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Evaluation of power and freshwater production based on integrated SCO2 combined Brayton cycle-organic Rankine cycle- RO desalination 32

Evaluation of power and freshwater production based on integ...

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32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy systems, ECOS 2019

作者： Khoshgoftar Manesh, Mohammad H. Firouzi, Parisa Kabiri, Saeed Blanco-Marigorta, Ana M. Division of Thermal Science and Energy Systems Department of Mechanical Engineering Faculty of Technology and Engineering University of Qom Qom Iran Center of Environmental Research University of Qom Qom Iran Department of Process Engineering Universidad de Las Palmas de Gran Canaria Las Palmas de Gran Canaria Spain

ISBN: (纸本)9788361506515

In order to improvement of the efficiency of the gas turbine and heat recovery of waste heat, a novel power and fresh water production system is proposed. This system is included combined supercritical CO2 regenerative Brayton cycle based on gas turbine, an organic Rankine cycle and Reverse Osmose (RO) desalination system. In this regard, thermodynamic modeling and simulation are performed for integrated cycle. In addition, exergetic and exergoeconomic analysis are reported for the proposed system parametric studies have been performed to evaluate the effect of system parameters on the exergy destruction and the unit cost of power and fresh water. Furthermore, the computer code has been developed for thermodynamic, exergetic and exergoeconomic analysis and comparison of integrated system. The results shows the proposed combined regenerative S-CO2 cycle, ORC and RO desalination system is promising improvement for gas turbine waste heat recovery, and it has advantages of deep recovery of waste heat, high exergetic efficiency and low power and freshwater costs. © ECOS 2019 - Proceedings of the 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy systems. All rights reserved.

关键词： Waste heat

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Cold plasma: a promising technology for improving the rheological characteristics of food

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Critical Reviews in Food Science and Nutrition 2022年第32期63卷 11370-11384页

作者： Kaavya, R. Pandiselvam, R. Gavahian, Mohsen Tamanna, R. Jain, Surangna Dakshayani, R. Khanashyam, Ananda Chandra Shrestha, Pratiksha Kothakota, Anjineyulu Arun Prasath, V. Mahendran, R. Kumar, Manoj Khaneghah, Amin Mousavi Nayik, Gulzar Ahmad Dar, Aamir Hussain Uddin, Jalal Ansari, Mohammad Javed Hemeg, Hassan A. Department of Dairy and Food Science South Dakota State University BrookingsSD United States Physiology Biochemistry and Post-Harvest Technology Division ICAR-Central Plantation Crops Research Institute Kerala Kasaragod India Department of Food Science National Pingtung University of Science and Technology Pingtung Taiwan Innovation and Technology Kraft Heinz Company ChicagoIL United States Department of Biotechnology Mahidol University Bangkok Thailand Department of Food Processing and Quality Control ThassimBeevi Abdul Kader College for Women Tamil Nadu Ramanathapuram India Department of Food Science and Technology Kasetsart University Bangkok Thailand Babarmahal Nepal Kerala Thiruvananthapuram India Department of Food Process Engineering National Institute of Technology Odisha Rourkela India Tamil Nadu Thanjavur India Chemical and Biochemical Processing Division ICAR-Central Institute for Research on Cotton Technology Maharashtra Mumbai India São Paulo Campinas Brazil Department of Food Science and Technology Government Degree College Shopian Jammu & Kashmir Srinagar India Department of Food Technology Islamic University of Science and Technology Kashmir Jammu & Kashmir Awantipora India Department of Pharmaceutical Chemistry College of Pharmacy King Khalid University Abha Saudi Arabia Department of Botany Hindu College Moradabad [Mahatma Jyotiba Phule Rohilkhand University Uttar Pradesh Bareilly India Department of Medical Laboratory Technology College of Applied Medical Sciences Taibah University Medina Saudi Arabia

