Studies on the propagation of errors in physical oceanographic computations

The results of an investigation on the limits of the random errors contained in the basic data of Physical Oceanography and their propagation through the computational procedures are presented in this thesis. It also suggest a method which increases the reliability of the derived results. The thesis is presented in eight chapters including the introductory chapter. Chapter 2 discusses the general theory of errors that are relevant in the context of the propagation of errors in Physical Oceanographic computations. The error components contained in the independent oceanographic variables namely, temperature, salinity and depth are deliniated and quantified in chapter 3. Chapter 4 discusses and derives the magnitude of errors in the computation of the dependent oceanographic variables, density in situ, gt, specific volume and specific volume anomaly, due to the propagation of errors contained in the independent oceanographic variables. The errors propagated into the computed values of the derived quantities namely, dynamic depth and relative currents, have been estimated and presented chapter 5. Chapter 6 reviews the existing methods for the identification of level of no motion and suggests a method for the identification of a reliable zero reference level. Chapter 7 discusses the available methods for the extension of the zero reference level into shallow regions of the oceans and suggests a new method which is more reliable. A procedure of graphical smoothening of dynamic topographies between the error limits to provide more reliable results is also suggested in this chapter. Chapter 8 deals with the computation of the geostrophic current from these smoothened values of dynamic heights, with reference to the selected zero reference level. The summary and conclusion are also presented in this chapter.

Development of optical fiber sensors for selected chemical and physical sensing applications

The objective of the preset work is to develop optical fiber sensors for various physical and chemical parameters. As a part of this we initially investigated trace analysis of silica, ammonia, iron and phosphate in water. For this purpose the author has implemented a dual wavelength probing scheme which has many advantages over conventional evanescent wave sensors. Dual wavelength probing makes the design more reliable and repeatable and this design makes the sensor employable for concentration, chemical content, adulteration level, monitoring and control in industries or any such needy environments. Use of low cost components makes the system cost effective and simple. The Dual wavelength probing scheme is employed for the trace analysis of silica, iron, phosphate, and ammonia in water. Such sensors can be employed for the steam and water quality analysers in power plants. Few samples from a power plant are collected and checked the performance of developed system for practical applications.

Physical characteristics of the coastal waters off the south-west coast of india with an attempt to study the possible relationship with sardine mackerel and anchovy fisheries

The present study is aimed at observing the variations, in space and time, of see of the important hydrographic parameters such as sea water temperature, salinity and Resolved oxygen within the coastal waters along the south-west coast of Indiametween Ratnagiri (17°OO*N,73°20'E) and cape comorin ( 8°10'N,77°30*E). Specific data relating to the process of upwelling and sinking was collected mainly to evaluate the extent and intensity of the vertical mixing processes active in the area under study. The study also attempted possible correlations between the observed parameters and the occurrence and migrations of some of the major pelagic fishery resources such as sardine,mackerel and anchovy in the area under study

Effective t-J model Hamiltonian parameters of monolayered cuprate superconductors from ab initio electronic structure calculations

The magnetic coupling constant of selected cuprate superconductor parent compounds has been determined by means of embedded cluster model and periodic calculations carried out at the same level of theory. The agreement between both approaches validates the cluster model. This model is subsequently employed in state-of-the-art configuration interaction calculations aimed to obtain accurate values of the magnetic coupling constant and hopping integral for a series of superconducting cuprates. Likewise, a systematic study of the performance of different ab initio explicitly correlated wave function methods and of several density functional approaches is presented. The accurate determination of the parameters of the t-J Hamiltonian has several consequences. First, it suggests that the appearance of high-Tc superconductivity in existing monolayered cuprates occurs with J/t in the 0.20¿0.35 regime. Second, J/t=0.20 is predicted to be the threshold for the existence of superconductivity and, third, a simple and accurate relationship between the critical temperatures at optimum doping and these parameters is found. However, this quantitative electronic structure versus Tc relationship is only found when both J and t are obtained at the most accurate level of theory.

