Model Calculations Research Articles

A method to calculate the two-phase distribution in a microchannel heat exchanger

Maldistribution seriously impacts the heat transfer performance of the microchannel heat exchanger (MCHX). Fully understanding the two-phase distribution in the heat exchanger is important for advancing academic research and engineering applications. This study introduces a novel method for quantifying two-phase distribution in a microchannel heat exchanger. An experimental setup was developed to measure the local vapor mass fraction in the heat exchanger header. Capacitance signals were measured under inlet vapor mass fractions from 0 to 1, and inlet flow rates of 10, 15, and 25 g s−1 corresponding to a mass flux of 17.47, 26.2, and 43.66 kg m−2s−1, respectively. The local vapor mass fraction in the header was estimated using the capacitance measurements. The mass flow rate in the header, the microchannel tube, and the vapor mass fraction in the tube were calculated using the proposed model. The calculation model was validated against literature data, and the results were analyzed. The analysis reveals the characteristics of vapor mass fraction and mass flow rate distribution in the MCHX and further elaborates on the effects of phase separation, entrainment ratio, and pressure drop balance on the distribution. The proposed method can evaluate distribution in the header and tubes of microchannel heat exchangers, and it is also applicable to other types of two-phase flow devices.

Graph-Based Unsupervised Feature Selection for Interval-Valued Information System.

Feature selection has become one of the hot research topics in the era of big data. At the same time, as an extension of single-valued data, interval-valued data with its inherent uncertainty tend to be more applicable than single-valued data in some fields for characterizing inaccurate and ambiguous information, such as medical test results and qualified product indicators. However, there are relatively few studies on unsupervised attribute reduction for interval-valued information systems (IVISs), and it remains to be studied how to effectively control the dramatic increase of time cost in feature selection of large sample datasets. For these reasons, we propose a feature selection method for IVISs based on graph theory. Then, the model complexity could be greatly reduced after we utilize the properties of the matrix power series to optimize the calculation of the original model. Our approach can be divided into two steps. The first is feature ranking with the principles of relevance and nonredundancy, and the second is selecting top-ranked attributes when the number of features to keep is fixed as a priori. In this article, experiments are performed on 14 public datasets and the corresponding seven comparative algorithms. The results of the experiments verify that our algorithm is effective and efficient for feature selection in IVISs.

Synergetic Experimental and Theoretical Investigation of Molecular Structure – Optical Properties Relationships of Anthrazoline-Based Polymeric Chains

The photoluminescence and UV-Vis absorption spectra of copolyamides containing 1,9-anthrazoline with para- and meta-[(substituted carbonyl)amino]phenyl-1-ene moieties in a polymer backbone were studied by a combination of experimental and theoretical approaches. The investigation was accomplished through time-dependent density functional theory electronic structure calculations of small-molecule models mimicking a polymer chain. Theoretical absorption and luminescence spectra of ten atomistic models were compared with corresponding experimental data, and the optical properties of two new luminescent molecules with bromine auxochrome were predicted. An analysis of the optical properties demonstrate an identical effect of the type and position of a substituent on the spectra for para- and meta-[(substituted carbonyl)amino]phenyl-1-ene moieties. It was found that the absorption and luminescence spectra of theoretical para-models demonstrate red shifts relative to the corresponding meta- ones. The same phenomenon was observed in experimental spectra of low-molecular-mass compounds and corresponding copolyamides in solution and bulk. Unique optical properties allow anthrazoline-based polymer compounds to be used in numerous advanced optoelectronic applications with desired optical and electronic characteristics.

Predictive Model of variable laboratory findings calculation and monitoring during plasmapheresis procedures

Predictive Model of variable laboratory findings calculation and monitoring during plasmapheresis procedures

Web apps for profile fitting and power balance analysis at Wendelstein 7-X.

Two novel web apps for W7-X are introduced: Profile Cooker and Power House. They are designed to streamline the workflow of profile fitting and power balance analysis while offering a graphical user interface that works in any common browser. This allows us to compile a comprehensive database of experimental power balance results. All fitting functions available in Profile Cooker are presented and compared on the basis of example profiles. The power balance equation assumed in Power House is established and its individual terms are discussed. The main focus of the power balance analysis is on the turbulent transport coefficients. A model for quick calculation of neutral beam power deposition based on experimental profiles is presented. Neoclassical root transition poses an issue for power balance analysis due to the uncertainty of the radial electric field. A global, neoclassical simulation with the code EUTERPE is performed for a set of experimental profiles to gain an understanding of the neoclassical root transition.