At the beginning of the 21st century, many consumers show interest in purchasing safe, healthy, and nutritious foods. The intent requirement of end-users and many food product manufacturers are trying to feature a new processing technique for the healthy food supply. The non-thermal nature of cold plasma treatment is one of the leading breakthrough technologies for several food processing applications. The beneficial response of cold plasma processing on food quality characteristics is widely accepted as a substitution technique for new food manufacturing practices. This review aims to elaborate and offer crispy innovative ideas on cold plasma application in various food processing channels. It highlights the scientific approaches on the principle of generation and mechanism of cold plasma treatment on rheological properties of foods. It provides an overview of the behavior of cold plasma in terms of viscosity, crystallization, gelatinization, shear stress, and shear rate. Research reports highlighted that the cold plasma treated samples demonstrated a pseudoplastic behavior. The published literatures indicated that the cold plasma is a potential technology for modification of native starch to obtain desirable rheological properties. The adaptability and environmentally friendly nature of non-thermal cold plasma processing provide exclusive advantages compared to the traditional processing technique. © 2022 Taylor & Francis Group, LLC.

关键词： Viscosity

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EEG-Based Odor Recognition Using Channel-Frequency Convolutional Neural Network

EEG-Based Odor Recognition Using Channel-Frequency Convoluti...

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第三十八届中国控制会议

作者： Xiaonei Zhang Huirang Hou Qinghao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University

Analyzing the response of the human brain to odors is critical to assess the function of olfactory and cognition. In this paper, an EEG(electroencephalograph)-based odor perception dataset is collected from ten subjects using thirteen odors stimuli. Based on the developed dataset, we employ channel-frequency convolutional neural network(CFCNN), combined with differential entropy(DE) features from different channels and frequency bands, to classify five odors that were consistently considered pleasant by the ten subjects. Meanwhile, the k-nearest neighbor(k-NN), linear discriminant analysis(LDA), support vector machine(SVM) and back propagation neural network(BPNN) are used as competing methods. The experimental results show that CFCNN is superior to the classic baselines and yields the highest accuracy in distinguishing five pleasant odors. Furthermore, compared with other four frequency bands, the gamma band presents the best classification accuracy, proving the closed relation between the olfaction and gamma band activity of the brain.

关键词： EEG olfaction classification CFCNN differential entropy

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An Infotaxis-based Odor Source Searching Strategy for a Mobile Robot Equipped with a TDLAS Gas Sensor

An Infotaxis-based Odor Source Searching Strategy for a Mobi...

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第三十八届中国控制会议

作者： Xu-Yang Dai Jia-Ying Wang Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University

As a source searching method, infotaxis has been used in mobile olfactory robots equipped with contact-type MOS(metal oxide semiconductor) gas sensors. This method navigates a robot to explore more cues in the global space and therefore costs much time at the early stage. To solve this problem, this paper presents a line integral infotaxis(LII) algorithm which is realized by applying a remote-type TDLAS(tunable diode laser absorption spectroscopy) gas sensor to the infotaxis. In addition, the robot often gets stuck in the place of high concentration during the infotaxis searching process, so an odor source declaration procedure which is implemented by calculating the odor particle flux on a closed curve is added to the LII. Simulation results show that the LII algorithm can enormously save time of exploration and solve the local convergence problem.

关键词： Olfactory robots TDLAS gas sensor line integral infotaxis odor source declaration odor particle flux

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An Automatic Detection and Recognition Method for Pointer-type Meters in Natural Gas Stations

An Automatic Detection and Recognition Method for Pointer-ty...

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第三十八届中国控制会议

作者： Yan Huang Xu-Yang Dai Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University

Currently, pointer-type meters in natural gas stations are read manually, which causes a waste of human *** have proposed lots of methods to realize automatic reading of such meters. However, these methods need high quality source image rigorously so that they cannot perform well in real environments. To solve this problem, an automatic detection and recognition method for pointer-type meters is proposed, which consists of R-FCNs(region-based fully convolutional networks),an improved local threshold segmentation method and a probability-circle method. The experimental results show that the method performs well when the source image is blurred, the illumination is complex or the camera's angle is tilted. It has good robustness and accuracy to detect and recognize the pointer-type meters automatically.

