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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Heterointercalation in Chevrel-Phase Sulfides: A Model Periodic Solid for the Investigation of Chain Electron Transfer

Modulation of electron density localization on periodic crystal solids through electron transfer from interstitial cations can directly influence the bonding configurations of small-molecule intermediates at the catalyst binding site. This study presents the microwave-assisted solid-state synthesis of four heterointercalant Chevrel-phase (CP) sulfides with varying metal cation intercalants with compositional and electronic structure investigations of the electron density redistribution as a result of intercalation. The heterointercalant CP sulfides, with the general formula Cu x M y Mo 6 S 8 (where M = Cr, Mn, Fe, Ni; x, y = 1.5−2.5), are presented here for the probe reaction of electrochemical CO 2 reduction. A change in product selectivity is observed toward the production of methanol at low overpotentials of −0.5 V vs reversible hydrogen electrode (RHE), as a result of the intercalant combination present within the CP interstitial cavity. Structural confirmation of all materials was examined through Rietveld refinement of the powder X-ray diffraction (PXRD) data, high-resolution transmission electron microscopy (HR-TEM), and selected-area electron diffraction (SAED). Electron transfer from the intercalated metal cations to the Mo 6 S 8 cluster was investigated via X-ray photoelectron spectroscopy (XPS) of the intercalated metal cations and the chalcogenide cluster. Electron transfer was further confirmed through X-ray absorption analysis (XAS) of the K-edges of Mo and intercalants. Intermediate studies of electrochemical reduction of formaldehyde to methanol resulted in a faradaic efficiency of ∼78% methanol production on Cu x Ni y Mo 6 S 8 . The results presented herein identify distinct principles for materials design that can be utilized in other compositional spaces within the broad families of periodic crystal solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

An algorithm for physics informed scan path optimization in additive manufacturing

Site specific microstructure control is a critical research area within the field of additive manufacturing due to its potential to revolutionize part performance. One way to achieve site specific microstructure control is through control of the solidification conditions via the construction of intricate scan paths; however, the search space for such a problem is large. Previous attempts only considered the solidification conditions at the top surface while also requiring either lots of manual-fine tuning or large amounts of computational resources. This paper introduces a general method for scan path optimization which considers the solidification conditions in the bulk of the material without an increase in computational expense. This method consists of three core components:1. A heat transfer model for simulating the temperature field at a given time.2. A surrogate model which takes scan pattern information and temperature data and predicts the solidification conditions of the bulk as well as the meltpool depths for a spot melt.3. A decision algorithm to decide which spot melt should be printed next based on the outputs of the surrogate model.Each of these components can be changed without changing the overall method. Within this work, this method is applied in the creation of an algorithm containing a semi-analytic heat transfer model to simulate the temperature field, a fully convolutional neural network (FCNN) as the surrogate model, and a greedy decision algorithm. The resulting algorithm produced complex scan patterns which gave strong results for simulated microstructure control.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Satellites, core hole excitations, and spin-resolved electronic structure in the spectroscopy of half-metallic CrO 2

Photoelectron satellites—the structures appearing on the low kinetic or high binding-energy side of the “main” or “elastic” photopeak—betray the complex many-body interactions set in motion by the sudden creation of the core hole. In this work, we demonstrate, using the technologically important ferromagnetic half-metal CrO 2 , how such satellites can manifest themselves in other core-level spectroscopies of the material and how they can reveal important details pertinent to its electronic structure. Specifically, we identify a fluorescence satellite in the Cr 𝐿 3 resonant x-ray-emission spectra that radiates at a constant emission energy across the Cr 𝐿 3 x-ray edge with energy ≈1.3 eV above the ordinary valence fluorescence. Here, we provide evidence that this feature arises from the valence recombination of the Cr 2⁢𝑝 core hole “dressed” by the same shakeup charge-transfer process present in both the Cr x-ray photoelectron and the Cr x-ray absorption spectra with its energy uniquely measuring the exchange splitting of the Cr 3⁢𝑑 level. Further analysis of the x-ray emission data reveals three additional features that radiate at constant loss energy that are attributed to combinations of Cr 3⁢𝑑⁢(𝑡 2⁢𝑔 ) → Cr 3⁢𝑑⁢(𝑡 2⁢𝑔 ), charge-transfer O 2⁢𝑝→Cr 3⁢𝑑, and crystal-field Cr⁢ 3⁢𝑑⁡(𝑡 2⁢𝑔 )→Cr⁢ 3⁢𝑑⁡(𝑒 𝑔 ) excitations. These assignments and their energies are supported by density-functional theory calculations, the accuracy of which we demonstrate by hard x-ray valence-photoemission measurements. Atomic multiplet calculations, which include crystal-field effects, help interpret x-ray photoelectron and x-ray absorption spectra of the covalently mixed Cr ion. Resonant Cr K-𝐿 2,3 ⁢𝐿 2,3 Auger-electron emission spectra support a ligand-to-metal nature of the charge-transfer process while highlighting the charge sensitivity differences between photon-in/electron-out and photon-in/photon-out spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Robust Interpretation of Electrochemical Impedance Spectra Using Numerical Complex Analysis

