Empirical Correlations Research Articles

A new empirical correlation of MMP prediction for oil – impure CO2 systems

CO2 flooding is a widely-used technique for enhancing oil production, with miscible CO2 flooding exhibiting higher recovery potential compared to both immiscible and near-miscible CO2 flooding. However, the problem of insufficient CO2 supply is increasingly critical in many reservoirs. When faced with a shortage of gas supply, the key to the successful implementation of miscible CO2 flooding lies in accurately predicting the MMP of impure CO2. This study leverages MMP data derived from both experimental and simulation results, utilizing both linear and nonlinear regression methodologies to formulate empirical correlations for MMP prediction. In addition, ridge regression is used to solve collinearity problem.Compared with former investigations, the impure CO2 correlation proposed in this study integrates the ratio of the specific injection gas mole fraction to the crude oil mole fraction as novel independent variables. This inclusion reflects the actual interaction between the specific injection gas and crude oil during the miscibility process. Furthermore, the correlation can be linearized to the greatest extent through this way and such linearization illustrates the fundamental concepts more distinctly, offering a more practical and comprehensible approach. This formula combines the prediction of the minimum miscible pressure with the interaction mechanism of the miscible process, and the dominant factors in the miscible process can be determined. In terms of reducing the minimum miscible pressure, the interaction between C4 + C5 in the injected gas and C1 + N2 in the crude oil component is the strongest, while the interaction between N2 in the injected gas and C2-6 in the crude oil was most significant in increasing the minimum miscible pressure by comparison.The correlations presented for impure CO2 yield an average absolute deviation of 2.18 % and sustain a relative deviation within ± 10 %, surpassing previously published correlations. This study highlights the accuracy and effectiveness of the developed correlations for estimating MMP for impure CO2. The suggested MMP correlation offers a practical and efficient means of determining MMP for the implementation of impure CO2 miscible flooding in the field.

CFD investigation on start-up transient of HPR1000 secondary side passive residual heat removal heat exchanger

In advanced pressurized water reactor HPR1000, the secondary side passive residual heat removal heat exchanger (SPRS HX) is a crucial component. It removes the decay heat using boiling and convection heat transfer in the event of accidents. The robust functioning of the SPRS HX significantly influences overall reactor safety. To investigate the thermal hydraulic attributes of SPRS HX, computational fluid dynamics (CFD) is used in this study. The tube region is simulated using the porous media method (PMM). To model the two-phase flow in the tank, the drift flux model (DFM) is employed. The assessment of heat transfer rate from the primary to the secondary sides is conducted by empirical correlations. The governing equations are addressed through the utilization of FLUENT. Specifically, the momentum and energy equations are augmented with additional source terms that account for flow resistance and heat transfer in the tube region. These modifications are enacted through User Defined Functions (UDF). Three-dimensional profiles of the void fraction, fluid temperature and velocity are acquired, allowing for a comprehensive analysis of the heat transfer attributes of tube region.

Empirical Modeling of High-Performance Self-Compacting Concrete with Induction-Furnace Slag

