Outer Boundary Research Articles

Experimental study of frosting characteristics of trace water vapor under cryogenic wind tunnel conditions

In cryogenic wind tunnels, the working fluid mixed with trace amounts of water vapor may form frost on the test model, which could affect the testing results. To investigate the frosting phenomenon under trace water condition, an experimental system is built for visualizing the frosting process on a cryogenic surface. The effects of variable factors on frost formation are analyzed focusing on the growth characteristics of frost layer. Under trace water and cryogenic surface conditions, the water vapor desublimates into crystals without obvious condensation. As the surface temperature increases from −183 ℃ to −123 ℃, the frost becomes thicker and more porous due to the thinner outer boundary layer. When the water vapor content rises from 30 ppm to 500 ppm, the frost morphology transforms from a flat layer to frost clumps with visible dendritic structure. Additionally, the decrease in nitrogen flow temperature and the increases in ambient pressure and surface roughness of the cryogenic surface are conducive to the development of the branches on the frost crystal, which accelerate the growth of the frost layer. Furthermore, a dimensionless correlation is proposed for predicting the frost thickness under cryogenic and trace water conditions, with an overall error within ±20 %.

Analysis of fluid flow characteristics in spherical nonlinear seepage flow model for dual-porous reservoir with the elastic outer boundary

Analysis of fluid flow characteristics in spherical nonlinear seepage flow model for dual-porous reservoir with the elastic outer boundary

3D cell aggregates amplify diffusion signals.

Biophysical models can predict the behavior of cell cultures including 3D cell aggregates (3DCAs), thereby reducing the need for costly and time-consuming experiments. Specifically, mass transfer models enable studying the transport of nutrients, oxygen, signaling molecules, and drugs in 3DCA. These models require the defining of boundary conditions (BC) between the 3DCA and surrounding medium. However, accurately modeling the BC that relates the inner and outer boundary concentrations at the border between the 3DCA and the medium remains a challenge that this paper addresses using both theoretical and experimental methods. The provided biophysical analysis indicates that the concentration of molecules inside boundary is higher than that at the outer boundary, revealing an amplification factor that is confirmed by a particle-based simulator (PBS). Due to the amplification factor, the PBS confirms that when a 3DCA with a low concentration of target molecules is introduced to a culture medium with a higher concentration, the molecule concentration in the medium rapidly decreases. The theoretical model and PBS simulations were used to design a pilot experiment with liver spheroids as the 3DCA and glucose as the target molecule. Experimental results agree with the proposed theory and derived properties.

Analysis of a multiphase free boundary problem

In this paper, we investigate a free boundary problem relevant in several applications, such as tumor growth models. Our problem is expressed as an elliptic equation involving discontinuous nonlinearities in a specified domain with a moving boundary. We establish the existence and uniqueness of solutions and provide a qualitative analysis of the free boundaries generated by the nonlinear term (inner boundaries). Furthermore, we analyze the dynamics of the outer region boundary. The final result demonstrates that under certain conditions, our problem is solvable in the neighborhood of a radial solution.

Modeling Cassini UVIS Interplanetary Hydrogen Lyα Observations from 1999 to 2017

The Cassini Orbiter Ultraviolet Imaging Spectrograph (UVIS) obtained interplanetary hydrogen Lyα observations from 1999 to 2017, with mid-2004 to 2017 observations obtained from Saturn orbit. During its Saturn orbital phase, the spacecraft moved from mostly downwind and sidewind in the heliosphere to upwind. We analyze the full set of observations with our existing hot hydrogen density model with a solar illumination model most recently used to study Solar and Heliospheric Observatory Solar Wind Anisotropy Experiment data and selected Cassini UVIS observations from 2003 to 2004. We find general agreement between data and model, but with evidence for a decline in UVIS Lyα sensitivity, with a significant decline in 2002 June during a starburn event and an overall roughly linear decline in sensitivity. While earlier work by Pryor et al. fit the UVIS Lyα data from 2003 to 2004 with a hydrogen density in the outer heliosphere (but after filtration at outer heliospheric boundaries) of 0.085 cm−3 using the UVIS laboratory sensitivity calibration, including the sensitivity decline found here leads to a revised hydrogen density estimate of n H = 0.14 ± 0.03 cm−3. This density estimate is consistent with a recent neutral hydrogen density estimate near the termination shock of 0.127 ± 0.015 cm−3 based on models of observations of pick-up hydrogen ions from the New Horizons spacecraft.