Electrochemical Impedance Spectroscopy (EIS) is a noninvasive technique widely used for understanding charge transfer and charge transport processes in electrochemical systems and devices. Standard approaches for the interpretation of EIS data involve starting with a hypothetical circuit model for the physical processes in the device based on experience/intuition and then fitting the EIS data to this circuit model. This work explores a mathematical approach for extracting key characteristic features from EIS data by relying on fundamental principles of complex analysis. These characteristic features can suggest the presence of inductors and constant phase elements (nonideal capacitors) from impedance data and enable us to answer questions about the identifiability and nonuniqueness of equivalent circuit models. In certain scenarios such as models with only resistors and capacitors, we are able to enumerate all possible families of circuit models. Finally, we apply the mathematical framework presented here to real-world electrochemical systems and highlight results using impedance measurements from a lithium-ion battery coin cell.

charge transfer↗
DOE OSTI2020

First Ever Polymer Flood Field Pilot To Enhance The Recovery Of Heavy Oils On Alaska’s North Slope - Pushing Ahead One Year Later

In June 2018 the team embarked on an ambitious project to address the slow development pace of Alaska’s 20+ billion barrels heavy oil resource via the first ever polymer flood pilot. Following the successful commencement of the pilot in August 2018, the field demonstration, supporting laboratory experiments and numerical simulation have steadily progressed. A significant amount of valuable data and lessons learned have been collected, and are reported in this paper. The ongoing pilot and the research activities is making headway toward the primary objective of validating the use of polymer flooding for extracting heavy oil in Alaska’s challenging environment. The pilot is conducted in two pre-existing pairs of horizontal injectors and producers in an isolated fault block of the Schrader Bluff heavy oil reservoir at the Milne Point Field. A customized polymer blending and pumping unit injects HPAM polymer at a concentration of 1,750 ppm to achieve a target viscosity of 45 cP. Supporting coreflood laboratory experiments have focused on quantification of polymer retention in the rock, and effect of injection water salinity, polymer, and their combinations on oil recovery. The injection and production response of the pilot flood pattern is utilized to develop a history matched reservoir simulation model for forecasting oil recovery beyond the pilot. Finally, specially designed laboratory experiments address anticipated operating concerns regarding post-polymer breakthrough such as oil-water separation efficiency and polymer induced fouling of heater tubes. Polymer has been injected continuously since startup except for two short equipment modification shutdowns, and more recently a prolonged disruption due to polymer hydration issues at the J-pad field site. Cumulatively, over 600,000 lbs. of polymer has been injected, corresponding to ~7%PV. The two producers show significant decrease in the water cut, gradually increasing oil rate, and no polymer breakthrough. Two main observations from the coreflood are a significant uncertainty in polymer retention values, and positive oil recovery response to low salinity water (2,600 mg/liter TDS). The heterogeneity in the flood pattern presents some challenges in obtaining a robust history matched simulation model. Experimental results on produced fluids treatment indicate the formation of a dense polymer deposit, at certain conditions, on heating tubes that can negatively impact the heat transfer efficiency. The scientific knowledge, including the lessons learned during unanticipated shutdowns, quality control, logistics and field data that is being acquired from this effort has referential value for other planned EOR projects. Finally, by all indications, the polymer field pilot is steadily progressing toward achieving the ultimate goal of unlocking the massive heavy oil resources on Alaska North Slope (ANS).