Exploring the long-term variations and high concentration episodes of peroxyacetyl nitrate in Megacity Seoul

Over the past few years, peroxyacetyl nitrate (PAN) has drawn significant attention as a key indicator of photochemical pollution owing to its intimate relationship with ozone and associated health effects. This study presents measurements conducted at the Korea University campus in Seoul during the high-ozone seasons from 2018 to 2021. PAN concentration was measured using fast gas chromatography with luminol chemiluminescence detection (GC-LCD), alongside measurements of O3, volatile organic compounds (VOCs), NO, NO2, and meteorological variables, including boundary layer height (BLH).The mean concentrations of PAN and O3 over the years were 0.56 ppbv and 35 ppbv in 2018, 1.29 ppbv and 58 ppbv in 2019, 0.21 ppbv and 50 ppbv 2020, and 0.53 ppbv and 46 ppbv in 2021, respectively. The annual variation observed in Seoul is consistent with trends seen in major cities worldwide during the COVID19 pandemic, reflecting a substantial reduction in urban emissions. Indeed, the mean concentration of NOx and VOCs decreased significantly by more than 50 % and 25%, respectively, from 2019 to 2021.At temperatures above 30°C, PAN decomposition was accelerated, decoupling a consistent positive relationship between PAN and O3 in 2020 and 2021. The results of a 0-D photochemical model (F0AM) calculation demonstrated that PAN formation primarily stems from anthropogenic VOCs, particularly >C2 alkenes. Elevated PAN concentrations during nighttime were attributed to boundary layer expansion and upper-air entrainment. Instances where PAN concentrations surged to at least 3 ppbv or higher in 2019 were attributed to biomass burning impacted air, as evidenced by concurrent elevations in K+ and OC in PM2.5, and O3.This study underscores the complex interplay of factors influencing PAN and ozone enhancements under decreased precursor levels, with an emphasis on dynamic change in the boundary layer, and long-distance transport of non-fossil sources during agricultural burning seasons.

A Deep Learning Framework for IoT Lightweight Traffic Multi-classification: Smart-cities

Aim and Background: Increased traffic volume is a major challenge for effective network management in the wake of the proliferation of mobile computing and the Internet of Things (IoT). Earlier models surrender efficiency to achieve high-precision classification outcomes, which are no longer fitting for limited assets in edge network circumstances, making traffic classification a difficult task for network administrators everywhere. Given the nature of the problem, the current state of the art in traffic classification is characterized by extremely high computational complexity and large parameters. Methodology: To strike a clever balance between performance and size, we present a deep learning (DL)-based traffic classification model. We begin by decreasing the amount of model parameters and calculations by modifying the model's scale, width, and resolution. To further improve the capability of feature extraction at the traffic flow level, we secondly incorporate accurate geographical information on the attention mechanism. Thirdly, we get multiscale flow-level features by employing lightweight multiscale feature fusion. Results: The results of our experiments demonstrate that our model has high classification accuracy and efficient operation. Our study presents a traffic categorization model with an accuracy of over 99.82%, a parameter reduction of 0.26M, and a computation reduction of 5.26M. Conclusions: Therefore, this work offers a practical design used in a genuine IoT situation, where IoT traffic and tools' profiles are anticipated and classified while easing the data dispensation in the higher levels of an end-to-end communication strategy.

Melting temperature of iron under the Earth’s inner core condition from deep machine learning

Constraining the melting temperature of iron under Earth’s inner core conditions is crucial for understanding core dynamics and planetary evolution. Here, we develop a deep potential (DP) model for iron that explicitly incorporates electronic entropy contributions governing thermodynamics under Earth’s core conditions. Extensive benchmarking demonstrates the DP’s high fidelity across relevant iron phases and extreme pressure and temperature conditions. Through thermodynamic integration and direct solid–liquid coexistence simulations, the DP predicts melting temperatures for iron at the inner core boundary, consistent with previous ab initio results. This resolves the previous discrepancy of iron’s melting temperature at ICB between the DP model and ab initio calculation and suggests the crucial contribution of electronic entropy. Our work provides insights into machine learning melting behavior of iron under core conditions and provides the basis for future development of binary or ternary DP models for iron and other elements in the core.

