Article
Thermodynamics
Keivan Ardam, Behzad Najafi, Andrea Lucchini, Fabio Rinaldi, Luigi Pietro Maria Colombo
Summary: The study focuses on proposing, implementing, and optimizing machine learning pipelines for estimating pressure drop in R134a flow through micro-fin tubes. The experimental activities and feature selection process lead to the identification of the optimal pipeline with high accuracy compared to physical models.
INTERNATIONAL JOURNAL OF REFRIGERATION
(2021)
Article
Mechanics
Feng Nie, Shiqi Yan, Haocheng Wang, Cong Zhao, Yanxing Zhao, Maoqiong Gong
Summary: This study develops a new universal correlation for predicting the frictional pressure drop (FPD) in two-phase flow. Machine learning models based on artificial neural network (ANN) and extreme gradient boosting (XGBoost) theory are used to predict the unknown data with high accuracy. The obtained key parameters are used to formulate the new correlation, which shows improved predictive performance compared to existing correlations.
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW
(2023)
Article
Engineering, Mechanical
Barroso-Maldonado Juan Manuel, Riesco-Avila Jose Manuel, Picon-Nunez Martin, Belman-Flores Juan Manuel
Summary: An Artificial Neural Network soft matrix correlation was developed in this study to estimate the pressure drop of air-water two-phase flow. The model's applicability was extended by using dimensionless physical numbers as inputs. Experimental measurements showed that the proposed ANN correlation model has higher accuracy and can be widely applied, including in laminar, transitional, and turbulent flow regimes.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Yongchao Rao, Shuli Wang, Lijun Li
Summary: This study conducted a numerical simulation to investigate the gas-liquid two-phase spiral annular flow pattern and its conversion law in a horizontal tube with twist tape by spiral on-way. It identified three main flow patterns and identified the main factor affecting the existence of the gas phase. Additionally, it discovered a new flow pattern compared to the local spiral flow pattern of the short twisted band.
Article
Engineering, Chemical
Shu Wang, Dong Hu, Fengling Yang, Peng Lin, Chuanlin Tang
Summary: This paper divides the airlift process into liquid-solid two-phase section and gas-liquid-solid three-phase section, establishing pressure drop models based on energy conservation and phase hold-up equations. The results show that pressure drop decreases rapidly first and then tends to be constant with the increase of pipe diameter, with different effects of air superficial velocity and immersion rate on pressure drop in two-phase and three-phase sections. Both measured and calculated pressure drop values are in good agreement, especially under specific conditions.
Article
Automation & Control Systems
Kshema Shaju, Sherin Babu, Binu Thomas
Summary: This study analyzes the effectiveness of the application of grey theory in feature selection for daily dew point temperature and daily pan-evaporation estimation models. Comparisons and analyses are made between the feature subset identified by grey theory and subsets selected based on different Pearson correlation coefficient slabs. The results show that the models using grey theory-based feature selection demonstrated average or above-average performances.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Biochemistry & Molecular Biology
Linnea Hases, Ahmed Ibrahim, Xinsong Chen, Yanghong Liu, Johan Hartman, Cecilia Williams
Summary: The study reveals sex differences in the transcriptome of normal colon and CRC tissue, with some biomarkers showing sex-specific prognostic value. 20 sex-specific CRC prognostic biomarkers, including ESM1, GUCA2A, and VWA2 for males and CLDN1 and FUT1 for females, are proposed, which can help improve CRC survival rates.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Mathematics, Interdisciplinary Applications
Keming Gu, Zhengfu Ning, Zhongqi Mu, Fangtao Lv
Summary: A semi-analytical model based on fractal theory is proposed to estimate the relative permeabilities of brine-gas, simplifying porous media as treelike nanotubes and utilizing classic formulas to calculate pressure drops. By introducing Poiseuille's law and Darcy's law, relative permeability curves can be drawn to reveal comprehensive elements affecting wettability, fluid viscosity, saturation, and morphological characteristics.
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
(2021)
Article
Biochemical Research Methods
Pengfei Liang, Hao Wang, Yuchao Liang, Jian Zhou, Haicheng Li, Yongchun Zuo
Summary: Feature-scML is an effective toolkit for analyzing single-cell RNA omics datasets, automating the machine learning process, and customizing visual analysis of the results.
CURRENT BIOINFORMATICS
(2022)
Article
Automation & Control Systems
Victor Hamer, Pierre Dupont
Summary: Current feature selection methods, especially in high-dimensional data, may suffer from instability, but a new stability measure proposed in this work, which incorporates the importance of selected features in predictive models, has been shown to correct overly optimistic estimates and improve decision-making accuracy.
