Model validation

We present algorithms and systems for interactive boundary computation of Boolean combinations of sculptured solids. The algorithm is applicable to all spline solids and computes an accurate boundary representation. To speed up the computation, the algorithm exploits parallelism at all stages. It has been implemented on a multi-processor SGI and takes one second on average per boolean operation to compute the boundary of high degree primitives. The system has also been integrated with an immersive design and manipulation environment. The resulting system is able to interactively evaluate boundaries of the models, display them for model validation and place them at appropriate position using collision detection algorithms. ¥ 16. Furthermore, algorithms for interactive collision detection and object placement need an exact description of the boundary 18. Other applications of boundary representation (B-rep) include computation of solid's mass properties. Main Contribution: We present fast, parallel algorithms and systems for computing the boundary of boolean combinations of sculptured solids. The resulting boundary is represented in terms of trimmed Bézier patches. Given two primc

This paper reports on a comprehensive model evaluation protocol for urban scale flow and dispersion models that has been developed within the framework of the COST action 732 on Quality Assurance and Improvement of Micro-Scale Meteorological Models. It briefly discusses the different components forming model evaluation with particular emphasis on model validation and on the implementation of the protocol for a specific test case: the MUST (Mock Urban Setting Test) experiment. The protocol was first developed with building-resolving models in mind, but more traditional integral models have also been included. Currently the Action is finalising the MUST exercise results and will suggest the best approach for further model evaluation and for the standardization of CFD modelling practise for micro-scale meteorological applications.

A polarimetric coherent electromagnetic scattering model for short branching vegetation is developed in this paper. With the realistic structures that reasonably describe the relative positions of the particles, this model is able to consider the coherent effect due to the phase difference between the scattered fields from different particles, and account for the second-order, near-field interaction between particles, to which the relative positions and orientation of the particles are essential. The model validation with measurements is also presented, and excellent agreement is obtained. The polarimetric radar backscatter measurements for soybean plants using truck-mounted scatterometers were conducted at L-band and C-band under different soil-moisture conditions. Through an extensive ground truth, the important plant and rough surface parameters such as the soil moisture and surface roughness, vegetation dielectric constant, and geometry of the soybean plants, were characterized for model verification. It is found that the second-order near-field scattering is significant at C-band for fully grown soybeans due to the high vegetation particle density, and at L-band, the contribution from the second-order near field is negligible. The coherence effect is shown to be important at L-band and to a much lesser extent at C-band. This model is then used to demonstrate its ability for estimating the physical parameters of a soybean field, including soil moisture from a polarimetric set of AIRSAR images.

The purpose of this study is to investigate the combined influence of process parameters (independent variables) such as homogenization speed (X 1 ), duration (X 2 ), and temperature (X 3 ) during the preparation of dacarbazine-loaded cubosomes. Box-Behnken design was used to rationalize the influence of these three factors on two responses, namely particle size (Y 1 ) and encapsulation efficiency (Y 2 ). Independent and dependent variables were analyzed with multiple regressions to establish a fullmodel second-order polynomial equation. F value was calculated to confirm the omission of insignificant parameters or interactions of parameters from the analysis to derive a reduced-model polynomial equation to predict the Y 1 and Y 2 of dacarbazine-loaded cubosomes. Pareto charts were also obtained to show the effects of X 1 , X 2 , and X 3 on Y 1 and Y 2 . For Y 1 , there was a model validated for more accurate prediction of response parameter by performing checkpoint analysis. The optimization process and Pareto charts were obtained automatically and they predicted the levels of independent parameters X 1 , X 2 , and X 3 (0.889794, 0.11886, and 0.56201, respectively) and minimized Y 1 . The optimal process parameters (homogenization's speed=~24,000 rpm, duration=5.5 min, and temperature=76°C) led to the production of cubosomes with 85.6 nm in size and 16.7% in encapsulation efficiency. The Box-Behnken design proved to be a useful tool in the preparation and optimization of dacarbazine-loaded cubosomes. For encapsulation efficiency (Y 2 ), further studies are needed to enhance the result and improve the model for such water-soluble drug encapsulation in cubosomes.

