bagi, Janos; Peerani, Paolo; Belian, Antony
2012-09-01
This paper describes the calibration, characterisation and Monte Carlo modelling of a new IAEA Uranium Neutron Collar (UNCL) for LWR fuel, which can be operated in both passive and active modes. It can employ either 35 3He tubes (in active configuration) or 44 tubes at 10 atm pressure (in its passive configuration) and thus can be operated in fast mode (with Cd liner) as its efficiency is higher than that of the standard UNCL. Furthermore, it has an adjustable internal cavity which allows the measurement of varying sizes of fuel assemblies such as WWER, PWR and BWR. It is intended to be used with Cd liners in active mode (with an AmLi interrogation source in place) by the inspectorate for the determination of the 235U content in fresh fuel assemblies, especially in cases where high concentrations of burnable poisons cause problems with accurate assays. A campaign of measurements has been carried out at the JRC Performance Laboratories (PERLA) in Ispra (Italy) using various radionuclide neutron sources (252Cf, 241AmLi and PuGa) and our BWR and PWR reference assemblies, in order to calibrate and characterise the counter as well as assess its performance and determine its optimum operational parameters. Furthermore, the fast-UNCL has been extensively modelled at JRC using the Monte Carlo code, MCNP-PTA, which simulates both the neutron transport and the coincidence electronics. The model has been validated using our measurements which agreed well with calculations. The WWER1000 fuel assembly for which there are no representative reference materials for an adequate calibration of the counter, has also been modelled and the response of the counter to this fuel assembly has been simulated. Subsequently numerical calibrations curves have been obtained for the above fuel assemblies in various modes (fast and thermal). The sensitivity of the counter to fuel rods substitution as well as other important aspects and the parameters of the fast-UNCL performance have been
Calibration of dimensional change in finite element models using AGR moderator brick measurements
NASA Astrophysics Data System (ADS)
McNally, K.; Hall, G.; Tan, E.; Marsden, B. J.; Warren, N.
2014-08-01
Physically based models, resolved using the finite element (FE) method, are often used to model changes in geometry and the associated stress fields of graphite moderator bricks within a reactor. These models require inputs that describe the loading conditions (field variables), and coded relationships describing the behaviour of material properties. Historically, behaviour on material properties have been obtained from Materials Test Reactor (MTR) experiments, however data relating to samples trepanned from operating reactors are increasingly being used to improve models. Geometry measurements from operating reactors offer the potential for improving the coded relationship for dimensional change in FE models. A non-linear mixed-effect model is presented for calibrating the parameters of FE models that are sensitive to mid-brick diameter, using channel geometry measurements obtained from inspection campaigns. The work makes use of a novel technique: the development of a Bayesian emulator, which is a surrogate for the FE model. The use of an emulator allows the influence of the inputs to the finite element model to be evaluated, and delivers a substantial reduction in the computational burden of calibration.
Modeling rare earth complexes: Sparkle/AM1 parameters for thulium (III)
NASA Astrophysics Data System (ADS)
Freire, Ricardo O.; Rocha, Gerd B.; Simas, Alfredo M.
2005-08-01
The Sparkle/AM1 model, recently defined for Eu(III), Gd(III) and Tb(III) [R.O. Freire, G.B. Rocha, A.M., Simas, Inorg. Chem. 44 (2005) 3299], is extended to Tm(III). A set of 15 structures of high crystallographic quality from the Cambridge Crystallographic Database, with ligands chosen to be representative of all complexes with nitrogen or oxygen directly bonded to the Tm(III) ion, was used as a training set. For the 15 complexes, the Sparkle/AM1 unsigned mean error, for all interatomic distances between the Tm(III) ion and the oxygen or nitrogen ligand atoms of the first sphere of coordination, is 0.07 Å, a level of accuracy useful for luminescent complex design.
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
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
2016-11-01
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
2015-10-29
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.
Error Modeling and Confidence Interval Estimation for Inductively Coupled Plasma Calibration Curves.
1987-02-01
confidence interval estimation for multiple use of the calibration curve is...calculate weights for the calibration curve fit. Multiple and single-use confidence interval estimates are obtained and results along the calibration curve are
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.
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.
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
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.
Model calibration and validation for OFMSW and sewage sludge co-digestion reactors.
Esposito, G; Frunzo, L; Panico, A; Pirozzi, F
2011-12-01
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 thus be used to assess the treatment efficiency and predict the methane production of full-scale digesters.
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.
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.
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.
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
Britton, Oliver J.; Bueno-Orovio, Alfonso; Van Ammel, Karel; Lu, Hua Rong; Towart, Rob; Gallacher, David J.; Rodriguez, Blanca
2013-01-01
Cellular and ionic causes of variability in the electrophysiological activity of hearts from individuals of the same species are unknown. However, improved understanding of this variability is key to enable prediction of the response of specific hearts to disease and therapies. Limitations of current mathematical modeling and experimental techniques hamper our ability to provide insight into variability. Here, we describe a methodology to unravel the ionic determinants of intersubject variability exhibited in experimental recordings, based on the construction and calibration of populations of models. We illustrate the methodology through its application to rabbit Purkinje preparations, because of their importance in arrhythmias and safety pharmacology assessment. We consider a set of equations describing the biophysical processes underlying rabbit Purkinje electrophysiology, and we construct a population of over 10,000 models by randomly assigning specific parameter values corresponding to ionic current conductances and kinetics. We calibrate the model population by closely comparing simulation output and experimental recordings at three pacing frequencies. We show that 213 of the 10,000 candidate models are fully consistent with the experimental dataset. Ionic properties in the 213 models cover a wide range of values, including differences up to ±100% in several conductances. Partial correlation analysis shows that particular combinations of ionic properties determine the precise shape, amplitude, and rate dependence of specific action potentials. Finally, we demonstrate that the population of models calibrated using data obtained under physiological conditions quantitatively predicts the action potential duration prolongation caused by exposure to four concentrations of the potassium channel blocker dofetilide. PMID:23690584
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.
