Parameter Dependence Research Articles

Spectral performance evaluation of a second-generation spectral detector CT.

The aim of this study was to characterize a second-generation wide-detector dual-layer spectral computed tomography (CT) system for material quantification accuracy, acquisition parameter and patient size dependencies, and tissue characterization capabilities. A phantom with multiple tissue-mimicking and material-specific inserts was scanned with a dual-layer spectral detector CT using different tube voltages, collimation widths, radiation dose levels, and size configurations. Accuracy of iodine density maps and virtual monoenergetic images (MonoE) were investigated. Additionally, differences between conventional and MonoE 70keV images were calculated to evaluate acquisition parameter and patient size dependencies. To demonstrate material quantification and differentiation, liver-mimicking inserts with adipose and iron were analyzed with a two-base decomposition utilizing MonoE 50 and 150keV, and root mean square error (RMSE) for adipose and iron content was reported. Measured inserts exhibited quantitative accuracy across a wide range of MonoE levels. MonoE 70keV images demonstrated reduced dependence compared to conventional images for phantom size (1vs. 27 HU) and acquisition parameters, particularly tube voltage (4vs. 37 HU). Iodine density quantification was successful with errors ranging from -0.58 to 0.44mg/mL. Similarly, inserts with different amounts of adipose and iron were differentiated, and the small deviation in values within inserts corresponded to a RMSE of 3.49±1.76% and 1.67±0.84mg/mL for adipose and iron content, respectively. The second-generation dual-layer CT enables acquisition of quantitatively accurate spectral data without compromises from differences in patient size and acquisition parameters.

Probing Hydrodynamic Fluctuation-Induced Forces with an Oscillating Robot.

We study the dynamics of an oscillating, free-floating robot that generates radially expanding gravity-capillary waves at a fluid surface. In open water, the device does not self-propel; near a rigid boundary, it can be attracted or repelled. Visualization of the wave field dynamics reveals that when near a boundary, a complex interference of generated and reflected waves induces a wave amplitude fluctuation asymmetry. Attraction increases as wave frequency increases or robot-boundary separation decreases. Theory on confined gravity-capillary wave radiation dynamics developed by Hocking in the 1980s captures the observed parameter dependence due to these "Hocking fields." The flexibility of the robophysical system allows detailed characterization and analysis of locally generated nonequilibrium fluctuation-induced forces [M. Kardar and R. Golestanian, Rev. Mod. Phys. 71, 1233 (1999)RMPHAT0034-686110.1103/RevModPhys.71.1233].

Investigations into penetration depth profiles of hydrogenic species in beryllium plasma-facing components via molecular dynamics simulations

During the operation of nuclear fusion reactors, plasma-facing components lining the reactor vessel are continually bombarded by plasma species. The penetration and subsequent trapping of these bombarding plasma ions has implications for component damage as well as in-vessel inventory. Accurately predicting the expected ion penetration depth profiles at a range of plasma ion and surface temperatures typical of fusion reactor operating conditions will inform the scrape-off layer design to limit particle radiation damage and tritium trapping in order to prolong the lifetime of the plasma-facing components and satisfy the DT fuel cycle requirements. By defining a statistical distribution for ion penetration depth and describing the evolution of its parameters across the fusion parameter space of interest, the expected ion deposition depth profiles can be calculated for any subset of ion and surface temperature ranges as needed. Molecular dynamics simulations were used to study the bombardment of beryllium lattices with surface temperatures of up to 1100 K by 5 eV–150 eV deuterium and tritium ions, and the resulting ion penetration depths were investigated. The distributions of two penetration depth quantities, considered from the perspectives of lattice damage and hydrogen retention are defined and their distribution parameter dependence on surface and ion temperature is identified. The expected positive correlation between penetration depth and ion temperature is observed, where the non-linear relationship between these quantities indicates the expected form of the velocity dependence of nuclear stopping power at low bombardment energies. Isotope effects on the distributions are also investigated, with results suggesting that heavier ions have comparably lower mobility within the sample and will generally accumulate closer to the surface. A short study on ion deposition rates is also performed; a non-linear increase of deposition rate with increasing bombarding ion energy has been observed, and evidence of a weak positive surface temperature correlation has been noted.