Dandekar, Abhijit↗
DOE OSTI2025

Quenching of single-particle strength inferred from nucleon-removal transfer reactions on 15 C

The difference in the proton and neutron separation energies (ΔS) of the weakly bound 15 C ground state is -19.86 MeV, an extreme value. Data from intermediate-energy heavy-ion induced (HI-induced) knockout reactions on nuclei spanning -20 ≲ ΔS ≲ +20 MeV, suggest that the degree to which single-particle strength is quenched, R s , has a negative correlation with ΔS, decreasing from unity around -20 MeV to around 0.2 at +20 MeV. For the 15 C ground state (R s = 0.96 (4) in HI-induced knockout), contrasting results have recently been obtained via the neutron-adding transfer reaction, which reveal a value of R s = 0.64 (15), similar to the value observed at modest and more extreme values of ΔS with reaction probes other than HI knockout. In order to explore the any potential differences between adding and removing processes in transfer reactions at extreme ΔS, single-neutron removal transfer reactions on 15 C were performed at 7.1 MeV/u in inverse kinematics. The removal of a valence neutron in 2s 1/2 orbit using both (p, d) and (d, t) reactions shows consistent quenching factors and agrees with those from the neutron-adding reaction. The present results, which can be compared with neutron knockout reaction, suggest that correlations, represented by the quenching factor, show limited dependence on neutron-proton asymmetry under the most extreme asymmetry conditions so far achieved in transfer reactions.

quenching factor↗
DOE OSTI2023

Impact of gel concentration on filter fluxes in microfiltration of Hanford tank wastes and simulants

Abstract Treatment processes have been proposed that will utilize crossflow filtration to concentrate sludge waste streams at the Department of Energy's Hanford Site. Challenges associated with solid–liquid separation of the waste streams drive a necessary evaluation of available Hanford high level waste (HLW) filtration data. Limiting flux conditions during crossflow filtration are elucidated with the formation of a cake layer on the membrane surface. A mass transfer coefficient between the gel and bulk concentrations plays a critical role in determining filter flux. A correlation between the gel concentration and mass transfer coefficient is made to assist in determining filter performance of select HLW streams. As a process alternative to crossflow filtration, gravity settling of waste streams may be deployed as a solid–liquid separation technique. However, this results in a contrasting performance with the centrifuged solids concentration. A method was developed to estimate expected filtration and settling performance based on physical characterization data for Hanford tank waste samples. By assessing the estimated processing performance of HLW, technical support can be provided during flowsheet planning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Crystal structures of an E1–E2–ubiquitin thioester mimetic reveal molecular mechanisms of transthioesterification

E1 enzymes function as gatekeepers of ubiquitin (Ub) signaling by catalyzing activation and transfer of Ub to tens of cognate E2 conjugating enzymes in a process called E1–E2 transthioesterification. The molecular mechanisms of transthioesterification and the overall architecture of the E1–E2–Ub complex during catalysis are unknown. Here, we determine the structure of a covalently trapped E1–E2–ubiquitin thioester mimetic. Two distinct architectures of the complex are observed, one in which the Ub thioester (Ub(t)) contacts E1 in an open conformation and another in which Ub(t) instead contacts E2 in a drastically different, closed conformation. Altogether our structural and biochemical data suggest that these two conformational states represent snapshots of the E1–E2–Ub complex pre- and post-thioester transfer, and are consistent with a model in which catalysis is enhanced by a Ub(t)-mediated affinity switch that drives the reaction forward by promoting productive complex formation or product release depending on the conformational state.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Triplet photodynamic and up-conversion luminescence in donor–acceptor dyads with slip-stacked vs. co-facial arrangement