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.
2010-09-01
difficulties that arise in the pursuit of a unified location/calibration capability. One is to develop fast and accurate raytracing techniques for modeling...that arise in the pursuit of a unified location/calibration capability. One is to develop fast and accurate raytracing techniques for modeling different... raytracing and travel-time calculation in 3D Earth models, such as the finite-difference eikonal method (e.g., Podvin and Lecomte, 1991), fast
NASA Astrophysics Data System (ADS)
Shi, Chuang; Li, Wenwen; Li, Min; Zhao, Qile; Sang, Jizhang
2015-07-01
Empirical mass density models for the thermosphere are widely used for object orbit determination and prediction, object collision avoidance, and re-entry analysis. But the error of these empirical models can often reach 15-30% or even larger during highly disturbed periods of the space environment. On the other hand, the mass density of the thermosphere can be derived from the orbit information contained in the two line elements (TLE) dataset. This technique provides an approach for calibrating the empirical model. Here we select TLE data of 36 low Earth orbiters (LEOs) recorded during 2000-2002 (solar maximum). The ratios of the TLE-derived densities to those from the empirical NRLMSISE00 model are calculated and used to calibrate the scale error of the NRLMSISE00 model by applying a linear height-dependent function. The calibration models for the NRLMSISE00 model during 2000-2002 are then obtained by a least squares adjustment procedure. The calibration factors at 250, 400, and 550 km from this calibration model are compared to the density ratios obtained by Emmert et al. (2008) who used TLE data from ∼5000 LEOs. The result indicates that the biases between these two independent factors at the 3 altitudes are all within +/-2%, and the standard deviations (STDs) are under 7%. Another 5 LEOs with altitudes ranging from 200 to 500 km are also selected to validate the precision of the calibration model. Their density ratios are calculated using the calibration model and the NRLMSISE00 model, respectively. The results demonstrate that by applying this calibration method the relative root mean square (RMS) error of the NRLMSISE00 model can be reduced by about 9%.
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.
A Legacy Magellanic Clouds Star Clusters Sample for the Calibration of Stellar Evolution Models
NASA Astrophysics Data System (ADS)
Fouesneau, Morgan
2014-10-01
Stellar evolution models are fundamental to all studies in astrophysics. These models are the foundations of the interpretation of colors and luminosities of stars necessary to address problems ranging from galaxy formation to determining the habitable zone of planets and interstellar medium properties. For decades the standard calibration of these models relied on a handful of star clusters. However, large uncertainties remain in the fundamental parameters underlying stellar evolution models. The project we propose is two-fold. First we propose to generate a new high quality reference dataset of the resolved stars in 121 Magellanic Cloud clusters, selected from 18 past programs to efficiently sample a large grid of stellar evolution models. Our team will measure the photometry of individual stars in those clusters and characterize individual completeness and photometric uncertainties. Second, we will migrate the calibration of the stellar evolution into a fully probabilistic framework, that will not only reflect the state-of-the-art, but will also be published with fully characterized uncertainties, based on the entire reference data set, rather than a few select clusters.We have entered an era dominated by large surveys {e.g. SDSS, PanSTARRS, Gaia, LSST} where the variations between families of stellar models are greater than the nominal precision of the instruments. Our proposed program will provide a library needed for a convergence in the stellar models and our understanding of stellar evolution.
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.
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
Relaxation Models of the (110) Zinc-Blende III-V Semiconductor Surfaces: Density Functional Study
Ye, H.; Chen, G.; Wu, Y.; Zhu, Y.; Wei, S. H.
2008-11-01
Clean III-V zinc-blende (110) surfaces are the most extensively studied semiconductor surface. For conventional III-V compounds such as GaAs and InP, the surface relaxation follows a bond rotation relaxation model. However, for III-nitrides recent study indicates that they follow a bond-constricting relaxation model. First-principles atom relaxation calculations are performed to explore the origin of the difference between the two groups of materials. By analyzing the individual shift trends and ionic properties of the top layer anions and cations, we attribute the difference between the conventional and nitride III-V compounds to the strong electronegativity of N, which leads to the s{sup 2}p{sup 3} pyramid bond angle to be larger than the ideal one in bulk (109.5{sup o}). The general trends of the atomic relaxation at the III-nitrides (110) surfaces are explained.
High-precision method of binocular camera calibration with a distortion model.