Eigenvector continuation for the pairing Hamiltonian

The development of emulators for the evaluation of many-body observables has gained increasing attention over the last years. In particular the framework of eigenvector continuation (EC) has been identified as a powerful tool when the Hamiltonian admits for a parametric dependence. By training the emulator on a set of training data the many-body solution for arbitrary parameter values can be robustly predicted in many cases. Furthermore, it can be used to resum perturbative expansions that otherwise diverge. In this work, we apply EC to the pairing Hamiltonian and show that EC-resummed perturbation theory is in qualitative agreement with the exact solution and that EC-based emulators robustly predict the ground-state energy once the training data are chosen appropriately. In particular the phase transition from the normal to the superfluid regime is quantitatively predicted using a very low number of training points. Published by the American Physical Society 2024

A novel Cosine-Cosine chaotic map-based video encryption scheme

The surge in online activities has led to the increasing popularity of sharing video data across diverse applications, including online education tutorials, social networking, video calling, and OTT platforms. Encryption prevents unauthorized access to the transmitted data over unreliable channels. The well-known features of chaos theory such as random behaviour, unpredictability, and initial parameters dependency facilitate its use in cryptography. Many security issues are faced by chaos-based cryptosystems because of their less complexity. Hence, a new Cosine-Cosine chaotic map characterized by intricate chaotic behaviour is designed in the current study. Additionally, we formulate an original video encryption scheme employing this Cosine-Cosine chaotic map. The encryption process involves five steps, beginning with the segmentation of the original video into frames based on its frame rate. In the second phase, a 384 bits pseudorandom key is generated that is further divided into three subkeys of 128 bits each. The novel Cosine-Cosine chaotic map-based sequence is generated. In the fourth step, red, green, and blue components are encrypted using the pseudorandom key and the chaotic sequence. In the last step, we combine encrypted frames to get cipher video. The security analysis validates that the proposed encryption protects against eavesdropping.

Pull-off of a rigid cone from a viscoelastic substrate

The pull-off of a sphere from an elastic substrate follows the well-known JKR solution, and a similar but less known solution is valid for a cone. The two differ qualitatively in the parametric dependences of the pull-off load, so we study the case of a viscoelastic substrate using a well-known Gent and Schultz approach for the effective work of adhesion, with the assumption that the elastic modulus in the bulk of the specimen is the relaxed one. The rate of peeling of the contact line (for given remote withdrawing speed) depends on elastic modulus for the spherical case, and not for the cone. However, for the spherical geometry, we predict that the highest load amplification should be actually smaller than the highest work of adhesion amplification, while for the cone the opposite is true, although of a smaller factor.

Research of nonstationary dynamic models of the organizational and technological process of railway transport technical vehicles repair

The problems of analytical and computer research of dynamic models of repair and operation of technical vehicles used in railway transport are among the urgent problems related to ensuring safety and stability of traffic, with the development of digital twins and the improvement of monitoring and diagnostic systems. The analysis of models described by various types of multidimensional nonlinear differential equations requires the use of modern methods of dynamical systems theory, numerical optimization and computer algebra. The purpose of the article is to conduct a qualitative and numerical analysis of mathematical models of organizational and technological processes (OTP) in railway transport, as well as the synthesis of new controlled OTP models. Nonstationary generalizations of a two-dimensional dynamic model describing the repair process of railway transport equipment are proposed. Various cases of using constant and time-dependent parameters are considered. The case of linear and exponential dependences of parameters on time is studied. For the studied models, trajectories are obtained taking into account the variation of constant parameters and taking into account the choice of parametric dependencies, a comparative analysis of the results is presented. The formulation of the problem of optimal control of the number of repaired and repaired railway wagons is proposed. Promising methods for solving this problem using numerical optimization methods, including those inspired by nature, are described. The results can be used in the tasks of constructing and analyzing mathematical models of dynamic systems, in the tasks of numerical modeling of transport systems and technological processes, in the tasks of optimizing the number of vehicles and improving the transportation process, as well as in the tasks of creating digital counterparts in the transport industry.

Source performance optimization in Cesiated mode in ROBIN

ITER reference design, an inductively coupled single driver RF (100 kW, 1 MHz)-source ROBIN is operational at IPR, Gandhinagar. The first phase of the operation yielded H- current density of 22–25 mA/cm2 and with electron to ion ratios > 1. The Cesium (Cs) consumption was very high compared to a similar source BATMAN operated at IPP, Garching. The lessons learned from the operational experience showed the operational limitations in presence of impurities and excessive evaporation of Cs into the source. Since then the source was disassembled, cleaned, and reassembled to enable the restart of operations under improved and controlled conditions. Recent experiments assisted by relevant diagnosis on the cleaned ROBIN source under controlled Cesiated conditions and improvements based on the lessons learned have resulted in achieving H- current densities > 30 mA/cm2 and electron to ion ratios < 1 and with Cs consumption reduced to ∼ 12 mg/hr. The role of plasma grid bias on the H- current densities and electron to ion ratios have been studied in detail. The observations and results related to Cs conditioning, source performance optimization, source parametric dependence on the beam, and related observations and findings related to the effects of the bias voltage on the source performance shall be presented and discussed.