Simulation of dynamics of rotating weakly ionized plasmas

In this paper, we present a simulation study on the generation of rotating gas in a cylindrical chamber, which contains weakly ionized gas with charge to neutral density ratio (10−6−10−3). In this chamber, a radial current component of current density, Jr, is driven by an external electric potential difference between the inner and the outer radial boundaries, and a static magnetic field B0 is imposed in the axial direction. The charged particles are accelerated in the azimuthal direction by the Lorentz force Jr×B0. The neutrals then gain an azimuthal acceleration through ion–neutral collisions. The centrifugal force increases as the azimuthal speed increases. In the simulation, a strong centrifugal acceleration of 1011 m/s2 is achieved with an azimuthal speed of 105 m/s. A density gradient is developed to balance the centrifugal force, and the density at the outer radial boundary can reach 1025−1026 m−3.

Identification of Galaxy Protoclusters Based on the Spherical Top-hat Collapse Theory

We propose a new method for finding galaxy protoclusters that is motivated by structure formation theory and also directly applicable to observations. We adopt the conventional definition that a protocluster is a galaxy group whose virial mass M vir < M cl at its epoch, where M cl = 1014 M ⊙, but would exceed that limit when it evolves to z = 0. We use the critical overdensity for complete collapse at z = 0 predicted by the spherical top-hat collapse model to find the radius and total mass of the regions that would collapse at z = 0. If the mass of a region centered at a massive galaxy exceeds M cl, the galaxy is at the center of a protocluster. We define the outer boundary of a protocluster as the zero-velocity surface at the turnaround radius so that the member galaxies are those sharing the same protocluster environment and showing some conformity in physical properties. We use the cosmological hydrodynamical simulation Horizon Run 5 (HR5) to calibrate this prescription and demonstrate its performance. We find that the protocluster identification method suggested in this study is quite successful. Its application to the high-redshift HR5 galaxies shows a tight correlation between the mass within the protocluster regions identified according to the spherical collapse model and the final mass to be found within the clusters at z = 0, meaning that the regions can be regarded as the bona fide protoclusters with high reliability. We also confirm that the redshift-space distortion does not significantly affect the performance of the protocluster identification scheme.

Improved modelling of SEP event onset within the WSA–Enlil–SEPMOD framework

Multi-spacecraft observations of solar energetic particle (SEP) events not only enable a deeper understanding and development of particle acceleration and transport theories but also provide important constraints for model validation efforts. However, because of computational limitations, a given physics-based SEP model is usually best suited to capture a particular phase of an SEP event, rather than its whole development from onset through decay. For example, magnetohydrodynamic (MHD) models of the heliosphere often incorporate solar transients only at the outer boundary of their so-called coronal domain – usually set at a heliocentric distance of 20–30 R⊙. This means that particle acceleration at coronal mass ejection (CME)-driven shocks is also computed from this boundary onwards, leading to simulated SEP event onsets that can be many hours later than observed, since shock waves can form much lower in the solar corona. In this work, we aim to improve the modelled onset of SEP events by inserting a “fixed source” of particle injection at the outer boundary of the coronal domain of the coupled WSA–Enlil 3D MHD model of the heliosphere. The SEP model that we employ for this effort is Solar Energetic Particle MODel (SEPMOD), a physics-based test-particle code based on a field line tracer and adiabatic invariant conservation. We apply our initial tests and results of SEPMOD’s fixed-source option to the 2021 October 9 SEP event, which was detected at five well-separated locations in the inner heliosphere – Parker Solar Probe, STEREO-A, Solar Orbiter, BepiColombo, and near-Earth spacecraft.

