Ohmic heating has emerged as an effective alternative to conventional thermal treatments for fruit juice preservation. However, the performance of an ohmic heating system is strongly influenced by the excitation waveform generated by its power electronics circuitry. Conventional systems typically employ square-wave excitation, which can produce rapid temperature rises and may adversely affect nutrient retention. There is therefore a need for alternative excitation waveforms that provide better control over the temperature rise while maintaining effective microbial inactivation. To address this need, this work proposes a novel ohmic heating system comprising a custom-designed square-wave generator and an RC differentiator that converts the square-wave output into exponentially decaying pulses. The square-wave generator is designed to deliver the voltage and current levels required for juice treatment, and the RC differentiator enables controlled energy delivery to the load by optimising the pulse width. The proposed circuit produces high-amplitude, short-duration exponential pulses with a peak electric field intensity of 140 V/cm and an optimised pulse width of 46 μs. The treatment system was analysed and experimentally validated using watermelon juice as the treatment medium. Experiments were conducted with electrode gaps ranging from 5 mm to 20 mm, operating frequencies of 1 kHz and 10 kHz and a maximum treatment temperature of 70°C. The influence of the generated exponential pulses on treatment performance was evaluated through microbial inactivation studies with Escherichia coli and nutrient retention measurements of vitamin C and total antioxidant activity. Experimental results showed that with the maximum treatment temperature limited to 70°C, the optimised differentiator-based system achieved a bacterial log reduction of 5.98 after 2.5 min, compared with 3.92 for the conventional square wave–driven system after 0.5 min. The proposed excitation method also maintained good nutrient retention characteristics while operating below 70°C. The results suggest that differentiator-based pulse shaping can improve the effectiveness of ohmic heating systems and highlight the potential of customised waveform-generation techniques for electric field–based food processing applications.
Heat transfer from solid into fluid channels is found in many natural and artificial systems involving heating and cooling processes. It is highly desirable to have a general and simple equation for predicting the transient fluid temperature in narrow flow channels. This study fills the gap by developing a semi-analytical model. The model involves heat conduction between solid and fluid and heat convection along the channel. The result of parameter analysis with the model for a rock/water system indicates that fluid temperature changes sharply during the early time. In the practical range of rock thermal conductivity, the fluid temperature change is not significantly affected by the rock thermal conductivity. The effect of fluid temperature at the entrance on the fluid temperature at the exit of the channel is almost linearly additive. Increasing channel width and length and reducing fluid flow rate improve fluid retention time in the channel, enhance the total heat transfer, and thus promote fluid temperature change over the flow channel. This work provides engineers with a closed-form equation for predicting the transient fluid temperatures at the exits of flow channels in their heat transfer systems.
Battery management has emerged as an imperative field in the sustainable energy revolution. The operating temperature, voltage, and current are key factors in the comprehensive analysis of battery performance. The simulations investigate battery thermal behavior at 0.5, 1, 2, and 3C discharge rates under controlled ambient temperature (35°C). The 3C condition is considered the worst-case discharge scenario because it generates the highest thermal load among the investigated operating conditions and is selected for further investigation. Among the tested coolants, the canola coolant yields the best results compared with air, 3M Novec, and cottonseed coolants. For canola coolant, the temperature range for LIB cells varies from 34.99°C to 38.98°C. The average temperatures observed for Cells 1 through 6 are 37.14°C, 37.23°C, 37.65°C, 37.63°C, 38.48°C, and 38.57°C, respectively. The maximum voltage recorded during all thermal simulations is 10.4 V, consistent with LIB module characteristics. Compared with (Air)5m/s, the 3M Novec, cottonseed, and canola cooling media provide 37.75%, 38.36%, and 38.40% improvements in thermal performance. Although canola and cottonseed coolants are biodegradable and renewable, they exhibit densities that are 64.13% and 65.93% lower, respectively, than those of the conventional coolant (3M Novec). The lower density of biocoolants could be advantageous for fuel economy and overall battery performance. Additionally, integrating artificial intelligence (AI) and machine learning into the optimization process can substantially improve cooling system efficiency and can smooth real-time thermal management.
