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Batch Distillation
Helping readers gain a solid, hands-on background in batch processing, this best-selling text explains how to effectively design, synthesize, and make operations decisions related to batch processes. Along with updating the references, this edition features special sections on complex column configurations and azeotropic, extractive, and reactive distillation. It also includes a new chapter on various kinds of uncertainties in batch distillation and a new chapter describing software packages for simulation, design, optimization, and control. A solutions manual is available for qualifying instructors.
eBook
Concentrating solar power and desalination plants : engineering and economics of coupling multi-effect distillation and solar plants
¨ The first available thermo-economic analyses of Concentrating Solar Power and Desalination (CSP+D) Plants, using real figures from operating plants ¨ Includes all the equations used in the modeling of each component, creating an invaluable template for implementing similar models ¨ Demonstrates modeling and validation of a Multi-effect Distillation (MED) Plant with increased energy recovery and enhanced thermal efficiency ¨ Extended parametric analysis helps readers decide when integrating a Thermal Desalination Plant will yield better results than connecting a Reverse Osmosis Plant. This ground-breaking book demonstrates how two key concerns in many communities across the globe- power and water- can be simultaneously addressed through the coupling of Concentrating Solar Power and Desalination (CSP+D) plants. The book provides a detailed evaluation of the integration of Multi-effect Distillation Plants into CSP plants based on Parabolic Trough Solar Collectors (PT-CSP+MED), as compared to independent water and power production through Reverse Osmosis unit connection to a CSP plant (CSP+RO). Through this compare and contrast method of analysis, the author establish guidelines to assist in identifying cases wherein PT-CSP+MED systems provide superior economic and thermodynamic benefits. The text describes the efficiencies and challenges of PT-CSP power generation in four different desalination plant scenarios, including detailed comparative thermodynamic efficiency analyses of several currently operating CSP+D systems. These findings are then placed in practical context through a complete thermo-economic analysis of two diverse potential sites, ascertaining the most viable CSP+D system in each region, as informed by actual operating conditions, meteorological data and real cost figures for each location.
Book
Bioactive Profile of Distilled Solid By-Products of Rosemary, Greek Sage and Spearmint as Affected by Distillation Methods
By-products of essential oils (EOs) in the industry represent an exploitable material for natural and safe antioxidant production. One representative group of such by-products is distilled solid residues, whose composition is properly modulated by the distillation method applied for the recovery of EOs. Recently, in terms of Green Chemistry principles, conventional extraction and distillation processes are considered outdated and tend to be replaced by more environmentally friendly ones. In the present study, microwave-assisted hydro-distillation (MAHD) was employed as a novel and green method for the recovery of EOs from three aromatic plants (rosemary, Greek sage and spearmint). The method was compared to conventional ones, hydro-distillation (HD) and steam-distillation (SD), in terms of phytochemical composition of distilled solid residues, which was estimated by spectrophotometric and chromatographic methods. Total phenolic content (TPC), total flavonoid content (TFC) and antioxidant activity (ABTS, DPPH and FRAP) results highlighted the distilled solid residues as good sources of antioxidants. Moreover, higher antioxidant activity was achieved for MAHD extracts of solid residues in comparison to HD and SD extracts. A metabolomics approach was carried out on the methanolic extracts of solid residues obtained by different distillation methods using LC-MS analysis followed by multivariate data analysis. A total of 29 specialized metabolites were detected, and 26 of them were identified and quantified, presenting a similar phenolic profile among different treatments, whereas differences were observed among different species. Rosmarinic acid was the most abundant phenolic compound in all extracts, being higher in MAHD extracts. In rosemary and Greek sage extracts, carnosol and carnosic acid were quantified in significant amounts, while trimers and tetramers of caffeic acid (salvianolic acids isomers) were identified and quantified in spearmint extracts, being higher in MAHD extracts. The obtained results pointed out that MAHD extracts of distilled solid by-products could be a good source of bioactives with potential application in the food, pharmaceutical and cosmetic industries, contributing to the circular economy.