Li, Weimin; Shan, Siyu; Liu, Hui
2017-03-10
A high-precision camera calibration method for binocular stereo vision system based on a multi-view template and alternative bundle adjustment is presented in this paper. The proposed method could be achieved by taking several photos on a specially designed calibration template that has diverse encoded points in different orientations. In this paper, the method utilized the existing algorithm used for monocular camera calibration to obtain the initialization, which involves a camera model, including radial lens distortion and tangential distortion. We created a reference coordinate system based on the left camera coordinate to optimize the intrinsic parameters of left camera through alternative bundle adjustment to obtain optimal values. Then, optimal intrinsic parameters of the right camera can be obtained through alternative bundle adjustment when we create a reference coordinate system based on the right camera coordinate. We also used all intrinsic parameters that were acquired to optimize extrinsic parameters. Thus, the optimal lens distortion parameters and intrinsic and extrinsic parameters were obtained. Synthetic and real data were used to test the method. The simulation results demonstrate that the maximum mean absolute relative calibration errors are about 3.5e-6 and 1.2e-6 for the focal length and the principal point, respectively, under zero-mean Gaussian noise with 0.05 pixels standard deviation. The real result shows that the reprojection error of our model is about 0.045 pixels with the relative standard deviation of 1.0e-6 over the intrinsic parameters. The proposed method is convenient, cost-efficient, highly precise, and simple to carry out.
On the Usefulness of Hydrologic Landscapes for Hydrologic Model Calibration and Selection
NASA Astrophysics Data System (ADS)
Sawicz, K. A.; Leibowitz, S. G.; Comeleo, R. L.; Jones, C., Jr.; Wigington, P. J., Jr.
2015-12-01
Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaningful information between different watersheds without access to streamflow time series. A revised HL classification scheme was developed for over 10,000 assessment units (the fundamental unit of area for an HL) within the Pacific Northwest (PNW; Oregon, Washington, and Idaho). Aggregation and validation of the PNW HL assessment units to the watershed-scale was then completed for the PNW through use of clustering approaches and the hydrologic response as defined by hydroclimatic signatures. A result generated from this study was that the HL assessment units with greater moisture surplus or deficit formed a stronger connection between watershed-scale PNW HL and hydrologic response. The next step was to investigate the usefulness of the information contained within the PNW with regard to hydrologic modeling calibration and model structure selection. The hypothesis that we set forward for this study is that hydrologic response, as inferred and derived from the HL assessment units, is helpful for the structural identification and calibration of hydrologic models. A selection of streamgage stations and their associated watershed area across the PNW were modeled with lumped and semi-distributed modeling structures. The resulting model calibration and parameter space exploration leads to the identification of assessment unit types that are more hydrologically influential to the overall hydrologic functions of the watershed.
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.
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
The Benefit of Multi-Mission Altimetry Series for the Calibration of Hydraulic Models
NASA Astrophysics Data System (ADS)
Domeneghetti, Alessio; Tarpanelli, Angelica; Tourian, Mohammad J.; Brocca, Luca; Moramarco, Tommaso; Castellarin, Attilio; Sneeuw, Nico
2016-04-01
The growing availability of satellite altimetric time series during last decades has fostered their use in many hydrological and hydraulic applications. However, the use of remotely sensed water level series still remains hampered by the limited temporal resolution that characterizes each sensor (i.e. revisit time varying from 10 to 35 days), as well as by the accuracy of different instrumentation adopted for monitoring inland water. As a consequence, each sensor is characterized by distinctive potentials and limitations that constrain its use for hydrological applications. In this study we refer to a stretch of about 140 km of the Po River (the longest Italian river) in order to investigate the performance of different altimetry series for the calibration of a quasi-2d model built with detailed topographic information. The usefulness of remotely sensed water surface elevation is tested using data collected by different altimetry missions (i.e., ERS-2, ENVISAT, TOPEX/Poseidon, JASON-2 and SARAL/Altika) by investigating the effect of (i) record length (i.e. number of satellite measurements provided by a given sensor at a specific satellite track) and (ii) data uncertainty (i.e. altimetry measurements errors). Since the relatively poor time resolution of satellites constrains the operational use of altimetric time series, in this study we also investigate the use of multi-mission altimetry series obtained by merging datasets sensed by different sensors over the study area. Benefits of the highest temporal frequency of multi-mission series are tested by calibrating the quasi-2d model referring in turn to original satellite series and multi-mission datasets. Jason-2 and ENVISAT outperform other sensors, ensuring the reliability on the calibration process for shorter time series. The multi-mission dataset appears particularly reliable and suitable for the calibration of hydraulic model. If short time periods are considered, the performance of the multi-mission dataset
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.
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
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.
Calibrating a forest landscape model to simulate frequent fire in Mediterranean-type shrublands
Syphard, A.D.; Yang, J.; Franklin, J.; He, H.S.; Keeley, J.E.
2007-01-01
In Mediterranean-type ecosystems (MTEs), fire disturbance influences the distribution of most plant communities, and altered fire regimes may be more important than climate factors in shaping future MTE vegetation dynamics. Models that simulate the high-frequency fire and post-fire response strategies characteristic of these regions will be important tools for evaluating potential landscape change scenarios. However, few existing models have been designed to simulate these properties over long time frames and broad spatial scales. We refined a landscape disturbance and succession (LANDIS) model to operate on an annual time step and to simulate altered fire regimes in a southern California Mediterranean landscape. After developing a comprehensive set of spatial and non-spatial variables and parameters, we calibrated the model to simulate very high fire frequencies and evaluated the simulations under several parameter scenarios representing hypotheses about system dynamics. The goal was to ensure that observed model behavior would simulate the specified fire regime parameters, and that the predictions were reasonable based on current understanding of community dynamics in the region. After calibration, the two dominant plant functional types responded realistically to different fire regime scenarios. Therefore, this model offers a new alternative for simulating altered fire regimes in MTE landscapes. ?? 2007 Elsevier Ltd. All rights reserved.