Low-cost dealkalization of bauxite residue by gypsum coordinated with industrial iron salt: Mineralogical mechanisms and field practice

The sustained-release of alkalinity in bauxite residue hinders the soil formation and ecological restoration processes in disposal areas. Ferric salts (Fe3+), known for their rapid neutralization reaction process and straightforward operational simplicity, showed a synergistic advantage with gypsum (CaSO4) in the alkaline regulation of bauxite residue. Nevertheless, the mineralogical mechanisms of the reaction between Fe3+ and Ca2+ and alkaline minerals in bauxite residue remained unclear. The present study aimed to elucidate the geochemical stability mechanisms of sodalite and cancrinite, major alkaline minerals in bauxite residue, driven by Fe3+ and Ca2+ from a mineral structural perspective and the integrated restoration effect was demonstrated by the field experiment. Unreacted shrinking core model (USCM) calculations demonstrated that Fe3+ was able to enter the lattice structure of sodalite and cancrinite to replace Na+ and assisted Ca2+ in successfully replacing Na+ in cancrinite. Moreover, Fe3+ and Ca2+ facilitated the formation of insoluble coating layers on their surface. In the lattice structure of sodalite and cancrinite, the replacement reaction for Na+ was influenced by the competition between Fe3+ and Ca2+. The Ca2+ preferentially replaced Na+, while Fe3+ accumulated near the Si-O bonds, balancing the negative charges of the Si-O and Al-O tetrahedra structure and further inhibited alkaline mineral dissolution. The pH and EC of bauxite residue decreased from 10.52 to 7.60 and 712 μS/cm to 501 μS/cm, respectively, after a one-year field-scale amelioration by the integration of Fe3+ and Ca2+. These findings highlighted the synergistic roles of Fe3+ and Ca2+ in regulating the alkalinity of bauxite residue and provided a practical strategy for ecological restoration in disposal areas.

Determination of Chip Compression Ratio for the Orthogonal Cutting Process

The chip compression ratio is the most important characteristic of various machining processes with chip generation. This characteristic enables the determination of kinetic and other energy loads on the tool and the machined material. This provides an overall evaluation of the machining process and the possibility of its subsequent optimization. This paper presents the results of determining this cutting characteristic by experimental method, analytical calculation, and numerical modeling. For the analytical calculation of the chip compression ratio, an analytical cutting model developed based on the variational principle of the minimum potential energy was used. A finite element model of orthogonal cutting was used for the numerical simulation of the above process characteristic. Experimentally, the chip compression ratio was determined by the ratio of the chip thickness to the cutting depth (undeformed cutting thickness). The chip thickness was determined by direct measurement using chip slices obtained during the cutting process. The Johnson–Cook constitutive equation was used as the machined material model and the Coulomb model was used as the friction model. The generalized parameters’ determination of the constitutive equation was performed through a DOE (Design of Experiment) sensitivity analysis. The variation range of these parameters was chosen based on the analysis of the effect of individual parameters of the constitutive equation on the chip compression ratio value. The largest deviations between the experimental and analytically calculated values of the chip compression ratio did not exceed 21%. At the same time, the largest deviations of simulated values of the indicated cutting characteristic and its experimental values did not exceed 20%. When comparing the experimental values of the chip compression ratio with the corresponding calculated and simulated values, the deviations were within 22%.