A locally conservative staggered least squares method on polygonal meshes

&lt;abstract&gt;&lt;p&gt;In this paper, we propose a novel staggered least squares method for elliptic equations on polygonal meshes. Our new method can be flexibly applied to rough grids and allows hanging nodes, which is of particular interest in practical applications. Moreover, it offers the advantage of not having to deal with inf-sup conditions and yielding positive definite discrete problems. Optimal a priori error estimates in energy norm are derived. In addition, a superconvergent estimates in energy norm are also developed by employing variational error expansion. The main difficulty involved here is to show the $ L^2 $ norm error estimates for the potential variable, where duality argument and the superconvergent estimates are the key ingredients. The single valued flux over the outer boundary of the dual partition enables us to construct a locally conservative flux. Numerical experiments confirm the theoretical findings and the performance of the adaptive mesh refinement guided by the least squares functional estimator are also displayed.&lt;/p&gt;&lt;/abstract&gt;

Joint mode selection and resource allocation to flexibly guarantee quality of service for downlink MISO-NOMA systems

Non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) detection, knownas SIC NOMA, enjoys higher spectral efficiency (SE), but suffers increased processing complexity and additional error propagation compared to Non-SIC NOMA,in whichthe receivers directly detect their own signalsfrom thesuperposed signalwithout SIC detection. We propose a joint Mode Selection and Power Allocation (MSPA) scheme that can flexibly realize different kinds of tradeoffs while guaranteeing minimum rate requirements (MRRs) for two-user MISO-NOMA downlink. Specifically, we first obtain rate region boundaries that guarantee two users’ MRRs for two candidatemodes: maximum-ratio transmission (MRT)/SIC NOMA and minimum mean square error beamforming (MMSE-BF)/Non-SIC NOMA. We then construct an expression of power allocation factors (transmit power factors) that can satisfy the two users’ MRRs for MRT/SIC NOMA (MMSE-BF/Non-SIC NOMA) by introducing a parameter λ. Finally, we achieve outer boundary of the union ofthe two modes' rate regionsby mode selection and derive expected users' rates on it. Numerical results demonstrate that the proposed MSPA can improve SE and flexibly achieve different kinds of tradeoffs by adjusting λ, while guaranteeing the two users’ MRRs simultaneously for high signal to noise ratio (SNR) scenario and alternately guaranteeing the two users’ MRRs for low SNR scenario.

Feedback Stabilization of a Two-Fluid Surface Tension System Modeling the Motion of a Soap Bubble at Low Reynolds Number: The Two-Dimensional Case

The aim of this paper is to design a feedback operator for stabilizing in infinite time horizon a system modeling the interactions between a viscous incompressible fluid and the deformation of a soap bubble. The latter is represented by an interface separating a bounded domain of mathbb {R}^2 into two connected parts filled with viscous incompressible fluids. The interface is a smooth perturbation of the 1-sphere, and the surrounding fluids satisfy the incompressible Stokes equations in time-dependent domains. The mean curvature of the surface defines a surface tension force which induces a jump of the normal trace of the Cauchy stress tensor. The response of the fluids is a velocity trace on the interface, governing the time evolution of the latter, via the equality of velocities. The data are assumed to be sufficiently small, in particular the initial perturbation, that is the initial shape of the soap bubble is close enough to a circle. The control function is a surface tension type force on the interface. We design it as the sum of two feedback operators: one is explicit, the second one is finite-dimensional. They enable us to define a control operator that stabilizes locally the soap bubble to a circle with an arbitrary exponential decay rate, up to translations, and up to non-contact with the outer boundary.