On data requirements for calibration of integrated models for urban water systems.
Langeveld, Jeroen; Nopens, Ingmar; Schilperoort, Remy; Benedetti, Lorenzo; de Klein, Jeroen; Amerlinck, Youri; Weijers, Stefan
2013-01-01
Modeling of integrated urban water systems (IUWS) has seen a rapid development in recent years. Models and software are available that describe the process dynamics in sewers, wastewater treatment plants (WWTPs), receiving water systems as well as at the interfaces between the submodels. Successful applications of integrated modeling are, however, relatively scarce. One of the reasons for this is the lack of high-quality monitoring data with the required spatial and temporal resolution and accuracy to calibrate and validate the integrated models, even though the state of the art of monitoring itself is no longer the limiting factor. This paper discusses the efforts to be able to meet the data requirements associated with integrated modeling and describes the methods applied to validate the monitoring data and to use submodels as software sensor to provide the necessary input for other submodels. The main conclusion of the paper is that state of the art monitoring is in principle sufficient to provide the data necessary to calibrate integrated models, but practical limitations resulting in incomplete data-sets hamper widespread application. In order to overcome these difficulties, redundancy of future monitoring networks should be increased and, at the same time, data handling (including data validation, mining and assimilation) should receive much more attention.
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.
Lake Michigan eutrophication model: calibration, sensitivity, and five-year hindcast analysis
Lesht, B.M.
1984-09-01
A dynamic, deterministic, eutrophication model of Lake Michigan that was developed by Rodgers and Salisbury (1981) and installed at Argonne National Laboratotry as part of Interagency Agreement AD-89 F-0-145-0 is described in this report. The focus is on model formulation, calibration and verification, and the relationship between these processes and the available field data. Field data are too sparse for detailed analysis, but the model does produce a reasonable five-year simulation of several water quality variables, including total phosphorus and chlorophyll-a. The model provides a valuable framework for understanding the nutrient cycle in Lake Michigan, but forecasts made using the model must be considered within the context of model limitations. 20 references, 37 figures, 7 tables.
NASA Astrophysics Data System (ADS)
Lovreglio, Ruggiero; Ronchi, Enrico; Nilsson, Daniel
2015-11-01
The formulation of pedestrian floor field cellular automaton models is generally based on hypothetical assumptions to represent reality. This paper proposes a novel methodology to calibrate these models using experimental trajectories. The methodology is based on likelihood function optimization and allows verifying whether the parameters defining a model statistically affect pedestrian navigation. Moreover, it allows comparing different model specifications or the parameters of the same model estimated using different data collection techniques, e.g. virtual reality experiment, real data, etc. The methodology is here implemented using navigation data collected in a Virtual Reality tunnel evacuation experiment including 96 participants. A trajectory dataset in the proximity of an emergency exit is used to test and compare different metrics, i.e. Euclidean and modified Euclidean distance, for the static floor field. In the present case study, modified Euclidean metrics provide better fitting with the data. A new formulation using random parameters for pedestrian cellular automaton models is also defined and tested.
Liu, Yan; Cai, Wensheng; Shao, Xueguang
2016-12-05
Calibration transfer is essential for practical applications of near infrared (NIR) spectroscopy because the measurements of the spectra may be performed on different instruments and the difference between the instruments must be corrected. For most of calibration transfer methods, standard samples are necessary to construct the transfer model using the spectra of the samples measured on two instruments, named as master and slave instrument, respectively. In this work, a method named as linear model correction (LMC) is proposed for calibration transfer without standard samples. The method is based on the fact that, for the samples with similar physical and chemical properties, the spectra measured on different instruments are linearly correlated. The fact makes the coefficients of the linear models constructed by the spectra measured on different instruments are similar in profile. Therefore, by using the constrained optimization method, the coefficients of the master model can be transferred into that of the slave model with a few spectra measured on slave instrument. Two NIR datasets of corn and plant leaf samples measured with different instruments are used to test the performance of the method. The results show that, for both the datasets, the spectra can be correctly predicted using the transferred partial least squares (PLS) models. Because standard samples are not necessary in the method, it may be more useful in practical uses.
NASA Astrophysics Data System (ADS)
Liu, Yan; Cai, Wensheng; Shao, Xueguang
2016-12-01
Calibration transfer is essential for practical applications of near infrared (NIR) spectroscopy because the measurements of the spectra may be performed on different instruments and the difference between the instruments must be corrected. For most of calibration transfer methods, standard samples are necessary to construct the transfer model using the spectra of the samples measured on two instruments, named as master and slave instrument, respectively. In this work, a method named as linear model correction (LMC) is proposed for calibration transfer without standard samples. The method is based on the fact that, for the samples with similar physical and chemical properties, the spectra measured on different instruments are linearly correlated. The fact makes the coefficients of the linear models constructed by the spectra measured on different instruments are similar in profile. Therefore, by using the constrained optimization method, the coefficients of the master model can be transferred into that of the slave model with a few spectra measured on slave instrument. Two NIR datasets of corn and plant leaf samples measured with different instruments are used to test the performance of the method. The results show that, for both the datasets, the spectra can be correctly predicted using the transferred partial least squares (PLS) models. Because standard samples are not necessary in the method, it may be more useful in practical uses.
