Scopus Research — Dr.Sami Muhsen

Achieving optimal compaction in asphalt mixtures is crucial to pavement performance; however, the internal mechanisms governing aggregate movement, force distribution, and void evolution remain insufficiently understood. This study aims to bridge the gap by exploring the effects of asphalt type, aggregate gradation, and mixing temperature on particle-scale compaction behavior using a calibrated Discrete Element Method (DEM) simulation model, offering a novel particle-level perspective. Few asphalt mixtures were analyzed, including conventional and SBS-modified binders with fine (Sample 13) and course (Sample 20) gradations, compacted at two temperatures (140 °C and 180 °C), resulting in distinct sample conditions. The simulation model, which replicated compaction using the Particle Flow Code (PFC), was validated against compaction degree measurements, yielding a Coefficient of Determination (R2) of 0.7105. Key input variables included binder type, gradation, and temperature, while outputs included internal particle force, migration velocity, displacement, and void distribution. The results revealed that increasing the mixing temperature from 140 °C to 180 °C increased average particle velocity by up to 92 %, while void concentration was significantly reduced in Polymer Modified Bitumen (PMB) Sample 20–180 °C. Additionally, a strong correlation (R2 = 0.87184) was observed between aggregate displacement and mixture workability, emphasizing the influence of thermal and rheological conditions on compaction efficiency. The findings support improved workability assessment and compaction control strategies in pavement engineering and demonstrate the effectiveness of DEM simulations for evaluation of internal behavior that remains difficult to observe through physical testing. © 2025

The shape of the tool is a decisive factor that influences the material flow and, thereby, the tribological and mechanical characteristics of composites in FSP. Thus, the impact of single-pin (SP) and double-pin (DP) tools on the microstructure, mechanical, and wear behavior of newly developed AA5083/AlCoCrFeNi HEA surface composites is studied in detail. The findings demonstrated that using a DP tool for the FSP of the AA5083/AlCoCrFeNi HEA surface composite significantly reduced the average grain size from 10.38 to 6.18 μm through continuous dynamic recrystallization (CDRX), while also making it easier for AlCoCrFeNi particles to spread across the AA5083 substrate/matrix. This improvement can be attributed to the DP tool's facilitation of flow velocity and excess plastic deformation. It was also found that due to grain refinement, better AlCoCrFeNi particle dispersion, and eradicating typical FSP defects, such as the clustering of reinforcing particulates, the AA5083/AlCoCrFeNi surface composite developed with the DP tool resulted in an improvement of 18 % over the sample processed with the single-pin tool. Results also revealed that using double-pin triggered a slight decrease in the wear rate (0.41–0.32 mm3/Nm) and the friction coefficient (0.40–0.33) owing to effective dispersion and minimization of the reinforcement particles across the matrix. © 2025 Elsevier B.V.

Discovering suitable anode materials that have exceptional electrochemical properties for Ca-ion batteries (CIBs) is seen as a major challenge for both the academic and industry research sectors. In this study, we aim to investigate the effectiveness of a recently developed 2-dimensional material called orthorhombic dialuminium dinitride (o-Al2N2) as a potential negative electrode for CIB using first-principles computations. The data obtained demonstrate that o-Al2N2 possesses a low kinetic diffusion barrier of 0.19 eV, a significant specific capacity of 649 mAhg−1, and operates at a voltage of about 0.231 V. The outcomes demonstrate that orthorhombic Al2N2 monolayer is a highly suitable anode material for CIBs due to its remarkable theoretical capacity, rapid Ca diffusion, strong binding energy with lithium adsorbent, and excellent structural stability. Exceptional characteristics of the 2D o-Al2N2 monolayer make it one of the top options for the anode component in future rechargeable CIBs. © 2024 Elsevier B.V.