Abstract This study led to the creation of empirical models of the properties of high-performance self-compacting concrete (HPSCC) with inductionfurnace slag (IFS) added as an extra cementitious ingredient. The ingredients were Portland cement, IFS ranging from 0 to 50% by cement weight, granite, river sand, water, and superplasticizer. Using a slump flow test, the filling-ability property of the newly produced HPSCC was investigated. Similarly, a compressive strength test was used to determine the hardened HPSCC's compressive strength. Using already established scientific ideas, the empirical model of the filling-ability characteristic of the fresh HPSCC was generated, on the basis of the slump flow and the volume of the paste of the fresh concrete. Likewise, the empirical model of the compressive strength of the hardened HPSCC was generated, based on the combination of the parameters of the strength developed over time, with the strength developed, due to the addition of the IFS. Based on these, the empirical model of the fillingability property of the fresh HPSCC was ρ r s f 2 = 0.002 ( 1 - V P ) - 11.34 {{{\rho _r}} \over {{s_f}^2}} = 0.002{\left( {1 - {V_P}} \right)^{ - 11.34}} , while that of the compressive strength of the hardened HPSCC was f c ( t ) = t 4.52 + 0.78 t ( − 0.0109 ( P i f s ) 2 + 0.2632 P i f s + 52.446 ) {f_c}\left( t \right) = {t \over {4.52 + 0.78t}}\left( { - 0.0109{{\left( {{P_{ifs}}} \right)}^2} + 0.2632{P_{ifs}} + 52.446} \right) . The empirical models were then validated using test data from this work. Strong links between the measured and the predicted values were identified by the empirical correlations, where the coefficient of determination (R2) value for the filling ability property, gave above 94% and the R2 value for the compressive strength, gave above 86%. The estimated slump flow and the compressive strength were approximately equal to the experimental values. The outcomes demonstrated that IFS may be utilized to produce an eco-friendly and environmentally sustainable HPSCC. The models can be adopted in designing HPSCC containing IFS as a supplementary cementitious material (SCM) and in predicting its filling-ability and compressive strength, which will benefit the construction industry.

Empirical correlations between ground motion intensity measures from the NGA‐West2 database and their use in vector generalized conditional intensity measures

AbstractThis paper examines the empirical correlations between 14 intensity measures (IMs) describing the frequency content, amplitude, cumulative effects, and duration aspects of ground motion based on the NGA‐West2 database. The correlation results in this paper are compared with the results of previous models based on the NGA‐West1 database, and the previous correlation coefficient models are updated and extended. The comparison results show that the trend of the correlation coefficients of the model established in this paper is essentially consistent with previous models based on the NGA‐West1 database, with most correlation coefficients observed in this paper being slightly lower than in previous studies. In addition, this paper extends the generalized conditional intensity measure (GCIM) ground motion selection method so that it can consider multiple conditional IMs (VGCIM), and gives full theoretical details. The differences between the theories of VGCIM and GCIM are discussed, and several possible application scenarios of VGCIM are illustrated. An example application of VGCIM is shown, and the results show that there are deviations between the target IMs conditional distribution constructed after considering multiple conditional IMs and considering one IM that is sufficient to make an impact in the ground motion selection. Finally, the effect of the correlation coefficient model on the IMs conditional distributions generated based on GCIM and VGCIM is discussed.

Modeling the liquid-liquid chromatography separation ofcannabinoids from hemp extracts.

The separation of cannabinoids from hemp materials is nowadays one of the most promising industrial applications of liquid-liquid chromatography (LLC). Despite various experimental research efforts to purify cannabinoids, there are currently few works on process modeling. Thus, this study aimed to explore a straightforward approach to model the LLC separation of cannabinoids from two hemp extracts with different compositions. The feed materials were simplified to mixtures of preselected key components (i.e., cannabidiol, tetrahydrocannabinol, cannabigerol, and cannabinol). The elution profiles of cannabinoids were simulated using the equilibrium-cell model with an empirical nonlinear correlation. The model parameters were derived from the elution profiles of single-solute pulse injections. For the validation of the proposed approach, LLC separations with the two hemp extracts were performed in descending mode with the solvent system composed of hexane/methanol/water 10/8/2 (v/v/v). The injected sample concentrations were gradually increased from 5 to 100mg/mL. The results showed that the approach could describe reasonably well the elution behavior of the cannabinoids, with deviations of only 1-2min between simulated and experimental elution times. However, to improve the prediction accuracy, the model parameters can be refitted to the elution profiles of 3-4 systematically selected pulse injections with specific hemp extracts.