Scientists need a better and larger set of tools to validate land-use change models, because it is essential to know a model's prediction accuracy. This paper describes how to use the relative operating characteristic (ROC) as a quantitative measurement to validate a land-cover change model. Typically, a crucial component of a spatially explicit simulation model of land-cover change is a map of suitability for land-cover change, for example a map of probability of deforestation. The model usually selects locations for new land-cover change at locations that have relatively high suitability. The ROC can compare a map of actual change to maps of modeled suitability for land-cover change. ROC is a summary statistic derived from several two-by-two contingency tables, where each contingency table corresponds to a different simulated scenario of future land-cover change. The categories in each contingency table are actual change and actual non-change versus simulated change and simulated non-change. This paper applies the theoretical concepts to a model of deforestation in the Ipswich watershed, USA.

This paper presents the SILAM dispersion modelling system that has been developed for solving various forward and inverse dispersion problems. The current operational version is based on a Lagrangian dispersion model that applies an iterative advection algorithm and a Monte Carlo random-walk diffusion representation. The system can utilize meteorological data from either the HIRLAM or ECMWF numerical weather prediction models. We present an evaluation of SILAM against the data of the European Tracer Experiment (ETEX). The model showed an overall time correlation coefficient of 0.6 (over 150 stations), with specific values for the two ETEX measurement arcs of 0.75 and 0.74, respectively. The number of well-reproduced observation sites are 55, 37, and 40-for a Figure of Merit in Time of 40.2, a correlation coefficient of 40.7, and mean observed and modelled values being within a factor of 2, respectively. We have also investigated the sensitivity of the model to the meteorological input data and model setup. The most important factors with regard to the model performance were (i) the selection of the meteorological input data set and (ii) the method used for the atmospheric boundary layer height estimation. The study allowed selection of the optimum setup for the operational model configuration. We also tried to find explanations for the successes and failures of the specific methodologies in order to facilitate broader conclusions on their applicability in emergency dispersion modelling. r

This paper presents a basic tutorial on epistemic uncertainty q uantification methods. Epistemic uncertainty, characterizing lack-of-knowledge, is often prevalent in engineering applications. However, the methods we have for analyzing and propagating epistemic uncertainty are not as nearly widely used or well-understood as methods to propagate aleatory uncertainty (e.g. inherent variability characterized by probability distributions). We examine three methods used in propagating epistemic uncertainties: interval analysis, Dempster-Shafer evidence theory, and second-order probability. We demonstrate examples of their use on a problem in structural dynamics.

Artificial Neural Network (ANN) and regression models were developed using watershed-scale geomorphologic parameters to predict surface runoff and sediment losses of the St. Esprit watershed, Quebec, Canada. Ge o- morphological parameters describing the land surface drainage characteristics and surface water flow behav- iour were empirically associated with measured rainfall and runoff data and used as input to a three-layered back-propagation

In the framework of climate change, the increase in ocean heat waves frequency is expected to impact marine life. Large scale positive temperature anomalies already occurred in the northwestern Mediterranean Sea in 1999, 2003, and 2006. These anomalies were associated with mass mortality events of macrobenthic species in coastal areas (0-40 m in depth). The anomalies were particularly severe in 1999 and 2003 when thousands of kilometres of coasts and about 30 species were affected. The aim of this study was to develop a methodology to assess the current risk of mass mortality associated with temperature increase along NW Mediterranean continental coasts. A 3D regional ocean model was used to obtain the temperature conditions for the period 2001-2010, for which the model outputs were validated by comparing them with in situ observations in affected areas. The model was globally satisfactory although extremes were underestimated and required correction. Combined with information on the thermo-tolerance of a key species (the red gorgonian Paramuricea clavata) as well as its spatial distribution, the modelled temperature conditions were then used to assess the risk of mass mortality associated with thermal stress for the first time. Most of the known areas of observed mass mortality were found using the model, although the degree of risk in certain areas was underestimated. Using climatic IPCC scenarios, the methodology could be applied to explore the impacts of expected climate change in the NW Mediterranean. This is a key issue for the development of sound management and conservation plans to protect Mediterranean marine biodiversity in the face of climate change.