The increasing vulnerability of high-rise structures to compound seismic and flood hazards necessitates efficient, data-driven optimization frameworks to enhance structural resilience. Despite advances in structural health monitoring and design optimization, existing approaches often rely on computationally expensive finite element simulations or conventional single-hazard models, lacking adaptability for rapid multi-hazard scenarios. This study aims to develop an intelligent structural optimization framework that integrates Long Short-Term Memory (LSTM), Bidirectional Gated Recurrent Unit (Bi-GRU), and Convolutional Neural Network–Support Vector Machine (CNN-SVM) hybrid models to predict and enhance structural performance under combined earthquake and flood loading. The methodology involved generating a synthetic dataset from multi-parameter structural simulations, training LSTM and CNN-SVM models to predict five key structural responses (lateral displacement, inter-story drift ratio, energy dissipation, base shear, and natural frequency) based on design and hazard input parameters. Results showed that the CNN-SVM hybrid model achieved superior predictive accuracy Coefficient of Determination ((R²) > 0.96)) compared to LSTM, with maximum reductions of 51.4 % in lateral displacement and 58.7 % in inter-story drift ratio, alongside a 35.4 % increase in energy dissipation and a 14.2 % improvement in base shear capacity. These enhancements comply with ASCE 41–17 Immediate Occupancy drift limits and outperform drift reduction benchmarks reported in prior Machine Learning (ML)-based optimization studies. The proposed framework demonstrates a significant potential for rapid, code-compliant structural optimization and real-time performance monitoring, offering a scalable and practical solution for resilient high-rise infrastructure design in multi-hazard environments. © 2025

Emulsified asphalt plays a critical role in sustainable pavement construction but evaluating its storage stability remains time-consuming and often lacks precision. Existing methods are typically based on sedimentation-based tests, which require several days to complete and do not provide real-time information on emulsion behavior. This study addresses that gap by exploring the electrokinetic properties of emulsified asphalts using Electrokinetic Potential (EP, ζ), coupled with microscopy-based particle size characterization, to assess stability across emulsifier types, dosages, Solid Contents (SC), and additives. The research introduces a framework integrating electrophoretic mobility measurements and image-based particle statistics to establish a mechanistic understanding of emulsion stability. Emulsions were prepared with five emulsifier systems and tested at varied dosages and SCs. EP was measured using electrophoretic light scattering, while droplet dimensions were obtained by image analysis. Results showed that a 1000-fold dilution gave reliable EP readings. Brij-35, SDBS, and CS-5 produced higher EP values (±120 mV) and smaller areas, indicating better stability, whereas Tween 80 and HSB1618 showed lower stability and larger sizes. Optimal performance occurred at ∼3 % emulsifier dosage and 50–55 % SC. Additives like NaCl reduced EP by over 50 %, indicating Electrical Double Layer compression. Correlations were found: positive between EP and fine particles, and negative between EP and average size. This study presents a rapid, quantitative method for evaluating emulsified asphalt stability and offers a guideline for formulation design. The findings have practical significance for enhancing long-term emulsion performance in road construction and provide a valuable tool for quality control in asphalt technology. Copyright © 2025. Published by Elsevier Ltd.

This study investigates the thermal performance of evaporators in vapour compression refrigeration systems, with a focus on the design, experimental analysis, and impact of various operating parameters. The evaporator used in the experiments was tested in the Air Condition Laboratory at Al-Mustaqbal University, with key specifications including a total tube length of 19.2 meters, tube diameter of 7 mm, and fin geometry configured for optimal heat transfer. The experimental setup included measuring the evaporator’s performance under various conditions, specifically with refrigerant R-22. The average evaporator temperature was maintained at 5℃, with the refrigerant entering at -1.6℃ and exiting at 3.6℃. The pressure within the evaporator was recorded at 584 kPa, while the condenser operated at 40℃ and 1533.5 kPa. Key thermodynamic parameters, such as the overall heat transfer coefficient (0.466 kJ/m²·s·℃ for copper), were calculated and analyzed. Key findings from the experiments include a direct relationship between the evaporator’s area and its cooling capacity, as expressed by the equation Q=U×Θm×A. Additionally, it was observed that the refrigeration capacity increases with the temperature difference between the refrigerant and the air. The study also found that the coefficient of performance (COP) of the refrigeration cycle improves with an increase in the evaporator’s effect, though it decreases as the evaporator temperature rises. The study concludes that the presence of lubricating oil within the system complicates heat transfer and pressure drop, making the thermal design of the evaporator challenging. Furthermore, it was determined that high-pressure refrigerants enhance evaporator capacity, and the heat transfer capacity is significantly influenced by the temperature differential between the refrigerant and the medium being cooled. The findings contribute to a better understanding of evaporator design and optimization for improved system performance. Copyright: ©2025 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).