Mechanism investigation and model assessment of methane flow condensation in minichannels based on numerical simulation

Cryogenic refrigerants represented by methane differ significantly in thermophysical properties from working fluids at ambient temperature. Thus, examining their small-scale heat transfer and flow characteristics is essential for designing compact condensers within the cryogenic field. The numerical simulation of methane condensation in minichannels is conducted, and the process of phase-change mass and energy transfer is investigated by programming. Detailed condensation flow field information is obtained, and surface tension and gravity influences are elucidated. Synergy analysis indicates that the synergy near the tube wall still needs to be improved. Heat transfer performance is proved to be dependent on the relative significance of turbulence intensity and condensate film thickness. The tube inclination exerts a more noticeable influence on the condensation heat transfer for large diameters, which is supported by the dominance of gravity in the condensation heat transfer mechanism at larger diameters. At higher vapor quality and mass flux, the heat transfer enhancement governed by surface tension is more significant. The condensate at the bottom is mainly formed by the accumulation of condensate sliding off the tube top driven by gravity as the diameter increases, reducing the heat transfer region. The mass flux augments the frictional pressure drop more noticeably at high vapor quality. The prediction performance of empirical correlations is evaluated, and all the selected correlations underestimate the frictional pressure drop of methane. Moreover, the figure of merit analysis demonstrates that the pressure drop produced by diameter reduction is more substantial than heat transfer enhancement, suggesting the requirement to assess the pressure drop loss in practical applications.

Effect of elevated crossflow temperature on jet primary atomization

Liquid jet in hot gas crossflow is widely employed in industrial combustion devices, especially in the propulsion systems. In this work, the effect of elevated crossflow temperature on the primary atomization of a liquid jet is experimentally investigated, including breakup regime, surface wavelength, column breakup height, and near-field trajectory. The experiments are conducted at crossflow temperatures of 300 K and 500 K, with gas Weber number ranging from 8.82 to 67.55 and momentum flux ratio from 10 to 50. The gas Weber number and momentum flux ratio are kept constant via increasing the crossflow velocity when crossflow temperature increases. The results show that the elevated crossflow temperature weakens surface breakup, particularly at high momentum flux ratios, which makes the transition of breakup regime from column breakup to surface breakup require higher gas Weber number or momentum flux ratio. Besides, the elevated crossflow temperature leads to a slight increase in surface wavelength, column breakup height and near-field trajectory, with the increase in trajectory being more pronounced at lower gas Weber numbers. Finally, an empirical correlation for the near-field trajectory is obtained, including the effects of crossflow temperature, gas Weber number, and momentum flux ratio.

Influence of radiation modelling in under-resolved FDS free-burn simulations

Focusing on the impact of radiation modelling in under-resolved fire simulations, the paper presents LES of free-burn scenarios. The work aims to evaluate the performance of the current fire modelling capabilities of the Fire Dynamics Simulator (FDS) code and to identify the best practices for FDS practitioners in terms of simulating radiative heat transfer. To this purpose, both optically thin and optically thick approaches are considered and their predictive capabilities over different grid sizes is evaluated. The impact of various radiation modelling parameters with the optically thick approach (i.e., path length, number of solid angles) is also considered. Comparisons of the predicted centreline flame temperatures and axial velocities as well as of the predicted radiative heat fluxes at different locations are presented. Overall, there were obvious differences between the two approaches with the optically thin being more accurate when compared to both experimental data and empirical correlations available in the literature.

A neural based modeling approach for predicting effective thermal conductivity of brewer’s spent grain

PurposeBrewer's spent grain (BSG) is the main by-product of the brewing industry, holding significant potential for biomass applications. The purpose of this paper was to determine the effective thermal conductivity (keff) of BSG and to develop an Artificial Neural Network (ANN) to predict keff, since this property is fundamental in the design and optimization of the thermochemical conversion processes toward the feasibility of bioenergy production.Design/methodology/approachThe experimental determination of keff as a function of BSG particle diameter and heating rate was performed using the line heat source method. The resulting values were used as a database for training the ANN and testing five multiple linear regression models to predict keff under different conditions.FindingsExperimental values of keff were in the range of 0.090–0.127 W m−1 K−1, typical for biomasses. The results showed that the reduction of the BSG particle diameter increases keff, and that the increase in the heating rate does not statistically affect this property. The developed neural model presented superior performance to the multiple linear regression models, accurately predicting the experimental values and new patterns not addressed in the training procedure.Originality/valueThe empirical correlations and the developed ANN can be utilized in future work. This research conducted a discussion on the practical implications of the results for biomass valorization. This subject is very scarce in the literature, and no studies related to keff of BSG were found.

