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Natural gas properties and flow computation 天然气性质与流量计算
Q2 Earth and Planetary Sciences Pub Date : 2010-01-01 DOI: 10.5772/9871
I. Marić, I. Ivek
The detailed procedure for the calculation of thermodynamic properties based on formulations explicit in Helmholtz energy (Lemmon & Starling, 2003) and on AGA-8 detail characterization equation (Starling & Savidge, 1992) is given in (ISO-207651-1, 2005). Here we elaborate an alternative procedure for the calculation of properties of a natural gas that was originally published in the Journal Flow Measurement and Instrumentation (Maric, 2005 & 2007). The procedure is derived using fundamental thermodynamic equations (Olander, 2007), DIPPR AIChE (DIPPR® Project 801, 2005) generic ideal heat capacity equations, and AGA-8 (Starling & Savidge, 1992) extended virial-type equations of state. The procedure specifies the calculation of specific heat capacities at a constant pressure cp and at a constant volume cv, the JT coefficient μJT, and the isentropic exponent κ of a natural gas. The effect of a JT expansion on the accuracy of natural gas flow rate measurements will be pointed out. The possibilities of using the computational intelligence methods - Artificial Neural Networks - ANNs (Ferrari & Stengel, 2005, Wilamowski et al., 2008) and machine learning tools - Group Method of Data Handling - GMDH (Ivakhnenko, 1971, Nikolaev & Iba, 2003) for meta-modeling the effects of natural gas properties in flow rate measurements (Maric & Ivek, 2010) will be illustrated. The practical examples of ANN and GMDH surrogate models for the compensation of natural gas flow rate measurement error caused by the thermodynamic effects, with the corresponding accuracies and execution times will be given. The models are particularly suitable for implementation in low computing power embedded systems.
基于亥姆霍兹能量(Lemmon & Starling, 2003)和AGA-8详细表征方程(Starling & Savidge, 1992)的明确公式计算热力学性质的详细步骤见(iso -207651- 1,2005)。在这里,我们详细阐述了一种计算天然气性质的替代程序,该程序最初发表在《流量测量与仪器仪表》杂志(Maric, 2005年和2007年)。该过程是使用基本热力学方程(Olander, 2007), DIPPR AIChE (DIPPR®项目801,2005)一般理想热容量方程和AGA-8 (Starling & Savidge, 1992)扩展的viri型状态方程推导出来的。该程序规定了天然气定压比热容cp和定容比热容cv、JT系数μJT和等熵指数κ的计算方法。指出了JT膨胀对天然气流量测量精度的影响。将说明使用计算智能方法-人工神经网络- ann (Ferrari & Stengel, 2005年,Wilamowski等人,2008年)和机器学习工具-数据处理组方法- GMDH (Ivakhnenko, 1971年,Nikolaev & Iba, 2003年)对天然气特性在流量测量中的影响进行元建模(Maric & Ivek, 2010年)的可能性。给出了人工神经网络和GMDH替代模型补偿天然气流量测量误差的实例,并给出了相应的精度和执行时间。这些模型特别适合在低计算能力的嵌入式系统中实现。
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引用次数: 2
636 Changes Favorable to LDCs Needed, Likely 可能需要有利于最不发达国家的变化
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410100609
F. Moring
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引用次数: 0
636 Strategies Lead to New Federal, State Tax Planning 636战略导致新的联邦,州税收规划
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410100607
Robert E. Willett
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引用次数: 0
Production Technology To Add Significant New Reserves 生产技术增加重要的新储量
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410100806
M. Haas
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引用次数: 0
Support for marketing difficult, expensive in an industry without standards 支持营销难度大、成本高的行业没有标准
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410090502
C. Callender
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引用次数: 0
Gics raise accounting issues gic引发了会计问题
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410070204
Curtis J. Klement
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引用次数: 0
A Gathering Primer 收集底漆
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410100805
Richard G. Smead
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引用次数: 0
Third-party access now part of gathering test? 第三方访问现在是收集测试的一部分?
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410070504
Douglas F. John
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引用次数: 0
Gas cost incentives raise concerns 天然气成本激励措施引发了担忧
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410110304
W. T. Benham
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引用次数: 0
Better Meeting Places for Gas Sellers and Buyers 为天然气买卖双方提供更好的会面场所
Q2 Earth and Planetary Sciences Pub Date : 2008-08-20 DOI: 10.1002/GAS.3410100809
F. Moring
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引用次数: 0
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