Because of their high electrocatalytic activity, sensitivity, selectivity, and long-term stability in electrochemical sensors and biosensors, numerous nanomaterials are being used as suitable electrode materials thanks to developments in nanotechnology. Electrochemical sensors and biosensors are two areas where two-dimensional layered materials (2DLMs) are finding increasing utility due to their unusual structure and physicochemical features. Nanosensors, by their unprecedented sensitivity and minute scale, can probe deeper into the structural integrity of piles, capturing intricacies that traditional tools overlook. These advanced devices detect anomalies, voids, and minute defects in the pile structure with unparalleled granularity. Their effectiveness lies in detection and their capacity to provide real-time feedback on pile health, heralding a shift from reactive to proactive maintenance methodologies. Harvesting data from these nanosensors, data was incorporated into a probabilistic model, executing the reliability index calculations through Monte Carlo simulations. Preliminary outcomes show a commendable enhancement in the predictability of vertical bearing capacity, with the coefficient of variation dwindling by up to 12%. The introduction of nanosensors facilitates instantaneous monitoring and fortifies the long-term stability of pile foundations. This study accentuates the transformative potential of nanosensors in geotechnical engineering. © 2024

This study investigates natural convection in a cold elliptical enclosure that is around an equilateral triangle with curved vertices, which represent the hot walls (Th) at five different triangle location cases. The oval shell surrounding the hot curved triangles fills with air. This study primarily investigates how arcs enhance natural convection by examining their impact on streams and isothermal lines at various locations within a curved triangle. However, the main parameters carried out in this work are the Rayleigh number, triangle location, and Nusselt number. The Rayleigh numbers used in this work are varied by the interval 104 ≤ Ra ≤ 106, which was applied for all locations of a curved triangle. The Ansys 2020 R1 software has been used to analyse the concept of natural convection by solving the governing equation using the finite volume method with the presented Boussinesq approximation. Furthermore, the high Rayleigh number (106) results in a significant and clear breakthrough. On the other hand, the Nusselt number's minimal value occurs on the middle arc of the inner curved triangle in most cases of curved triangle locations. Also, it reveals that the bottom location of a curved triangle is optimal since it has the maximum Nusselt number at the middle arcs of the triangle. Copyright: ©2024 The authors.

Selecting an appropriate anode material (AM) has been considered to be a crucial initial step in advancing high-performance batteries. Within this piece of research, we examine the suitability of the BC6NA monolayer (referred to as BC6NAML) as an AM by first-principles calculations. The BC6NAML exhibits metallic behavior consistently, even with varying concentrations of Na atoms, making it an ideal choice for battery usages. Our findings revealed that the theoretical storage capacity for Na-adhered BC6NAML was 406.36 mAhg−1, surpassing graphite, TiO2, BC6NA, and numerous other 2D materials. The BC6NAML also demonstrates a diffusion barrier of 0.39 eV and favorable diffusivity of Na-ions. Although the open-circuit voltage (OCV) of BC6NAML was temperate and lower compared to the OCV of other AMs like TiO2, our results suggested that it is possible to utilize BC6NAML as one of the encouraging host materials for sodium-ion batteries (SIBs). Consequently, this investigation into the potential anodic application of BC6NAML proves valuable for future experimental studies into sodium storage for SIBs. © 2024 Elsevier Inc.

