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Model Response (model + response)
Selected AbstractsEffect of autumn and winter meteorological variables on spring aphid populations in the Po valley, Northern ItalyJOURNAL OF APPLIED ENTOMOLOGY, Issue 8 2001D. Rongai Prediction of aphid populations is crucial to the successful application of control strategies. In previous studies clear relationships between aphid catches and meteorological variables were highlighted. The primary objective of this study was to quantify the effects of autumn and winter meteorological variables on the aphid species populations the following spring. The data on all the species caught at two Italian sites (Ozzano Emilia and Budrio) up to 31 May from 1992 to 1999 were used for this study. Different models were found according to the aphid biological cycle (i.e. holocycle, anholocycle, holo-anholocycle). A fourth group of minor species, designated as ,others', was properly modelled as holo-anholocycle species. A satisfactory fit was observed when holocycle species were plotted against minimum temperature and precipitation in October, anholocycle species against minimum temperature and precipitation in December,January, holo-anholocycle species and ,others' against wind speed and number of frosty days in November, and minimum temperature and precipitation in December,January. Model response was more consistent at Budrio (open flat site) than at Ozzano Emilia (flat site delimited by a hill). A coherent pattern was found with an overall comparison of the estimates against observations. The possibility offered by these empirical models for forecasting spring aphid populations of all species at a given site is clearly of interest. This first study encouraged further investigation aimed at validating models before applying them in practice. [source] Model predicting dynamics of biomass, structure and digestibility of herbage in managed permanent pastures.GRASS & FORAGE SCIENCE, Issue 2 2006Abstract A mechanistic model, simulating the dynamics of production, structure and digestibility of managed permanent pastures, was developed. Its evaluation consisted of (i) studying model response to a range of grassland communities, cutting frequencies and site characteristics, and (ii) testing the model against experimental data, focusing on biomass accumulation and digestibility during three different cutting cycles, herbage production under a frequent cutting regime, and sward dynamics during the winter. The model realistically predicted the dynamics of biomass, structure and digestibility of herbage for various communities of permanent pastures, in different sites and under different management conditions for upland areas of the Auvergne region in France. The predicted responses to environmental conditions and cutting regimes were close to field observations and experimental results. Although the model successfully predicted the dynamics of average herbage production, it lacked precision in predicting the low biomass production observed in relation to the weather conditions found in a few specific years. The model was able to predict the dynamics of the sward during winter and is, therefore, fit for producing multiple-year simulations. To improve the prediction of variability of biomass production and to predict the medium- to long-term dynamics of permanent pastures, the model could be refined by adding seasonal and multiple-year variation in nitrogen availability and in the proportion of grass functional groups in the grassland community. [source] On the effects of triangulated terrain resolution on distributed hydrologic model responseHYDROLOGICAL PROCESSES, Issue 11 2005Enrique R. Vivoni Abstract Distributed hydrologic models based on triangulated irregular networks (TIN) provide a means for computational efficiency in small to large-scale watershed modelling through an adaptive, multiple resolution representation of complex basin topography. Despite previous research with TIN-based hydrology models, the effect of triangulated terrain resolution on basin hydrologic response has received surprisingly little attention. Evaluating the impact of adaptive gridding on hydrologic response is important for determining the level of detail required in a terrain model. In this study, we address the spatial sensitivity of the TIN-based Real-time Integrated Basin Simulator (tRIBS) in order to assess the variability in the basin-averaged and distributed hydrologic response (water balance, runoff mechanisms, surface saturation, groundwater dynamics) with respect to changes in topographic resolution. Prior to hydrologic simulations, we describe the generation of TIN models that effectively capture topographic and hydrographic variability from grid digital elevation models. In addition, we discuss the sampling methods and performance metrics utilized in the spatial aggregation of triangulated terrain models. For a 64 km2 catchment in northeastern Oklahoma, we conduct a multiple