Comparing the Past and Present Traces of Cultural Assets with the Reference of Literature and Architecture Arts to Each Other: Milas Greek Orthodox Church and Its Surroundings in Resat Nuri Güntekin s Novel Ateş Gecesi (Night of Fire)

Milas district, located in the province of Muğla, is a rich settlement in terms of historical and cultural monuments. Among the mentioned monuments in the settlement, especially religious monuments exhibit a great diversity and cover a wide range of historical periods. This diversity and historical range are directly related to cultural and religious communities that have lived in the region. However, some religious monuments in the district are disappearing or losing their architectural identities to a great extent due to reasons such as lack of preservation awareness, property issues, and neglect by users. One of the most important religious monuments that has largely lost its architectural identity in the Milas district is the Milas Greek Orthodox Church. This monument holds significant importance in Milas's cultural and religious inventory. The monument and its surroundings are also described in some parts of the plots in terms of some architectural features in Reşat Nuri Güntekin's novel Ateş Gecesi (Night of Fire), which was serialized in Yedigün Magazine in 1940 and published as a book in 1942. Although it has largely lost its architectural identity today, the Milas Greek Orthodox Church is still frequently mentioned in local legends, city memories, place and location names, and city literature, as can be seen in the pages of the "Ateş Gecesi" novel. The study aims to document and evaluate the changes that the Milas Greek Orthodox Church and its surroundings have undergone from past to present in the light of the "Ateş Gecesi" novel. The study was conducted in three stages, which involved examining the spatial and architectural descriptions mentioned in the Ateş Gecesi Novel, focusing on the narratives related to the Milas Greek Orthodox Church and its surroundings, and documenting and evaluating the current conditions of the spatial and architectural descriptions mentioned in the focused narratives. As a result of the study, it was determined that the Milas Rum Orthodox Church and its surroundings had largely lost their architectural identity over approximately a century, from the time the novel was written to the present day. However, within the interior space of the church structure, many elements related to the original architectural identity are still present. In contrast, it is considered that the outer walls, garden arrangement, and boundaries of the structure have lost their original qualities. It was also found that very few examples of traditional residential buildings that constitute the regional context have survived to the present day. In addition to its cultural and religious identity, the Milas Rum Orthodox Church necessitates the development of a comprehensive architectural conservation approach for its historical and archaeological context, monument, and immediate surroundings. Therefore, it is considered crucial to plan the region between the Milas Rum Orthodox Church and Milas Kartal Gazinosu, taking into account the Çaputçu Han section, with a comprehensive conservation approach.

How to Perform Reliable IR Compensation in Electrocatalysis?

iR compensation is one of the most used techniques in electrochemical analysis, which is designed to correct the voltage loss between the working electrode and the reference electrode in the electrolyte (Rsolution).[1] It is conducted using two methods frequently, namely the after-the-scan and the on-the-fly methods. A factor is often engaged when performing the iR compensation, which is an empirical value (e.g., 80%~100%) chosen by researchers. After the compensation, the experimental data (mainly electrocatalytic indicators like overpotential and Tafel slope) can be greatly “improved”.[2] However, the abuse of iR compensation, especially in electrocatalysis studies, can generate misleading and exaggerated results.In this study, we present a detailed analysis of the applicability of the iR compensation technique in current electrocatalysis studies by revisiting the technical assumptions.[3] A few considerations are discussed. Firstly, it is pointed out that the resistance obtained from the electrochemical impedance spectroscopy is not always the resistance that needs to be compensated. The main reason is the involvement of the catalyst material resistance (Rcatalyst) and the contact resistance between the substrate and the catalyst material (Rcontact) (Figure 1). Depending on the types of activity (intrinsic activity, sample activity, electrode activity, and industrial activity) of interest, one should choose different resistance values. For example, only Rsolution should be compensated when studying the electrode activity, but both Rcontact and Rsolution should be compensated for sample activity analysis. Secondly, the resistance may be potential/time-dependent, meaning the value should be measured at the reaction condition, other than the often-used open circuit potential. Thirdly, the distribution of resistance on the catalyst surface sites is uneven, suggesting that one single value cannot be used for sites at different surface traits. Fourthly, most researchers use linear sweep voltammetry (LSV) where the current is always contributed by both the Faradic current and non-Faradic current. However, only the Faradic current should be compensated because non-Faradic current does not flow between the working and reference electrodes.Regarding these considerations and experimental methods, we further suggested a standard workflow to perform iR compensation in electrocatalysis studies.[3] Figure 1. Voltage loss across a three-electrode system with a modified working electrode and the corresponding equivalent circuit diagram. (1) surface of the substrate; (2) surface of the catalyst contacting the substrate; (3) surface of the catalyst contacting the electrolyte solution; (4) outer boundary of the diffuse layer; (5) junction of the reference electrode. Reference: Bard, A. J.; Faulkner, L. R. Electrochemical Methods: Fundamentals and Applications, 2nd ed.; John Wiley & Sons, Inc., 2001 Anantharaj, S.; Noda, S. J. Mater. Chem. A 2022, 10, 17, 9348– 9354 Zheng, W. ACS Energy Lett. 2023, 8, 4, 1952–1958 Figure 1