For wind energy conversion systems (WECS), forecasting wind speed is crucial for meeting customer demands while monitoring, controlling, planning, and dispatching the electricity production. The goal of the research is to more easily predict wind speed for planning and feasible studies of wind farms. All data was derived from weather stations in a windy city in a mountain area for one month within five years. A kernel ridge regression (RR) model is suggested, and the results are compared with two reference prediction models of support vector machines (SVM) and artificial neural networks (ANN), to validate the model's efficiency for three different predicting horizons (1-h, 12-h, and 24-h ahead). The root means square error (RMSE), and root mean square (R2) are utilized to assess the effectiveness of a prediction model. Using one layer and 30 neurons, the optimum outcome was achieved with an RMSE of 0.264 and a value of 0.811. Tests revealed that 70%–30% for training and testing yields the lowest RMSE of 1.244 compared to 1.874 for 60%–40%. A study of ANN, SVM, and ridge regression found that predictions made with the RR provided the most precision in comparison to the R2 and RMSE values. This study's relevance lies in its ability to forecast wind speeds and for this reason, ridge regression using mutual information feature selection performs better than other methods when trying to forecast wind velocity. Cost and risk management in wind power planning will benefit from this research. © 2023 Elsevier Ltd

In this paper, the fractional-order chaotic system form of a four-dimensional system with cross-product nonlinearities is introduced. The stability of the equilibrium points of the system and then the feedback control design to achieve this goal have been analyzed. Furthermore, further dynamical behaviors including, phase portraits, bifurcation diagrams, and the largest Lyapunov exponent are presented. Finally, the global Mittag–Leffler attractive sets (MLASs) and Mittag–Leffler positive invariant sets (MLPISs) of the considered fractional order system are presented. Numerical simulations are provided to show the effectiveness of the results. © 2023 by the authors.

A comprehensive study is established to investigate on the thermal buckling instability and the subsequent post-critical deflection of a rotating nanocomposite microbeam reinforced with graphene platelet. The main scope of the current research is shedding light on the effectiveness of reinforcing a rotating microbeam with graphene platelet subjected to a constant temperature development. The Timoshenko beam theory comes along the von-Karman strain displacement relations to extract the governing equations of motion in accordance with the modified couple stress theory. The modified Halpin–Tsai micromechanical model is implemented to determine the practical elasticity modulus of the nanocomposite beam. The Ritz technique is accompanied by the Chebyshev orthonormal polynomial set to discretize the weak form of the nonlinear equations of motion. The Newton–Raphson technique is applied to the discretized static nonlinear equations of motion to compute the static deformation due to the centrifugal force. On the basis of two effective algorithms the nonlinear equations of motion are attacked to find out the critical buckling temperature change as well as the succeeding post-critical deflection. It is observed that adjoining the graphene phase in the form of an X-pattern promotes the static strength of a rotating microbeam against the buckling instability. However, in contrast, for stationary microbeams and microbeams that rotate with a velocity below a threshold speed adjoining the graphene platelet reinforcement in the form of an O-Pattern not only does not strengthen the microbeam but also weakens it against the buckling instability. Moreover, the buckling modeshape of rotating simply-clamped microbeams is more impressed by the graphene phase. © 2022 Elsevier Ltd

In this work, a Nonlinear Higher Order Extended State Observer (NHOESO) is presented to replace the Linear Extended State Observer (LESO) used in Conventional Active Disturbance Rejection Control (C-ADRC) solutions. In the NHOESO, the standard LESO is completed with a two-term smooth nonlinear function with saturation-like characteristics. The proposed novel NHOESO enables precise observation of the generalized disturbances with higher-order derivatives. The stability of the NHOESO is examined with the aid of the Lyapunov method. A simulation of an uncertain nonlinear Single-Input–Single-Output (SISO) system with time-varying external disturbances confirms that the proposed NHOESO copes well with the generalized disturbance, which is not true for other ESOs. © 2023 by the authors.

