Direct support and general support maintenance repair parts and special tools lists ... : power plant, utility (MUST) gas turbine engine (Amertech Corp model APP-1), NSN 6115-00-937-0929.

"7 September 1979."

Outer continental shelf (OCS) oil and gas supply model /

"DOE/EIA-0372/1-3."

Heterogeneous model for gas transport in carbon molecular sieves

A dual resistance model with distribution of either barrier or pore diffusional activation energy is proposed in this work for gas transport in carbon molecular sieve (CMS) micropores. This is a novel approach in which the equilibrium is homogeneous, but the kinetics is heterogeneous. The model seems to provide a possible explanation for the concentration dependence of the thermodynamically corrected barrier and pore diffusion coefficients observed in previous studies from this laboratory on gas diffusion in CMS.(1.2) The energy distribution is assumed to follow the gamma distribution function. It is shown that the energy distribution model can fully capture the behavior described by the empirical model established in earlier studies to account for the concentration dependence of thermodynamically corrected barrier and pore diffusion coefficients. A methodology is proposed for extracting energy distribution parameters, and it is further shown that the extracted energy distribution parameters can effectively predict integral uptake and column breakthrough profiles over a wide range of operating pressures.

Risk-based maintenance model for offshore oil and gas pipelines:a case study

Offshore oil and gas pipelines are vulnerable to environment as any leak and burst in pipelines cause oil/gas spill resulting in huge negative Impacts on marine lives. Breakdown maintenance of these pipelines is also cost-intensive and time-consuming resulting in huge tangible and intangible loss to the pipeline operators. Pipelines health monitoring and integrity analysis have been researched a lot for successful pipeline operations and risk-based maintenance model is one of the outcomes of those researches. This study develops a risk-based maintenance model using a combined multiple-criteria decision-making and weight method for offshore oil and gas pipelines in Thailand with the active participation of experienced executives. The model's effectiveness has been demonstrated through real life application on oil and gas pipelines in the Gulf of Thailand. Practical implications. Risk-based inspection and maintenance methodology is particularly important for oil pipelines system, as any failure in the system will not only affect productivity negatively but also has tremendous negative environmental impact. The proposed model helps the pipelines operators to analyze the health of pipelines dynamically, to select specific inspection and maintenance method for specific section in line with its probability and severity of failure.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Phase transitions and spatially ordered counterion association in ionic-lipid membranes: A statistical model

We propose a statistical model to account for the gel-fluid anomalous phase transitions in charged bilayer- or lamellae-forming ionic lipids. The model Hamiltonian comprises effective attractive interactions to describe neutral-lipid membranes as well as the effect of electrostatic repulsions of the discrete ionic charges on the lipid headgroups. The latter can be counterion dissociated (charged) or counterion associated (neutral), while the lipid acyl chains may be in gel (low-temperature or high-lateral-pressure) or fluid (high-temperature or low-lateral-pressure) states. The system is modeled as a lattice gas with two distinct particle types-each one associated, respectively, with the polar-headgroup and the acyl-chain states-which can be mapped onto an Ashkin-Teller model with the inclusion of cubic terms. The model displays a rich thermodynamic behavior in terms of the chemical potential of counterions (related to added salt concentration) and lateral pressure. In particular, we show the existence of semidissociated thermodynamic phases related to the onset of charge order in the system. This type of order stems from spatially ordered counterion association to the lipid headgroups, in which charged and neutral lipids alternate in a checkerboard-like order. Within the mean-field approximation, we predict that the acyl-chain order-disorder transition is discontinuous, with the first-order line ending at a critical point, as in the neutral case. Moreover, the charge order gives rise to continuous transitions, with the associated second-order lines joining the aforementioned first-order line at critical end points. We explore the thermodynamic behavior of some physical quantities, like the specific heat at constant lateral pressure and the degree of ionization, associated with the fraction of charged lipid headgroups.

Greenhouse gas emissions from alternative futures of deforestation and agricultural management in the southern Amazon

The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006-2050) impacts on carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO(2)-equivalents (CO(2)-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO(2)-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.