The role of dynamical polarization of the ligand-to-metal charge transfer excitations in the ab initio determination of effective exchange parameters

The role of the bridging ligand on the effective Heisenberg coupling parameters is analyzed in detail. This analysis strongly suggests that the ligand-to-metal charge transfer excitations are responsible for a large part of the final value of the magnetic coupling constant. This permits us to suggest a variant of the difference dedicated configuration interaction (DDCI) method, presently one of the most accurate and reliable for the evaluation of magnetic effective interactions. This method treats the bridging ligand orbitals mediating the interaction at the same level than the magnetic orbitals and preserves the high quality of the DDCI results while being much less computationally demanding. The numerical accuracy of the new approach is illustrated on various systems with one or two magnetic electrons per magnetic center. The fact that accurate results can be obtained using a rather reduced configuration interaction space opens the possibility to study more complex systems with many magnetic centers and/or many electrons per center.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Predicting the thermal inactivation of bacteria in a solid matrix: simulation studies on the relative effects of microbial thermal resistance parameters and process conditions

A combined mathematical model for predicting heat penetration and microbial inactivation in a solid body heated by conduction was tested experimentally by inoculating agar cylinders with Salmonella typhimurium or Enterococcus faecium and heating in a water bath. Regions of growth where bacteria had survived after heating were measured by image analysis and compared with model predictions. Visualisation of the regions of growth was improved by incorporating chromogenic metabolic indicators into the agar. Preliminary tests established that the model performed satisfactorily with both test organisms and with cylinders of different diameter. The model was then used in simulation studies in which the parameters D, z, inoculum size, cylinder diameter and heating temperature were systematically varied. These simulations showed that the biological variables D, z and inoculum size had a relatively small effect on the time needed to eliminate bacteria at the cylinder axis in comparison with the physical variables heating temperature and cylinder diameter, which had a much greater relative effect. (c) 2005 Elsevier B.V All rights reserved.

Direct Computation of Stochastic Flow in Reservoirs with Uncertain Parameters

A direct method is presented for determining the uncertainty in reservoir pressure, flow, and net present value (NPV) using the time-dependent, one phase, two- or three-dimensional equations of flow through a porous medium. The uncertainty in the solution is modelled as a probability distribution function and is computed from given statistical data for input parameters such as permeability. The method generates an expansion for the mean of the pressure about a deterministic solution to the system equations using a perturbation to the mean of the input parameters. Hierarchical equations that define approximations to the mean solution at each point and to the field covariance of the pressure are developed and solved numerically. The procedure is then used to find the statistics of the flow and the risked value of the field, defined by the NPV, for a given development scenario. This method involves only one (albeit complicated) solution of the equations and contrasts with the more usual Monte-Carlo approach where many such solutions are required. The procedure is applied easily to other physical systems modelled by linear or nonlinear partial differential equations with uncertain data.

Estimation of optimal gravity wave parameters for climate models using data assimilation

There is a current need to constrain the parameters of gravity wave drag (GWD) schemes in climate models using observational information instead of tuning them subjectively. In this work, an inverse technique is developed using data assimilation principles to estimate gravity wave parameters. Because mostGWDschemes assume instantaneous vertical propagation of gravity waves within a column, observations in a single column can be used to formulate a one-dimensional assimilation problem to estimate the unknown parameters. We define a cost function that measures the differences between the unresolved drag inferred from observations (referred to here as the ‘observed’ GWD) and the GWD calculated with a parametrisation scheme. The geometry of the cost function presents some difficulties, including multiple minima and ill-conditioning because of the non-independence of the gravity wave parameters. To overcome these difficulties we propose a genetic algorithm to minimize the cost function, which provides a robust parameter estimation over a broad range of prescribed ‘true’ parameters. When real experiments using an independent estimate of the ‘observed’ GWD are performed, physically unrealistic values of the parameters can result due to the non-independence of the parameters. However, by constraining one of the parameters to lie within a physically realistic range, this degeneracy is broken and the other parameters are also found to lie within physically realistic ranges. This argues for the essential physical self-consistency of the gravity wave scheme. A much better fit to the observed GWD at high latitudes is obtained when the parameters are allowed to vary with latitude. However, a close fit can be obtained either in the upper or the lower part of the profiles, but not in both at the same time. This result is a consequence of assuming an isotropic launch spectrum. The changes of sign in theGWDfound in the tropical lower stratosphere, which are associated with part of the quasi-biennial oscillation forcing, cannot be captured by the parametrisation with optimal parameters.