NASA Astrophysics Data System (ADS)
Wi, S.; Yang, Y. C. E.; Steinschneider, S.; Khalil, A.; Brown, C. M.
2014-09-01
This study utilizes high performance computing to test the performance and uncertainty of calibration strategies for a spatially distributed hydrologic model in order to improve model simulation accuracy and understand prediction uncertainty at interior ungaged sites of a sparsely-gaged watershed. The study is conducted using a distributed version of the HYMOD hydrologic model (HYMOD_DS) applied to the Kabul River basin. Several calibration experiments are conducted to understand the benefits and costs associated with different calibration choices, including (1) whether multisite gaged data should be used simultaneously or in a step-wise manner during model fitting, (2) the effects of increasing parameter complexity, and (3) the potential to estimate interior watershed flows using only gaged data at the basin outlet. The implications of the different calibration strategies are considered in the context of hydrologic projections under climate change. Several interesting results emerge from the study. The simultaneous use of multisite data is shown to improve the calibration over a step-wise approach, and both multisite approaches far exceed a calibration based on only the basin outlet. The basin outlet calibration can lead to projections of mid-21st century streamflow that deviate substantially from projections under multisite calibration strategies, supporting the use of caution when using distributed models in data-scarce regions for climate change impact assessments. Surprisingly, increased parameter complexity does not substantially increase the uncertainty in streamflow projections, even though parameter equifinality does emerge. The results suggest that increased (excessive) parameter complexity does not always lead to increased predictive uncertainty if structural uncertainties are present. The largest uncertainty in future streamflow results from variations in projected climate between climate models, which substantially outweighs the calibration uncertainty.
NASA Astrophysics Data System (ADS)
Wi, S.; Yang, Y. C. E.; Steinschneider, S.; Khalil, A.; Brown, C. M.
2015-02-01
This study tests the performance and uncertainty of calibration strategies for a spatially distributed hydrologic model in order to improve model simulation accuracy and understand prediction uncertainty at interior ungaged sites of a sparsely gaged watershed. The study is conducted using a distributed version of the HYMOD hydrologic model (HYMOD_DS) applied to the Kabul River basin. Several calibration experiments are conducted to understand the benefits and costs associated with different calibration choices, including (1) whether multisite gaged data should be used simultaneously or in a stepwise manner during model fitting, (2) the effects of increasing parameter complexity, and (3) the potential to estimate interior watershed flows using only gaged data at the basin outlet. The implications of the different calibration strategies are considered in the context of hydrologic projections under climate change. To address the research questions, high-performance computing is utilized to manage the computational burden that results from high-dimensional optimization problems. Several interesting results emerge from the study. The simultaneous use of multisite data is shown to improve the calibration over a stepwise approach, and both multisite approaches far exceed a calibration based on only the basin outlet. The basin outlet calibration can lead to projections of mid-21st century streamflow that deviate substantially from projections under multisite calibration strategies, supporting the use of caution when using distributed models in data-scarce regions for climate change impact assessments. Surprisingly, increased parameter complexity does not substantially increase the uncertainty in streamflow projections, even though parameter equifinality does emerge. The results suggest that increased (excessive) parameter complexity does not always lead to increased predictive uncertainty if structural uncertainties are present. The largest uncertainty in future streamflow
Approaches to highly parameterized inversion-A guide to using PEST for groundwater-model calibration
Doherty, John E.; Hunt, Randall J.
2010-01-01
Highly parameterized groundwater models can create calibration difficulties. Regularized inversion-the combined use of large numbers of parameters with mathematical approaches for stable parameter estimation-is becoming a common approach to address these difficulties and enhance the transfer of information contained in field measurements to parameters used to model that system. Though commonly used in other industries, regularized inversion is somewhat imperfectly understood in the groundwater field. There is concern that this unfamiliarity can lead to underuse, and misuse, of the methodology. This document is constructed to facilitate the appropriate use of regularized inversion for calibrating highly parameterized groundwater models. The presentation is directed at an intermediate- to advanced-level modeler, and it focuses on the PEST software suite-a frequently used tool for highly parameterized model calibration and one that is widely supported by commercial graphical user interfaces. A brief overview of the regularized inversion approach is provided, and techniques for mathematical regularization offered by PEST are outlined, including Tikhonov, subspace, and hybrid schemes. Guidelines for applying regularized inversion techniques are presented after a logical progression of steps for building suitable PEST input. The discussion starts with use of pilot points as a parameterization device and processing/grouping observations to form multicomponent objective functions. A description of potential parameter solution methodologies and resources available through the PEST software and its supporting utility programs follows. Directing the parameter-estimation process through PEST control variables is then discussed, including guidance for monitoring and optimizing the performance of PEST. Comprehensive listings of PEST control variables, and of the roles performed by PEST utility support programs, are presented in the appendixes.
