Final Set Of Parameters Research Articles

Modeling water resources of a highly irrigated alluvial plain (Italy): calibrating soil and groundwater models

Modern and effective water management in large alluvial plains that have intensive agricultural activity requires the integrated modeling of soil and groundwater. The models should be complex enough to properly simulate several, often non-linear, processes, but simple enough to be effectively calibrated with the available data. An operative, practical approach to calibration is proposed, based on three main aspects. First, the coupling of two models built on well-validated algorithms, to simulate (1) the irrigation system and the soil water balance in the unsaturated zone and (2) the groundwater flow. Second, the solution of the inverse problem of groundwater hydrology with the comparison model method to calibrate the model. Third, the use of appropriate criteria and cross-checks (comparison of the calibration results and of the model outputs with hydraulic and hydrogeological data) to choose the final parameter sets that warrant the physical coherence of the model. The approach has been tested by application to a large and intensively irrigated alluvial basin in northern Italy.

Propulsive Velocity Optimization of 3-Joint Fish Robot Using Genetic-Hill Climbing Algorithm

Underwater robot is a new research field which is emerging quickly in recent years. Previous researches in this field focus on Remotely Operated Vehicles (ROVs), Autonomous Underwater Vehicles (AUVs), underwater manipulators, etc. Fish robot, which is a new type of underwater biomimetic robot, has attracted great attention because of its silence in moving and energy efficiency compared to conventional propeller-oriented propulsive mechanism. However, most of researches on fish robots have been carried out via empirical or experimental approaches, not based on dynamic optimality. In this paper, we proposed an analytical optimization approach which can guarantee the maximum propulsive velocity of fish robot in the given parametric conditions. First, a dynamic model of 3-joint (4 links) carangiform fish robot is derived, using which the influences of parameters of input torque functions, such as amplitude, frequency and phase difference, on its velocity are investigated by simulation. Second, the maximum velocity of the fish robot is optimized by combining Genetic Algorithm (GA) and Hill Climbing Algorithm (HCA). GA is used to generate the initial optimal parameters of the input functions of the system. Then, the parameters are optimized again by HCA to ensure that the final set of parameters is the “near” global optimization. Finally, both simulations and primitive experiments are carried out to prove the feasibility of the proposed method.

A multistart weight‐adaptive recursive parameter estimation method

The determination of the parameters for hydrologic models has been the subject of a large number of studies during the last 3 decades. A multitude of methods have been developed for this purpose. Generally, the mismatch between the model simulations and the observations is lumped into an objective function, which is then is optimized by these methods. This can lead to parameter values that result in a good model performance under certain (e.g., low flow) conditions but not under other (e.g., high flow) conditions. The objective of this paper is to demonstrate a calibration algorithm which leads to a good model performance under all boundary conditions. This algorithm is referred to as Multistart Weight‐Adaptive Recursive Parameter Estimation (MWARPE). For this purpose the equations of the Extended Kalman Filter (EKF) have been used recursively in a Monte‐Carlo approach, strongly increasing the chance that a globally optimal parameter set is obtained instead of a local optimum. The method has been applied to a rainfall‐runoff model for the Zwalm catchment in Belgium, using a 1‐year, a 2‐year, and a 3‐year calibration period. The results have been compared to the Shuffled Complex Evolution (SCE)‐UA method. A synthetic study revealed that for narrow parameter limits the SCE‐UA algorithm outperformed MWARPE, while for broad parameter limits the opposite occurred. For the test case using in situ observed data, the SCE‐UA method resulted in slightly lower RMSE values than MWARPE, but MWARPE performed better outside the calibration period. It has been found that MWARPE can bypass local optima in the determination of the final parameter set. Also, the best initial parameter sets (with the lowest RMSE) do not lead to the best final parameter values. To apply the method only four parameters need to be specified, more specifically the number of starting points, the number of iterations per starting point, one parameter used to initialize the model error covariance matrix, and the observation error. For this reason, the method could be a simple alternative to more complex methods if model parameters have to be determined when time and/or computational power are limited.