We report the design/synthesis and characterization of organic donor–acceptor (D–A) dyads can provide precious data allowing to improve the efficiency of classical photo-induced bimolecular interactions/processes. In this report, two novel triplet D–A dyads (4 and 5) were synthesized and fully characterized. While the optical absorption and emission profiles of these new systems exhibit similar spectral structures as that of the triplet donor/sensitizer quinoidal thioamide (QDN), the transient absorption (TA) spectra of these two dyads produced new features that can be associated with triplet transients and charge transfer species. However, the kinetics of the excited-state processes/dynamics is significantly influenced by the geometrical arrangement(s) of donor/acceptor chromophores. Further analysis of the TA data suggests that the dyad with slip-stack geometry (4) is less effective in undergoing both intra- and inter-dyad triplet energy transfer than the dyad with co-facial geometry (5). Subsequently, triplet sensitization of 9,10-diphenylanthracene (DPA) using both dyads led to upconverted photoluminescence via triplet–triplet annihilation of DPA triplet transients. But, it was found that a maximum upconversion quantum yield could be achieved at a low power density using the co-facial type dyad 5. Altogether, these results provide valuable guidance in the design of triplet donor–acceptor dyads, which could be used for light-harvesting/modulation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluation and development of flow condensation correlations using the data from low GWP refrigerants in an axial micro-fin aluminum tube

To mitigate global warming, the world is transitioning to refrigerants with low global warming potential (GWP). Supporting this shift requires a model that can accurately predict the heat transfer and pressure drop of new refrigerants, crucial for designing efficient heat exchangers. Existing models, however, are largely based on currently deployed refrigerants and primarily developed for unexpanded micro-fin tubes with spiral angles of 6° to 30°. Their applicability to new refrigerants, especially in expanded micro-fin tubes, is uncertain. This study assesses the performance of four well-known condensation models for six emerging refrigerants—R-32, R-454B, R-454C, R-455A, R-1234yf, and R-1234ze(E)—against experimental data. Initially, the Han and Lee (2005) model shows the best prediction accuracy with a mean absolute deviation (MAD) of 22.1 %. To enhance the accuracy of heat transfer models for new refrigerants and geometries with large temperature glides, two approaches are proposed. Here, the first approach applies a simple correction factor, reducing the MAD of the Cavallini et al. (2009) model from 68.2 % to 15.4 %. The second approach uses the variable metric method for minimization, fitting new constants to the data. This optimization results in the Kedzierski and Goncalves (1997) model achieving the highest accuracy, with a MAD of 13.1 %. For pressure drop models, the Cavallini et al. (1997) model is the most accurate with a MAD of 6.4 %, followed by the Haraguchi et al. (1993) model with a MAD of 9.4 %. Due to its simplicity, the Haraguchi et al. (1993) model is a practical option for predicting frictional pressure drop.

Axial micro-fin tubes↗
DOE OSTI2022

Automated System-wide Event Detection and Classification Using Machine Learning on Synchrophasor Data

As the number of phasor measurement units (PMUs) deployed in a power system increases, and their data volume streamed to the control canter intensifies, operators are facing challenges related to the analysis of such data, which need to be observed and responded to as the measurements are displayed in the Control Room. Humans are generally unable to process such large amount of data efficiently and rapidly. There is an apparent need for automated ways to analyze the data, extract actionable information about occurrence of specific events, and characterize the events quickly and cost effectively. This paper discusses the use of machine learning (ML) to facilitate such tasks by providing automated, highly computationally efficient, and cost-effective ways of extracting actionable information from synchrophasor big data in real-time. We developed Big Data Smart (BDSmart) ML-based prototype tool for the Control Room use that automatically analyses data properties from synchrophasor system measurements taken across the three grid Interconnections in the USA (Western, Eastern and ERCOT). The data collected from several hundreds of PMUs located across the Interconnections over a period of two years have been made available for our extensive study. As a result, we were able to identify a number of big data properties that influence how ML methodology is applied to select, develop, train and test the data models that can eventually be used for the tool implementation. The resulting set of candidate algorithms spans unsupervised, supervised, semi-supervised and transfer-learning approaches. Many ML techniques, such as decision trees, multinomial logistic regression, feed-forward neural networks, K-nearest neighbor, multiclass support vector machine, and single and multi-channel convolutional neural networks, are implemented, and their performance is examined. We offer the results from testing the data models. The novelty of our study is in the approaches for bad data detection and mitigation, selection of a simplified feature for event detection, and data label improvements. As a result, we came up with a list of recommendations for the utilities on how to improve the PMU recording practices to cater to the future ML applications aimed at automating the analysis of synchrophasor data.