resolution validation experiment by utilizing the tRIBS model over a wide range of spatial aggregation levels. Hydrologic performance is assessed as a function of the terrain resolution, with the variability in basin response attributed to variations in the coupled surface,subsurface dynamics. In particular, resolving the near-stream, variable source area is found to be a key determinant of model behaviour as it controls the dynamic saturation pattern and its effect on rainfall partitioning. A relationship between the hydrologic sensitivity to resolution and the spatial aggregation of terrain attributes is presented as an effective means for selecting the model resolution. Finally, the study highlights the important effects of terrain resolution on distributed hydrologic model response and provides insight into the multiple resolution calibration and validation of TIN-based hydrology models. Copyright © 2005 John Wiley & Sons, Ltd. [source] Generalized strain probing of constitutive modelsINTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, Issue 15 2004Youssef M. A. Hashash Abstract Advanced material constitutive models are used to describe complex soil behaviour. These models are often used in the solution of boundary value problems under general loading conditions. Users and developers of constitutive models need to methodically investigate the represented soil response under a wide range of loading conditions. This paper presents a systematic procedure for probing constitutive models. A general incremental strain probe, 6D hyperspherical strain probe (HSP), is introduced to examine rate-independent model response under all possible strain loading conditions. Two special cases of HSP, the true triaxial strain probe (TTSP) and the plane-strain strain probe (PSSP), are used to generate 3-D objects that represent model stress response to probing. The TTSP, PSSP and general HSP procedures are demonstrated using elasto-plastic models. The objects resulting from the probing procedure readily highlight important model characteristics including anisotropy, yielding, hardening, softening and failure. The PSSP procedure is applied to a Neural Network (NN) based constitutive model. It shows that this probing is especially useful in understanding NN constitutive models, which do not contain explicit functions for yield surface, hardening, or anisotropy. Copyright © 2004 John Wiley & Sons, Ltd. [source] A new approach to response surface development for detailed gas-phase and surface reaction kinetic model optimizationINTERNATIONAL JOURNAL OF CHEMICAL KINETICS, Issue 2 2004Scott G. Davis We propose a new method for constructing kinetic response surfaces used in the development and optimization of gas-phase and surface reaction kinetic models. The method, termed as the sensitivity analysis based (SAB) method, is based on a multivariate Taylor expansion of model response with respect to model parameters, neglecting terms higher than the second order. The expansion coefficients are obtained by a first-order local sensitivity analysis. Tests are made for gas-phase combustion reaction models. The results show that the response surface obtained with the SAB method is as accurate as the factorial design method traditionally used in reaction model optimization. The SAB method, however, presents significant computational savings compared to factorial design. The effect of including the partial and full third order terms was also examined and discussed. The SAB method is applied to optimization of a relatively complex surface reaction mechanism where large uncertainty in rate parameters exists. The example chosen is laser-induced fluorescence signal of OH desorption from a platinum foil in the water/oxygen reaction at low pressures. We introduce an iterative solution mapping and optimization approach for improved accuracy. © 2003 Wiley Periodicals, Inc. Int J Chem Kinet 36: 94,106, 2004 [source] Identification of plastic material parameters with error estimationPROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2005Jaan Unger In recent years, inverse analysis has become a common approach to typical engineering problems such as model identification. In this contribution, the inverse problem is discussed in light of taking experimental uncertainties into account. This involves in particular the propagation of experimental errors and the analysis of the sensitivity of the model response to variations in the model parameters to be determined. The method is applied to an elasto-viscoplastic material model which is used in the context of electromagnetic high-speed forming. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Network-magnetotelluric method and its first results in central and eastern Hokkaido, NE JapanGEOPHYSICAL JOURNAL INTERNATIONAL, Issue 1 2001Makoto Uyeshima Summary A new field observation technique based on the magnetotelluric (MT) method has been developed to determine deep and large-scale 3-D electrical conductivity distributions in the Earth. The method is named ,Network-MT', and employs a commercial telephone network, to measure voltage differences with long dipole lengths ranging from 10 to several tens of kilometres. This observation configuration enables us to obtain the telluric field distribution with nearly continuous coverage over a target region. Response functions are estimated between the respective voltage differences and the horizontal magnetic fields at a reference point. Owing to the long electrode spacing, the observed responses are relatively free from the effects of small-scale near-surface heterogeneity with a scalelength shorter than the typical electrode spacing. Therefore, physically meaningful direct comparison between the observations and model responses is feasible even if the fine-scale features of near-surface heterogeneity are ignored. This extensively reduces the difficulty, especially in 3-D MT interpretation. The first Network-MT experiment was performed in central and eastern Hokkaido, NE Japan, in 1989. It took about five months to complete all of the measurements, and used 209 dipoles to cover the target area of 200(EW) × 200(NS) km2. The long electrode spacing enabled us to obtain the voltage differences with a high signal-to-noise ratio. For 175 dipoles, the squared multiple coherency between the voltage difference and the horizontal magnetic field at Memambetsu Geomagnetic Observatory was determined to be more than 0.9 in the period from 102 to 104 s. 193 MT impedances were computed in tensor form by linear combination of the response functions. The estimated impedances generally possessed smooth period dependence throughout the period range. No drastic spatial change was observed in the characteristics of the tensors for neighbouring sites, and some regional trend could be detected in the spatial distribution. Thus, we confirmed the merit of the Network-MT method, that its responses are little affected by small-scale near-surface structures. The regional feature of the response implied a significant influence of the coast effect, and was well correlated with the regional geological setting in Hokkaido. Conventional Groom,Bailey tensor decomposition analysis revealed that the target region is not regionally one- or two-dimensional. Therefore, we developed a 3-D forward modelling scheme specially designed for the Network-MT experiment, and tried to reproduce the Network-MT responses directly. In the 3-D model, a realistic land,sea distribution was considered. The resistivity of sea water was fixed to be 0.25 , m and, as a first trial of 3-D modelling, the resistivity of the land was assumed to be uniform and its value was determined to be 200 , m by a simple one-parameter inversion. Overall agreements between the observations and the best-fit model responses indicated the importance of the 3-D coast effect in the target region. However, there remained significant discrepancies, especially in the phase of the responses, which provide a clue to determining a regional deep 3-D structure. [source] Inferential non-centred principal curve analysis of time-intensity curves in sensory analysis: the methodology and its application to beer astringency evaluationJOURNAL OF CHEMOMETRICS, Issue 5-6 2007Nancy François Abstract Improving technologies and better understanding of sensory phenomena have lead sensory analysts to develop statistical methods to assess sensations that endure over time (e.g. the bitterness or astringency of a beer) dynamically. The data produced by this type of experiment is classically a time-intensity (TI) curve, and their analysis remains an active research topic. The classical approach, widely used in this context, starts by extracting some significant parameters from the initial curves (maximum intensity, area under the curve (AUC), etc.). Descriptive data analysis or statistical modelling is then applied to get information from these summary parameters. This paper presents a different method, called inferential non-centred principal curve analysis (INCPCA), for the analysis of TI curves. It combines multivariate analysis (to visualise the curves in a space of smaller dimensions) with statistical modelling (aimed at enhancing the significance of factor effects). Non-centred principal curves (NCPCs) are first extracted from the curves matrix. They decompose the TI curves into different interpretable components. Score plots are used to represent the projection of the initial curves in the space of the first principal curves and allow factors and judge effects to be visualised. Mixed modelling is then applied to test the significance of these effects using PCA scores as model responses. The classical and INCPCA methods are illustrated on a TI experiment exploring the relation between beer astringency and three factors of interest: pH, O2 content and aging. Eight beers arranged in a 23 factorial design were tested in triplicate by eight trained judges. Copyright © 2007 John Wiley & Sons, Ltd. [source] | ||||||||||||||||