Analysis of potassium ion diffusion from neurons to capillaries: Effects of astrocyte endfeet geometry.

Neurovascular coupling (NVC) refers to a local increase in cerebral blood flow in response to increased neuronal activity. Mechanisms of communication between neurons and blood vessels remain unclear. Astrocyte endfeet almost completely cover cerebral capillaries, suggesting that astrocytes play a role in NVC by releasing vasoactive substances near capillaries. An alternative hypothesis is that direct diffusion through the extracellular space of potassium ions (K+ ) released by neurons contributes to NVC. Here, the goal is to determine whether astrocyte endfeet present a barrier to K+ diffusion from neurons to capillaries. Two simplified 2D geometries of extracellular space, clefts between endfeet, and perivascular space are used: (i) a source 1μm from a capillary; (ii) a neuron 15 μm from a capillary. K+ release is modelled as a step increase in [K+ ] at the outer boundary of the extracellular space. The time-dependent diffusion equation is solved numerically. In the first geometry, perivascular [K+ ] approaches its final value within 0.05 s. Decreasing endfeet cleft width or increasing perivascular space width slows the rise in [K+ ]. In the second geometry, the increase in perivascular [K+ ] occurs within 0.5s and is insensitive to changes in cleft width or perivascular space width. Predicted levels of perivascular [K+ ] are sufficient to cause vasodilation, and the rise time is within the time for flow increase in NVC. These results suggest that direct diffusion of K+ through the extracellular space is a possible NVC signalling mechanism.

Characterization of the Mean First-Passage Time Function Subject to Advection in Annular-like Domains

Cell migration in a biological medium towards a blood vessel is modeled, as a random process, sucessively inside an annulus (two-dimensional domain) and an annular cylinder (three-dimensional domain). The conditional probability function u for the cell moving inside such domains (tissue) fulfills by assumption a diffusion–advection equation that is subject to a Dirichlet boundary condition on the outer boundary and a Robin boundary condition on the inner boundary. The mean first-passage time (MFPT) function determined by u estimates the average time for the travelling cell to reach various interesting targets. The MFPT function fulfills a Poisson equation inside a domain with suitable boundary conditions, which give rise to various mathematical problems. The main novelty of this study is the characterization of such an MFPT function inside an annulus and an annular cylinder, which is subject to a Robin boundary condition on the inner boundary and a Dirichlet boundary condition on the outer one, and these are integral functions whose densities are the solution of an inhomogeneous system of linear integral equations.

Greedy knot selection algorithm for restricted cubic spline regression.

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one such method, for example, highly relevant to Cox proportional hazard regression model analysis. RCS regression uses third-order polynomials joined at knot points to model non-linear relationships. The standard approach is to place knots by a regular sequence of quantiles between the outer boundaries. A regression curve can easily be fitted to the sample using a relatively high number of knots. The problem is then overfitting, where a regression model has a good fit to the given sample but does not generalize well to other samples. A low knot count is thus preferred. However, the standard knot selection process can lead to underperformance in the sparser regions of the predictor variable, especially when using a low number of knots. It can also lead to overfitting in the denser regions. We present a simple greedy search algorithm using a backward method for knot selection that shows reduced prediction error and Bayesian information criterion scores compared to the standard knot selection process in simulation experiments. We have implemented the algorithm as part of an open-source R-package, knutar.

