Neste trabalho aplica-se um método semi-empírico que utiliza uma técnica de otimização não linear para determinação das eficiências volumétrica e combinada do compressor hermético alternativo. Relações para estimar aproximadamente o fluxo de massa e a potência elétrica do compressor também são propostas. Todas estas características do compressor são calculadas através das relações físicas do modelo, empregadas nos cálculos de otimização. O método é implementado no software EES (Engineering Equation Solver) e baseia-se nos trabalhos de Jahing (1999) e Jahing et al. (2000). No presente método, cinco medições experimentais do fluxo de massa e potência elétrica são suficientes para determinar os parâmetros de ajuste do modelo. Este procedimento permite a geração de mapas de compressores satisfatórios sem a necessidade de um maior número de dados experimentais como no caso da norma ARI 540. Estes resultados obtidos com o modelo podem ser usados para o projeto de novos compressores. / In the present work is applied a semi-empirical method that uses a non-linear optimization technique for determination of the volumetric and combined efficiencies of hermetic reciprocating compressor. Relations to approximately estimate the mass flow and the electric power of the compressor are also proposed. All these compressor characteristics are calculated through physical model relations, used in the optimization calculations. The method is implemented in the EES (Engineering Equation Solver) software and is based on the works of Jahing (1999) and Jahing et al. (2000). In the method, four experimental measurements of the mass flow and electric power are enough to determine the fitting parameters of the model. This procedure allows the generation of satisfactory compressor maps without the necessity of a higher number of experimental data, as in the case of norm ARI 540 application. The results obtained with the model can be used for the design of new compressors.

none

In the past few decades, several researchers have studied the effects of ASR induced expansion in concrete. Several models have been proposed to model the effects of ASR in concrete. While most of these models focus on plain concrete, there is limited amount of research to model the influence of ASR expansion in reinforced concrete. Additionally, the existing models are complex and difficult to implement for practicing engineers. In this study the shortcomings with the existing models are addressed. A minimalist semi-empirical model is developed to represent the degradation of reinforced concrete due to ASR expansion. The model is validated using historical experimental data. Only two key parameters are needed to represent the expansive behavior, specifically, the maximum unreinforced concrete strain due to ASR expansion and the rise time. Mechanical properties of the reinforced concrete are also needed. From the predicted expansions, it is then shown that it is possible to model the number and spacing of cracks of a partly restrained reinforced concrete beam affected by ASR gels. The model is validated with recent experimental results on large scale reinforced concrete specimens. Predictions agree well with the observed number of cracks.

Neste trabalho aplica-se um método semi-empírico que utiliza uma técnica de otimização não linear para determinação das eficiências volumétrica e combinada do compressor hermético alternativo. Relações para estimar aproximadamente o fluxo de massa e a potência elétrica do compressor também são propostas. Todas estas características do compressor são calculadas através das relações físicas do modelo, empregadas nos cálculos de otimização. O método é implementado no software EES (Engineering Equation Solver) e baseia-se nos trabalhos de Jahing (1999) e Jahing et al. (2000). No presente método, cinco medições experimentais do fluxo de massa e potência elétrica são suficientes para determinar os parâmetros de ajuste do modelo. Este procedimento permite a geração de mapas de compressores satisfatórios sem a necessidade de um maior número de dados experimentais como no caso da norma ARI 540. Estes resultados obtidos com o modelo podem ser usados para o projeto de novos compressores. / In the present work is applied a semi-empirical method that uses a non-linear optimization technique for determination of the volumetric and combined efficiencies of hermetic reciprocating compressor. Relations to approximately estimate the mass flow and the electric power of the compressor are also proposed. All these compressor characteristics are calculated through physical model relations, used in the optimization calculations. The method is implemented in the EES (Engineering Equation Solver) software and is based on the works of Jahing (1999) and Jahing et al. (2000). In the method, four experimental measurements of the mass flow and electric power are enough to determine the fitting parameters of the model. This procedure allows the generation of satisfactory compressor maps without the necessity of a higher number of experimental data, as in the case of norm ARI 540 application. The results obtained with the model can be used for the design of new compressors.

