Simmons timetool
1985) depending on gas flow rate, tank design and fluids properties (e.g. Different regimes are observed when sparging gas into stirred tanks namely flooded, loaded, completely dispersed, and gas recirculation (Nienow et al. Gas–liquid reactors are very common unit operations in the biochemical and chemical industries, where ensuring appropriate interphase contact and gas dispersion is critical. The data-richness and high time resolution of the used technique represent desirable features for modern control system strategies. This work aims to propose a methodology to obtain real time information by installing an acoustic piezoelectric sensor on the outside of a stirred tank. In this work, AE is applied to monitor gas–liquid mixing in a 3L stirred tank, with the objective to identify the operating bubble dispersion regime. This is mainly due to difficulties in retrofitting the devices to existing plants as well as to slow responses. 2010) have used AE energy information to predict gas phase fraction in a two phase (air–water) slug flow.Īlthough, many researchers have investigated various methods to determine multiphase mixing regimes in stirred tanks in real time, as reported in subsequent sections, their applications have been limited to R&D. While the first known reference on gas–liquid flow dates from the 1920s (Bragg Sir 1921), more recent works (Addali et al. ( 2004), for example, applied AE to a jacketed stirred tank for monitoring of a heterogeneous reaction. Applications in multiphase mixing are also reported in the literature, Nordon et al. 1998) and V-blenders (Crouter and Briens 2015). Other studies have applied AE to powder pneumatic conveying (Esbensen et al. (Aldrich and Theron 2000) have used directional microphones to estimate particle size in a ball mill using continuous regression. More recent studies have also investigated AE as a means of monitoring physico-chemical changes within processes involving powder and fluids. Most of AE research has focused on fault detection (leakage, failure.) (Boyd and Varley 2001), corrosion (Cole and Watson 2005), grinding (Griffin and Chen 2016) and tool wearing (Elforjani and Shanbr 2018 Li et al. The signal will often be a combination of numerous acoustic events all propagating to the sensor via different paths. The latter, also known as acoustic emission (AE), is composed only by a sensor recording acoustic waves generated by the process itself. The former consists of a transmitter generating an acoustic wave within the system and a receiver acquiring the response of the stimulated system.
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Traditionally acoustic techniques are categorised as either with active or passive acoustics. Amongst several potential sensing methods, acoustic emission (AE) is a low cost, data-rich technique with applicability for in-line monitoring.
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Desirable features for process measurements are to be non-invasive and suitable for in-line application with real time response, in order to avoid delays in intervening with control measures. To further advance the field, innovation is needed not only in the theoretical foundations but also in identifying new technical solutions (Hu et al. Improving process monitoring is a common need within the process industry, including chemical, food, biochemical and pharmaceuticals (Boyd and Varley 2001). The developed method allowed to successfully recognise the operating regime with an accuracy higher than 90% both in absence and presence of suspended particles. The system was operated in different flow regimes (non-gassed condition, loaded and complete dispersion) achieved by varying impeller speed and gas flow rate, with the objective to feed machine learning algorithms with the acoustic spectrum to univocally identify the different conditions. Whilst moving up through the vessel, gas bubbles collapse, break or coalesce generating sound waves transmitted through the wall to the acoustic transmitter. The system was a 3L stirred tank equipped with a Rushton Turbine and a ring sparger. In this work, a methodology to compute acoustic emission data, recorded using a piezoelectric sensor, to evaluate the gas–liquid mixing regime within gas–liquid and gas–solid–liquid mixtures was developed. Operations involving gas–liquid agitated vessels are common in the biochemical and chemical industry ensuring good contact between the two phases is essential to process performance.