关键词： Pointer-type meter automatic reading R-FCNs threshold segmentation probability-circle method

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Rip brane cosmology from a viscous holographic dark fluid

arXiv

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arXiv 2020年

作者： Brevik, I. Timoshkin, A.V. Department of Energy and Process Engineering Norwegian University of Science and Technology Trondheim7491 Norway Tomsk State Pedagogical University Kievskaja Street 60 Tomsk634061 Russia Tomsk State University of Control Systems and Radio Electronics Lenin Avenue 36 Tomsk634050 Russia

This article is devoted to the application of the holographic principle to describe Rip brane cosmological models in the presence of a bulk viscosity. We make use of the generalized infrared-cutoff holographic dark energy, introduced by Nojiri and Odintsov. We consider various examples: Rip brane cosmology corresponding to the Little Rip case, asymptotic de Sitter theory, and the so-called Big Freeze theory leading to a singularity. Analytical expressions for infrared cutoffs, as well as the particle and the future horizons at the brane, are obtained. The equations for energy conservation on the brane within the holographic theory are obtained in each case. The correspondence between viscous cosmology and holographic cosmology on the brane is shown. Copyright © 2020, The Authors. All rights reserved.

关键词： Holography

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Viscous coupled fluids in terms of a log-corrected equation of state

arXiv

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arXiv 2021年

作者： Brevik, Iver Myrzakulov, K. Timoshkin, A.V. Zhadyranova, A. Department of Energy and Process Engineering Norwegian University of Science and Technology TrondheimN-7491 Norway Eurasian National University Nur-Sultan010008 Kazakhstan Ratbay Myrzakulov Eurasian International Centre for Theoretical Physics Nur-Sultan010009 Kazakhstan Tomsk State Pedagogical University Kievskaja Street 60 Tomsk634061 Russia International Laboratory of Theoretical Cosmology Tomsk State University of Control Systems and Radioelectronics Lenin Avenue 36 Tomsk634050 Russia

We consider a class of cosmological fluids that possess properties analogous to those of crystalline solids undergoing isotropic deformations. Our research is based on a modified log-corrected power-law equation of state in the presence of a bulk viscosity. This formalism represents a class of so-called logotropic fluids, and allows explaining an accelerating late-time universe. In order to obtain a more detailed picture of its evolution, we add in our model a coupling of the log-corrected power-law fluid to dark matter, and study various interacting forms between them. We solve the system of equations for a modified log-power-law fluid coupled to dark matter, and obtain expressions for the log-corrected power-law energy density, and the energy density for dark matter. A comparative analysis is made with the model of a nonviscous log-corrected power-law fluid without interaction with dark matter. © 2021, CC BY.

关键词： Equations of state

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Thermodynamic aspects of entropic cosmology with viscosity

arXiv

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arXiv 2020年

作者： Brevik, Iver Timoshkin, A.V. Department of Energy and Process Engineering Norwegian University of Science and Technology TrondheimN-7491 Norway Tomsk State Pedagogical University Kievskaja Street 60 Tomsk634061 Russia Tomsk State University of Control Systems and Radio Electronics Lenin Avenue 36 Tomsk634050 Russia

We describe the evolution of the early and late universe from thermodynamic considerations, using the generalized non-extensive Tsallis entropy with a variable exponent. A new element in our analysis is the inclusion of a bulk viscosity in the description of the cosmic fluid. Using the generalized Friedmann equation, a description of the early and the late universe is obtained. © 2020, CC BY.