This article investigates the statically analysis regarding the thermal buckling behavior of a nonuniform small-scale nanobeam made of functionally graded material based on classic beam theories along with the nonlocal Eringen elasticity. The material distribution of functionally graded structures is composed of temperature-dependent ceramic and metal phases in axial and thickness directions, called two-dimensional functionally graded (2D-FG). The partial differential (PD) formulations and end conditions are extracted by using to the conservation energy method. The porosity voids are assumed in the nonuniform functionally graded (FG) structure. The thermal loads are in the axial direction of the beam. The extracted nonlocal PD equations are also solved by employing generalized differential quadrature method (GDQM). Last but not least, the information acquired is used to produce miniature sensors, providing a unique perspective on the growth of nanoelectromechanical systems (NEMS). © 2023 Techno-Press, Ltd.

Owing to ruinous effects of thermal shocks on the nanocomposite structures, this study scrutinizes the thermal shock resistance of the poroelastic nanocomposite circular sector plates in the scheme of elasticity theory and application of the harmonic differential quadrature approach (HDQA). Due to the fact that the related studies published priorly were just able to predict the response of the simply-supported plates, the current research would be considered as the first study on the transient thermal shock response of the above-mentioned plates with fully-clamped boundary conditions. To determine the system's time-dependent response, differential equations are translated to the Laplace domain. Then, the modified declaration of the Dubner and Abate's technique is exploited to derive the time realization of the system's response from the Laplace domain. The validation procedure of the current analysis is performed by comparing the outcomes with those claimed in the published researches. In order to clearly assess the system's shock resistance against the abrupt thermal load, effect of various parameters such as thermal relaxation time (TRT), different scattering models and volume fraction of the nano reinforcement, boundary conditions, intensity of the shock, poroelastic properties of the nanocomposite, and radius to thickness ratio of the sector plate on the thermo-elastodynamic response of the system are investigated. It is revealed that the sensitivity of the system's response to increase of TRT subsides when TRT is over an upper bond. © 2022

A study on the principal parametric stimulation of rotating microbeams strengthened by means of graphene platelet is presented. The microbeam is exposed to a temperature gradient. On the basis of the assumptions of the hypothesis of the Timoshenko for beams alongside the modified couple stress hypothesis the nonlinear motion equations are achieved. It is supposed that the rotating speed of the microbeam varies harmonically about a mean quantity. The frequency of the harmonic term of the rotating velocity is presumed to be almost two times an axial or a transversal natural frequency. In such situation, the principal parametric agitation is stimulated. Assuming a proportional damping, a least square scheme is employed to define the Rayleigh's coefficients. The impacts of the rotating speed, the weight fraction as well as the scattering pattern of the graphene platelets, and the damping coefficient on the presented results are examined. The results illuminate that as a consequence of the addition of the damping coefficient, the critical incitement amplitude constant increases more for reinforced microbeams rather than not-reinforced microbeams. Moreover, by means of enlarging the weight fraction of the graphene platelets, the critical incitement amplitude constant develops more for a rotating X microbeam rather than an O microbeam. Additionally, at moderate to high magnitudes of the damping coefficient, the instability area border aligned with the fundamental axial mode is impressed by the graphene platelet scattering pattern although it is invariant for small values of the damping coefficient. Moreover, by the development of the temperature the instability area border aligned with the fundamental transversal mode gets broader, while the critical incitement amplitude coefficient decreases; the both more for on O scattering pattern for the graphene platelet. Furthermore, the instability region boundary is more influenced by the graphene platelet weight fraction, while the critical incitement amplitude coefficient is more impressed by the damping coefficient design value. © 2022 Elsevier Ltd