Classification of dendritic spiking neurons’ shape through clustering and machine learning techniques

A synapse is a specialized region between two adjacent neurons that allows information to be transmitted from one cell to another. The formation of these connections and transfer of signals via electrical impulses is a critical characteristic of neuronal cells. The synapse is formed by the axonal bouton on the axon side and the dendritic spine, a specialized outgrowth of the dendritic membrane, on the dendrite side. Dendritic spines exhibit diverse shapes and sizes, differing significantly across brain regions, cell categories, and animal species. Changes in dendritic spine morphology occur in neurodevelopmental and neurodegenerative ailments while also responding to external stimuli. Although deemed to facilitate synaptic plasticity, further investigation is essential for establishing the correlation between spine construction and its function. To address the issue in modern neurobiology of characterizing synapse morphology on 3D neuron images, the development of effective analytical methods is necessary. Our team has produced an open-source software solution for precise dendritic spine segmentation using 3D dendrite images. This software calculates the 10 most widely used 3D-adapted morphological features [1, 2] and enables classification and clustering of dendritic spine data sets to determine their shape. In addition to numerical features for describing the shape of a dendritic spine, researchers proposed using a histogram of chord lengths, known as the chord length distribution histogram (CLDH). This involves generating a set of random chords within the dendritic spine’s volume, connecting its outer boundaries and forming a histogram. By setting n=30 000, the probabilistic fluctuations of the histogram become insignificant. The derived metrics were then used for clustering and classifying the dataset. Classification based on predetermined morphological groups is a frequently used approach for analyzing the morphology of dendritic spines. This method involves categorizing spines into established groups such as thin, mushroom, and stubby. Experimenters generally perform classification in a semi-automated manner, leading to considerable error. We have created a spine categorization tool using a machine learning algorithm. The tool classifies spines based on a consensus reached by eight experts who manually labeled the training dataset. The accuracy of this method surpasses 77% when using classical morphological features and is comparable to expert labeling. The implementation of this approach reduces classification bias and complexity. Recent studies, including those using live microscopy in vitro and in vivo, indicate that dendritic spine shapes exhibit a continuum rather than distinct categories [3]. Therefore, it is essential to establish a dependable methodology for evaluating and examining the morphology of dendritic spines. We have created a clustering tool that establishes both the number of groups and their content based on data, rather than the experimenter’s discretion. This tool leverages the k-means and DBSCAN algorithms for its representation. Three clustering methods are presented to determine the number of clusters: the silhouette method, the elbow method, and a novel method, developed by the authors, based on the max class divergence criteria. The authors assume that cluster quality improves as clusters differ significantly in the number of mushroom/thin/stubby spine classes, as marked by experts. The benefit of this approach is that it considers the particular data type for clustering. Without this knowledge, assessing the quality of clustering is challenging. The use of the CLDH metric for clustering yielded a consistent and stable number of clusters (n=5) across all three methods described. These clusters contain dendritic spines that share similar shapes and have been validated by experts. In contrast, using classical metrics resulted in a variable cluster count ranging from n=4 to n=14. These findings suggest that the CLDH metric, with its complexity, provides enough information about synapse shape to enable precise clustering.

