Numerical Results Research Articles

Effects of steel bolts on retrofitting the buckling performance of storage rack system uprights

Storage rack systems, essential for product storage, encounter design challenges, particularly for uprights under axial loading. Despite being produced from thin-walled steel sheets, these systems are required to support excessive loads. Extensive research has focused on maximizing the load-bearing capacity of rack uprights in recent years. This study aims to enhance the axial load capacity of upright profiles through a retrofitting method of installing steel bolts and spacers. Experimental, numerical, and analytical evaluations were conducted to assess the effectiveness of bolt installation in enhancing axial strength of the uprights. Bolt installation altered buckling modes, suppressing distortional buckling. Results consistently showed an increase in axial load capacity with bolt installation, particularly notable in taller uprights. Comparison of experimental, numerical, and analytical results revealed good alignment, highlighting the positive impact of bolt installation on structural stability. Numerical analysis slightly underestimated experimental outcomes, especially for longer lengths, while the analytical approach showed a combination of overestimation and underestimation, with significant overestimation for longer lengths. The study concludes that bolt installation effectively increases the axial load capacity, especially for taller uprights. These findings offer remarkable insights on the positive effect of bolt installation for optimizing storage rack systems by enhancing structural stability and eliminating distortional buckling.

Analysis of mechanical response and failure characteristics of tunnels crossing active faults considering axial force and geometrical nonlinearity

Tunnels subjected to active fault dislocation may experience significant damage. This paper establishes a novel methodology and solution procedure for analyzing the mechanical response and failure characteristics of tunnels subjected to active fault dislocation based on an elastic foundation beam model. The proposed methodology includes axial, transverse, and vertical soil-tunnel interaction terms, in addition to geometrical nonlinearity and axial force terms in the governing equation. This approach has a significantly extended application range, effectively addressing the problems encountered in tunnels crossing active faults with diverse crossing angles, dip angles, and fault types. The proposed methodology is verified by comparison to a 3D FEM model with various fault types, experimental tests, and on-site case, and the results are in excellent quantitative and qualitative agreement with the numerical, experimental, and on-site results. When fault displacement is below 0.5m, disregarding geometric nonlinearity results in calculation errors of approximately 10% to 17% for peak axial force (Nmax), 18% to 22% for peak shear force (Vmax), and 20% to 30% for peak bending moment (Mmax). Finally, the responses caused by different factors, i.e., fault type, fault displacement, tunnel stiffness, and tunnel diameter, are investigated in detail to better understand tunnels crossing active faults. The results show that amongst the various fault types, the Vmax and the Mmax experienced by tunnels subjected to oblique slip-fault dislocation surpass those of other fault types, accompanied by the most extensive failure range. The augmentation of fault displacement, tunnel stiffness, and tunnel diameter precipitates a corresponding escalation in the Nmax, Vmax, Mmax, and failure range. Under oblique-slip fault dislocation, the tunnel undergoes an initial phase of shear failure, followed by tension-bending failure, delineated by distinct fault displacement thresholds of 0.1m and 0.2m, respectively. The proposed methodology provides the advantage of reliable stability analysis and design of tunnels crossing active faults.

Mechanism study on the influences of buffer osmotic pressure on microfluidic chip-based cell electrofusion.

Cell electrofusion is a key process in many research fields, such as genetics, immunology, and cross-breeding. The electrofusion efficiency is highly dependent on the buffer osmotic pressure properties. However, the mechanism by which the buffer osmotic pressure affects cell electrofusion has not been theoretically or numerically understood. In order to explore the mechanism, the microfluidic structure with paired arc micro-cavities was first evaluated based on the numerical analysis of the transmembrane potential and the electroporation induced on biological cells when the electrofusion was performed on this structure. Then, the numerical model was used to analyze the effect of three buffer osmotic pressures on the on-chip electrofusion in terms of membrane tension and cell size. Compared to hypertonic and isotonic buffers, hypotonic buffer not only increased the reversible electroporation area in the cell-cell contact zone by 1.7 times by inducing a higher membrane tension, but also significantly reduced the applied voltage required for cell electroporation by increasing the cell size. Finally, the microfluidic chip with arc micro-cavitieswas fabricated and tested for electrofusion of SP2/0 cells. The results showed that no cell fusion occurred in the hypertonic buffer. The fusion efficiency in the isotonic buffer was about 7%. In the hypotonic buffer, the fusion efficiency was about 60%, which was significantly higher compared to hypertonic and isotonic buffers. The experimental results were in good agreement with the numerical analysis results.