Journal Article
A Lightweight Nighttime Vehicle and Pedestrian Detection Method Based on CWD Feature Distillation
To address the issues of complex structure, high parameter count, and computational load in the improved YOLO-WDS model, a lightweight design based on Channel-Wise Distillation (CWD) is proposed, leveraging its ability to handle feature alignment in dense prediction tasks. First, the channel numbers of the improved YOLO-WDS model are adjusted to generate lightweight detection models at different scales—light-s, light-m, and light-l. Second, distillation experiments are designed using the CWD feature distillation method to enhance the detection accuracy of the light-series models. Finally, the effectiveness of the proposed method is validated through experiments, and comparisons of different distillation positions demonstrate the superiority of CWD feature distillation in balancing model lightweighting and detection accuracy. The results show that, compared to the improved YOLO-WDS model, the parameter counts of the distilled light-series models are reduced by 39.27%, 56.56%, and 67.77%, respectively, while the computational loads are reduced by 23.81%, 47.29%, and 48.25%. Additionally, compared to YOLOv8, the detection accuracy is improved by 1.7%, 0.9%, and 0.3%, respectively, achieving model lightweighting while maintaining high detection accuracy.
Journal Article
Knowledge Distillation: A Survey
In recent years, deep neural networks have been successful in both industry and academia, especially for computer vision tasks. The great success of deep learning is mainly due to its scalability to encode large-scale data and to maneuver billions of model parameters. However, it is a challenge to deploy these cumbersome deep models on devices with limited resources, e.g., mobile phones and embedded devices, not only because of the high computational complexity but also the large storage requirements. To this end, a variety of model compression and acceleration techniques have been developed. As a representative type of model compression and acceleration, knowledge distillation effectively learns a small student model from a large teacher model. It has received rapid increasing attention from the community. This paper provides a comprehensive survey of knowledge distillation from the perspectives of knowledge categories, training schemes, teacher–student architecture, distillation algorithms, performance comparison and applications. Furthermore, challenges in knowledge distillation are briefly reviewed and comments on future research are discussed and forwarded.
Journal Article
Teacher-student collaborative knowledge distillation for image classification
A single model usually cannot learn all the appropriate features with limited data, thus leading to poor performance when test data are used. To improve model performance, we propose a teacher-student collaborative knowledge distillation (TSKD) method based on knowledge distillation and self-distillation. The method consists of two parts: learning in the teacher network and self-teaching in the student network. Learning in the teacher network allows the student network to use knowledge from the teacher network. Self-teaching in the student network is to build a multi-exit network based on self-distillation and provide deep features as supervised information for training. In the inference stage, we use ensembles to vote on the classification results of multiple sub-models in the student network. The experimental results demonstrate the superior performance of our method compared with a traditional knowledge distillation method and a self-distillation-based multi-exit network.
Journal Article
Processes and separation technologies for the production of fuel-grade bioethanol: a review
Bioethanol produced from biological resources is considered as an alternative, renewable, and sustainable energy source in the context of the circular economy. Moreover, bioethanol is a biofuel that has similar energy content to gasoline, but emits less toxic pollutants compared to fossil fuels. Yet bioethanol must be anhydrous to be mixed with regular gasoline and is then utilized as a vehicle fuel. Different techniques have been developed to obtain anhydrous ethanol. Here, we compare techniques for dehydration of bioethanol, including adsorption and distillation. We present the performance of the process, product recovery, and energy consumption of the pressure swing adsorption method, which is effective and widely used.
Journal Article
Study of the energetic, exergetic, and thermal balances of a solar distillation unit in comparison with a conventional system during the distillation of rosemary leaves
The solar energy produced by Scheffler parabola (10 m
2
) is not fully exploited by the solar distillation system of aromatic and medicinal plants. In this work, the optical losses in the primary and secondary reflectors, and the thermal losses at each part of this system (solar still, steam line, condenser) were determined. A thermal energetic and exergetic analysis were also performed for a solar distillation system of rosemary leaves. For average intensity radiation of 849.1W/m
2
and 6 Kg of rosemary leaves during 4 h of distillation, exergy and optical efficiencies of the system achieved up to 26.62% and 50.97%, respectively. The thermal efficiency of the solar still, steam line, and condenser is about 94.80%, 94.30%, and 87.76%, respectively. The essential oil yield per unit of consumed energy and the total efficiency of the solar distillation system, taking into account the heat losses in the solar still, steam line, and condenser, as well as the optical losses in the two reflectors, is 6.18 mL/ kWh and 40.00%, respectively. The efficiency can be as high as 42.42 % if the steam line is insulated. Moreover, the comparison between the solar steam distillation and conventional steam distillation shows that solar distillation is much more efficient since it gives better results and especially it avoids the emission of 12.10 kg of CO
2
during extraction.
Journal Article