NASA Astrophysics Data System (ADS)
Stephenson, John; Gallagher, Kerry; Holmes, Chris
2006-10-01
We present a new approach for modelling annealing of fission tracks in apatite, aiming to address various problems with existing models. We cast the model in a fully Bayesian context, which allows us explicitly to deal with data and parameter uncertainties and correlations, and also to deal with the predictive uncertainties. We focus on a well-known annealing algorithm [Laslett, G.M., Green, P.F., Duddy, I.R., Gleadow. A.J.W., 1987. Thermal annealing of fission tracks in apatite. 2. A quantitative-analysis. Chem. Geol., 65 (1), 1-13], and build a hierachical Bayesian model to incorporate both laboratory and geological timescale data as direct constraints. Relative to the original model calibration, we find a better (in terms of likelihood) model conditioned just on the reported laboratory data. We then include the uncertainty on the temperatures recorded during the laboratory annealing experiments. We again find a better model, but the predictive uncertainty when extrapolated to geological timescales is increased due to the uncertainty on the laboratory temperatures. Finally, we explictly include a data set [Vrolijk, P., Donelick, R.A., Quenq, J., Cloos. M., 1992. Testing models of fission track annealing in apatite in a simple thermal setting: site 800, leg 129. In: Larson, R., Lancelet, Y. (Eds.), Proceedings of the Ocean Drilling Program, Scientific Results, vol. 129, pp. 169-176] which provides low-temperature geological timescale constraints for the model calibration. When combined with the laboratory data, we find a model which satisfies both the low-temperature and high-temperature geological timescale benchmarks, although the fit to the original laboratory data is degraded. However, when extrapolated to geological timescales, this combined model significantly reduces the well-known rapid recent cooling artifact found in many published thermal models for geological samples.
Rosa, Isabel M D; Purves, Drew; Carreiras, João M B; Ewers, Robert M
Land cover change (LCC) models are used in many studies of human impacts on the environment, but knowing how well these models predict observed changes in the landscape is a challenge. We used nearly three decades of LCC maps to run several LCC simulations to: (1) determine which parameters associated with drivers of LCC (e.g. roads) get selected for which transition (forest to deforested, regeneration to deforested or deforested to regeneration); (2) investigate how the parameter values vary through time with respect to the different activities (e.g. farming); and (3) quantify the influence of choosing a particular time period for model calibration and validation on the performance of LCC models. We found that deforestation of primary forests tends to occur along roads (included in 95 % of models) and outside protected areas (included in all models), reflecting farming establishment. Regeneration tends to occur far from roads (included in 78 % of the models) and inside protected areas (included in 38 % of the models), reflecting the processes of land abandonment. Our temporal analysis of model parameters revealed a degree of variation through time (e.g. effectiveness of protected areas rose by 73 %, p < 0.001), but for the majority of parameters there was no significant trend. The degree to which model predictions agreed with observed change was heavily dependent on the year used for calibration (p < 0.001). The next generation of LCC models may need to embed trends in parameter values to allow the processes determining LCC to change through time and exert their influence on model predictions.
Calibration of Gurson-type models for porous sheet metals with anisotropic non-quadratic plasticity
NASA Astrophysics Data System (ADS)
Gologanu, M.; Kami, A.; Comsa, D. S.; Banabic, D.
2016-08-01
The growth and coalescence of voids in sheet metals are not only the main active mechanisms in the final stages of fracture in a necking band, but they also contribute to the forming limits via changes in the normal directions to the yield surface. A widely accepted method to include void effects is the development of a Gurson-type model for the appropriate yield criterion, based on an approximate limit analysis of a unit cell containing a single spherical, spheroidal or ellipsoidal void. We have recently [2] obtained dissipation functions and Gurson-type models for porous sheet metals with ellipsoidal voids and anisotropic non-quadratic plasticity, including yield criteria based on linear transformations (Yld91 and Yld2004-18p) and a pure plane stress yield criteria (BBC2005). These Gurson-type models contain several parameters that depend on the void and cell geometries and on the selected yield criterion. Best results are obtained when these key parameters are calibrated via numerical simulations using the same unit cell and a few representative loading conditions. The single most important such loading condition corresponds to a pure hydrostatic macroscopic stress (pure pressure) and the corresponding velocity field found during the solution of the limit analysis problem describes the expansion of the cavity. However, for the case of sheet metals, the condition of plane stress precludes macroscopic stresses with large triaxiality or ratio of mean stress to equivalent stress, including the pure hydrostatic case. Also, pure plane stress yield criteria like BBC2005 must first be extended to 3D stresses before attempting to develop a Gurson-type model and such extensions are purely phenomenological with no due account for the out- of-plane anisotropic properties of the sheet. Therefore, we propose a new calibration method for Gurson- type models that uses only boundary conditions compatible with the plane stress requirement. For each such boundary condition we use
NASA Astrophysics Data System (ADS)
Yang, Kun; Zhu, La; Chen, Yingying; Zhao, Long; Qin, Jun; Lu, Hui; Tang, Wenjun; Han, Menglei; Ding, Baohong; Fang, Nan
2016-02-01
Soil moisture is a key variable in climate system, and its accurate simulation needs effective soil parameter values. Conventional approaches may obtain soil parameter values at point scale, but they are costly and not efficient at grid scale (10-100 km) of current climate models. This study explores the possibility to estimate soil parameter values by assimilating AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observing System) brightness temperature (TB) data. In the assimilation system, the TB is simulated by the coupled system of a land surface model (LSM) and a radiative transfer model (RTM), and the simulation errors highly depend on parameters in both the LSM and the RTM. Thus, sensitive soil parameters may be inversely estimated through minimizing the TB errors. A crucial step for the parameter estimation is made to suppress the contamination of uncertainties in atmospheric forcing data. The effectiveness of the estimated parameter values is evaluated against intensive measurements of soil parameters and soil moisture in three grasslands of the Tibetan Plateau and the Mongolian Plateau. The results indicate that this satellite data-based approach can improve the data quality of soil porosity, a key parameter for soil moisture modeling, and LSM simulations with the estimated parameter values reasonably reproduce the measured soil moisture. This demonstrates it is feasible to calibrate LSMs for soil moisture simulations at grid scale by assimilating microwave satellite data, although more efforts are expected to improve the robustness of the model calibration.