Computation of unsteady electromagnetic scattering about 3D complex bodies in free space with high-order difference potentials

We extend the previously developed high-order accurate method for acoustic scattering to electromagnetic scattering, i.e., from the scalar setting to a vector setting. First, the governing Maxwell's equations are reduced from their original first-order form to a system of second-order wave equations for the individual Cartesian components of electromagnetic field. In free space, these wave equations are uncoupled. Yet at the boundary of the scatterer, the variables that they govern (i.e., Cartesian field components) remain fully coupled via the boundary conditions that account for the specific scattering mechanism. Next, the wave equations are equivalently replaced with Calderon's boundary equations with projections obtained using the method of difference potentials and a compact high-order accurate scheme. The Calderon's boundary equations are combined with the boundary conditions and the overall system is solved by least squares. The resulting vector methodology (electromagnetic) inherits many useful properties of the scalar one (acoustic). In particular, it offers sub-linear computational complexity, does not require any special treatment of the artificial outer boundary, and has the capacity to solve multiple similar problems at a low individual cost per problem. We demonstrate the performance of the new method by computing the scattering of a given impinging wave about a double-cone hypersonic shape.

Simple pseudo-steady state productivity index correlations for infinite-conductivity horizontal wells based on a rigorous, semi-analytical model

Simple pseudo-steady state (PSS) productivity index (PI) correlations are developed for horizontal wells producing at a constant rate from a closed, rectangular reservoir based on a rigorous infinite-conductivity model (ICM). The main three correlations are functions of the half-length wellbore segments number (mt) only and mt can be determined by the general correlation, which is a function of dimensionless well length (LD). The correlations are developed by using a nonlinear regression technique (with zero error) based on over thousand semi-analytical runs for a rigorous ICM covering 90 cases of different well and reservoir configurations. The 90 cases are averaged with less than 5% error in the total pressure drop calculation for the most of them to reduce the number of correlations and to remove the slight effect of well penetration ratio (PR). The PSS PI correlations are simply used to calculate mt, average pressure drop at transient-state, average starting time of PSS, and average total pressure drop at the beginning of PSS. At PSS, the reservoir outer boundaries are dominant, and the pressure drop will depend on the temporal and the spatial time-independent functions. The simple PSS PI correlations have been verified, and can be easily implemented in a standard spreadsheet code.The results show that LD is directly proportional to PSS PI and more significant than reservoir thickness (h) on horizontal-well productivity evaluation, which confirms the principle of the economic feasibility for drilling horizontal well in the oil industry. The results also show that the horizontal-well productivity by this study is several times higher than its counterparts by the methods reported in the literature because the method used by this study is based on a rigorous infinite-conductivity solution where no significant pressure drop occurs, while the previous methods are based on approximate infinite-conductivity solutions (AICSs). Therefore, there is a big underestimation in productivity calculation by using the previous methods which crucially reflect on reservoir evaluation. The new correlations give accurate PSS PI for over 3000 cases of diverse well and reservoir configurations, besides giving a rough PSS PI for the other cases.

LANDSAT 9 IMAGERY BASED MANGROVE FOREST MAPPING USING MAXIMUM LIKELIHOOD CLASSIFIER AND SUPPORT VECTOR MACHINE ALGORITHM

The successful launch of Landsat 9 in 2021 emphasizes the commitment to the continuity of the Landsat mission to provide global medium resolution satellite records. The benefit of the availability of the Landsat dataset is the extraction of information related to mangrove forest cover through mapping, especially in Gili Lawang. The main challenge in mangrove mapping is selecting a classification method that provides the most accurate results. This article aims to explore the use of the Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM) algorithms in the context of mangrove mapping using Landsat 9 imagery on Gili Lawang. The two algorithms show differences in detecting the area of mangrove, non-mangrove and water bodies, respectively for SVM 371.89 ha, 58.11 ha, 3.73 ha; while the MLC algorithm is 328.88 ha, 98.41 ha, and 6.45 ha. The MLC algorithm identifies non-mangrove objects at the outer boundary of Gili Lawang, while SVM identifies the same area as mangrove objects due to the influence of the training area created and low separability. The SVM algorithm has better accuracy with a Kappa statistic of 0.85 compared to MLC with a value of 0.73.&#x0D; &#x0D; Keywords: Gili Lawang, Landsat 9, Mangrove, Support Vector Machine, Maximum Likelihood Classifier