When there was a lack of computing power, several approximate formulas (Weymouth, Panhandle, AGA, etc.) were developed to obtain pressure drop in gas pipelines, which are in many instances still being used. As it is well-known, they can be sometimes grossly inaccurate, necessitating the addition of an arbitrary parameter ("pipe efficiency") for each case. The right answer, now that we have computers and numerical integration methods, is to perform integration of the mechanical energy balance at least, if not both the mechanical and the overall energy balance when possible. While we advocate the numerical integration to obtain pressure drop, sometimes hydraulic calculations are embedded in several application procedures (pipe design, leak detection, compressor station operating optimization, etc.), and they require algebraic expressions to be used. We investigate the use of existing approximate formulas, a procedure to adjust the "pipe efficiency" for a given set of conditions, the building of new nonlinear surrogate models, and a Quadratic Metamodel amenable to nonconvex optimization procedures, as opposed to the current rational formulations.
The minimum number of units in a
network has been proposed to be
obtained using a very simple formula using graph theory (
Hohmann, E. C.
Ph.D. Thesis, University of Southern
California, Los Angeles, CA, 1971.; LinnhoffB.
Comput. Chem. Eng.19793295). This is done, usually, assuming that thermodynamic feasibility
holds, especially in Pinch technology, where it is applied above and
below the pinch, but also for cases where the pinch is ignored. While
the failure of this formula is informally known in the community,
to our knowledge no realistic counterexample was presented before.
We provide such an industrial counterexample. In addition, we propose
to use a recently developed MILP model (BarbaroA.BagajewiczM.
Eng.2005291945) that guarantees finding the global minimum number of
exchangers. Finally, we point out the large number of alternative
solutions that real industrial problems may exhibit.
This paper presents a comparison of two heat exchanger network retrofit methods as they are applied to crude units: the well-known and widely used Pinch Design Method (PDM) and a recently developed Heat Integration Transportation Model (HIT), a recently developed mathematical programming-based MILP model [Nguyen et al. Ind. Chem. Eng. Res. 2010, 49, 13]. We show that the three-step procedure (targeting, design, and evolution) used by Pinch Technology renders solutions with excessive and unrealistic splitting of streams as well as visibly less profit compared to the results of HIT.
We review the performance of different
technologies published in
a recent patent by Ji and Bagajewicz (2007) aimed at increasing distillates
yield. We also present different implementation schemes composed of
various combinations of the two technologies and compare both distillate
yield and energy expenditure to the current conventional distillation
process for light, intermediate, and heavy crudes. We demonstrate
sizable increases of yield as well as significant profit. The criteria
for analysis were yield, energy savings, gross margin, and potential
extra revenue for each scheme. While the comparisons are made on the
basis of grassroots design, we took one technology and assumed a
retrofit of an existing column via simple change in the heat recovery,
to assess the extra investment needed.
In this paper, we show the implementation of the Generalized Likelihood Ratio (GLR) method to detect and also identify the size and location of leaks in pipelines. We introduce the use of accurate hydraulic models for hypothesis testing and the use of economics to determine the thresholds of detection and identification. We compare the leak detection power and costs to those of other simple leak detection methods. The economic comparison includes computing the losses for not detecting the leaks (false negatives) and detecting leaks that do not exist (false positives). We also illustrate the improvement in the power of our method by using more-accurate instrumentation.
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