Genetic background differences and nonassociative effects in mouse trace fear conditioning

Fear conditioning, including variants such as delay and trace conditioning that depend on different neural systems, is widely used to behaviorally characterize genetically altered mice. We present data from three strains of mice, C57/BL6 (C57), 129/SvlmJ (129), and a hybrid strain of the two (F(1) hybrids), trained on various versions of a trace fear-conditioning protocol. The initial version was taken from the literature but included unpaired control groups to assess nonassociative effects on test performance. We observed high levels of nonassociative freezing in both contextual and cued test conditions. In particular, nonassociative freezing in unpaired control groups was equivalent to freezing shown by paired groups in the tests for trace conditioning. A number of pilot studies resulted in a new protocol that yielded strong context conditioning and low levels of nonassociative freezing in all mouse strains. During the trace-CS test in this protocol, freezing in unpaired controls remained low in all strains, and both the C57s and F(1) hybrids showed reliable associative trace fear conditioning. Trace conditioning, however, was not obtained in the 129 mice. Our findings indicate that caution is warranted in interpreting mouse fear-conditioning studies that lack control conditions to address nonassociative effects. They also reveal a final set of parameters that are important for minimizing such nonassociative effects and demonstrate strain differences across performance in mouse contextual and trace fear conditioning.

New Born Radii Deriving Method for Generalized Born Model.

Here we report a method to calculate Born radii, an important parameter used in a Generalized Born model. Traditional methods to derive Born radii are mostly based on a complicated formula, while our method is easier and more direct. Atoms are classified according to their atom type, and the Born radii of each type are obtained by fitting to experimental solvation free energy. The SMARTS language is used for the exact definition of atoms types, and Ullmann's subgraph isomorphism algorithm is used to deduce the environment. A generic algorithm is used for the parameter fitting because of its efficiency in searching a huge phase space, and its results are then optimized by using the conjugate gradient method. The final parameter set is fitting from a training set containing 357 molecules and is tested using a test set of 44 small organic molecules, and the average error is 0.58 kcal/mol for 36 neutral molecules and is 1.67 kcal/mol for 8 ions. The model is further tested under organic molecules, biopolymers...

New Born Radii Deriving Method for Generalized Born Model

Here we report a method to calculate Born radii, an important parameter used in a Generalized Born model. Traditional methods to derive Born radii are mostly based on a complicated formula, while our method is easier and more direct. Atoms are classified according to their atom type, and the Born radii of each type are obtained by fitting to experimental solvation free energy. The SMARTS language is used for the exact definition of atoms types, and Ullmann's subgraph isomorphism algorithm is used to deduce the environment. A generic algorithm is used for the parameter fitting because of its efficiency in searching a huge phase space, and its results are then optimized by using the conjugate gradient method. The final parameter set is fitting from a training set containing 357 molecules and is tested using a test set of 44 small organic molecules, and the average error is 0.58 kcal/mol for 36 neutral molecules and is 1.67 kcal/mol for 8 ions. The model is further tested under organic molecules, biopolymers, and a protein-inhibitor complex and yields reliable results in all these cases. This method can be used to accelerate molecular docking calculations.

Calibration of a semi-distributed model for conjunctive simulation of surface and groundwater flows / Calage d’un modèle semi-distribué pour la simulation conjointe d’écoulements superficiels et souterrains