In order to validate the dry-cast model developed by us, a multifaceted experimental approach was undertaken whereby three process variables can be followed independently in real time. Since it is extremely difficult to determine experimentally the concentration and temperature profiles within the cast polymer solution, experiments were designed so as to provide information on the coupled mass-and heattransfer processes by measuring other process variables. The experimental data-acquisition technique combined gravimetric, inframetric, and light-reflection analyses which provided information on the overall mass change, surface temperature, and the onset and duration of phase separation, respectively. Structural studies were conducted using scanning electron microscopy. These studies revealed that macrovoids or "fingers" can be formed in dry-cast membranes. A hypothesis for the formation of fingers based on the model predictions and experimental observations is proposed.

Twenty pH-controlled batch cultures with Lactobacillus helveticus were carried out in whey permeate-yeast extract medium according to a composite design with three factors: pH setpoint, and yeast extract and initial whey permeate concentrations. Growth and production parameters were estimated from experimental data with the Richards and Luedeking and Piret models, respectively, and analyzed statistically with response surfaces. The maximum specific growth rate, max , depended primarily on pH, with an optimum of 0.7 h Ϫ1 near pH 5.5. Whey permeate concentration had no direct effect on maximum specific growth rate, but showed a strong interaction with pH. Yeast extract addition had a strong positive effect on maximum specific growth rate. During nitrogen-limited batch cultures X max depended on yeast extract concentration and pH, as well as on interactions of these variables with whey permeate concentration. The growth-associated lactic acid production parameter a was constant at 4.5 g lactic acid (g biomass) Ϫ1 , while the nongrowth-associated production parameter b, estimated during growth and early stationary phase, was a linear function of pH. This study allowed for the first detailed multifactor kinetic analysis of Lb. helveticus growth and lactic acid production, with a limited number of experiments, and demonstrated the importance of interactions among tested culture conditions.

This paper reviews the literature on applied general equilibrium analysis of agricultural and resource policies. It begins with an historical overview, followed by an assessment of the benefits of this methodology for examining sectoral policies. The chapter then turns to questions of disaggregation of commodities, households, regions and factors of production. Parameter specification and model closure are discussed, as well as problems of modeling policies which affect agriculture. There are also special sections on agriculture and the environment, product differentiation and imperfect competition and model validation. The paper closes with a discussion of future challenges to the field.

A summary of the evaluation of an air flow and contaminant model as part of the IEA-ECBCS Annex 23 `Multizone Airflow Modelling' is presented. Evaluation, rather validation, is the goal. The most important points of the cases analyzed during this project are presented and commented from the point of view of analytical evaluation, comparison with experimental data and user sensitivity. The conclusion addresses the need for user-friendly tools and guidelines for the analysis of simulation output.

This paper discusses verification, validation, and accreditation of simulation models. The different approaches to deciding model validity are presented; how model verification and validation relate to the model development process are discussed; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity are described; ways to document results are given; a recommended procedure is presented; and accreditation is briefly discussed.

Silicon carbide Schottky, merged PiN Schottky (MPS), and PiN diode technologies are modeled for on-state and reverse recovery conditions. The on-state operation of the PiN diode is modeled through four unique regimes of operation, including current densities resulting in emitter recombination, which results in a stored charge plateau during reverse recovery of SiC PiN diodes. An expression for the moving boundary redistribution capacitance is developed to accurately describe the reverse recovery process in PiN diodes. Furthermore, the extraction of stored charge and junction capacitance from transient reverse recovery measurements is also demonstrated for all diode technologies. The on-state operation of Schottky and merged PiN Schottky diodes is described and a method to model the surge current in MPS diodes is discussed. The performance of the model is demonstrated for a commercially available 600 V, 4 A Schottky diode and a 10 kV, 7.5 A PiN diode. Measurements demonstrating the extraction of model parameters and model validation results are included.