Mechanisms of Offshore Solid and Liquid Freshwater Flux from the East Greenland Current

Abstract The mechanisms that control the export of freshwater from the East Greenland Current, in both liquid and solid form, are explored using an idealized numerical model and scaling theory. A regional, coupled ocean–sea ice model is applied to a series of calculations in which key parameters are varied and the scaling theory is used to interpret the model results. The offshore ice flux, occurring in late winter, is driven primarily by internal stresses and is most sensitive to the thickness of sea ice on the shelf coming out of Fram Strait and the strength of alongshore winds over the shelf. The offshore liquid freshwater flux is achieved by eddy fluxes in late summer while there is an onshore liquid freshwater flux in winter due to the ice–ocean stress, resulting in only weak annual mean flux. The scaling theory identifies the key nondimensional parameters that control the behavior and reproduces the general parameter dependence found in the numerical model. Climate models predict that winds will increase and ice export from the Arctic will decrease in the future, both of which will lead to a decrease in the offshore flux of sea ice, while the influence on liquid freshwater may increase or decrease, depending on the relative changes in the onshore Ekman transport and offshore eddy fluxes. Additional processes that have not been considered here, such as more complex topography and synoptic wind events, may also contribute to cross-shelf exchange. Significance Statement The purpose of this study is to provide a basic understanding of what controls the flux of sea ice and low-salinity water from the East Greenland shelf into the interior of the Greenland and Iceland Seas. This is a potentially important process since it has been shown that sufficient freshening of the surface waters in the interior of the Nordic seas can inhibit deep convection and the associated air–sea heat flux and water mass transformation. A combination of idealized computer models and basic theory indicates that the fluxes of liquid and solid freshwater are controlled by different mechanisms and occur at different times of the year. Accurate representation in climate models will require representation of small-scale processes such as mesoscale eddies and gradients of ice thickness across the shelf.

Rydberg-atom acceleration by circular Airy laser pulses.

Circular Airy pulsed beams are introduced to significantly optimize the acceleration of neutral Rydberg atoms. Compared with the conventional pulsed Gaussian beams used in the previous report, the circular Airy structure abruptly self-focuses and subsequently propagates with weak diffraction, resulting in a much higher accelerating efficiency for both radial and longitudinal velocities, as well as a longer accelerating range along the propagation axis. The parameter dependencies of the beams on the acceleration are also analyzed.

Forward dijet production at the LHC within an impact parameter dependent TMD approach

We investigate possible signatures of gluon saturation using forward p + A → j + j + X di-jet production processes at the Large Hadron Collider. In the forward rapidity region, this is a highly asymmetric process where partons with large longitudinal momentum fraction x in the dilute projectile are used as a probe to resolve the small x partonic content of the dense target. Such dilute-dense processes can be described in the factorization framework of Improved Transverse Momentum Distributions (ITMDs). We present a new model for ITMDs where we explicitly introduce the impact parameter (b) dependence in the ITMDs, to properly account for the nuclear enhancement of gluon saturation effects, and discuss the phenomenological consequences for p − Pb, p − Xe and p − O collisions at the LHC. While the case of p − p and e − p collisions is used to fix the model parameters, we find that, on average, the nuclear enhancement of the saturation scale is noticeably weaker than expected from naive scaling with a simple dependence on the atomic number. Since our model explicitly accounts for event-by-event fluctuations of the nuclear geometry, it can also be applied to study forward central correlations in p − A collisions.

An in vitro experimental investigation of oscillatory flow in the cerebral aqueduct

This in vitro study aims at clarifying the relation between the oscillatory flow of cerebrospinal fluid (CSF) in the cerebral aqueduct, a narrow conduit connecting the third and fourth ventricles, and the corresponding interventricular pressure difference. Dimensional analysis is used in designing an anatomically correct scaled model of the aqueduct flow, with physical similarity maintained by adjusting the flow frequency and the properties of the working fluid. The time-varying pressure difference across the aqueduct corresponding to a given oscillatory flow rate is measured in parametric ranges covering the range of flow conditions commonly encountered in healthy subjects. Parametric dependences are delineated for the time-averaged pressure fluctuations and for the phase lag between the transaqueductal pressure difference and the flow rate, both having clinical relevance. The results are validated through comparisons with predictions obtained with a previously derived computational model. The parametric quantification in this study enables the derivation of a simple formula for the relation between the transaqueductal pressure and the stroke volume. This relationship can be useful in the quantification of transmantle pressure differences based on non-invasive magnetic-resonance-velocimetry measurements of aqueduct flow for investigation of CSF-related disorders.