A hydrological simulation model was developed for conjunctive representation of surface and groundwater processes. It comprises a conceptual soil moisture accounting module, based on an enhanced version of the Thornthwaite model for the soil moisture reservoir, a Darcian multi-cell groundwater flow module and a module for partitioning water abstractions among water resources. The resulting integrated scheme is highly flexible in the choice of time (i.e. monthly to daily) and space scales (catchment scale, aquifer scale). Model calibration involved successive phases of manual and automatic sessions. For the latter, an innovative optimization method called evolutionary annealing-simplex algorithm is devised. The objective function involves weighted goodness-of-fit criteria for multiple variables with different observation periods, as well as penalty terms for restricting unrealistic water storage trends and deviations from observed intermittency of spring flows. Checks of the unmeasured catchment responses through manually changing parameter bounds guided choosing final parameter sets. The model is applied to the particularly complex Boeoticos Kephisos basin, Greece, where it accurately reproduced the main basin response, i.e. the runoff at its outlet, and also other important components. Emphasis is put on the principle of parsimony which resulted in a computationally effective modelling. This is crucial since the model is to be integrated within a stochastic simulation framework.

CMS silicon tracker developments

The CMS Silicon tracker consists of 70 m 2 of microstrip sensors which design will be finalized at the end of 1999 on the basis of systematic studies of device characteristics as function of the most important parameters. A fundamental constraint comes from the fact that the detector has to be operated in a very hostile radiation environment with full efficiency. We present an overview of the current results and prospects for converging on a final set of parameters for the silicon tracker sensors.

Nonisotropic Excitation Energy Transport in Organized Molecular Systems: Monte Carlo Simulation-Based Analysis of Fluorescence and Fluorescence Anisotropy Decay

An improved application is presented of the Monte Carlo method including simultaneous parameter fitting to analyze the experimental time-resolved fluorescence and fluorescence anisotropy decay of two organized molecular systems exhibiting a number of different, nonisotropic energy transfer processes. Using physical models and parameter fitting for these systems, the Monte Carlo simulations yield a final set of parameters, which characterize the energy transfer processes in the investigated systems. The advantages of such a simulation-based analysis for global parametric fitting are discussed. Using this approach energy transfer processes have been analyzed for two porphyrin model systems, i.e., spin-coated films of zinc tetra(octylphenyl)-porphyrins (ZnTOPP) and the tetramer of zinc mono(4-pyridyl)triphenylporphyrin (ZnM(4Py)TrPP). For the ZnTOPP film energy transfer rate constants of 1 10 12 s -1 and 80 10 9 s -1 have been found, and are assigned to intra- and interstack transfer, respectively. For the tetramers, the transfer rate constants of 38 10 9 and 5 10 9 s -1 correspond to energy transfer to nearest and next nearest neighbor

Shape optimization of a vehicle hat-shelf: Improving acoustic properties for different load cases by maximizing first eigenfrequency

This paper presents design optimization of the geometry of a vehicle hat-shelf. At first two existing finite element discretizations are investigated for two different element types. The structural model is then parameterized. Only four design variables have been chosen to control the shape modification of the hat-shelf. The aim of this paper is to decrease the vehicle interior noise due to three different excitations for two cases of fluid damping. With respect to the support conditions of the hat-shelf these three load cases and the two cases of different damping are considered simultaneously by maximizing the lowest eigenfrequency of the structural model. Although remarkable differences in the natural frequencies are discovered for the four discretizations, a similar dependence of the objective function in terms of the design variables is observed. Thus, a multigrid strategy can be applied. The coarsest mesh is used to obtain suitable initial sets of optimization variables, one of the finer meshes serves for a pre-optimization and the finest mesh is optimized to find the final set of parameters. While the lowest eigenfrequency of the original model is found at about 31 Hz, the corresponding value in the optimized variant exceeds 100 Hz being the upper bound of the frequency range under consideration. Evaluation of the noise transfer function proves that this strategy decreases its average between 4.4 and 13.9 dB.