A spatially discretised thermo-electrochemical model is developed to calculate the temperature distribution in a tubular solid oxide fuel cell (SOFC). Model validation is accomplished based on the operating data from a demonstration plant. Using a mechanical model of the ceramic membrane-electrode assembly, the distribution of thermo-mechanical stress is calculated from the temperature profile. The resulting risk of fracture failure, being one of the crucial life-limiting factors of SOFC, is determined by means of Weibull analysis. The methodology and results are presented in two parts: Part I covers the dynamic operating properties of the SOFC and the time scale of material creep in its ceramic components. Part II deals with the risk of fracture failure related to transient operating scenarios, discusses its dependency on the operating conditions and derives a low-risk operating strategy. The dynamic operating behaviour is found to be dominated by the large thermal inertia of the solid cell components. An analysis of the creep relaxation indicates a significant relief of mechanical stress in the electrodes within a few hours of operation. This justifies a novel assumption regarding the stress-free state in the mechanical analysis of the fuel cell, which significantly increases the plausibility of the resulting risk of fracture failure.

This study proposed a modified nonlinear storage function runoff model to take into account the storage hysteresis effect, in which there exists difference of the storage–discharge relationship between the rising and recession limb. Since the modified storage function runoff has seven parameter, a parameter-calibration method, which combines the genetic algorithm with the least square criterion. For model calibration and validation, twenty rainfall–runoff events (1968–2005) recorded at Wudu gage in Keelung River in northern Taiwan were used in the study. The results of model validation reveal that the modified storage function runoff model not only produces the realistic storage–discharge relationship, but also provides a good estimation of the runoff.► The modified nonlinear storage function runoff model (MPSFRM) takes into account the difference of storage-discharge relationship between the rising and recession limb. ► MPSFRM produces the realistic storage-discharge relationship. ► MPSFRM can also provide a good estimation of the runoff volume, peak discharge, and hydrograph.

In this study, a novel process simulation model (PSM) was developed for anaerobic digestion using Aspen Plus ® (version 7.3.2). PSM has two parts, one for hydrolysis working based on extent of reaction and the other on kinetics of reactions. A total of 53 reactions were used in the model including inhibitions, rate kinetics, pH, ammonia, volume and HRT. Each reaction set in the kinetic reactor has a FORTRAN program to calculate the kinetics of biogas production. PSM was validated with earlier research studies and industrial experiments in Aspen Plus ® . The P-value after statistical analysis was found to be 0.324, which showed there was no significant difference between different validations, even after a change in process conditions, loading rate, HRT and substrate. The sensitivity analysis with a ±10% change in composition and extent of reaction would result in average 4.56% higher value than the experimental value.

The ''PTVAM'' tsunami vulnerability assessment model [Papathoma and Dominey-Howes: 2003, Nat. Hazards Earth Syst. Sci. 3, 733-744; Papathoma et al.: 2003, Nat. Hazards Earth Syst. Sci. 3, 377-389], like all models, requires validation. We use the results from posttsunami surveys in the Maldives following the December 26, 2004 Indian Ocean tsunami to 'evaluate' the appropriateness of the PTVAM attributes to understanding spatial and temporal vulnerability to tsunami damage and loss. We find that some of the PTVAM attributes are significantly important and others moderately important to understanding and assessing vulnerability. Some attributes require further investigation. Based upon the ground-truth data, we make several modifications to the model framework and propose a revised version of the PTVAM (PTVAM 2).

Extensive optimisation of a mathematical model's fit to a relatively small set of empirical data, may lead to over-optimistic validation results. If the assessment of the final, optimised model is based on the same validation method and the same input data that were used as basis for the extensive model optimisation, accumulated spurious correlations may appear as real predictive ability in the final model validation. An example of this is the use of extensive variable selection in multiple regression, based on a cross-model validation scheme.

