Fundamentals of Classical Thermodynamics (2nd Edition)

Wylen, Gordon John Van; Sonntag, R. E.; Dybbs, A.

doi:10.1115/1.3423632

Cited by 123 publications

(155 citation statements)

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“…Numerical values of vapor pressure function constants and critical properties are listed in Table A.3 of Appendix A. Oil vapor pressure is computed as a function of NAPL-phase concentration according to Raoult's Law [Van Wylen and Sonntag 1978], according to Equation (4.2.7). The effect of total system pressure on the oil vapor pressure and the Poynting effect [Wark 1995], is computed using the assumption that the gas phase behaves as an ideal solution and an ideal gas mixture according to Equation (4.2.8).…”

Section: Oil Vapor Pressurementioning

confidence: 99%

“…Numerical values of the water vapor constants are listed in Tables A.6 through A.8 of Appendix A. Water vapor internal energy is computed from its enthalpy using the thermodynamic relationship [Van Wylen and Sonntag 1978] shown in Equation (4.6.4). Water vapor enthalpy and internal energy as a function of temperature for saturated conditions according to Equations (4.6.3) and (4.6.4) are shown graphically in Figure 4.10.…”

Section: Gas-phase Enthalpy and Internal Energymentioning

confidence: 99%

“…Compositional NAPL contains a mixture of liquid-oil components. According to Raoult's Rule for multicomponent, multiphase equilibrium [Van Wylen and Sonntag 1978] the vapor pressure for each oil is computed from its saturated vapor pressure and mole fraction in the NAPL phase, where each component's saturated vapor pressure is computed as a function of temperature.…”

Section: Gas-phase Pressurementioning

confidence: 99%

“…The air pressure is computed from Dalton's partial pressure law for ideal gas mixtures [Van Wylen and Sonntag 1978], according to Equation (4.2.9).…”

Section: Air Pressurementioning

confidence: 99%

“…Gas-phase densities are computed according to Dalton's ideal gas law for mixtures [Van Wylen and Sonntag 1978], where the sum of the gas component partial pressures equals the total gas pressure. The low solubility assumption for air and oil solubility in the aqueous phase allows the aqueous-phase density to be approximated with the density of liquid water.…”

Section: Densitymentioning

confidence: 99%

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STOMP Subsurface Transport Over Multiple Phases Version 2.0 Theory Guide

White¹,

Oostrom²

2000

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In writing this guide for the STOMP simulator, the authors have assumed that the reader comprehends concepts and theories associated with (multiple-phase) hydrology, heat transfer, thermodynamics, radioactive chain decay, and relative permeability-saturation-capillary pressure constitutive functions. The authors further assume that the reader is familiar with the computing environment on which they plan to compile and execute the STOMP simulator.The STOMP simulator requires an ANSI FORTRAN 77 compiler to generate an executable code. The memory requirements for executing the simulator are dependent on the complexity of physical system to be modeled and the size and dimensionality of the computational domain. Likewise execution speed depends on the problem complexity, size and dimensionality of the computational domain, and computer performance. One-dimensional problems of moderate complexity can be solved on conventional desktop computers, but multidimensional problems involving complex flow and transport phenomena typically require the power and memory capabilities of workstation or mainframe type computer systems.iii iv SummaryThe U. S. Department of Energy, through the Office of Technology Development, has requested the demonstration of remediation technologies for the cleanup of volatile organic compounds and associated radionuclides within the soil and groundwater at arid sites. This demonstration program, called the VOC-Arid Soils Integrated Demonstration Program (Arid-ID), has been initially directed at a volume of unsaturated and saturated soil contaminated with carbon tetrachloride, on the Hanford Site near Richland, Washington. A principal subtask of the Arid-ID program involves the development of an integrated engineering simulator for evaluating the effectiveness and efficiency of various remediation technologies. The engineering simulator's intended users include scientists and engineers who are investigating subsurface phenomena associated with remediation technologies. Principal design goals for the engineer simulator include broad applicability, verified algorithms, quality assurance controls, and validated simulations against laboratory and field-scale experiments. An important goal for the simulator development subtask involves the ability to scale laboratory and field-scale experiments to fullscale remediation technologies, and to transfer acquired technology to other arid sites. The STOMP (Subsurface Transport Over Multiple Phases) simulator has been developed by the Pacific Northwest National Laboratory (a) for modeling remediation technologies. Information on the use, application, and theoretical basis of the STOMP simulator are documented in three companion guide manuals. This manual, the Theory Guide (Version 2.0), provides the most recent theory and discussions on the governing equations, constitutive relations, and numerical solution algorithms for the STOMP simulator.The STOMP simulator's fundamental purpose is to produce numerical predictions of thermal and hydrogeologic flow and trans...

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Section: Oil Vapor Pressurementioning

confidence: 99%

Section: Gas-phase Enthalpy and Internal Energymentioning

confidence: 99%

Section: Gas-phase Pressurementioning

confidence: 99%

“…The air pressure is computed from Dalton's partial pressure law for ideal gas mixtures [Van Wylen and Sonntag 1978], according to Equation (4.2.9).…”

Section: Air Pressurementioning

confidence: 99%

Section: Densitymentioning

confidence: 99%

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STOMP Subsurface Transport Over Multiple Phases Version 2.0 Theory Guide

White¹,

Oostrom²

2000

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Impact of EGR fraction on diesel engine performance considering heat loss and temperature-dependent properties of the working fluid

Aithal

2009

Int. J. Energy Res.

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SUMMARYExhaust gas recirculation (EGR) to reduce feed gas NO x emission is common practice in modern diesel engines. Dilution of the intake air with cooled recirculated exhaust gas limits the production of in-cylinder NO x due to a lowering of the adiabatic flame temperature and a reduction in oxygen content of the intake mixture. EGR also reduces the mixture-averaged ratio of specific heats (g) of the combustion charge leading to a reduction in the thermodynamic cycle efficiency. This trade-off between minimizing NO x production and maximizing cycle efficiency is of critical importance when calibrating EGR control schemes. Modeling tools that allow a quantitative analysis of this trade-off can be very beneficial in tuning EGR systems over a range of operating conditions. In this study, the systematic development of a model that allows an assessment of the impact of EGR on three parameters, namely (a) the thermodynamic cycle efficiency, (b) the mixture temperatures during the cycle and (c) the mixture-averaged g, is presented. This is accomplished through a numerical solution of the energy equation while considering the effects of heat loss and temporally varying mixture-averaged values of g. Results for a simple phenomenological model relating fuel-burn rate with EGR fraction and the impact of EGR fraction on NO x reduction are also included.

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