A critical issue in the development of gas condensate reservoirs is accurate prediction of well deliverability. In this investigation a procedure has been developed for accurate prediction of well production rates using semi-empirical approach. The use of state of the art fine grid numerical simulation is time consuming and computationally demanding, therefore not suitable for real time rapid production management decisions required on site. Development of accurate fit-for-purpose correlations for fluid property prediction below the saturation pressure was a major consideration to properly allow for retrograde condensation, complications of multiphase flow and mobility issues. Previous works are limited to use of experimentally measured pressure, volume, temperature (PVT) property data, together with static relative permeability correlations for simulation of well deliverability. To overcome the above limitations appropriate fluid property correlations required for prediction of well deliverability and dynamic three phase relative permeability correlation have been developed to enable forecasting of these properties at all the desired reservoir conditions The developed correlations include; condensate hybrid compressibility factor, viscosity, density, compositional pseudo-pressure, and dynamic three phase relative permeability. The study made use of published data bases of experimentally measured gas condensate PVT properties and three phase relative permeability data. The developed correlations have been implemented in both vertical and horizontal well models and parametric studies have been performed to determine the critical parameters that control productivity in gas condensate reservoirs, using specific case studies. The improved correlations showed superior performance over existing correlations on validation. The investigation has built on relevant literature to present an approach that modifies the black oil model for accurate well deliverability prediction for condensate reservoirs at conditions normally ignored by the conventional approach. The original contribution to knowledge and practice includes (i) the improved property correlations equations, (4.44, 4.47, 4.66, 4.69, 4.75, 5.21) and (ii) extension of gas rate equations, for condensate rate prediction in both vertical and horizontal wells. Standard industry software, the Eclipse compositional model, E-300 has been used to validate the procedure. The results show higher well performance compared with the industry standard. The new procedure is able to model well deliverability with limited PVT and rock property data which is not possible with most available methods. It also makes possible evaluation of various enhanced hydrocarbon recovery techniques and optimisation of gas condensate recovery.

The age of “easy” oil has steadily declined through the years as many conventional land-based fields have been depleted to residual levels. Novel technologies, however, have reawakened old fields, allowing incremental oil to be added to their recoverable oil in place (ROIP). Underground Gravity Drainage (UGD), an example of one of these technologies, combines improved horizontal and deviated drilling technologies with the longstanding concept of gravity drainage. In this work, a better understanding of gravity drainage has been gained through (1) development of a numerical, three-dimensional, three-phase reservoir simulator (UT-EMPRES), (2) development of a universal, semi-empirical model of production rates through primary depletion, and (3) analysis of the important aspects of gravity drainage through simulation. UT-EMPRES is a new three-phase, finite-difference reservoir simulator, which utilizes a simple, easy-to-use Microsoft Excel interface to access MATLAB-programmed simulation code. This simulator produces nearly identical results to other well-established simulators, including UTCHEM and CMG. UT-EMPRES has some unique features, allows for easy post-processing in MATLAB, and has been utilized extensively in the other two areas of this thesis. The generalized flow rate model (GFRM) is a semi-empirical equation that is used to forecast the dynamic primary production rate of a reservoir with an arbitrary number of wells all operating at the same constant pressure condition. The model is an extension of the classic tank model, which is inherently a single flowing phase development. With the ability to make a priori predictions of production figures, users can screen various prospect assets on the basis of economic potential through optimization routines on the GFRM. Gravity drainage and its approximation through numerical simulation are analyzed. A sensitivity study was conducted on three-phase gravity drainage, leading to the conclusion that small changes in vertical permeability and portions of the relative permeability-saturation relationships can greatly affect production rates. Finally, two-phase (oil and air) and regions of three-phase (water, oil, air) flow simulations were found to exhibit exponential decline in phase production rates, which may enable the GFRM to be applicable to UGD-type processes. / text

This thesis is a summary of studies that were carried out as part of candidacy for aPhD degree. The purpose of these studies was to evaluate some factors in shipdesign that are intended for navigating in ice using numerical simulations. A semiempiricalnumerical procedure was developed by combining mathematical modelsthat describe the various elements of the continuous-mode icebreaking process inlevel ice. The numerical procedure was calibrated and validated using full- andmodel-scale measurements. The validated numerical model was in turn used toinvestigate and clarify issues that have not been previously considered.An icebreaker typically breaks ice by its power, its weight and a strengthened bowwith low stem angle. The continuous icebreaking process involves heave and pitchmotions that may not be negligible. The numerical procedure was formulated toaccount for all of the possible combinations of motions for six degrees of freedom(DOFs). The effects of the motion(s) for certain DOF(s) were investigated bycomparing simulations in which the relevant motion(s) were first constrained andthen relieved.In the continuous-mode icebreaking process, a ship interacts with an icebreakingpattern consisting of a sequence of individual icebreaking events. The interactionsamong the key characteristics of the icebreaking process, i.e., the icebreakingpattern, ship motions, and ice resistance, were studied using the numericalprocedure in which the ship motions and excitation forces were solved for in thetime domain and the ice edge geometry was simultaneously updated.Observations at various test scales have shown that the crushing pressure arisingfrom the ice–hull interaction depends on the contact area involved. A parametricstudy was carried out on the numerical procedure to investigate the effect of thecontact pressure on icebreaking.The loading rates associated with the ship’s forward speed have been anticipatedto play an important role in determining the bending failure loads, in view of thedynamic water flow underneath the ship and the inertia of the ice. The dynamicbending behavior of ice could also explain the speed dependence of the icebreakingresistance component. A dynamic bending failure criterion for ice was derived,incorporated into the numerical procedure and then validated using full-scale data.The results obtained using the dynamic and static bending failure criteria werecompared to each other.In addition, the effect of the propeller flow on the hull resistance for ships runningpropeller first in level ice was investigated by applying the information obtainedfrom model tests to the numerical procedure. The thrust deduction in ice wasdiscussed.