A traceable physical calibration of the vertical advection-diffusion equation for modelling ocean heat uptake

The classic vertical advection-diffusion (VAD) balance is a central concept in studying the ocean heat budget, in particular in simple climate models (SCMs). Here we present a new framework to calibrate the parameters of the VAD equation to the vertical ocean heat balance of two fully-coupled climate models that is traceable to the models’ circulation as well as to vertical mixing and diffusion processes. Based on temperature diagnostics, we derive an effective vertical velocity w∗ and turbulent diffusivity k∗ for each individual physical process. In steady-state, we find that the residual vertical velocity and diffusivity change sign in mid-depth, highlighting the different regional contributions of isopycnal and diapycnal diffusion in balancing the models’ residual advection and vertical mixing. We quantify the impacts of the time-evolution of the effective quantities under a transient 1%CO2 simulation and make the link to the parameters of currently employed SCMs.

Vertical structure and physical processes of the Madden-Julian oscillation: Biases and uncertainties at short range

An analysis of diabatic heating and moistening processes from 12-36 hour lead time forecasts from 12 Global Circulation Models are presented as part of the "Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)" project. A lead time of 12-36 hours is chosen to constrain the large scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up for the models as they adjust to being driven from the YOTC analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large scale dynamics is reasonably constrained, moistening and heating profiles have large inter-model spread. In particular, there are large spreads in convective heating and moistening at mid-levels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behaviour shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems.

Optimization of the physical refining of sunflower oil concerning the final contents of trans-fatty acids

The final contents of total and individual trans-fatty acids of sunflower oil, produced during the deacidification step of physical refining were obtained using a computational simulation program that considered cis-trans isomerization reaction features for oleic, linoleic, and linolenic acids attached to the glycerol part of triacylglycerols. The impact of process variables, such as temperature and liquid flow rate, and of equipment configuration parameters, such as liquid height, diameter, and number of stages, that influence the retention time of the oil in the equipment was analyzed using the response-surface methodology (RSM). The computational simulation and the RSM results were used in two different optimization methods, aiming to minimize final levels of total and individual trans-fatty acids (trans-FA), while keeping neutral oil loss and final oil acidity at low values. The main goal of this work was to indicate that computational simulation, based on a careful modeling of the reaction system, combined with optimization could be an important tool for indicating better processing conditions in industrial physical refining plants of vegetable oils, concerning trans-FA formation.

A physical organic chemistry approach to dissolution of cellulose: effects of cellulose mercerization on its properties and on the kinetics of its decrystallization

The effects of alkali treatment on the structural characteristics of cotton linters and sisal cellulose samples have been studied. Mercerization results in a decrease in the indices of crystallinity and the degrees of polymerization, and an increase in the alpha-cellulose contents of the samples. The relevance of the structural properties of cellulose to its dissolution is probed by studying the kinetics of cellulose decrystallization, prior to its solubilization in LiCl/N,N-dimethylacetamide (DMAc). Our data show that the decrystallization rate constants and activation parameters are only slightly dependent on the physico-chemical properties of the starting celluloses. This multi-step reaction is accompanied by a small enthalpy and large, negative, entropy of activation. These results are analyzed in terms of the interactions within the biopolymer chains during decrystallization, as well as those between the two ions of the electrolyte and both DMAc and cellulose.

Thermal stability of extracellular hemoglobin of Glossoscolex paulistus: Determination of activation parameters by optical spectroscopic and differential scanning calorimetric studies

Glossoscolex paulistus hemoglobin (HbGp) was studied by dynamic light scattering (DLS), optical absorption spectroscopy (UV-VIS) and differential scanning calorimetry (DSC). At pH 7.0, cyanomet-HbGp is very stable, no oligomeric dissociation is observed, while denaturation occurs at 56 degrees C, 4 degrees C higher as compared to oxy-HbGp. The oligomeric dissociation of HbGp occurs simultaneously with some protein aggregation. Kinetic studies for oxy-HbGp using UV-VIS and DES allowed to obtain activation energy (E(a)) values of 278-262 kJ/mol (DES) and 333 kJ/mol (UV-VIS). Complimentary DSC studies indicate that the denaturation is irreversible, giving endotherms strongly dependent upon the heating scan rates, suggesting a kinetically controlled process. Dependence on protein concentration suggests that the two components in the endotherms are due to oligomeric dissociation effect upon denaturation. Activation energies are in the range 200-560 kJ/mol. The mid-point transition temperatures were in the range 50-65 degrees C. Cyanomet-HbGp shows higher mid-point temperatures as well as activation energies, consistent with its higher stability. DSC data are reported for the first time for an extracellular hemoglobin. (C) 2010 Elsevier B.V. All rights reserved.