Data analysis of non-linear radiative electro-periodic MHD flow past a stretching sheet with activation energy impact

Electro-periodic Magneto-hydrodynamics (EPMHD), activation energy, and non-linear radiation are pivotal elements in engineering and industry also contribute to advancements in fields like heat transfer, materials science, and chemical engineering. Through similarity transformation, governing partial differential equations simplify into ordinary differential equations. Precise computational solutions are derived using the Nachtsheim-Swigert shooting iteration method (NSSIM) and the reliable 6th-order Runge-Kutta integration algorithm (RKIA). The profiles of velocities, temperatures, concentrations, skin friction, heat and mass transfer rate are presented by graphically. The novel aspect of this research is that thermal performance is enhanced by non-linear radiation by around 2.28%, whereas linear radiation only produces a 0.28% improvement in thermal performance. Also the mass transfer rate experiences a decrease of about 25.76% with increasing chemical reactions in the presence of activation energy and a more substantial 62.22% reduction in its absence, notably showing a comparatively milder decline of 36.46% in the presence of activation energy than in its absence. Furthermore, this study yields three novel linear regression equations, skillfully derived from the numerical and graphical results. This research have practical applications in understanding and optimizing processes involving fluid dynamics, such as the behavior of certain materials or substances subjected to stretching or deformation.

Construction optimization of spatial arch bridges based on inverse hanging and RGA method

Form-finding and construction process are complex for spatial arch bridge. To facilitate the design and construction of spatial arch bridge, an algorithm with combination of inverse hanging and real-coded genetic algorithm (RGA) method is proposed. The experimental device suitable for inverse hanging experiment of spatial arch bridge is firstly proposed. The experimental results are compared with the numerical results to validate the accuracy of proposed form-finding algorithm. The validated results indicated that the error which is mainly caused by measure error is below 5%. Then, the form-finding algorithm and RGA is combined to perform construction optimization for planar and spatial arch bridge. With the proposed optimization algorithm, the form-finding of spatial arch bridge is completed and the optimization of installation order of hangers can be performed based on the form-finding results. The tensioning force corresponding to different installation sequences is significantly different (546kN and 177kN). By using RGA, the max stress of arch is significantly decreased and generally below 100MPa. The RGA is efficient in optimize the installation sequence. The control value of tension force of all hangers can be computed by using the RGA and reverse construction simulation. The nonlinear effect and the influence of geometrical size on tensioning force can be automatically considered. The results of this study indicate that the proposed algorithm is an efficient and accurate method for the construction optimization of spatial arch bridges.

Characterization of detonation waves by simultaneous OH and NO planar laser-induced fluorescence

This study presents a thorough evaluation of the simultaneous planar laser-induced fluorescence (PLIF) on hydroxyl (OH) radicals and nitric oxide (NO), for characterizing hydrogen detonation fronts. The study combines experimental and numerical results to evaluate the benefits and drawbacks of different visualization strategies, namely OH-PLIF alone, NO-PLIF alone, OH-PLIF + shock det. (comparable to simultaneous OH-PLIF and schlieren), and combined OH- and NO-PLIF. Main findings are: (i) For the first time, simultaneous single-shot OH- and NO-PLIF visualizations are demonstrated on detonation waves for three mixtures with varying stability levels: Mixture (a) 2H2-O2-3.76Ar, Mixture (b) 2H2-O2-3.76N2, and Mixture (c) 3H2-CH4-3.5O2-3.76Ar; (ii) the simultaneous visualization evidences the self-similarity of both techniques, with a clear interlock of OH-PLIF imaging into NO-PLIF imaging. This means that the structure of the OH-reaction zone, typically visualized from OH-PLIF, can be accurately described from NO-PLIF imaging alone, from which induction zones can also be visualized. In addition, both can clearly depict the wrinkling of the front and the presence of unburned pockets; (iii) the effectiveness of the four visualization strategies at characterizing the detonation wave of a H2-O2-3.76Ar mixture is determined using ZND and spectroscopic simulations. Interestingly, the induction zone (Δi) is more accurately predicted by NO-PLIF (3% error) than with the combined OH + shock det. (10% error). This study highlights the potential of NO-PLIF diagnostic in characterizing detonation waves with low levels of confinement (i.e., d/λ>>>1) both qualitatively (e.g., reaction zone structure) and quantitatively (e.g., Δi measurements) using a single diagnostic. Additionally, the simultaneous OH- and NO-PLIF diagnostic may offer significant advantages in characterizing the detonation waves in engine-relevant conditions (i.e., in complex geometries with unburned pockets or local quenching events), as combining both diagnostics enables to discriminate unburned pockets and local quenching events.