Enhancing magnetically driven microswimmer velocity via low Reynolds number hydrodynamic interactions

The motion of comoving magnetic microswimmers is modeled by considering the inter-hydrodynamic interactions (HI) under low Reynolds number conditions. The microswimmer is a two-link design consisting of a magnetic head attached to a slender tail via a torsional spring, and it is driven by an external planar oscillatory magnetic field. The inter-HI considered are the head-head and tail-tail interactions. The propulsion velocity for the comoving mode is calculated and compared with that of an isolated mode. The comparative results show that the comoving mode velocity can be either similar or greater than the isolated mode, depending on the actuation frequency. The parametric dependency results show that the velocity generated in comoving mode depends on the average separation distance and length-to-width ratio of the tail. For proof of concept, a low-cost fabrication protocol is implemented to design a millimeter-sized magnetic flagellated swimmer. The experimental result shows that the comoving swimming mode generates larger velocity in comparison to isolated swimming.

Condensation and evaporation of boson stars

Axion-like particles, including the QCD axion, are well-motivated dark matter candidates. Numerical simulations have revealed coherent soliton configurations, also known as boson stars, in the centers of axion halos. We study evolution of axion solitons immersed into a gas of axion waves with Maxwellian velocity distribution. Combining analytical approach with controlled numerical simulations we find that heavy solitons grow by condensation of axions from the gas, while light solitons evaporate. We deduce the parametric dependence of the soliton growth/evaporation rate and show that it is proportional to the rate of the kinetic relaxation in the gas. The proportionality coefficient is controlled by the product of the soliton radius and the typical gas momentum or, equivalently, the ratio of the gas and soliton virial temperatures. We discuss the asymptotics of the rate when this parameter is large or small.

On Continuous Parameter Dependence of Roots of Analytic Functions

Let An(Ω)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {A}}_n(\\Omega )$$\\end{document} be the set of analytic functions on a domain Ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega $$\\end{document} of the complex plane which have n roots in Ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega $$\\end{document}, counted with multiplicity. In this note we consider functions in An(Ω)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {A}}_n(\\Omega )$$\\end{document} which depend continuously on a parameter. A simple short proof shows that the set of roots in the Hausdorff metric depends continuously on the parameter. If the parameter space is connected and all roots are known to lie in one of two disjoint open subsets Ω1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega _1$$\\end{document}, Ω2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega _2$$\\end{document} of the complex plane, then the number of the roots, counted with multiplicity, in Ω1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega _1$$\\end{document} and Ω2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega _2$$\\end{document}, respectively, is independent of the parameter. Each set of roots generates a unique monic polynomial. It is shown that the map which associates with each function in An(Ω)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {A}}_n(\\Omega )$$\\end{document} the corresponding monic polynomial is continuous when An(Ω)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {A}}_n(\\Omega )$$\\end{document} is equipped with the topology of uniform convergence on compact subsets of Ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega $$\\end{document}. Possible applications are indicated.

Optimal data compression for Lyman-α forest cosmology

ABSTRACT The Lyman-α three-dimensional correlation functions have been widely used to perform cosmological inference using the baryon acoustic oscillation scale. While the traditional inference approach employs a data vector with several thousand data points, we apply near-maximal score compression down to tens of compressed data elements. We show that carefully constructed additional data beyond those linked to each inferred model parameter are required to preserve meaningful goodness of fit tests that guard against unknown systematics, and to avoid information loss due to non-linear parameter dependences. We demonstrate, on suites of realistic mocks and Data Release 16 data from the Extended Baryon Oscillation Spectroscopic Survey, that our compression approach is lossless and unbiased, yielding a posterior that is indistinguishable from that of the traditional analysis. As an early application, we investigate the impact of a covariance matrix estimated from a limited number of mocks, which is only well conditioned in compressed space.