Ethylene glycol with nanoparticles behaves as a non-Newtonian fluid and its rheology can be best predicted by the power-law rheological approach. Further nanoparticles (molybdenum disulfide and silicon dioxide) are responsible for anti-oxidation, anti-evaporation, and anti-aging. Therefore, their dispersion in ethylene glycol is considered as these properties make the nanofluid stable. This article examines the impact of molybdenum disulfide and silicon dioxide on the thermal enhancement of ethylene glycol as it is a worldwide used coolant. Moreover, simultaneous effects of temperature and concentration gradients, Joule heating, viscous dissipation, thermal radiations, and buoyancy forces are modeled and developed, and investigations are computed by the finite element method. An increase in temperature due to the composition gradient and an increase in concentration due to the temperature gradient are observed. A significant increase in the Ohmic phenomenon with an increase in the intensity of the magnetic field is observed. Numerical experiments are performed by considering single-type nanoparticles ((Formula presented.)) and hybrid-type nanoparticles (simultaneous dispersion of (Formula presented.) and (Formula presented.) is considered). During the visualization of simulations, the effective thermal conductivity of (Formula presented.) - (Formula presented.) -ethylene glycol is observed. Copyright © 2022 Nazir, Sohail, Singh, Muhsen, Galal, Tag El Din and Hussain.

As a first attempt, free and forced vibrations of functionally graded (FG) porous nanoscale beams embedded in a Kerr foundation under a moving force with constant speed and acceleration are studied analytically and numerically based on the nonlocal strain gradient Rayleigh beam model. It is assumed that the material characteristics of the nanobeam across the thickness are graded according to the power-law function involving different porosity distribution patterns. The governing equation for the motion of the nanobeam is derived by utilizing the extended Hamilton's principle. With the help of the Galerkin decomposition approach, natural frequencies and dynamic responses of the system are acquired. Several comparative studies are performed with published data in the open literature for validation purposes. Finally, the effects of various parameters such as gradient index, porosity characteristics, foundation properties, and size-dependent parameters on forced and free vibrations of the system are clarified. The results declared that the critical force speed decreases with increasing the gradient index. It is also inferred that for the system with a uniform porosity distribution, the cancellation and critical force speeds increase/decrease for low/high values of the gradient index as the porosity volume fraction increases. Meanwhile, it is indicated that by accurately adjusting the properties of the FG porous material, undesirable vibration of the system can be eliminated. The outcomes of the present investigation could be beneficial in the optimum design of inhomogeneous small-scale transportation systems. © 2022 Elsevier Ltd

A nonlinear vibrational analysis of sandwich curved panels having multi-scale face sheets has been performed in this article based on differential quadrature method (DQM). All mechanical properties of multi-scale skins have been established in the context of three-dimensional Mori-Tanaka scheme for which the influences of glass fibers and random carbon nanotubes (CNTs) have been taken into account. The governing equations for sandwich the panel have been developed based upon thin shell formulation in which geometry nonlinearities have been taken into account. Next, DQ approach has been applied to solve the governing equations for determining the relationships of frequencies with deflections for curved panels. It will be demonstrated that the relationships of frequencies with deflections are dependent on the changing of CNT weight fractions, fibers alignment, fibers volume, panel radius and skin thickness. Copyright © 2022 Techno-Press, Ltd.

It can be considered that the suspension system is one of the most important systems in the VEHICLE. Where it is responsible for the stability and balance of the vehicle's structure on the roads and curves to ensure the comfort of passengers. Also, it absorbs the shocks resulting from the unevenness of the road and prevents it from reaching the wheelhouse. The influence of the suspension constructive parameters in order to obtain the smallest level of displacements of the sprung mass has been investigated. The following control parameters are the stiffness of the sprung, unsprung mass, and the damping of the sprung mass. The parameter which affects most displacements of the sprung mass was determined by applying the analysis of variance (ANOVA). The investigation was conducted using MATLAB/SIMULINK software, and a line model of a quarter of the vehicle was created. It was determined that the stiffness of sprung has the most significant influence on the displacement of the sprung-mass, which further affect the vehicle's comfort. © 2022 Nadica Stojanovic et al., published by Sciendo.