An ionic liquid crystal functionalized nanocellulose lubricant additives

Cellulose, one of nature's most abundant, clean, and sustainable resources, has often shown unsatisfactory results when used as bio-lubricant additives. Herein, nanocellulose (NC) from amorphous waste natural poplar was extracted using deep eutectic solvent encapsulation treatment and chlorine bleaching process. Subsequently, 1-hexadecyl-3-methylimidazolium bromide was integrated onto NC using a one-step hydrothermal treatment (high-temperature and high-pressure environment) to obtain ionic liquid crystal (ILC) functionalized products (named as ILC-NC). After ball-milling process and solid phase separation step, ILC-NC exhibits excellent dispersion stability and lubrication properties in the liquid phase (including water and vegetable oil). Based on the polar and colloidal activity properties of ILC, it can form an ordered molecular layer on NC surface and form a lubricating film-like structure, making NC smoother and sliding well. Compared to ILC/NC aqueous dispersion, ILC-NC reduces the coefficient of friction and wear rate on steel disk surface by 68.75 % and 74.07 %, respectively. The minimum coefficient of friction was further reduced to 0.032 as dispersing ILC-NC in sunflower oil, showing a reduction of 0.134 (77.91 %) compared to pure sunflower oil. Finally, the lubrication theoretical model calculation reveals the lubrication state of ILC-NC on the steel disk surface and proposes the lubrication mechanism.

Oceanic and Sedimentary Microbial Sulfur Cycling Controlled by Local Organic Matter Flux During the Ediacaran Shuram Excursion in the Three Gorges Area, South China.

The increased difference in the sulfur isotopic compositions of sedimentary sulfate (carbonate-associated sulfate: CAS) and sulfide (chromium-reducible sulfur: CRS) during the Ediacaran Shuram excursion is attributed to increased oceanic sulfate concentration in association with the oxidation of the global ocean and atmosphere. However, recent studies on the isotopic composition of pyrites have revealed that CRS in sediments has diverse origins of pyrites. These pyrites are formed either in the water column/shallow sediments, where the system is open with respect to sulfate, or in deep sediments, where the system is closed with respect to sulfate. The δ34S value of sulfate in the open system is equal to that of seawater; on the contrary, the δ34S value of sulfate in the closed system is higher than that of seawater. Therefore, obtaining the isotopic composition of pyrites formed in an open system, which most likely retain microbial sulfur isotope fractionation, is essential to reconstruct the paleo-oceanic sulfur cycle. In this study, we carried out multiple sulfur isotope analyses of CRS and mechanically separated pyrite grains (>100 μm) using a fluorination method, in addition to secondary ion mass spectrometry (SIMS) analyses of insitu δ34S values of pyrite grains in drill core samples of Member 3 of the Ediacaran Doushantuo Formation in the Three Gorges area, South China. The isotope fractionation of microbial sulfate reduction (MSR) in the limestone layers of the upper part of Member 3 was calculated to be 34ε = 55.7‰ and 33λ = 0.5129 from the δ34S and Δ33S' values of medium-sized pyrite grains ranging from 100 to 300 μm and the average δ34S and Δ33S' values of CAS. Model calculations revealed that the influence of sulfur disproportionation on the δ34S values of these medium-sized pyrite grains was insignificant. In contrast, within the dolostone layers of the middle part of Member 3, isotope fractionation was determined to be 34ε = 47.5‰. The 34ε value in the middle part of Member 3 was calculated from the average δ34S values of the rim of medium-sized pyrite grains and the average δ34S values of CAS. This observation revealed an increase in microbial sulfur isotope fractionation during the Shuram excursion at the drill core site. Furthermore, our investigation revealed correlations between δ34SCRS values and CRS concentrations and between CRS and TOC concentrations, implying that organic matter load to sediments controlled the δ34SCRS values rather than oceanic sulfate concentrations. However, these CRS and TOC concentrations are local parameters that can change only at the kilometer scale with local redox conditions and the intensity of primary production. Therefore, the decreasing δ34SCRS values likely resulted from local redox conditions and not from a global increase in the oceanic sulfate concentration.