Synchrophasors, Machine Learning, System-wide Even↗
DOE OSTI2023

Machine Learning for Prediction of Thermodynamic Descriptors

Our objective is to apply machine learning (ML) algorithms for the prediction of molecular catalysis descriptors from geometric properties derived from experimental crystallographic databases. Catalysis is often considered a “low-data” discipline that is poorly suited for ML methods. An exception is the extensive structural information that is available for molecular catalysts through the Cambridge Structural Database (CSD), which contains atomically precise molecular structures from X-ray diffraction analysis for >600K metal complexes. As a proof-of-principle, we targeted the prediction of hydricity, a thermodynamic property that provides understanding and control of catalytic hydride transfer. We built a training set composed of ~100 molecular complexes with a known hydricity and structural information from the CSD. This data set was converted into a machine-readable format using the smooth overlap of atomic positions (SOAP) representation and further labeled with simple electronic descriptors for the metal centers. Multiple different neural networks were trained on this data set, and the accuracy of the hydricity predictions ranged from < 2 kcal/mol to 20 kcal/mol. The accuracy of each model was highly sensitive to which compounds were in the train versus test set, underscoring the challenges associated with small and chemically diverse data sets. Finally, to further augment the data set, we attempted to experimentally measure several new hydricity values, however these experiments were unsuccessful due to undesired chemical reactivity of the selected complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Optimizing flow condensation models for next-generation refrigerants in axial micro-fin aluminum tubes

To support the transition to next-generation refrigerants, accurate modelling of heat transfer and pressure drop is essential for designing efficient heat exchangers. Current models, largely based on traditional refrigerants and unexpanded micro-fin tubes, may not reliably predict performance for new refrigerants and expanded micro-fin geometries. This study evaluates four condensation models using experimental data for six A2L refrigerants: R-32, R-454B, R-454C, R-455A, R-1234yf, and R-1234ze(E). For heat transfer models, the Han and Lee (2005) model initially yields the best accuracy (mean absolute Deviation, MAD = 22.1%). To further improve predictions, a correction factor reduces the Cavallini et al. (2009) model’s MAD from 68.2% to 15.4%, while optimization of the Kedzierski and Goncalves (1997) model achieves a MAD of 13.1%. For pressure drop, the Cavallini et al. (1997) model proves most accurate (MAD = 6.4%), with the simpler Haraguchi et al. (1993) model also effective (MAD = 9.4%). Keywords: Flow condensation models, heat transfer coefficient, frictional pressure drop, next-generation refrigerants, aluminum micro-fin tubes

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
DOE OSTI2023

Fourier-informed knot placement schemes for B-spline approximation

Fitting B-splines to scientific data is especially challenging when the given data contain noise, jumps, or corners. Here, we describe how periodic data sets with these features can be efficiently approximated with B-splines by analyzing the Fourier spectrum of the data. Our method uses a collection of spectral filters to compute high-order derivatives, smoothed versions of noisy data, and the locations of jump discontinuities. Further, these quantities are then combined to choose knots that capture the qualitative features of the data, leading to accurate B-spline approximations with few knots. The method we introduce is direct and does not require any intermediate B-spline fitting before choosing the final knot distribution. Aside from fast Fourier transforms to transfer to and from Fourier space, the method runs in linear time with very little communication. We assess performance on several test cases in one and two dimensions, including data sets with jump discontinuities and noise. These tests show the method fits discontinuous data without spurious oscillations and remains effective in the presence of noise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Energy Dependent Fission Product Yields (2nd year Milestone and Deliverables)