Wave dispersion in a phononic metaplate with Boater-like cells

Meta-structure based on acoustic-mismatch among different materials shows distinct properties and also leads potential damage at the multi-material interfaces under complex loading conditions. In this paper, a phononic metaplate with Boater-like cells is proposed based on the concept of acoustic black hole and vibrator-plate models with the aim to explore the possibility of multi-acoustic meta-phenomena in a mono metaplate. Firstly, the proposed model is introduced and the governing equations for wave dispersion are formulated. Then the band structures are investigated. The wave dispersion at the double degeneracy points, Dirac-like cone, as well as bi-refraction are explored. At last, parameter dependence of band gaps is analyzed. The results indicate that multi-acoustic meta-phenomena could be realized in this phononic metaplate with Boater like cells, including bi-refraction and formation of band gaps. Considering low-cost and easily manufactured, the prototype in this paper provides a simpler but effective pattern for the metaplate design.

Optimizing strategy for the discovery of compositionally-biased or low-complexity regions in proteins

Proteins can contain tracts dominated by a subset of amino acids and that have a functional significance. These are often termed ‘low-complexity regions’ (LCRs) or ‘compositionally-biased regions’ (CBRs). However, a wide spectrum of compositional bias is possible, and program parameters used to annotate these regions are often arbitrarily chosen. Also, investigators are sometimes interested in longer regions, or sometimes very short ones. Here, two programs for annotating LCRs/CBRs, namely SEG and fLPS, are investigated in detail across the whole expanse of their parameter spaces. In doing so, boundary behaviours are resolved that are used to derive an optimized systematic strategy for annotating LCRs/CBRs. Sets of parameters that progressively annotate or ‘cover’ more of protein sequence space and are optimized for a given target length have been derived. This progressive annotation can be applied to discern the biological relevance of CBRs, e.g., in parsing domains for experimental constructs and in generating hypotheses. It is also useful for picking out candidate regions of interest of a given target length and bias signature, and for assessing the parameter dependence of annotations. This latter application is demonstrated for a set of human intrinsically-disordered proteins associated with cancer.

Analysis of response signals to minimally invasive laser modulation in laser cutting

AbstractA robust real‐time monitoring system for the laser cutting process has been targeted by researchers and users for several decades without significant breakthrough. The use of coaxial photodiodes provides a cost‐effective and straightforward system; however, the assessment of the process state based on the spatially integrated detected signals can lead to misinterpretation due to the numerous and interacting parameter dependencies of the signals. To obtain a clear correlation of the signals to the process state, minimally invasive laser modulation stimulates characteristic state‐dependent response signals. In this study, the response signals to a laser power modulation are analyzed in the visible and infrared range. Furthermore, a spatially and temporally resolved analysis of the process response is enabled by means of high‐speed videography. This provides a comprehensive understanding of the process state in terms of temperature and geometry response to the modulation and offers a reliable exploitation of process emissions for real‐time monitoring and control applications.

Predicting micropollutant removal through nanopore-sized membranes using several machine-learning approaches based on feature engineering.

Predicting the efficacy of micropollutant separation through functionalized membranes is an arduous endeavor. The challenge stems from the complex interactions between the physicochemical properties of the micropollutants and the basic principles underlying membrane filtration. This study aimed to compare the effectiveness of a modest dataset on various machine learning tools (ML) tools in predicting micropollutant removal efficiency for functionalized reverse osmosis (RO) and nanofiltration (NF) membranes. The inherent attributes of both the micropollutants and the membranes are utilized as input factors. The chosen ML tools are supervised algorithm (adaptive network-based fuzzy inference system (NF), linear regression framework (linear regression (LR)), stepwise linear regression (SLR) and multivariate linear regression (MVR)), and unsupervised algorithm (support vector machine (SVM) and ensemble boosted tree (BT)). The feature engineering and parametric dependency analysis revealed that characteristics of micropollutants, such as maximum projection diameter (MaxP), minimal projection diameter (MinP), molecular weight (MW), and compound size (CS), exhibited a notably positive impact on the correlation with removal efficiency. Model combination with key variables demonstrated high prediction accuracy in both supervised and unsupervised ML for micropollutant removal efficiency. An NF-grid partitioning (NF-GP) model achieved the highest accuracy with an R 2 value of 0.965, accompanied by low error metrics, specifically an RMSE and MAE of 3.65. It is owed to the handling of the complex spatial and temporal aspects of micropollutant data through division into consistent subsets facilitating improved identification of rejection efficiency and relationships. The inclusion of inputs with both negative and positive correlations introduces variability, amplifies the system responsiveness, and impedes the precision of predictive models. This study identified key micropollutant properties, including MaxP, MinP, MW, and CS, as crucial factors for efficient micropollutant rejection during real-time filtration applications. It also allowed the design of pore size of self-prepared membranes for the enhanced separation of micropollutants from wastewater.