Calibrating Cellular Automata of Land Use/cover Change Models Using a Genetic Algorithm
NASA Astrophysics Data System (ADS)
Mas, J. F.; Soares-Filho, B.; Rodrigues, H.
2015-08-01
Spatially explicit land use / land cover (LUCC) models aim at simulating the patterns of change on the landscape. In order to simulate landscape structure, the simulation procedures of most computational LUCC models use a cellular automata to replicate the land use / cover patches. Generally, model evaluation is based on assessing the location of the simulated changes in comparison to the true locations but landscapes metrics can also be used to assess landscape structure. As model complexity increases, the need to improve calibration and assessment techniques also increases. In this study, we applied a genetic algorithm tool to optimize cellular automata's parameters to simulate deforestation in a region of the Brazilian Amazon. We found that the genetic algorithm was able to calibrate the model to simulate more realistic landscape in term of connectivity. Results show also that more realistic simulated landscapes are often obtained at the expense of the location coincidence. However, when considering processes such as the fragmentation impacts on biodiversity, the simulation of more realistic landscape structure should be preferred to spatial coincidence performance.
Calibration of a distributed routing rainfall-runoff model at four urban sites near Miami, Florida
Doyle, W. Harry; Miller, Jeffrey E.
1980-01-01
Urban stormwater data from four Miami, Fla. catchments were collected and compiled by the U.S. Geological Survey and were used for testing the applicability of deterministic modeling for characterizing stormwater flows from small land-use areas. A description of model calibration and verification is presented for: (1) A 40.8 acre single-family residential area, (2) a 58.3-acre highway area, (3) a 20.4-acre commercial area, and (4) a 14.7-acre multifamily residential area. Rainfall-runoff data for 80, 108, 114, and 52 storms at sites, 1, 2, 3, and 4, respectively, were collected, analyzed, and stored on direct-access files. Rainfall and runoff data for these storms (at 1-minute time intervals) were used in flow-modeling simulation analyses. A distributed routing Geological Survey rainfall-runoff model was used to determine rainfall excess and route overland and channel flows at each site. Optimization of soil-moisture- accounting and infiltration parameters was performed during the calibration phases. The results of this study showed that, with qualifications, an acceptable verification of the Geological Survey model can be achieved. (Kosco-USGS)
Mathematical Model and Calibration Procedure of a PSD Sensor Used in Local Positioning Systems
Rodríguez-Navarro, David; Lázaro-Galilea, José Luis; Bravo-Muñoz, Ignacio; Gardel-Vicente, Alfredo; Domingo-Perez, Francisco; Tsirigotis, Georgios
2016-01-01
Here, we propose a mathematical model and a calibration procedure for a PSD (position sensitive device) sensor equipped with an optical system, to enable accurate measurement of the angle of arrival of one or more beams of light emitted by infrared (IR) transmitters located at distances of between 4 and 6 m. To achieve this objective, it was necessary to characterize the intrinsic parameters that model the system and obtain their values. This first approach was based on a pin-hole model, to which system nonlinearities were added, and this was used to model the points obtained with the nA currents provided by the PSD. In addition, we analyzed the main sources of error, including PSD sensor signal noise, gain factor imbalances and PSD sensor distortion. The results indicated that the proposed model and method provided satisfactory calibration and yielded precise parameter values, enabling accurate measurement of the angle of arrival with a low degree of error, as evidenced by the experimental results. PMID:27649189
Runoff prediction in a poorly gauged basin using isotope-calibrated models
NASA Astrophysics Data System (ADS)
Yamanaka, Tsutomu; Ma, Wenchao
2017-01-01
Predictions in ungauged basins have been a major challenge in hydrologic sciences, and there is still much work needed to achieve robust and reliable predictions for such basins. Here, we propose and test a novel approach for predicting runoff from poorly gauged basins using a minimum complex model calibrated with isotope data alone (i.e., without observed discharge data). The model is composed of two water-stores (soil water and groundwater) and considers their connectivity to runoff in terms of both water and isotope budgets. In a meso-scale basin in which riverbed deformations frequently occur, making automatic observation of river discharge difficult, we measured hydrogen and oxygen isotope composition (δ2H and δ18O) of precipitation and river water twice-weekly for one year. Runoff predicted by the model agreed well with that observed monthly or bimonthly. Monte Carlo simulation revealed a strong coherence between model performance in isotope simulation and runoff prediction, demonstrating that the use of isotopes as dynamic proxies of calibration targets helps reliably constrain model parameters. Our results indicate that this approach can serve as a powerful tool for prediction of runoff hydrographs, particularly for basins in which the stage-discharge relationship is highly variable.