Spectra and energy levels ofCo2+in zinc oxide metaborate

¯ 3m) with Zn 21 ions occupying sites of T3d symmetry. It is presumed that Co 21 substitutes for Zn 21 during the crystal-growth process. The observed spectra of Co 21 are analyzed, and the identified energy levels are compared to calculated levels derived from lattice-sum models and the crystal-field, three-parameter theory. Twenty-six experimental Stark ~electronic! energy levels of Co 21 (3d 7 ) are compared to calculated levels with a final rms deviation of 26 cm 21 . The atomic parameters for Co 21 (3d 7 ), including the Slater, spin-orbit, and interconfigurational parameters, are in general agreement with the corresponding parameters obtained for divalent cobalt in other host crystals. The initial crystal-field parameters Bnm determined from the lattice-sum calculations represent an excellent starting set for the splitting analyses and undergo only modest changes to a final set of parameters. Comments are also made in relation to the use of the crystal as a saturable absorber for near-infrared Q-switched solid-state lasers.

Stochastic calibration of an orographic precipitation model

In this study a stochastic approach to calibration of an orographic precipitation model (Rhea, 1978) was applied in the Gunnison River Basin of south-western Colorado. The stochastic approach to model calibration was used to determine: (1) the model parameter uncertainty and sensitivity; (2) the grid-cell resolution to run the model (10 or 5 km grids); (3) the model grid rotation increment; and (4) the basin subdivision by elevation band for parameter definition. Results from the stochastic calibration are location and data dependent. Uncertainty, sensitivity and range in the final parameter sets were found to vary by grid-cell resolution and elevation. Ten km grids were found to be a more robust model configuration than 5 km grids. Grid rotation increment, tested using only 10 km grids, indicated increments of less than 10 degrees to be superior. Basin subdivision into two elevation bands was found to produce ‘optimal’ results for both 10 and 5 km grids. © 1998 John Wiley & Sons, Ltd.

Stochastic calibration of an orographic precipitation model

In this study a stochastic approach to calibration of an orographic precipitation model (Rhea, 1978) was applied in the Gunnison River Basin of south-western Colorado. The stochastic approach to model calibration was used to determine: (1) the model parameter uncertainty and sensitivity; (2) the grid-cell resolution to run the model (10 or 5 km grids); (3) the model grid rotation increment; and (4) the basin subdivision by elevation band for parameter definition. Results from the stochastic calibration are location and data dependent. Uncertainty, sensitivity and range in the final parameter sets were found to vary by grid-cell resolution and elevation. Ten km grids were found to be a more robust model configuration than 5 km grids. Grid rotation increment, tested using only 10 km grids, indicated increments of less than 10 degrees to be superior. Basin subdivision into two elevation bands was found to produce 'optimal' results for both 10 and 5 km grids.

Techniques and parameters to analyze seismicity patterns associated with large earthquakes

A pattern recognition algorithm is developed to provide potential improvements over existing earthquake prediction practices. The parameters employed in the analysis include degree of spatial nonrandomness in two distance ranges, spatial correlation dimension, spatial repetitiveness of earthquakes with a similar size, average depth of events, time interval for the occurrence of a constant number of events, and ratio of the numbers of events in two magnitude intervals. The parameter temporal variations are compared quantitatively with the time series of large events using a technique of association in time. The significance of the association frequencies is evaluated by comparison with chance associations estimated from corresponding simulated random time series. The developed techniques differ from existing approaches in the following aspects. The parameters here emphasize the spatial distribution of earthquakes. Possible correlations among the parameters are evaluated to determine the final set of parameters to be monitored. Threshold values for the assumed anomalies are chosen with consideration of properties of the available earthquake catalogs, such as the number of large events to be retrospectively predicted. Equal weight is given to both locally high and locally low parameter values. Care is taken to distinguish between anomalies preceding large events and those following previous events. It is shown that the relationship between precursory local extrema and precursory trends is nonunique, with precursory local extrema of the same type frequently associated with opposite observable precursory trends. The application of the seismicity parameters and pattern recognition techniques is demonstrated using synthetic earthquake catalogs generated by models of segmented fault systems in a three‐dimensional elastic solid [Ben‐Zion, 1996].