Empowering geological data analysis with specialized software GIS modules

This research is devoted to the development of a geographic information system (GIS) for the analysis of geological data. It presents two specialized software modules designed to solve complex geological problems related to potential progress to disturbed masses and magnetotelluric sounding. These modules are integrated into the QGIS environment, offering efficient data processing and analysis capabilities, contributing to a deeper understanding of geological structures. The study presents a mathematical model for the problem of magnetotelluric sounding (MTS) and the continuation of potentials towards the perturbed masses, demonstrating numerical results using the developed algorithm. To confirm the accuracy of the model, a comparative analysis was carried out with empirical data for various chemical elements, which showed high accuracy, especially at shallow depths, with an error rate of less than 2%. In addition, the study highlights the importance of powerful GIS for the analysis and interpretation of geological data, including geochemical, geophysical and remote sensing information. The advanced functionality of QGIS simplifies data processing and visualization, which makes it an invaluable tool for geologists and researchers.

Numerical modeling of the fracturing mechanisms of unconsolidated sand reservoirs under water injection

Produced Water Re-Injection is a standard practice in oil and gas operations. When performed at sufficiently high pressures, it can trigger the fracturing of the reservoir, which should be controlled to stimulate the formation without compromising its safety. While the mechanisms of the hydraulic fracturing of brittle rocks are well-understood, this understanding is more challenging in the case of unconsolidated sand reservoirs. Recent experimental studies indicate that pseudofractures in such formations primarily result from shear banding and flow channelization. There is a need for further interpretation of the experimental findings through numerical models that account for the proper physical phenomena. For that, a coupled finite element model of water percolation, particle transport and strain localization is developed to replicate the experiments of radial injection of water in mixtures of sand and fines by Nguyen et al., 2022: An experimental setup with radial injection cell for investigation of fracturing in unconsolidated sand reservoirs under fluid injection. Journal of Petroleum Science and Engineering 213:11036. To simulate shear banding, the model accounts for strain-softening behavior and introduces material imperfections in a few weak elements. Particle mobilization starts once a critical fluid velocity is reached and permeability is assumed to be a function of particle concentration. The numerical models can replicate the geometry of the observed radial pseudofractures, as well as the measured fracturing pressures. They also qualitatively capture the effects of the initial stress state on the fracturing pressure, the fracture length and on the permeability increases during the fracturing regime as observed in the laboratory tests. Notably, the numerical results gave hints on the role of the coupling between strain localization and particle transport on the formation of the pseudofractures. These findings are used to propose an updated conceptual model for the hydraulic fracturing of sand packs.

A penta-linear backbone model for unbonded post-tensioned concrete masonry shear walls

Unbonded post-tensioned concrete masonry (UPCM) shear walls are an effective seismic force resisting system due to their ability to mitigate expected damage through their self-centering capabilities. A few design procedures were proposed to predict the in-plane flexural response of UPCM walls, albeit following only basic mechanics and/or extensive iterative methods. Such procedures, however, may not be capable of capturing the complex nonlinear relationships between different parameters that affect UPCM walls’ behavior or are tedious to be adopted for design practice. In addition, the limited datasets used to validate these procedures may cast doubt on their accuracy and validity for new, unseen data, further hindering their adoption by practitioners and design standards. To address these issues, an experimentally-validated nonlinear numerical model was adopted in this study and subsequently employed to simulate 95 UPCM walls with different design parameters to compensate for the lack of relevant experimental data in the current literature. Guided by mechanics and using this database, an evolutionary algorithm, multigene genetic programming (MGGP), was adopted to uncover the relationships controlling the response of UPCM walls, and subsequently develop simplified closed-form wall behavior prediction expressions. Specifically, through integrating MGGP and basic mechanics, a penta-linear backbone model was developed to predict the load-displacement backbone for UPCM walls up to 20% strength degradation. Compared to existing predictive procedures, the prediction accuracy of the developed model and its closed-form nature are expected to facilitate better understanding of such wall behaviors and subsequently open the gate to further incorporate other experimental and numerical results to ultimately incorporate UPCM in mainstream designs in the near future.