An Overlooked Component of the Meridional Overturning Circulation

Abstract Upwelling along the western boundary of the major ocean basin subtropical gyres has been diagnosed in a wide range of ocean models and state estimates. This vertical transport is O(5 × 106) m3 s−1, which is on the same order of magnitude as the downward Ekman pumping across the subtropical gyres and zonally integrated meridional overturning circulation. Two approaches are used here to understand the reason for this upwelling and how it depends on oceanic parameters. First, a kinematic model that imposes a density gradient along the western boundary demonstrates that there must be upwelling with a maximum vertical transport at middepths in order to maintain geostrophic balance in the western boundary current. The second approach considers the vorticity budget near the western boundary in an idealized primitive equation model of the wind- and buoyancy-forced subtropical and subpolar gyres. It is shown that a pressure gradient along the western boundary results in bottom pressure torque that injects vorticity into the fluid. This is balanced on the boundary by lateral viscous fluxes that redistribute this vorticity across the boundary current. The viscous fluxes in the interior are balanced primarily by the vertical stretching of planetary vorticity, giving rise to upwelling within the boundary current. This process is found to be nearly adiabatic. Nonlinear terms and advection of planetary vorticity are also important locally but are not the ultimate drivers of the upwelling. Additional numerical model calculations demonstrate that the upwelling is a nonlocal consequence of buoyancy loss at high latitudes and thus represents an integral component of the meridional overturning circulation in depth space but not in density space. Significance Statement The purpose of this study is to better understand what is forcing water to upwell along the western boundary at midlatitudes of the major ocean basins. This is a potentially important process since upwelling can bring heat and nutrients closer to the surface, where they can be exchanged with the atmosphere. Also, since ocean currents vary with depth, pathways followed in the upper ocean are different from those found for the deeper ocean, so the amount and location of upwelling influence where these waters go. Idealized numerical models and theory are used to demonstrate that the upwelling is ultimately driven by density changes along the western boundary of the basin that result from heat loss at high latitudes.

Temperature field analysis in tunnel construction ventilation with emphasis on duct leakage and thermal conductivity

Mechanical ventilation is the primary measure for cooling during construction of high geo-temperature tunnel. Based on heat transfer theory and characteristics of press-in ventilation, a comprehensive calculation model considering the influence of construction process is proposed, and the reliability of the model is verified by on-site test. The effects of duct leakage rate and thermal conductivity of different excavation length on temperature field distribution during construction ventilation were analyzed based on the prediction model. The following conclusions are drawn: As the excavation length increases, the duct outlet temperature first increases and then decreases. The duct outlet temperature is mainly affected by geo-temperature and boundary control temperature of working face, the air leakage rate and excavation length are not the main factors. The highest temperature in the duct is about 40 °C. The distance between the position of highest temperature and working face increases with the increase of excavation length and decreases with the increase of air leakage rate. With the increase of excavation length, the impact of thermal conductivity on outlet temperature of duct is first enhanced and then stabilized under the same excavation length. The heat-insulated duct can effectively reduce the outlet air temperature and prolong the service life of the duct, while minimizing the air leakage of the duct.

Evolution of tooth surface morphology and tribological properties of helical gears during mixed lubrication sliding wear

In mixed lubrication, the interplay of lubricant flows, solid asperity contact, and material wear between tooth surfaces creates complex and unpredictable contact states on tooth surface. To comprehensively understand the interaction between the lubrication and wear characteristics of the rough tooth surfaces of helical gears, this study established a mixed lubrication sliding wear calculation model for helical gears based on the mixed elastohydrodynamic lubrication model and Archard’s model. Specifically, the study aimed to examine the effects of surface topography features on average film thickness, contact area ratio, and accumulated wear at the meshing point. The findings demonstrated that the texture and power spectral density distributions of a non-Gaussian reconstructed surface closely resembled those of the actual ground surface. Furthermore, for non-Gaussian rough surfaces, a larger wavelength ratio enhanced microwedge motion, which increased film thickness and reduced wear. Additionally, a negatively skewed surface demonstrated better lubrication performance compared to both positively skewed and Gaussian surfaces. This improved performance is evident in the smaller contact area ratio and lower accumulated wear value of the negatively skewed surface.

Numerical investigation of photovoltaic performance improvement using Al2O3 nanofluid

To further elucidate the impact of fluctuations in environmental temperature and radiation intensity within a day on the temperature and performance of photovoltaic systems with and without nanofluid cooling, this study established a photovoltaic panel temperature and efficiency calculation model based on a nanofluid cooling system that considers the dynamic changes of photovoltaic panel temperature and air temperature over time. An empirical formula for predicting photovoltaic panel efficiency has been derived based on experimental data. Then a PV panel temperature and efficiency calculation model is established and validated. The simulation results show that using nanofluids to cool the PV panel can significantly reduce the temperature and improve the PV efficiency. Compared to the bare PV panel, the average PV panel temperature decreases by 7.99℃, 8.48℃, and 8.92℃ respectively when nanofluid volume fraction is 1 vol.%, 3 vol.%, and 5 vol.%, and it decreases by 8.48℃, 9.27℃, and 9.94℃ respectively when nanofluid mass flow rate is 0.08 m3/h, 0.10 m3/h, and 0.12 m3/h. As the nanofluids' concentration increases, nanofluids' cooling ability in the high temperature range also increases.

