Search Results (6)

Sour waters are one of the main aqueous byproducts generated during petroleum refining and require processing in sour water treatment units (SWTUs) to remove contaminants such as H₂S and NH₃ in compliance with environmental legislations. Therefore, monitoring the composition of SWTU effluxents, including acid gas, ammoniacal gas, and treated water, is essential. This study aims to present an AI (artificial intelligence) hybrid-based methodology to develop soft sensors capable of real-time prediction of H₂S and NH₃ mass fractions in the effluents of SWTUs and validate them using real data from industrial units. Initially, a new database based on the dynamic simulation of a two-stripping-column SWTU phenomenological model, developed in Aspen Plus Dynamics^® V10, was generated, aiming at non-faulty runs, unlike our previous work. Ensemble methods (decision trees), such as gradient boosting and random forest, and support vector machines were compared for soft sensor creation using these simulated data. The best outcome was the development of six soft sensors based on random forest with R² greater than 0.87, MAE less than 0.12, MSE less than 0.17, and RMSE less than 0.41. Variable importance analysis revealed that the temperature of the second stage of Column 1 significantly influences the thermodynamic equilibrium of H₂S and NH₃ separation from sour waters, being critical for five of the six soft sensors. After this initial stage using data from the phenomenological model, data from an industrial-scale SWTU were used to develop real soft sensors. The results proved the effectiveness of the conjugated use of a physical model and industrial data approach in the development of soft sensors for two-column SWTUs. Full article

Where vineyard exposure to bushfire smoke cannot be avoided or prevented, grape and wine producers need strategies to transform smoke-affected juice and wine into saleable product. This study evaluated the potential for spinning cone column (SCC) distillation to be used for the remediation of ‘smoke taint’. Compositional analysis of ‘stripped wine’ and condensate collected during SCC treatment of two smoke-tainted red wines indicated limited, if any, removal of volatile phenols, while their non-volatile glycoconjugates were concentrated due to water and ethanol removal. Together with the removal of desirable volatile aroma compounds, this enhanced the perception of smoke-related sensory attributes; i.e., smoke taint intensified. Stripped wines also became increasingly sour and salty as ethanol (and water) were progressively removed. A preliminary juice remediation trial yielded more promising results. While clarification, heating, evaporation, deionization and fermentation processes applied to smoke-tainted white juice gave ≤3 µg/L changes in volatile phenol concentrations, SCC distillation of smoke-tainted red juice increased the volatile phenol content of condensate (in some cases by 3- to 4-fold). Deionization of the resulting condensate removed 75 µg/L of volatile phenols, but fermentation of reconstituted juice increased volatile phenol concentrations again, presumably due to yeast metabolism of glycoconjugate precursors. Research findings suggest SCC distillation alone cannot remediate smoke taint, but used in combination with adsorbents, SCC may offer a novel remediation strategy, especially for tainted juice. Full article

Sour water stripping can treat the sour water produced by crude oil processing, which has the effect of environmental protection, energy saving and emission reduction. This paper aims to reduce energy consumption of the unit by strengthening process parameter optimization. Firstly, the basic model is established by utilizing Aspen Plus, and the optimal model is determined by comparative analysis of back propagation neural network (BPNN), radial basis function neural network (RBFNN) and generalized regression neural network (GRNN) models. Then, the sensitivity analysis of Sobol is used to select the operating variables that have a significant influence on the energy consumption of the sour water stripping system. Finally, the particle swarm optimization (PSO) algorithm is used to optimize the operating conditions of the sour water stripping unit. The results show that the RBFNN model is more accurate than other models. Its network structure is 5-66-1, and the expected value has an approximately linear relationship with the output value. Through sensitivity analysis, it is found that each operating parameter has an impact on the sour water stripping process, which needs to be optimized by the PSO algorithm. After 210 iterations of the PSO algorithm, the optimal system energy consumption is obtained. In addition, the cold/hot feed ratio, sideline production position, tower bottom pressure, hot feed temperature, and cold feed temperature are 0.117, 18, 436 kPa, 146 °C, and 35 °C, respectively; the system energy consumption is 5.918 MW. Compared with value of 7.128 MW before optimization, the energy consumption of the system is greatly reduced by 16.97%, which shows that the energy-saving effect is very significant. Full article