An analysis of parameters affecting ampacity in aircraft bipolar MVDC power cables via coupled electrical, thermal, and computational fluid dynamic modelling

AbstractThe next generation of aircraft, including more electric aircraft and all‐electric aircraft, require electric power systems with high power density and low system mass specifications. Increasing the voltage of the system to the range of a few kV, medium voltage (MV), is a reasonable approach to achieving high‐power‐density and low‐system‐mass EPSs for aircraft applications. Higher voltages, however, pose many challenges for aviation MV power cables such as arcs and arc tracking, partial discharges (PDs), and thermal management. In this regard, thermal management is more challenging since heat transfer by convection is greatly reduced at wide‐body aircraft's cruising altitudes due to the reduced air pressure. In this paper, a finite element method (FEM) model is developed in COMSOL Multiphysics for an aircraft bipolar MVDC (±5 kV) power cable. Using the model, the maximum permissible cable current at a low pressure of 18.8 kPa (at an altitude of 12.2 km from sea level, the usual cruising altitude for wide‐body aircraft) is calculated. Also, an analytical model is developed based on analytical and proven empirical correlations governing conductive, radiative, and convective heat transfers at the steady state to estimate the ampacity of the bipolar cable system at reduced pressure. It was shown that the proposed analytical model can be used for atmospheric pressure and systems with a larger number of poles, expanding its range of applications. The results of the FEM and analytical models correlate at wide ranges of parameters such as ambient temperature, duct size, distance between the positive and negative pole cables, and the overall diameter of the cables. The influence of horizontal and vertical arrangement of poles is included in the analytical model. The results of this study can be used to design bipolar MVDC power cable systems for the envisaged wide‐body AEA.

Flame propagation characteristics and inherent instability in premixed carbon-free hydrogen/ammonia/oxygen combustibles

Hydrogen-ammonia fuel is an ideal clean energy, and its use in the combustion field is important for achieving energy transformation. This study carried out a series of flame propagation experiments of hydrogen/ammonia/oxygen mixtures and analyzed the instability phenomenon and the competition mechanism of inherent instability during flame propagation at different fuel ratios (0.5–2.0), equivalence ratios (0.5–1.5), and initial pressures (0.1 atm − 1.0 atm). The results show that the hydrogen/ammonia combustion in oxygen is extremely susceptible to instability. Only when the P0 = 0.1 atm, does the flame surface remain smooth in the observable region. Crack initiation and development are observed on the flame surface at P0 = 0.5 atm, and the flame propagated to a late stage with a sudden increase in velocity, which is due to the destabilization of the flame. The increase in fuel ratio gradually shifts the Lewis value away from 1, but does not change the state of thermal-diffusional factor on flame stability. The flame thickness reaches the minimum at φ = 0.8. As the initial pressure increases from 0.1 atm to 1.0 atm, the Lewis number remains almost constant, while the flame thickness, Markstein length, and critical instability radius all decrease rapidly. At the theoretical equivalence ratio and fuel ratio of 1.0, the flame thickness decreased rapidly from 0.143 mm to 0.015 mm, with a decrease of 89.5 %. The flame thickness for hydrogen/ammonia combustion in air is approximately five times that in oxygen for the same operating conditions, implying that the oxygen atmosphere greatly increases the hydrodynamic instability of the hydrogen/ammonia premixed flame. The critical Peclet number (Pecr) of the hydrogen/ammonia/oxygen flames rises exponentially with increasing Markstein number (Ma), and the empirical correlation can be expressed as Pecr = 166.11 × exp (Ma/1.04) + 47.86 (P0 = 0.5 atm) and Pecr = 538.29 × exp (Ma/0.53) + 142.78 (P0 = 1.0 atm).

A Review of Pressure Drop and Mixing Characteristics in Passive Mixers Involving Miscible Liquids.