This paper presents MATERA, a framework that integrates modeling in the Unified Modeling Language (UML), with requirement traceability across a model-based testing (MBT) process. The Graphical User Interface (GUI) of MAT-ERA is implemented as a plug-in in the NoMagic's MagicDraw modeling tool, combining existing capabilities of MagicDraw with custom ones. MATERA supports graphical specification of the requirements using SysML and tracing of them to the UML models specifying the SUT. Model validation is performed in MagicDraw using both predefined and custom validation rules. The resulting models are automatically transformed into input for the Conformiq Qtronic tool, used for automated test generation. Upon executing the test scripts generated by Qtronic in the NetHawk's East execution environment, the results of statistic analysis of the test run are presented in the GUI. The back-traceability of the covered requirements from test to models is also provided in the GUI to facilitate the identification of the source of possible errors in the models. The approach we present shows that existing model-based languages and tools are an enabler for model-based testing and for providing integrated tool support across the MBT process.

We report on the absolute calibration of a micro channel plate (MCP) detector, installed as detector in a Thomson parabola spectrometer. The calibration delivers the relation between a registered count numbers in the CCD camera (on which the MCP phosphor screen is imaged) as a result of the impact of an ion beam onto the MCP. The particle response of the whole detection system was evaluated by using laser accelerated ions with proton energies up to 3 MeV and carbon ion energies up to 16 MeV. In order to obtain an absolute measurement of the number of ions incident on the MCP detector, slotted CR-39 track detector was installed in front of the MCP. The signal registered on the MCP due to ions propagating through the CR-39 slots is compared to the number of particles counted on the adjacent CR-39 stripes after the etching. The calibration of the response of MCP has been extended to higher energy ions and protons on the basis of a simple model validated by comparison with the calibration data. This sensitive detection set-up makes it possible to measure in a single laser shot the ion spectrum in absolute terms.

Gray-box models of residential HVAC system are developed. Measurements were made on the inputs and outputs of each subsystem. The parameters of the models were found by nonlinear least squares optimization. Models were simulated in Matlab Simulink Ò and compared with the measurements. Integrated HVAC model was developed by cascading the individual subsystem models.

We propose a semiempirical graphene field effect transistor (G-FET) model for analysis and design of G-FET based circuits. The model describes the current-voltage characteristic for a G-FET over a wide range of operating conditions. The gate bias dependence of the output power spectrum is studied and compared with simulated values. A good agreement between the simulated and the experimental power spectrum up to the 3rd harmonic is demonstrated which confirms the model validity. Moreover, S-parameter measurements essentially coincide with the results obtained from the simulation. The model contains a small set of fitting parameters which can straightforwardly be extracted from S-parameters and DC measurements. The developed extraction method gives a more accurate estimation of the drain and source contact resistances compared to other approaches. As a design example, we use a harmonic-balance load-pull approach to extract optimum embedding impedances for a subharmonic G-FET mixer.

The montado/dehesa landscapes of the Iberian Peninsula are savannah-type open woodlands dominated by evergreen oak species (Quercus suber L. and Q. ilex ssp. rotundifolia). Scattered trees stand over an undergrowth of shrubs or herbaceous plants. To partition leaf area index between trees and the herbaceous/shrubby understorey requires good estimates of tree canopy cover and is of key importance to understand the ecology and the changes in land cover. The two vegetation components differ in phenology as well as in radiation and rainfall interception, water and CO 2 fluxes. The main goal of this study was to estimate tree canopy cover in a montado/dehesa region of southern Portugal (Alentejo) using remote sensed data. For this purpose we developed empirical models combining measurements obtained through the analysis of aerial photos and reflectance from Landsat Thematic Mapper (TM) individual channels, vegetation indices, and the components of the Kauth-Thomas (K-T) transformation. A set of 142 plots was designed, both in the aerial photos and in the satellite data. Several simple and multiple linear regression models were adjusted and validated. A subset of 75% of the data (n = 106) was used for model fitting, and the remainder (n = 36) was used for model assessment. The best linear equation includes Landsat TM channels 3, 4, 5 and 7 (r 2 = 0.74), but the Normalised Difference Vegetation Index (NDVI), the components of the K-T transformation, and the Atmospherically Resistant Vegetation Index (ARVI) also performed well (r 2 = 0.72, 0.70, and 0.69, respectively). The statistics of prediction residuals and tests of model validation indicates that these were also the models with better predictive capability. These results show that detection of low/medium tree canopy cover in this type of land cover (i.e. evergreen oak woodlands) can be accomplished with the help of high and medium spatial resolution satellite imagery. #