JOURNAL OF MACHINE LEARNING RESEARCH
(2021)
Article
Thermodynamics
Yusi Tian, Yonggang Jiao, Fei Han, Zuo Cheng, Jian Li
Summary: In this paper, the structure of the interrupted microchannel is improved by numerical simulation, and the two-phase characteristics of the new microchannel are quantified using gas-liquid flow ratios, relative standard deviations, and pressure drop fluctuations. The simulation results show that the widening design of the two side branches offsets the effect of inertia force and balances the flow resistance in the downstream branches. The gas flow relative standard deviation of the interrupted microchannel is significantly lower than that of the traditional microchannel at high void fraction.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2023)
Article
Engineering, Chemical
Donghyun Kim, Hwabhin Kwon, Geun-Ho Cho, Haeun Kim, Haeun Seo, Yeon-Gil Jung, Jiyeon Choi, Hanki Kim, Jungjoon Yoo, Dongsoo Lee, Insung Hwang, Ungyu Paik, Taeseup Song, Heesung Park, SeungCheol Yang
Summary: This study evaluated the performance and pumping power of the Flow-electrode capacitive mixing (F-CapMix) system, and found that both the gross power density and pumping power density increased as the flow channel narrowed. However, the net power density decreased due to the higher pumping power required.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Thermodynamics
Freddy Houndekindo, Taha B. M. J. Ouarda
Summary: This paper evaluates six feature selection methods for estimating different wind speed quantiles across Canada. The results show that LASSO and MRMR are the most efficient algorithms with few parameters to tune and good generalization performance. The study also finds that certain predictors are more important for specific exceedance probabilities, and distance from the coast and surface roughness length are the most important predictors regardless of exceedance probability.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Thermodynamics
Dong Ho Nguyen, Koung Moon Kim, Thi To Nguyen Vo, Gyu Hyeon Shim, Ji Hoon Kim, Ho Seon Ahn
Summary: In this study, electroless plating of nickel, copper, and silver was used on stainless steel 316 plate heat exchangers to enhance their thermal-hydraulic efficiency. Optimized process parameters were determined for improving surface properties and reducing mass loss, leading to a significant increase in performance as indicated by various evaluation criteria.
CASE STUDIES IN THERMAL ENGINEERING
(2021)
Article
Computer Science, Theory & Methods
Lu Zhou, Ye Zhu, Tianrui Zong, Yong Xiang
Summary: The paper proposes a DDoS attack flow classification system called SAFE, which accurately and quickly identifies attack flows in the network layer. The proposed method achieves better classification performance in terms of accuracy and efficiency compared to existing methods.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Thermodynamics
L. Marocco, M. Sala, G. Centurelli, S. Straub, L. Colombo
Summary: This study investigates the fully developed turbulent aided mixed convection of liquid metals with Prandtl number of 0.025 and 0.005 flowing vertically in a homogeneously heated pipe using Large Eddy Simulations. The results show that heat transfer reduction and recovery are mainly influenced by laminar and turbulent buoyancy terms, with a laminarization state observed at low Reynolds numbers. Comparisons with RANS simulations demonstrate qualitative agreement in reproducing the Nusselt number decrease and recovery at different Richardson numbers.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Thermodynamics
Luca Molinaroli, Andrea Lucchini, Luigi Pietro Maria Colombo
Summary: This paper discusses the experimental analysis results of using R450A and R513A as drop-in alternatives to R134a in a water-to-water heat pump. Compared to R134a, the use of R450A leads to a reduction in capacity and COP, while the use of R513A results in variations in heating capacity and COP. The paper also discusses the increase in rotational frequency of the compressor shaft to restore heating capacity.
INTERNATIONAL JOURNAL OF REFRIGERATION
(2022)
Article
Thermodynamics
Alessandro Morelli, Marco Tognoli, Antonio Ghidoni, Behzad Najafi, Fabio Rinaldi
Summary: This work proposes an optimized physical heat transfer correlation in smooth horizontal fire-tubes using a one-dimensional reduced Finite Volume Method. The correlation is validated over a wide range of operating conditions through experimental data and Computational Fluid Dynamics (CFD) simulations. The calibrated physical correlations provide accurate estimations of heat transfer and pressure drops with reduced computational cost.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Green & Sustainable Science & Technology
Marco Tognoli, Behzad Najafi, Andrea Lucchini, Luigi Pietro Maria Colombo, Fabio Rinaldi
Summary: The present study aims to estimate the fuel saving potential of a multi-setpoint control strategy for a fire-tube boiler with varying steam pressure demands. The case study focuses on the steam consumption profile of an Italian cheese factory. The results demonstrate a 4.5% reduction in yearly fuel consumption by employing the multi-setpoint strategy.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Engineering, Chemical
Stefano Passoni, Igor Matteo Carraretto, Riccardo Mereu, Luigi Pietro Maria Colombo
Summary: This study focuses on the numerical prediction of pressure gradient and void fraction in gas-liquid stratified flow, and investigates the influence of grid discretization and turbulence model on the simulation accuracy. The results show that different turbulence models are required depending on the gas velocity and flow regime. Compared with one-dimensional models, CFD simulations are more accurate in predicting the pressure gradient at gas superficial velocities lower than 1.3 m/s.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2023)
Article
Physics, Fluids & Plasmas
William Ferretto, Igor Matteo Carraretto, Andrea Tiozzo, Marco Montini, Luigi Pietro Maria Colombo
Summary: Water accumulation in gas pipelines is a major issue in flow assurance, and using surfactant injection for deliquification is a promising alternative. However, the behavior of foam pipe flow in the presence of other phases is not well understood. This study proposes a simulation approach using the OLGA tool to model air-water-foam flows in horizontal pipes. The simulation results show good agreement with experimental data, but there is an overestimation of pressure gradient and the mean absolute prediction error ranges from 5% to 30%.