Modeling Spectralon's Bidirectional Reflectance for In-flight Calibration of Earth-Orbiting Sensors
NASA Technical Reports Server (NTRS)
Flasse, Stephane P.; Verstraete, Michel M.; Pinty, Bernard; Bruegge, Carol J.
1993-01-01
The in-flight calibration of the EOS Multi-angle Imaging SpectroRadiometer (MISR) will be achieved, in part, by observing deployable Spectralon panels. This material reflects light diffusely, and allows all cameras to view a near constant radiance field. This is particularly true when a panel is illuminated near the surface normal. To meet the challenging MISR calibration requirements, however, very accurate knowledge of the panel reflectance must be known for all utilized angles of illumination, and for all camera and monitoring photodiode view angles. It is believed that model predictions of the panels Bidirectional Reflectance Distribution Function (BRDF) can be used in conjunction with a measurements program to provide the required characterization. This paper describes the results of a model inversion which was conducted using measured Spectralon BRDF data at several illumination angles. Four physical parameters of the material were retrieved, and are available for use with the model to predict reflectance for any arbitrary illumination or view angle. With these data the root mean square difference between the model and the observations is currently of the order of the noise in the data, at about +/- l%. With this success the model will now be used in a variety of future studies, including the development of a measurements test plan, the validation of these data, and the prediction of a new BRDF profile, should the material degrade in space.
Cone-Probe Rake Design and Calibration for Supersonic Wind Tunnel Models
NASA Technical Reports Server (NTRS)
Won, Mark J.
1999-01-01
A series of experimental investigations were conducted at the NASA Langley Unitary Plan Wind Tunnel (UPWT) to calibrate cone-probe rakes designed to measure the flow field on 1-2% scale, high-speed wind tunnel models from Mach 2.15 to 2.4. The rakes were developed from a previous design that exhibited unfavorable measurement characteristics caused by a high probe spatial density and flow blockage from the rake body. Calibration parameters included Mach number, total pressure recovery, and flow angularity. Reference conditions were determined from a localized UPWT test section flow survey using a 10deg supersonic wedge probe. Test section Mach number and total pressure were determined using a novel iterative technique that accounted for boundary layer effects on the wedge surface. Cone-probe measurements were correlated to the surveyed flow conditions using analytical functions and recursive algorithms that resolved Mach number, pressure recovery, and flow angle to within +/-0.01, +/-1% and +/-0.1deg , respectively, for angles of attack and sideslip between +/-8deg. Uncertainty estimates indicated the overall cone-probe calibration accuracy was strongly influenced by the propagation of measurement error into the calculated results.
Modeling and simulation research of a new calibration platform for visual test system
NASA Astrophysics Data System (ADS)
Bo, Liu; Dong, Ye; Che, Rensheng
2009-05-01
It's a new method that 3D motion parameters of rocket motor nozzle are measured by vision measuring technology, but the dynamic mesurement precision of vision measuring system should be evaluated. The calibration platform with nozzle model can simulate the actual motion of rocket motor nozzle, and supply standard motion parameters for dynamic calibration to vision measurement system. After analyzing the motion of some type rocket motor nozzle, a new parallel table for calibration is proposed. The mechanism is made up of a base, a moving table and three links. There are three degrees of freedom, rotation on X or Y coordinate axis, displacement on Z coordinate axis. The rotation angle is measured by photoelectric encoder, the displacement is measured by grating scale. The closed loop test system have two main features. First, the rotation center is fixed because of cross shaft. Second, the position and pose of table can measured with high precision. Then the normal kinematic solution to position-pose of the table is presented. The virtual prototype is constructed on Pro/E, and the movement simulation is processed through Adams, thus the correctness of normal kinematic solutions to position-pose is verified.
Model-based calibration of an interferometric setup with a diffractive zoom-lens
NASA Astrophysics Data System (ADS)
Bielke, Alexander; Baer, Goran; Pruss, Christof; Osten, Wolfgang
2015-08-01
The fabrication of aspheres and freeform surfaces requires a high-precision shape measurement of these elements. In terms of accuracy, interferometric systems provide the best performance for specular surfaces. To test aspherical lenses, it is necessary to adapt or partially adapt the test wavefront to the surface under test. Recently, we have proposed an interferometric setup with a diffractive zoom-lens that includes two computer generated holograms for this purpose.1 Their surface phases are a combination of a cubic function for the adaption of aberrations and correction terms necessary to compensate substrate-induced errors. With this system based on Alvarez design a variable defocus and astigmatism controlled by a lateral shift of the second element is achieved. One of the main challenges is the calibration of the system. We use a black-box model2 recently introduced for a non-null test interferometer, the so called tilted wave interferometer3 (TWI). With it, the calibration data are calculated by solving an inverse problem. The system is divided in the two parts of illumination and imaging optics. By the solution of an inverse problem, we get a set of data, which describes separately the wavefronts of the illumination and imaging optics. The main difference to the TWI is the flexible diffractive element, which can be used in continuous positions. To combine the calibration data of a couple of positions with the exact placement, we designed alignment structures on the hologram. We will show the general functionality of this calibration and first simulation results.