A Breakthrough Authentication Protocol for Fortifying IoT-Cloud Security

Abstract: Physical layer key generation, leveraging the reciprocity and randomness of wireless fading channels, has garnered significant research interest in recent years. While theoretical studies have demonstrated its potential to generate informationtheoretically secure keys, challenges remain in translating theory into practice. This paper provides an overview of the physical layer key generation process and discusses its practical challenges. Various passive and active attacks are analyzed and evaluated through numerical studies. A new key generation scheme using random probing signals and combining usergenerated randomness with channel randomness is introduced to counteract active attacks. Numerical results demonstrate that the proposed scheme achieves higher security strength than existing schemes using constant probing signals under active attacks. Secret-key generation relying on wireless channel reciprocity is an intriguing solution as it can be efficiently implemented at the physical layer of emerging wireless communication networks, while providing information-theoretic security guarantees. In this paper, we investigate and compare the secret-key capacity based on the sampling of the entire complex channel state information (CSI) or only its envelope, the received signal strength (RSS).

Experimental and numerical study on vibration response, VIV mechanism and aerostatic coefficients of triple-separated decks under different vertical distances

In this study, aerodynamic interference effects (AIE) on the vibration response, aerostatic coefficient (AC) and vortex-induced vibration (VIV) mechanism of the triple-separated decks under different incoming wind directions and vertical distances were investigated via wind tunnel tests and numerical simulations, respectively. The test results show that the AIE increases the displacement of VIV, and the VIV responses reaches maximum value under S/H = −1.0 (S is the vertical distance between the centers of RB and HB decks, and H is the height of RB deck) when the RB deck is on the windward side (the maximum displacements of VIV are 193.86% and 37.30% higher than the case of single RB deck and S/H = 0.0, respectively). The pressure distribution and flow structure show that the scale of vortex that alternately shed off from the tail of the deck becomes stronger and the fluctuating pressure coefficient increases under AIE, which increase the VIV amplitude of the RB deck and cause the VIV of HB decks. The experimental and numerical results indicated that the aerostatic coefficients (AC) of the leeward girder are more affected by the AIE. The interference factor (IF) of drag coefficient (CD) is far less than 1.0 under the case of F-5 (S/H = 0.0).

Structure-preserving algorithms for guiding center dynamics based on the slow manifold of classical Pauli particle

The classical Pauli particle (CPP) serves as a slow manifold, substituting the conventional guiding center dynamics. Based on the CPP, we utilize the averaged vector field (AVF) method in the computations of drift orbits. Demonstrating significantly higher efficiency, this advanced method is capable of accomplishing the simulation in less than one-third of the time of directly computing the guiding center motion. In contrast to the CPP-based Boris algorithm, this approach inherits the advantages of the AVF method, yielding stable trajectories even achieved with a tenfold time step and reducing the energy error by two orders of magnitude. By comparing these two CPP algorithms with the traditional RK4 method, the numerical results indicate a remarkable performance in terms of both the computational efficiency and error elimination. Moreover, we verify the properties of slow manifold integrators and successfully observe the bounce on both sides of the limiting slow manifold with deliberately chosen perturbed initial conditions. To evaluate the practical value of the methods, we conduct simulations in non-axisymmetric perturbation magnetic fields as part of the experiments, demonstrating that our CPP-based AVF method can handle simulations under complex magnetic field configurations with high accuracy, which the CPP-based Boris algorithm lacks. Through numerical experiments, we demonstrate that the CPP can replace guiding center dynamics in using energy-preserving algorithms for computations, providing a new, efficient, as well as stable approach for applying structure-preserving algorithms in plasma simulations.

FDS-MOMEDA: optimization-blind deconvolution in finite high-dimensional spaces for extracting pulse signal in rolling bearing fault diagnosis

