Software-based analysis is one of the main methods for detecting and locating a leak from pipelines without the need for extensive instrumentation. However, software-based methods are generally sensitive to process disturbances, which cause the method to fail. In order to deal with these disturbances without increasing the number of measurements, an observer is designed for leak detection in natural gas pipelines as a case study. The proposed design implements a linear unknown input observer with time delays that considers changes of temperature and pressure as unknown inputs and includes measurement noise in the process. The unknown input observer found in the literature is modified for an application of leak detection. Nonisothermal modeling and simulation of a natural gas pipeline with time-variant consumer usage are performed to test the proposed method. Effects of pressure drop and temperature change on observer estimation are simulated and compared to a simulated leak event.
Background
Enzymatic hydrolysis is a major step for cellulosic ethanol production. A thorough understanding of enzymatic hydrolysis is necessary to help design optimal conditions and economical systems. The original HCH-1 (Holtzapple–Caram–Humphrey–1) model is a generalized mechanistic model for enzymatic cellulose hydrolysis, but was previously applied only to the initial rates. In this study, the original HCH-1 model was modified to describe integrated enzymatic cellulose hydrolysis. The relationships between parameters in the HCH-1 model and substrate conversion were investigated. Literature models for long-term (> 48 h) enzymatic hydrolysis were summarized and compared to the modified HCH-1 model.
Results
A modified HCH-1 model was developed for long-term (> 48 h) enzymatic cellulose hydrolysis. This modified HCH-1 model includes the following additional considerations: (1) relationships between coefficients and substrate conversion, and (2) enzyme stability. Parameter estimation was performed with 10-day experimental data using α-cellulose as substrate. The developed model satisfactorily describes integrated cellulose hydrolysis data taken with various reaction conditions (initial substrate concentration, initial product concentration, enzyme loading, time). Mechanistic (and semi-mechanistic) literature models for long-term enzymatic hydrolysis were compared with the modified HCH-1 model and evaluated by the corrected version of the Akaike information criterion. Comparison results show that the modified HCH-1 model provides the best fit for enzymatic cellulose hydrolysis.
Conclusions
The HCH-1 model was modified to extend its application to integrated enzymatic hydrolysis; it performed well when predicting 10-day cellulose hydrolysis at various experimental conditions. Comparison with the literature models showed that the modified HCH-1 model provided the best fit.
Electronic supplementary material
The online version of this article (10.1186/s13068-019-1371-5) contains supplementary material, which is available to authorized users.
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