The present review focuses on the recent studies carried out in passive micromixers for understanding the hydrodynamics and transport phenomena of miscible liquid-liquid (LL) systems in terms of pressure drop and mixing indices. First, the passive micromixers have been categorized based on the type of complexity in shape, size, and configuration. It is observed that the use of different aspect ratios of the microchannel width, presence of obstructions, flow and operating conditions, and fluid properties majorly affect the mixing characteristics and pressure drop in passive micromixers. A regime map for the micromixer selection based on optimization of mixing index (MI) and pressure drop has been identified based on the literature data for the Reynolds number (Re) range (1 ≤ Re ≤ 100). The map comprehensively summarizes the favorable, moderately favorable, or non-operable regimes of a micromixer. Further, regions for special applications of complex micromixer shapes and micromixers operating at low Re have been identified. Similarly, the operable limits for a micromixer based on pressure drop for Re range 0.1 < Re < 100,000 have been identified. A comparison of measured pressure drop with fundamentally derived analytical expressions show that Category 3 and 4 micromixers mostly have higher pressure drops, except for a few efficient ones. An MI regime map comprising diffusion, chaotic advection, and mixed advection-dominated zones has also been devised. An empirical correlation for pressure drop as a function of Reynolds number has been developed and a corresponding friction factor has been obtained. Predictions on heat and mass transfer based on analogies in micromixers have also been proposed.

Features of fluoroethers-filled flat plate pulsating heat pipe: Influence of cooling temperature and semi-empirical modeling

We studied the effects of heat input and cooling temperature on the operational characteristics and heat transfer characteristics of flat plate pulsating heat pipes (FPPHP) using HFE-7100, HFE-7200 and HFE-7300 as working fluids. Empirical correlation equations were fitted to predict the thermal performance of FPPHP. The results showed that the start-up heat input, ultimate heat input, thermal resistance, and evaporation section temperature were positively correlated with boiling point under most operating conditions. At a cooling temperature of 20℃, the FPPHP start-up heat inputs for HFE-7100, HFE-7200, and HFE-7300 are 50 W, 70 W, and 110 W, respectively. After the start-up of the FPPHP, with the increase of cooling temperature, the flow patterns of slug flow, churn flow, annual flow, and vapor region appear successively. FPPHP has lower thermal resistance and ultimate heat input at higher cooling temperatures. At a cooling temperature of 80℃, the ultimate heat inputs of the three fluoroethers in FPPHP are 50 W, 50 W, and 90 W, respectively. In addition, it fills the gap in the empirical equations related to FPPHP and fluoroether working solutions and expands the Ku value range in the current experimental equations to 0.084.

Investigation of Spray Characteristics for Detonability: A Study on Liquid Fuel Injector and Nozzle Design

Detonation engines are gaining prominence as next-generation propulsion systems that can significantly enhance the efficiency of existing engines. This study focuses on developing an injector utilizing liquid fuel and a gas oxidizer for application in detonation engines. In order to better understand the spray characteristics suitable for the pulse detonation engine (PDE) system, an injector was fabricated by varying the Venturi nozzle exit diameter ratio and the geometric features of the fuel injection hole. Analysis of high-speed camera images revealed that the Venturi nozzle exit diameter ratio plays a crucial role in determining the characteristics of air-assist or air-blast atomization. Under the conditions of an exit diameter ratio of Re/Ri = 1.0, the formation of a liquid film at the exit was observed, and it was identified that the film’s length is influenced by the geometric characteristics of the fuel injection hole. The effect of the fuel injection hole and Venturi nozzle exit diameter ratio on SMD was analyzed by using droplet diameter measurement. The derived empirical correlation indicates that the atomization mechanism varies depending on the Venturi nozzle exit diameter ratio, and it also affects the distribution of SMD. The characteristics of the proposed injector, its influence on SMD, and its velocity, provide essential groundwork and data for the design of detonation engines employing liquid fuel.