Introduction to the project: One of the Laboratory missions is to provide consistent, high-precision fission product; yield data critical for testing fission models and maintaining the safety and security of the nation’s nuclear weapons stockpile. However, high-quality, energy-differential fission product yield data is missing for certain actinides and neutron energies important to constrain the new U.S. Nuclear Data Program evaluation effort; It has been shown that the reactor antineutrino anomaly may be at least partially caused by roughly 20 fission products. The fission product yield data is missing or incomplete for many of these isotopes, thus it is necessary to accurately determine these values to better constrain the anomaly; Aitor Bracho is measuring very short-lived (seconds to minutes) fission product yields of 235 U and 239 Pu using monoenergetic neutron beams at E n = 60 and 560 keV; Aitor Bracho is using a direct approach utilizing a state-of-the-art rabbit transfer system, superior HPGe detector, and digital acquisition systems for fission decay measurements. The goals of this project: lop experimental capabilities and data analysis techniques to carry out the gamma-ray spectra analysis necessary for fission product yield calculation; Provide high-precision and energy-dependent fission product data supporting fission theory, neutrino physics, and applied physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Synergistic Retrieval of Temperature and Humidity Profiles from Space-Based and Ground-Based Infrared Sounders Using an Optimal Estimation Method

The atmospheric temperature and humidity profiles of the troposphere are generally measured by radiosondes and satellites, which are essential for analyzing and predicting weather. Nevertheless, the insufficient observation frequencies and low detection accuracy of the boundary layer restricts the description of atmospheric state changes by the temperature and humidity profiles. Therefore, this work focus on retrieving the temperature and humidity profiles using observations of the FengYun-4 (FY-4) Geostationary Interferometric Infrared Sounder (GIIRS) combined with ground-based infrared spectral observations from the Atmospheric Emitted Radiance Interferometer (AERI), which are more accurate than space-based individual retrieval results and have a wider effective retrieval range than ground-based individual retrieval results. Based on the synergistic observations, which are made by matching the space-based and ground-based data with those of different spatial and temporal resolutions, a synergistic retrieval process is proposed to obtain the temperature and humidity profiles at a high frequency under clear-sky conditions based on the optimal estimation method. In this research, using the line-by-line radiative transfer model (LBLRTM) as the forward model for observing simulations, a retrieval experiment was carried out in Qingdao, China, where an AERI is situated. Taking radiosonde data as a reference for comparing the retrieval results of the temperature and humidity profiles of the troposphere, the root-mean-square error (RMSE) of the synergistic retrieval algorithm below 400 hPa is within 2 K for temperature and within 12% for relative humidity. Compared with the GIIRS individual retrieval, the RMSE of temperature and relative humidity for the synergistic method is reduced by 0.13–1.5 K and 2.7–4.4% at 500 hPa, and 0.13–2.1 K and 2.5–7.2% at 900 hPa. Moreover, the forecast index (FI) calculated from the retrieval results shows reasonable consistency with the FIs calculated from the ERA5 reanalysis and from radiosonde data. The synergistic retrieval results have higher temporal resolution than space-based retrieval results and can reflect the changes in the atmospheric state more accurately. Overall, the results demonstrated the promising potential of the synergistic retrieval of temperature and humidity profiles at high accuracy and high temporal resolution under clear-sky conditions from FY-4/GIIRS and AERI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Universal correlation for falling film evaporation heat transfer coefficients of water and seawater

Horizontal falling film evaporators are widely utilized in desalination industries to increase fresh water supply. However, universal correlations for seawater falling film evaporation under varied operational and geometrical conditions are simply unavailable in open literature. Thus, this study aims to develop such a universal correlation for both plain and enhanced tubes. The detailed heat transfer mechanisms are reviewed, and rational parameters are incorporated to develop the universal correlation. A dataset of 994 data points from 9 sources covering a wide range of conditions was compiled. These conditions include Reynolds numbers from 10 to 7235, heat fluxes from 7.7 to 208 kW/m -2 , saturation temperatures from 278 to 401 K, salinities from 0 to 60 gsalt kg -1 water, tube diameters from 15.8 to 50.8 mm, and liquid feeder height to diameter ratios from 1 to 2.25. Upon analysis, it was found that most of the recommended existing correlations exhibited poor predictive accuracy, as evidenced by larger MADs. The developed correlation in this study demonstrated the best predictive accuracy for the entire dataset, yielding a MAD of 16.8 % and an R 2 of 0.82. Furthermore, the performance of the new correlation was individually assessed across a broader spectrum of operational and design conditions, reflecting the individual conditions’ influences with an overall MAD of 20 %.

42 ENGINEERING↗