Optimisation of environmental gas cleaning routes for solid wastes cogeneration systems - Part I - Analysis of waste incineration steam cycle

Research of advanced technologies for energy generation contemplates a series of alternatives that are introduced both in the investigation of new energy sources and in the improvement and/or development of new components and systems. Even though significant reductions are observed in the amount of emissions, the proposed alternatives require the use of exhaust gases cleaning systems. The results of environmental analyses based on two configurations proposed for urban waste incineration are presented in this paper; the annexation of integer (Boolean) variables to the environomic model makes it possible to define the best gas cleaning routes based on exergetic cost minimisation criteria. In this first part, the results for steam cogeneration system analysis associated with the incineration of municipal solid wastes (MSW) is presented. (c) 2007 Elsevier Ltd. All rights reserved.

Constitutive model for long term municipal solid waste mechanical behavior

This paper presents some improvements in the model proposed by Machado et al. [Machado SL, Carvalho MF, Vilar OM. Constitutive model for municipal solid waste. J Geotech Geoenviron Eng ASCE 2002; 128(11):940-51] now considering the influence of biodegradation of organic matter in the mechanical behavior of municipal solid waste. The original framework considers waste as composed of two component groups; fibers and organic paste. The particular laws of behavior are assessed for each component group and then coupled to represent waste behavior. The improvements introduced in this paper take into account the changes in the properties of fibers and mass loss due to organic matter depletion over time. Mass loss is indirectly calculated considering the MSW gas generation potential through a first order decay model. It is shown that as the biodegradation process occurs the proportion of fibers increases, however, they also undergo a degradation process which tends to reduce their ultimate tensile stress and Young modulus. The way these changes influence the behavior of MSW is incorporated in the final framework which captures the main features of the MSW stress-strain behavior under different loading conditions. (C) 2007 Elsevier Ltd. All rights reserved.

Numerical prediction of gas concentrations and fluctuations above a triangular hill within a turbulent boundary layer

The objective of the present work is to propose a numerical and statistical approach, using computational fluid dynamics, for the study of the atmospheric pollutant dispersion. Modifications in the standard k-epsilon turbulence model and additional equations for the calculation of the variance of concentration are introduced to enhance the prediction of the flow field and scalar quantities. The flow field, the mean concentration and the variance of a flow over a two-dimensional triangular hill, with a finite-size point pollutant source, are calculated by a finite volume code and compared with published experimental results. A modified low Reynolds k-epsilon turbulence model was employed in this work, using the constant of the k-epsilon model C(mu)=0.03 to take into account the inactive atmospheric turbulence. The numerical results for the velocity profiles and the position of the reattachment point are in good agreement with the experimental results. The results for the mean and the variance of the concentration are also in good agreement with experimental results from the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Exergy-based method for analyzing the composition of the electricity cost generated in gas-fired combined cycle plants

The proposed method to analyze the composition of the cost of electricity is based on the energy conversion processes and the destruction of the exergy through the several thermodynamic processes that comprise a combined cycle power plant. The method uses thermoeconomics to evaluate and allocate the cost of exergy throughout the processes, considering costs related to inputs and investment in equipment. Although the concept may be applied to any combined cycle or cogeneration plant, this work develops only the mathematical modeling for three-pressure heat recovery steam generator (HRSG) configurations and total condensation of the produced steam. It is possible to study any n x 1 plant configuration (n sets of gas turbine and HRSGs associated to one steam turbine generator and condenser) with the developed model, assuming that every train operates identically and in steady state. The presented model was conceived from a complex configuration of a real power plant, over which variations may be applied in order to adapt it to a defined configuration under study [Borelli SJS. Method for the analysis of the composition of electricity costs in combined cycle thermoelectric power plants. Master in Energy Dissertation, Interdisciplinary Program of Energy, Institute of Eletro-technical and Energy, University of Sao Paulo, Sao Paulo, Brazil, 2005 (in Portuguese)]. The variations and adaptations include, for instance, use of reheat, supplementary firing and partial load operation. It is also possible to undertake sensitivity analysis on geometrical equipment parameters. (C) 2007 Elsevier Ltd. All rights reserved.