PRE-PRIM as a pre-processor to simulations: a cohesive unit

Large scale computer simula tions are in widespread and growing use in government, business and science. Large numbers of parameters may initially appear to be needed in simulations; the user needs the flexibility to evaluate as many parameters as possible. Mathe matical and statistical tools can reduce the final set of parame ters to an efficient minimum. This paper describes the con cepts underlying PRE-PRIM, a preprocessor to simulations integrated by the present author. PRE-PRIM assures that (a) a wide number of parameters can be analyzed with a minimum number of simulation runs, (b) efficiency and replicability in the coefficients of these parameters is established, and (c) a protocol for the sequence of simulation runs is determined.

Ionic transport in crystals of pure and doped sodium chloride

A recent analysis of the results of conductivity measurements on well-annealed single crystals of pure, Sr 2+-doped and S 2−-doped NaCl produced values of the thermodynamic parameters that control the defect concentrations and therefore the conductivity of the crystal. The parameters derived from fitting the data for each crystal were then averaged to yield a “final parameter set”; because the anion migration enthalpy in this set was in marked disagreement with a value that had been obtained previously from measurements on quenched crystals, it seemed important to assess the likely accuracy of our parameter set. This has now been done through calculations of transport numbers, degree of association, and particularly diffusion coefficients. The results of these calculations are reported in this paper.

A General Method for Error Description of CMMs Using Polynomial Fitting Procedures

Summary Until now the error description of CMMs has been carried out assuming rigid body kinematics. This paper resents a method for describing the error structure of the CMM including both the non rigid body effects and the thermal induced effects. Individual error parameters are described by special polynomial fitting procedures. A final set of parameters can he generated from the measured quantities of the CMM by a special computer program. Using these parameters, a small error correction program has been developed, which has been applied to a suitable 3CMM. Results of this work will be presented.

Automatic Water-Level Control in South Africa

The principle of proportional, integral, and derivative sensing constitutes the theme of this paper. A study was made of the different types of control elements involved. This resulted in the selection of a PID-controller as the most suitable. This controller was designed and installed and three different methods were employed for determining the optimum parameter settings. These comprise direct calculation, analog computer simulation, and actual practical tests on site. The final parameter settings resulted in efficient and effective automatic water-level control to within a spectrum of 1.18 in.-1.57 in. (3cm-4cm) at full supply level at incoming flows and floods ranging from 285 cfs-25,000 cfs (8m³/s-700m³/s). These results were due to the mechanism actually reacting to a water-level change of as small as 1 mm.

ESR of α-Copper Phthalocyanine. II. Powder Line Shape and MO Calculations

The ESR spectrum of polycrystalline α-Cu phthalocyanine, reported by us previously, has been analyzed in detail by powder line shape and MO calculations. The superhyperfine (shf) tensors are shown to be essentially isotropic and hence the system can be described by an axial spin Hamiltonian. The low-field spectrum consists of four well-defined peaks from which the spin-Hamiltonian parameters g‖ and A can be readily determined. The high-field spectrum is a superposition of four sets of nine-component lines over-lapping to result in 15 almost equally spaced peaks. This fact suggests that the hyperfine (hf) constant B is about twice the shf constant aN. This relation has been used to estimate the values of g⊥, B, and aN. Only a slight adjustment of parameters was needed to synthesize a derivative line shape which fitted well to the experimental spectra. For one of the hf components (M = 32), the resonance field is not a monotonic function of θ, the angle between molecular axis and the magnetic field. The effect of this anomaly on the spectrum, particularly the intensity ratio of the shf lines is discussed. The final set of parameters (g‖ = 2.158, g⊥ = 2.041, | A | = 0.0212 cm−1, | B | = 0.0029 cm−1, | aN | = 0.0017 cm−1) are in good agreement with those obtained by a semiempirical MO calculation which takes into account the out-of-plane π bonding with the 16-membered ring of the phthalocyanine molecule.