Rolling bearing fault diagnosis is crucial for ensuring the safe and reliable operation of mechanical equipment. Detecting faults directly from measurement signals is challenging due to severe noise and interference. Blind deconvolution (BD), as a preferred method, effectively recovers periodic pulses from the measured vibration signals of faulty bearings. This study introduces a simulated annealing-based BD approach to enhance the pulse signal components reflecting faults in vibration signals measured on rolling bearings. This method iteratively searches for the optimal coordinates in a high-dimensional orthogonal optimization space, where the optimal coordinates reflect the combination of the inverse filter coefficients. Compared to the generalized spherical optimization space used in the ‘Optimization-Blind Deconvolution’ method in previous works, the proposed finite high-dimensional optimization space helps overcome the problem of inverse filter coefficient convergence, allowing for the design of inverse filters without limit of its shape. To better accommodate the cyclostationarity characteristics of bearing signal measured in reality, the proposed method employs a target vector that allows for uncertainty in pulse occurrence instants, thus overcomes challenges introduced by pseudo-periodic phenomena resulting from bearing slippage. Numerical simulations and experimental results on real bearing vibration signals confirm that the proposed method can design more flexible filters to enhance pulse-like patterns in signals, effectively utilize limited filter resources. Its capacity to tolerate inaccurate fault period estimates, high background noise, and pulse randomness enables it to effectively address vibration measurement signals in real-world scenarios.

Use of explainable machine learning models in blast load prediction

The effects of blast waves and their consequent damage to structures have been an increasingly popular research topic in the past decade. Various methods are used in blast load prediction on structures, including experimental, semi-empirical and numerical approaches. However, there is a demand for developing time-efficient predictive methods that help various professionals, such as engineering practitioners and first responders, in their regular activities. Machine learning (ML), as a subset of artificial intelligence (AI), has gained significant attention in various engineering applications over the past decades for its ability to aid decision-making. However, a critical gap exists in the comprehensive analysis of these ML models' transparency and interpretability levels. This paper presents a novel approach to employing explainable machine learning (XML) to predict the blast loads generated by high explosives. The primary objective is to assess the validity of utilising a machine learning (ML) framework for blast load predictions, examining the scientific consistency of the model's prediction process. This research utilises XML to interpret the ML model-based blast load prediction framework, marking the first documented use of XML in published literature for blast load prediction. This research study utilised three ML models, namely a) Decision Tree, b) Random Forest, and c) Extreme Gradient Boost (XGB) models, to predict blast loads on rigid structures. Validated numerical model results were used to generate the dataset to train the ML models, and the respective dataset consists of approximately 600 independent blast events. The models were evaluated for their predictability using error metrics: adjusted coefficient of determination (adjusted R2), root mean square error (RMSE), and mean absolute error (MAE). The overall ML model performance evaluation showed that the best-performing model, XGB, could make predictions with 98 % accuracy compared to validated numerical predictions. The XML explanations for the XGB models showcased that the blast load prediction procedure of the models aligns with the blast physics principles, ensuring the credibility of the developed ML models. In summary, these XML predictive models can be considered accurate and reliable for blast load prediction on structures.

Directional false discovery rate control in large-scale multiple comparisons

The advance of high-throughput biomedical technology makes it possible to access massive measurements of gene expression levels. An important statistical issue is identifying both under-expressed and over-expressed genes for a disease. Most existing multiple-testing procedures focus on selecting only the non-null or significant genes without further identifying their expression type. Only limited methods are designed for the directional problem, and yet they fail to separately control the numbers of falsely discovered over-expressed and under-expressed genes with only a unified index combining all the false discoveries. In this paper, based on a three-classification multiple testing framework, we propose a practical data-driven procedure to control separately the two directions of false discoveries. The proposed procedure is theoretically valid and optimal in the sense that it maximizes the expected number of true discoveries while controlling the false discovery rates for under-expressed and over-expressed genes simultaneously. The procedure allows different nominal levels for the two directions, exhibiting high flexibility in practice. Extensive numerical results and analysis of two large-scale genomic datasets show the effectiveness of our procedure.

Second-order water wave properties over Roseau’s three-parameter bottom topography

Summary In his book Asymptotic Wave Theory (North-Holland 1976), Roseau develops the only known exact solution for linear wave propagation over a shoal. Remarkably, almost half a century later, the only properties of that solution which appear to have been used to validate more wide-ranging models are the limiting values of wave height in the far field. The primary aim of this work is to remedy this situation by providing a robust computational setting where the solution may be fully evaluated randomly both on the surface and the interior, speedily and to a high degree of accuracy. Such ‘benchmark’ solutions will facilitate a much more rigorous approach to validation of more general alternative approximation models. One such has some of its numerical results here examined and subsequently largely vindicated by the present calculations. Computation of the absolutely convergent solution integrals is supported by cubic spline approximation of an integrand component which satisfies a certain difference equation and the work is extended to cover bottom profiles with overhang including the extreme case where the overhang degenerates to a semi-infinite flat plate. The further development of solutions at second-order reveals details of mean Eulerian current and the attendant Stokes drift enabling mass transport computations; all illustrated through the entire depth with a range of contouring and arrows plots. The force field that drives a second harmonic component is calculated and shows excellent agreement with its equivalent in the more general modal expansion model applied to a non-identical but somewhat similar profile. This further validates the modelling approach and application described in that work.