Simulation of freezing a sea water droplet moving in a cold air

A rapid freezing of a sea water droplet moving in a cold air is modeled. A droplet freezing model is a key component needed for computational forecasting of ice accretion on surfaces of ships and other equipment operating in low-temperature regions. The freezing process consists of the three stages: 1) water cooling to the incipient solidification temperature; 2) liquid solidification; 3) further freezing of the primarily solidified droplet. An icy region, being formed during the 2nd stage, initially represents a slurry, composed of ice crystals suspended in water. Further cooling is associated with an increase in the crystal concentration that at a certain threshold causes slurry transformation into a spongy (porous) ice. The solidification stage model is composed of the three coupled differential equations formulated in the moving coordinate system. All the physical and thermophysical water properties, required for modeling droplet freezing, are calculated by using the empirical correlations. The set of the equations is solved numerically. The solidification process is illustrated by computational examples for different droplet sizes and water salinities. The computed icy region thickness vs. time, as well as temperature distributions and porosities along droplet radius at different time moments are shown.

Photocatalytic dye degradation, H2 evolution, electrical and mechanical performances of mechano-synthesized multifunctional Bi2Te3 nanoparticles: Effect of milling time and thermal treatment

Bi2Te3 nanoparticles are synthesized by mechanical alloying the Bi and Te powders under the Ar and pressed powdered samples are sintered at 573 K. Rietveld refined XRD patterns, FESEM images and EDX spectra reveal the microstructure, morphology and phase purity of the samples. Bandgaps are obtained from the FTIR spectra and a blue shift with size reduction indicates the size confinement effect. The non Debye type ac conductivity and dielectric constant variations with milling time and sintering are measured. The improved photocatalytic degradation efficiency of the sintered sample (83.59 %) using Rhodamine B dye under visible light elucidates reduced porosity effect. The photocatalytic hydrogen evolution efficiencies of these nanoparticles are measured and a probable mechanism is depicted. The highest H2 generation efficiency (1462.5 μmol g−1h−1) is observed with the sintered sample. Microhardness measurement reveals normal indentation size effect. Empirical correlations among electrical conductivity, microhardness and photodegradation are established for the first time.

On Inter‐bubble Hydrodynamics and Cluster Formation in Non‐Newtonian Bubbly Columns: A Review

AbstractA comprehensive understanding of the inter‐bubble dynamics and the cluster formations in non‐Newtonian fluids is pivotal for chemical and biomedical engineering applications. In this review, we summarize current research efforts to provide a fundamental understanding and engineering principles of the interactions between bubbles and the dynamics of bubble clusters in non‐Newtonian fluids. Although the majority of research is still predominantly conducted through experimentation, the significance of computational fluid dynamics in elucidating interaction mechanisms has become increasingly prominent in recent years. Moreover, the gas‐liquid systems reviewed in this paper are driven by gravity, which is closer to the actual industrial processes. We indicate the effects of non‐Newtonian fluid special rheological properties (especially viscoelasticity and shear‐dependent viscosity) on the interaction between multiple bubbles and the formation of clusters. We summarize the main empirical correlations in related research, which are useful for the optimization of industry. Ultimately, we address the current trends, limitations, and future directions in this research field.

Investigation of effects of impeller geometry on the spatial distribution of turbulent field and micro-mixing performance in a stirred reactor equipped with multiple impellers

There are few studies on the effects of spatial distribution of hydrodynamics on the micro-mixing in stirred reactors. In this work, a statistical approach is introduced to quantitatively assess the spatial distributions of hydrodynamic parameters, using the turbulent dissipation rate as an example. According to the results, the effects of impeller geometry and angular velocity on the turbulent dissipation rate can be well described in terms of the volume-averaged values and spatial distribution functions. In the present study, a more uniform distribution of the turbulent dissipation rate is achieved by the multiple impellers with an inclinational angle of 15° at the same rotational speed. However, increasing the inclinational angle can decrease the volume-averaged value. The cumulative percentage of area-averaged turbulent dissipation rate is well modeled by an exponential function. The effects of impeller types on the meso- and micro-mixing processes are also investigated. It is found that the micro-mixing process has more significant influences than the meso-mixing process in the bottom region and near the free surface. The effects of impeller types on the micro-mixing performance are further investigated using the Villermaux–Dushman reaction system, both experimentally and numerically. An empirical correlation that considers the spatial distribution of turbulent parameters for the reaction rate of I2 synthesis is proposed. The results show that the predictions of segregation index, which represents micro-mixing performance, are improved by a numerical model coupled with the new reaction rate model.