Investigation on the multi-scale interactions in gas–liquid jet bubbling reactor

Due to the unreliability of the mechanical seal of the mechanical stirring reactor in traditional carbonyl synthesis reactions, a gas–liquid jet bubbling reactor has been developed that is a new type of hydraulic stirring. A cold model device was constructed to address the complex flow field characteristics of a gas–liquid jet bubbling reactor, and a gas–liquid phase testing method was established to obtain the gas–liquid phase flow parameters in the cold model device. A mathematical model of a cold model device was established based on computational fluid dynamics. The reliability and accuracy of the calculation model were verified by combining experimental data of the cold model device, and the gas–liquid two-phase flow characteristics of an industrial grade reactor were obtained. The multiscale characteristics of gas–liquid two-phase signals in industrial reactors and the multiscale gas–liquid two-phase interactions were analyzed by combining wavelet analysis, power spectrum analysis, and fractal analysis. Based on the multiscale gas–liquid interaction mechanism model of gas–liquid interaction, the liquid phase interaction in d1-d6 inside the reactor was increased. The gas–liquid mass transfer process was enhanced, and the liquid level fluctuation and temperature difference of industrial grade reactors were significantly reduced.

A novel calculation model for friction and torque of tubular string in horizontal well

A novel calculation model for friction and torque of tubular string in horizontal well

Study on creep performance of shotcrete lining for tunnels

Creep, as a long-term deformation characteristic of shotcrete, significantly influences the load-bearing performance and durability of tunnel support structures. This study conducted creep tests on shotcrete under varying stress levels. The results reveal that shotcrete exhibits linear creep response within the stress range of 30% to 40%, while the critical stress range for nonlinear creep response occurs between 40% and 50%. Employing SEM-EDS and XRD analysis methods, the impact of accelerator on the microstructure evolution and creep mechanism of shotcrete is explored. The accelerator accelerates the hydration of C3S, promoting the generation of AFt and C-S-H gel, leading to rapid solidification of the matrix and enhanced early strength. With the consumption of SO42- ions, AFt gradually transforms into AFm, resulting in increased matrix porosity. This phenomenon contributes to the reduced later-stage strength and substantial creep deformation of shotcrete. Based on experimental outcomes, this study evaluates the applicability of existing creep calculation models to shotcrete.

Life cycle carbon emission assessment and carbon payback period analysis for the regeneration of old residential areas in cold regions: Case study in Qingdao, China

Communities urgently need to explore green and low-carbon transformation pathways due to high energy consumption and carbon emissions. However, existing studies lack a comprehensive assessment of carbon emissions and analysis regarding carbon reduction during renovation of old residential areas in cold regions. Therefore, this study employs a Life Cycle Assessment (LCA) and the payback period method to evaluate carbon emissions throughout the life cycle comprehensively. It constructs a carbon-emission calculation model based on LCA, specifically tailored to the retrofitting of old residential areas in cold cities. Additionally, it investigates the effectiveness of three typical retrofit measures undertaken in Qingdao, a region located in the cold A zone, focusing on whole-life-cycle energy savings and carbon reduction. The findings reveal that the average annual carbon emission intensity per unit area for Cases 1, 2, and 3 is 12.59 kg-CO2 e/(m2·a), 27.05 kg-CO2 e/(m2·a), and 23.39 kg-CO2 e/(m2·a), respectively. Their corresponding carbon payback periods were 6.06, 7.23, and 16.00 years, respectively, which could be further shortened through material recycling. The environmental impact assessment of typical retrofitting measures contributes to the promotion of sustainable development. Furthermore, this study offers guidance for establishing an effective assessment system that supports the design of energy-saving retrofits.