We present an application of the Java™ programming language to specify and implement reactive real-time systems. We have developed and tested a collection of classes and methods to describe concurrent modules and their asynchronous communication by means of signals. The control structures are closely patterned after those of the synchronous language Esterel, succinctly describing concurrency, sequencing and preemption. We show the user-friendliness and efficiency of the proposed technique by using an example from the automotive domain.

Many sites of groundwater contamination rely heavily on complex numerical models of flow and transport to develop closure plans. This has created a need for tools and approaches that can be used to build confidence in model predictions and make it apparent to regulators, policy makers, and the public that these models are sufficient for decision making. This confidence building is a long-term iterative process and it is this process that should be termed "model validation." Model validation is a process not an end result. That is, the process of model validation cannot always assure acceptable prediction or quality of the model. Rather, it provides safeguard against faulty models or inadequately developed and tested models. Therefore, development of a systematic approach for evaluating and validating subsurface predictive models and guiding field activities for data collection and long-term monitoring is strongly needed. This report presents a review of model validation studies that pertain to groundwater flow and transport modeling. Definitions, literature debates, previously proposed validation strategies, and conferences and symposia that focused on subsurface model validation are reviewed and discussed. The review is general in nature, but the focus of the discussion is on site-specific, predictive groundwater models that are used for making decisions regarding remediation activities and site closure. An attempt is made to compile most of the published studies on groundwater model validation and assemble what has been proposed or used for validating subsurface models. The aim is to provide a reasonable starting point to aid the development of the validation plan for the groundwater flow and transport model of the Faultless nuclear test conducted at the Central Nevada Test Area (CNTA).

Advances in dose-volume/outcome (or normal tissue complication probability, NTCP) modeling since the seminal Emami paper from 1991 are reviewed. There has been some progress with an increasing number of studies on large patient samples with three-dimensional dosimetry. Nevertheless, NTCP models are not ideal. Issues related to the grading of side effects, selection of appropriate statistical methods, testing of internal and external model validity, and quantification of predictive power and statistical uncertainty, all limit the usefulness of much of the published literature. Synthesis (meta-analysis) of data from multiple studies is often impossible because of suboptimal primary analysis, insufficient reporting and variations in the models and predictors analyzed. Clinical limitations to the current knowledge base include the need for more data on the effect of patient-related cofactors, interactions between dose distribution and cytotoxic or molecular targeted agents, and the effe...

A meso-scale front-tracking model (FTM) of nonequilibrium binary alloy dendritic solidification has been extended to incorporate Kurz, Giovanola, and Trivedi (KGT) dendrite kinetics and a Scheil solidification path. Model validation via comparison with thermocouple measurements from a solidification experiment, in which natural convection is limited by design, is presented. Via solution of the flow field due to natural thermal buoyancy, it is shown that resultant liquid-phase convection creates conditions in which equiaxed solidification is favored. Comparison with simulations in which casting solidification is diffusion controlled show that natural convection has greatest effect at intermediate times, but that at early and late stages of columnar solidification, the differences are relatively small. It is, however, during the time of greatest divergence between the simulations that the authors' predictive index for equiaxed zone formation is enhanced most by convection. Finally, the columnar-to-equiaxed transition is directly simulated, in directional solidification controlled by diffusion.