Background: The inter-individual differences in taste perception find a possible rationale in genetic variations. We verified whether the presence of four different single nucleotide polymorphisms (SNPs) in genes encoding for bitter (TAS2R38; 145G > C; 785T > C) and sweet (TAS1R3; −1572C > T; −1266C > T) taste receptors influenced the recognition of the basic tastes. Furthermore, we tested if the allelic distribution of such SNPs varied according to BMI and whether the associations between SNPs and taste recognition were influenced by the presence of overweight/obesity. Methods: DNA of 85 overweight/obese patients and 57 normal weight volunteers was used to investigate the SNPs. For the taste test, filter paper strips were applied. Each of the basic tastes (sweet, sour, salty, bitter) plus pure rapeseed oil, and water were tested. Results: Individuals carrying the AV/AV diplotype of the TAS2R38 gene (A49P G/G and V262 T/T) were less sensitive to sweet taste recognition. These alterations remained significant after adjustment for gender and BMI. Moreover, a significant decrease in overall taste recognition associated with BMI and age was found. There was no significant difference in allelic distribution for the investigated polymorphisms between normal and overweight/obese patients. Conclusions: Our findings suggest that overall taste recognition depends on age and BMI. In the total population, the inter-individual ability to identify the sweet taste at different concentrations was related to the presence of at least one genetic variant for the bitter receptor gene but not to the BMI. Full article

For the sour water strippers in petroleum refinery plants, three prediction models were developed first, including the estimators of sour water feed concentrations using convenient online measurements, the minimum reboiler duty and the corresponding internal temperature at a specific location (T_stage,29). Feedforward control schemes were developed based on these prediction models. Four categories of control schemes, including feedforward, feedback, feedback with external reset, and feedforward-feedback, were proposed and evaluated by the rigorous dynamic simulation model of the sour water stripper for their dynamic responses to the sour water feed stream disturbances. The comparison of control performance, in terms of the settling time, integrated absolute error (IAE) of the NH₃ concentration of the stripped sour water and IAE of the specific reboiler duty, reveals that FFT (feedforward control of T_stage,29) and FBA-DT3 (feedback control with 3 min concentration measurement delay) are the best control schemes. The second-best control scheme is FBAT (cascade feedback control of concentration with temperature). Full article

This study investigates the relationships between basic tastes and fattiness sensitivity and food liking in 11-year-old children. The basic taste sensitivity of 106 children was measured using different methods, namely detection (DT) and recognition (RT) thresholds, and taste responsiveness. Caffeine and quinine (bitter), sucrose (sweet), citric acid (sour), sodium chloride (salty), and monosodium glutamate (umami) were investigated for DT and RT at five concentrations in water solutions. In addition, taste responsiveness and liking were collected for the high-intensity concentrations. PROP (6-n-propylthiouracil) responsiveness was tested on paper strips. Fattiness sensitivity was measured by a paired comparison method using milk samples with varying fat content. Liking for 30 food items was recorded using a food-list questionnaire. The test was completed in a gamified “taste detective” approach. The results show that DT correlates with RT for all tastes while responsiveness to PROP correlates with overall taste responsiveness. Caffeine and quinine differ in bitterness responsiveness and liking. Girls have significantly lower DTs than boys for bitterness and sweetness. Food liking is driven by taste and fattiness properties, while fatty food liking is significantly influenced by fattiness sensitivity. These results contribute to a better holistic understanding of taste and fattiness sensitivity in connection to food liking in preadolescents. Full article