关键词： Cosmology

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Facilitating renewable natural gas production for a circular bioeconomy: AI-Driven process visualization and data augmentation on biochar-mediated anaerobic digestion

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Chemical engineering Journal 2025年 516卷

作者： Xiaoman He Jingyuan Guo Xihui Kang Xue Ning Huichao Chen Daolun Liang Chen Deng Zutan Li Dekui Shen Huiyan Zhang Richen Lin Jerry D. Murphy Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and Environment Southeast University Nanjing 211189 China Advanced Biofuels and Bioproducts Process Development Unit Biological Systems and Engineering Division Lawrence Berkeley National Laboratory Emeryville CA 94608 USA School of Engineering and Architecture University College Cork T23XE10 Cork Ireland Research Ireland MaREI Centre for Energy Climate and Marine Environmental Research Institute University College Cork T23XE10 Cork Ireland School of Chemistry and Chemical Engineering Southeast University Nanjing 211189 China School of Engineering Westlake University Hangzhou Zhejiang 310030 China Institute of Advanced Technology Westlake Institute for Advanced Study Hangzhou Zhejiang 310024 China

The conversion of biomass residues into biochar is a promising strategy for enhancing sustainability within the circular bioeconomy, particularly through its role in improving renewable natural gas production. However, engineering biochar with optimal properties remains a complex challenge, as the relationship between preparation conditions, biochar characteristics, and anaerobic digestion (AD) performance is not fully understood. This study presents an AI-derived full-process prediction approach that integrates machine learning and generative models to guide the rational design of biochar, and optimize its use for biomethane production. Three tree-based regression models were employed to predict AD performance, with the eXtreme Gradient Boosting Regression model demonstrating superior accuracy. Feature importance analysis identified key biochar properties, including electrical conductivity, oxygen content, and specific surface area, as critical factors influencing biomethane production. These properties can be fine-tuned by adjusting pyrolysis conditions and selecting suitable biomass sources. A generative adversarial network was further used to explore a broader data space, helping to identify the optimal combination of parameters for maximizing AD efficiency. This novel AI-driven framework facilitates biochar-mediated renewable natural gas production, offering a scalable and sustainable approach for advancing circular bioeconomy.

关键词： Biochar-mediated anaerobic digestion Circular bioeconomy Data augmentation Machine learning Renewable natural gas

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Integrated intelligent and predictive control: A multi-agent adaptive type-2 fuzzy control architecture

arXiv

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arXiv 2019年

作者： Jamshidnejad, Anahita Frazzoli, Emilio Mahjoob, Mohammad J. de Schutter, Bart Department of Mechanical and Process Engineering Institute for Dynamic Systems and Control ETH Zürich Switzerland Faculty of Mechanical Engineering University of Tehran Iran Delft Center for Systems and Control Delft University of Technology Netherlands

We propose a novel two-layer multi-agent architecture aimed at efficient real-time control of large-scale and complex-dynamics systems. The proposed architecture integrates intelligent control approaches (which have a low computation time and fit real-time applications) with model-predictive control (which takes care of the optimality requirements of control). The bottom control layer (intelligent-control module) includes several distributed intelligent-control agents, the design parameters of which are tuned by the top layer (model-predictive control module). The model-predictive control module fulfills two significant roles: looking ahead to the effects of the control decisions, and coordinating the intelligent-control agents of the lower control layer. The resulting multi-agent control system has a very low computation time, and provides adaptivity, control coordination, and aims at excellent performance. Additionally, we give a general treatment of type-2 fuzzy membership functions, and introduce two categories for them: probabilistic-fuzzy (which is a novel concept introduced in this paper) and fuzzy-fuzzy (which is a new treatment of the existing type-2 fuzzy membership functions). The performance of the proposed modeling and control approaches are assessed via a case study involving a simple urban traffic network: the results show that the novel concept of probabilistic-fuzzy membership function outperforms the type-1 and type-2 membership functions that have already been introduced in the literature. Furthermore, the proposed two-layer integrated multi-agent control architecture significantly outperforms a multi-agent decentralized fuzzy control system (without coordination among the agents), while requiring a comparable computation *** Codes 49-XX Copyright © 2019, The Authors. All rights reserved.

关键词： Multi agent systems

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