Combining deep learning with physical parameters in POC and PIC inversion from spaceborne lidar CALIOP

POC and PIC are indispensable components in the global ocean carbon cycle, their transport and space distribution being driven by the biological carbon pump and the carbonate pump. However, passive ocean color remote sensing, usually employed for POC and PIC research, experiences serious shortcomings in polar winter conditions due to its reliance on sunlight, leading to scarce data coverage in the polar regions. In contrast, CALIOP has shown considerable promise in high-latitude ocean observing. Past approaches to estimate POC from CALIOP data relied on bbp measurements obtained through the application of algorithms that presume an empirical linear correlation between bbp and the backscatter coefficient measured at 180°. This method does not account for any spatiotemporal variability in the conversion coefficient. Furthermore, the potential of CALIOP to provide estimates of PIC has not been explored yet. Here, we developed an innovative Two-Branch-Two-Step (TBTS) model to estimate POC and PIC from CALIOP data, which effectively expands the spatial coverage of the MODIS products. This method exploits the strength of deep learning while encapsulating the generalizability of physical parameters. This method consists of two branches: (1) a deep learning branch based on lidar attenuated backscatter waveform and (2) a branch focusing on physical parameters, including the total column-integrated depolarization ratio and the subsurface cross-polarized component of column-integrated backscatter. The model’s generalizability and accuracy are confirmed through the evaluation of a test dataset and validation using in-situ measurements. Our model outperforms several other prevalent machine learning models. We also dissected the importance of different parts of the input data using SHAP tools, thereby providing insights into the black-box nature of deep learning models. Using CALIOP products, we put forth the inaugural estimation of interannually resolved PIC and POC standing stocks in polar regions. The implementation of CALIOP in polar regions bridges the gap inherent in passive ocean color measurements. Lidar-derived total global PIC standing stock is estimated to be 8% higher than that from MODIS, while the POC standing stock is boosted by 17.2%. The carbon standing stock in polar regions exhibits significant inter-annual variability and apparent seasonal periodicity. Hence, results from this research effort clearly reveal that the exploitation of the CALIOP-derived POC and PIC measurements, in combination with the application of new approaches and algorithms to future space lidar data, will undeniably enhance our comprehension of the polar ocean carbon cycle. However, it is important to acknowledge that the CALIOP products may inherit biases from the MODIS data used for training. Hence, where MODIS data is available, it’s still the “better” product to use, but where there isn’t MODIS data, the CALIOP product is extremely useful, especially in the polar regions.

Propylene and DME solubility in PAG oil: Experimental investigations and simplified modeling

This work experimentally investigated the solubility of Propylene and Dimethyl Ether (DME) in polyalkylene glycol (PAG) oil. The solubility experimental data were used to fit different local composition models from the literature, the Wilson and Heil equations, and the Non-Random Two-Liquid (NRTL) model. Two new empirical correlations were proposed to decrease the deviation between experiments and the models. The first correlation used six fitting coefficients and resulted in an average deviation of 1.2 % for Propylene and 2.8 % for DME. The second empirical correlation was proposed with a single solubility coefficient (SSC) and a compact form, which allows solubility to be determined explicitly. The correlation resulted in average deviations from experimental data of 1.6 % for Propylene and 2.5 % for DME. Moreover, the SSC correlation showed performance robustness against the decrease of available data points. The correlation was used to compare the solubility of Propylene and DME with the solubility of Propane. At the same conditions, Propane showed the lowest solubility while DME resulted in the most soluble refrigerant.