Article
Energy & Fuels
Farzad Dadras Javan, Italo Aldo Campodonico Avendano, Behzad Najafi, Amin Moazami, Fabio Rinaldi
Summary: This paper presents a methodology for predicting reduced load in a warehouse while also providing flexibility. Physics-based energy simulations are conducted to model flexibility events involving controlled temperature increases. Machine learning algorithms are then used to predict subsequent energy consumption values, allowing time to participate in demand response programs or prepare for charging electric vehicles. The performance of different ML algorithms is compared, with a tree-based algorithm achieving superior accuracy.
Article
Construction & Building Technology
Farhang Raymand, Behzad Najafi, Alireza Haghighat Mamaghani, Amin Moazami, Fabio Rinaldi
Summary: Smart meter-driven remote auditing allows rapid identification of buildings with low energy performance. This study focuses on using ML-based pipelines to characterize buildings and optimize their performance using electrical and chilled-water consumption data. Results show that optimizing the pipelines improves model accuracy and interpretability, and adding features from chilled-water consumption data further enhances accuracy and reduces feature count.
ENERGY AND BUILDINGS
(2023)
Article
Construction & Building Technology
Italo Aldo Campodonico Avendano, Farzad Dadras Javan, Behzad Najafi, Amin Moazami, Fabio Rinaldi
Summary: The study focuses on evaluating the impact of baseline load prediction pipelines performance on the accuracy of flexibility estimation provided by different types of buildings. Different machine learning algorithms, along with sliding-window and offline training schemes, are investigated and compared for hour-ahead baseline load prediction. Using smart meter measurements, optimal pipeline and training window sizes are identified for each building type. Physical simulations are conducted to simulate the consumption profiles of five buildings, both in regular operation and when offering flexibility. The results demonstrate that the identified optimal prediction pipeline (Extra Trees algorithm with a sliding window of 5 weeks) outperforms offline training (average r2 score of 0.91 vs. 0.87). Using these pipelines allows for accurate estimation of offered flexibility, ensuring fair compensation from the grid operator.
ENERGY AND BUILDINGS
(2023)
Article
Mechanics
Riccardo Attilio Franchi, Igor Matteo Carraretto, Gregorio Chiarenza, Giorgio Sotgia, Luigi Pietro Maria Colombo
Summary: The methodology and results of an experimental campaign on characterizing the two-phase flow of an oil-water mixture in downward inclined pipes are described. The goal was to assess the effects of downslope on flow patterns, pressure gradients, and phase holdup. The experiments covered a range of oil and water superficial velocities. The transition from annular to stratified-wavy flow pattern occurred at lower oil velocities compared to the horizontal configuration. The measured frictional pressure gradients and phase holdups were compared to models and showed good agreement. The implementation of the drift-flux model confirmed its applicability and derived a relationship for oil holdup.
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW
(2023)
Article
Green & Sustainable Science & Technology
Marco Tognoli, Shayan Keyvanmajd, Behzad Najafi, Fabio Rinaldi
Summary: This paper proposes and implements a novel approach to simulate the dynamic behavior of hot-water fire-tube boilers, utilizing both physical phenomena-based and data-driven modeling methodologies. The first model employs a one-dimensional finite volume method to accurately size the unit based on end-users' dynamic consumption profile. On the other hand, the data-driven model uses machine learning algorithms to estimate hot water's supply temperature, making it suitable for real-time prediction and model predictive control. The developed models have been validated and shown to have limited estimation bias and acceptable accuracy for various prediction horizons.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2023)
Article
Engineering, Chemical
Andrea Coletto, Pietro Poesio
Summary: Experiments and simulations were conducted to study the air volume fraction and hold-up in a bubble channel reactor. A new signal processing method was proposed to avoid the loss of bubble residence time. The results were in agreement with previous studies and a bubble-scale model was developed to explain the relationship between hold-up and air superficial velocity.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2024)