Accurate duct acoustic propagation models are required to characterize and subsequently reduce aircraft engine noise. The boundary conditions for these models ultimately rely on accurate measurements of the acoustic impedance for candidate nacelle liners. The standard two-microphone method is widely used to estimate acoustic impedance but does not provide uncertainty estimates that are essential for data quality assessment and model validation. A systematic framework is presented in this paper to propagate the experimental 95% confidence interval uncertainty estimates in the measured quantities to the calculated acoustic impedance data using the two-microphone method for small and large input uncertainties. One method is an analytical, small-perturbation technique using multivariate statistics. This method provides useful analytical scaling information. A second Monte Carlo method is utilized to validate the analytical multivariate method. Both methods are applied to the two-microphone method for simulated data representative of soundhard and sound-soft acoustic materials. The results indicate that for realistic experimental parameters, the uncertainty in the input measurements results in nonlinear perturbations. Therefore, the small-perturbation technique fails and the Monte Carlo method should be used to obtain uncertainty estimates. Furthermore, the nonlinear perturbations also distort the output statistical distributions of the calculated acoustic impedance and reflection coefficient, which results in significant deviation from Gaussian behavior. The distortion is a function of the acoustic impedance of the specimen itself. Finally, the Monte Carlo method is applied to experimental data for a ceramic tubular specimen and compared to the multivariate results to demonstrate the implementation and usefulness of the technique. r

Steam condensation plays a key role in removing heat from the atmosphere of the Westinghouse AP600 containment in case of a postulated accident. A model of steam condensation on containment surfaces under anticipated accident conditions is presented and validated against an extensive and sound database. Based on the diffusion layer theory and on the use of the heat/mass transfer analogy, one can deal with large temperature gradients across the gaseous boundary layer under high mass flux circumstances. The thermal resistance of the condensate film, as well as its wavy structure, have also been considered in this model. As compared to Anderson et al. (1998) (Experimental analysis of heat transfer within the AP600 containment under postulated accident conditions. Nucl. Eng. Des. (submitted)) experimental database, an average error lower than 15%, within the experimental confidence range, has demonstrated its remarkable accuracy. In particular, the model has shown a good response to the influence of primary variables in steam condensation (i.e. subcooling, noncondensable concentration and pressure), providing a mechanistic explanation for effects such as the presence of light noncondensable gas (i.e. helium as a simulant for hydrogen) in the gaseous mixture. In addition, the model has been contrasted against correlations used in safety analysis (i.e. Uchida, Tagami, Kataoka, etc.) and occasionally to Dehbi's database. This cross-comparison has pointed out several shortcomings in the use of these correlations and has extended the model validation to other databases.

This is a submission to the TODAES Special Issue on HLDVT 97. We present an application of the Java TM programming language to specify and implement reactive real-time systems. We have developed and tested a collection of classes and methods to describe concurrent modules and their asynchronous communication by means of signals. The control structures are closely patterned after those of the synchronous language Esterel, succinctly describing concurrency, sequencing and preemption. We show the user-friendliness and e ciency of the proposed technique by using an example from the automotive domain.

While planning target parameter retrieval experiment in farmers' fields using Synthetic Aperture Radar (SAR) remote sensing, it is very important to answer three questions. The first question is, "How large should a farmer's field be from where the target parameter sample should be collected ?‟. The answer to this question is very critical particularly when the experiment is to be carried out in South Asian countries where
in general, agricultural land holding by an individual farmer is small. The second question of importance is that “what should be the sample size for model development?” or in other words
“how many such large enough farmers‟ fields needs to be taken
so that enough target parameter samples will be available to be able to develop a meaningful relationship between remotely sensed parameter and the observed target parameter ? ”. The third important question is what should be the minimum sample size for meaningful model validation? In this paper answers to all these questions are obtained by adopting statistical approach when the experiment is planned for target parameter retrieval using synthetic Aperture radar (SAR). The required size of the sampling unit is determined by taking into account the characteristic-fading phenomenon of SAR signal and probabilistic statistical approach based upon the margin of error permissible by the experimenter in estimating average. The answer to the second question about how many farmers fields or in other words, sampling units be chosen during ground truth data collection such that a nearly true relationship can be developed between observed target parameter on ground and SAR backscatter, is obtained based upon the margin of error permissible by the experimenter in a regression estimate. Finally answer to third question has been reached by developing a procedure using "precision power approach‟ to arrive at the minimum size of validation sample required by the experimenter for a meaningful validation exercise. It should be noted that the approach presented in this paper to determine sample size for model development and model validation are general in nature and are equally applicable to other remote sensing data sets as well.