There is a need for reliable rules of thumb for various applications in the area of biochemistry, supramolecular chemistry and material sciences. Simultaneously, the amount of information, which we can gather from X-ray crystal geometries about the nature of recognition processes, is limited. Deeper insight into the noncovalent interactions playing the most important role is needed in order to revise these universal rules governing any recognition process. In this thesis, systematic development and study of the accuracy of the computational chemistry methods followed by their applications in protein DNA and host guest systems, are presented. The non-empirical quantum mechanical tools (DFT-D, MP2.5, CCSD(T) etc. methods) were utilized in several projects. We found and confirmed unique low lying interaction energies distinct from the rest of the distributions in several amino acid−base pairs opening a way toward universal rules governing the selective binding of any DNA sequence. Further, the predictions and examination of changes of Gibbs energies (ΔG) and its subcomponents have been made in several cases and carefully compared with experiments. We determined that the choline (Ch+) guest is bound 2.8 kcal/mol stronger (calculated ΔG) than acetylcholine (ACh+) to self-assembled triple helicate rigid...

Nanometer-scale silicon shows extraordinary electronic and optical properties that are not available for bulk silicon, and many investigations toward applications in optoelectronic devices are being pursued. Silicon nanoparticle films made from solution are a promising candidate for low-cost solar cells. However, controlling the properties of silicon nanoparticles is quite a challenge, in particular shape and size distribution, which effect device performance. At present, none of the solar cells made from silicon nanoparticle films have an efficiency exceeding the efficiency of those based on crystalline silicon. To address the challenge of controlling silicon nanoparticle properties, both theoretical and experimental investigations are needed. In this thesis, we investigate silicon nanoparticle properties via quantum mechanical modeling of silicon nanoparticles and synthesis of silicon nanoparticle films via colloidal grinding. Silicon nanoparticles with shapes including cubic, rectangular, ellipsoidal and flat disk are modeled using semi-empirical methods and configuration interaction. Their electronic properties with different surface passivation were also studied. The results showed that silicon nanoparticles with hydrogen passivation have higher HOMOLUMO gaps, and also the HOMO-LUMO gap depends on the size and the shape of the particle. In contrast, silicon nanoparticles with oxygen passivation have a lower HOMO-LUMO gap. Raman spectroscopy calculation of silicon nanoparticles show peak shift and asymmetric broadening similar to what has been observed in experiment. Silicon nanoparticle synthesis via colloidal grinding was demonstrated as a straightforward and inexpensive approach for thin film solar cells. Data analysis of silicon particles via SEM images demonstrated that colloidal grinding is effective in reducing the Si particle size to sub-micron in a short grinding time. Further increases in grinding time, followed by filtration demonstrated a narrowing of the Si particle size and size-distribution to an average size of 70 nm. Raman spectroscopy and EDS data demonstrated that the Si nanoparticles contain oxygen due to exposure to air during grinding. I-V characterization of the milled Si nanoparticles showed an ohmic behaviour with low current at low biases then Schottky diode behaviour or a symmetric curve at large biases. / Graduate / 0794 / 0544 / zahraalbu@hotmail.com

Nanometer-scale silicon shows extraordinary electronic and optical properties that are not available for bulk silicon, and many investigations toward applications in optoelectronic devices are being pursued. Silicon nanoparticle films made from solution are a promising candidate for low-cost solar cells. However, controlling the properties of silicon nanoparticles is quite a challenge, in particular shape and size distribution, which effect device performance. At present, none of the solar cells made from silicon nanoparticle films have an efficiency exceeding the efficiency of those based on crystalline silicon. To address the challenge of controlling silicon nanoparticle properties, both theoretical and experimental investigations are needed. In this thesis, we investigate silicon nanoparticle properties via quantum mechanical modeling of silicon nanoparticles and synthesis of silicon nanoparticle films via colloidal grinding. Silicon nanoparticles with shapes including cubic, rectangular, ellipsoidal and flat disk are modeled using semi-empirical methods and configuration interaction. Their electronic properties with different surface passivation were also studied. The results showed that silicon nanoparticles with hydrogen passivation have higher HOMOLUMO gaps, and also the HOMO-LUMO gap depends on the size and the shape of the particle. In contrast, silicon nanoparticles with oxygen passivation have a lower HOMO-LUMO gap. Raman spectroscopy calculation of silicon nanoparticles show peak shift and asymmetric broadening similar to what has been observed in experiment. Silicon nanoparticle synthesis via colloidal grinding was demonstrated as a straightforward and inexpensive approach for thin film solar cells. Data analysis of silicon particles via SEM images demonstrated that colloidal grinding is effective in reducing the Si particle size to sub-micron in a short grinding time. Further increases in grinding time, followed by filtration demonstrated a narrowing of the Si particle size and size-distribution to an average size of 70 nm. Raman spectroscopy and EDS data demonstrated that the Si nanoparticles contain oxygen due to exposure to air during grinding. I-V characterization of the milled Si nanoparticles showed an ohmic behaviour with low current at low biases then Schottky diode behaviour or a symmetric curve at large biases. / Graduate / 0794 / 0544 / zahraalbu@hotmail.com