Perfect splitting in rectangular-waveguide junctions for analog computing

It has recently been shown how computing operations such as high-speed switching, routing, and solving partial differential equations can be performed by exploiting perfect splitting of electromagnetic waves in networks of waveguides from microwaves to the optical regime. Here we propose a technique to achieve perfect splitting of electromagnetic waves using junctions of rectangular waveguides. The structure consists of air-filled rectangular waveguides interconnected at a junction. They are designed to have their cutoff frequency above the cutoff frequency of a further waveguides used as inputs. The proposed structure is studied theoretically with use of transmission-line models, and it is demonstrated that perfect splitting can occur at frequencies below the cutoff frequency of the interconnected waveguides (evanescent coupling). Numerical results are used to validate the designs, and it is demonstrated that the theoretical model fits the numerical data well. As examples of computing operations, it is shown how the proposed structure can be used to compare the amplitude of two incident signals (comparison operation) and also for routing of information to different output ports by exploiting the linear superposition of scattered waves excited at the junction of rectangular waveguides, opening new opportunities and possibilities for future exploration and exploitation of electromagnetic waves for high-speed computing. Published by the American Physical Society 2024

Investigation of the Static Pressure Drop and Production that Occurs due to Flow Patterns in a Perforated Horizontal Wellbore

This study examined the intricate interaction between flow patterns and production within a perforated horizontal wellbore. The study precisely assessed the behavior of static pressure drop by utilizing an array of flow regimes encompassing bubble, dispersed bubble, transitional bubble/slug, slug, stratified, transitional slug/stratified wave, and stratified wave. Remarkably, an upward trend in static pressure drop was observed with increasing water phase presence, while the converse was true for the air phase. Besides, the air phase superficial velocity exhibited a direct correlation with the magnitude of pressure drop fluctuations. The liquid production demonstrated a peak during bubble and slug flow regimes, followed by a descent during the transition to stratified and stratified wave flow. This decline can be attributed to mixing pressure drops localized during the perforations. Furthermore, an upward trend in average liquid production was observed with increasing mixture superficial velocity, primarily due to the dominant presence of the water phase. Additionally, the percentage of liquid production was positively associated with the water's superficial velocity when the air's superficial velocity was held constant. While the experimental and numerical results were in agreement for slugs and structured flows, there were discrepancies in the behavior of static pressure for bubbles, small bubbles, and structured waves.

Optimal fiscal policy under finite planning horizons

AbstractWe propose a novel framework that revisits the seminal Chamley-Judd zero capital taxation result in light of bounded rationality stemming from a finite policy planning horizon and structural frictions in fiscal institutions. We show a mechanism that generates positive optimal capital taxation in the long run. Our numerical results indicate that the current tax system in the United States could be near-optimal in a constrained environment where policymakers exhibit limited policy planning horizons and imperfect altruism toward household welfare under subsequent governments.

Discrete element model for effective electrical conductivity of spark plasma sintered porous materials

AbstractThis paper aims to analyse electrical conduction in partially sintered porous materials using an original resistor network model within discrete element framework. The model is based on sintering geometry, where two particles are connected via neck. Particle-to-particle conductance depends on neck size in sintered materials. Therefore, accurate evaluation of neck size is essential to determine conductance. The neck size was determined using volume preservation criterion. Additionally, grain boundary correction factor was introduced to compensate for any non-physical overlaps between particles, particularly at higher densification. Furthermore, grain boundary resistance was added to account for the porosity within necks. For numerical analysis, the DEM sample was generated using real particle size distribution, ensuring a heterogeneous and realistic microstructure characterized by a maximum-to-minimum particle diameter ratio of 15. The DEM sample was subjected to hot press simulation to obtain geometries with different porosity levels. These representative geometries were used to simulate current flow and determine effective electrical conductivity as a function of porosity. The discrete element model (DEM) was validated using experimentally measured electrical conductivities of porous NiAl samples manufactured using spark plasma sintering (SPS). The numerical results were in close agreement with the experimental results, hence proving the accuracy of the model. The model can be used for microscopic analysis and can also be coupled with sintering models to evaluate effective properties during the sintering process.