This study investigates the valorisation potential of clay soils from MVAM ESSAKO and LO'O-BIYENG (Ebolowa, Cameroon) for cement-stabilised earth bricks (CSEBs). Two representative soils were characterised using geotechnical tests, mechanical testing and FTIR analysis after stabilisation with 2%–8% Portland cement (28 days curing). The soils exhibit moderate plasticity (IP: 20.6%–22.4%) with methylene blue values of 2.43–2.80. Cement addition significantly improves performance: At 8% cement, compressive strength reaches 5.68–5.81 MPa (exceeding the 5 MPa requirement for structural masonry), flexural strength is 0.81–1.06 MPa and water absorption decreases to < 20%. FTIR analysis reveals spectral changes consistent with mineralogical transformations associated with stabilisation: decreasing intensity of kaolinite-related bands at 3695 cm−1 (suggestive of dehydroxylation) and increasing intensity of bands in the 1000–1100 cm−1 region (consistent with the formation of cementitious silicate phases). The integrated approach demonstrates that Ebolowa clay soils are suitable for producing CSEBs, offering a potential local alternative for sustainable masonry in humid tropical environments. These two representative soils show promising results, but further studies are needed to confirm extrapolation to the wider range of soils in the Ebolowa region.
Solar air collectors have been widely used in industries and agriculture because of their structural simplicity and economic feasibility. Still, their thermal performance characteristics are constrained by insufficient convective thermal exchange between the absorbing surface and the airflow. In this study, a numerical investigation and optimization of the thermal performance characteristics of the double-pass counter-flow flat-plate solar air collector are carried out using the CFD–Taguchi method. The heat and airflow under forced convection conditions have been modeled in ANSYS using a three-dimensional steady-state (CFD) model. Key factors such as mass flow rate (0.01–0.07–0.15 kg/s), channel height configurations, and material properties (copper, aluminum, and steel) have been studied. Using Taguchi analysis and ANOVA technique, an optimal combination of the parameters to enhance the thermal characteristics has been obtained. The simulation results reveal that the maximum efficiency attained is 0.531, where mass flow rate was found to be the predominant parameter accounting for 99.46% of total effects. Higher efficiency can be achieved with increased flow rate as a result of higher convection process; however, an increase in the mass flow rate decreases air outlet temperature because of a shorter exposure period. The effect of channel height and material was very small (less than 0.2%). The theoretical model has been checked using literature data; the largest error was 6.65%. From this study, it can be noticed that focusing on proper airflow management is more important than proper material selection.
This work focuses on developing a Low-cost, low-grade electrical-thermal solar humidification system, as a promising solution for freshwater production. To increase the air humidity ratio at the humidifier exit, a designed and instrumented solar humidifier harnesses solar radiation and receives both a forced hot air stream from a solar air collector and water droplets falling onto its absorber plate, where the droplets evaporate. The solar humidifier dimensions were 330 × 50 × 1000 mm. PV panels supplied electrical power to circulate water and air for preheating by a flat-plate and an air solar collector. Key factors influencing air’s relative humidity (RH) are air flow rates (0.5 m3/min to 1.5 m3/min), water drip rate (4 to 10 drops/s), and the solar humidifier’s absorber surface geometry (flat or dimpled). Tests were extended from 8:00 to 17:00 to evaluate air RH and temperature on clear-sky days in Baghdad, Iraq. Results showed that the highest outlet air RH was 61.2%, 72.4%, and 69.9% for water dripping rates of 4, 7, and 10 drops/s, corresponding to 0.167, 0.297, and 0.423 g/s, respectively, with a constant airflow rate of 0.5 m3/min. The best dripping rate was 7 drops/s. The outlet air RH from the humidifier was 72.4% and 85.6% for flat and dimpled absorbers, respectively, at an airflow rate of 0.5 m3/min and 7 water drops/s (0.297 g/s). The humidifier’s effectiveness was 85% and 70%, respectively. It is concluded that the dimpled absorber achieves significantly better humidification performance than the flat-plate absorber across all airflow rates. The humidifier pressure drops increases from 0.13 Pa to 0.36 Pa for the flat plate and dimpled plate, respectively, at solar noon, for a flow rate of 0.5 m3/min.
The ever-increasing heat dissipation requirements of modern high-performance electronics critically demand advanced cooling techniques beyond conventional fluids. Nanofluids have emerged as a next-generation solution for enhanced boiling heat transfer. This study experimentally investigates the pool boiling performance of mono- and hybrid nanofluids at a low volume concentration of 0.01% on a smooth copper surface under saturated conditions using deionized water (DIW) as the base fluid. Three mono nanofluids (Al₂O₃/DIW, Ag/DIW, and GNPs/DIW) and three compositions of hybrid nanofluids with a constant mixing ratio of 50:50 (Al₂O₃-Ag/DIW, Al₂O₃-GNPs/DIW, and Ag-GNPs/DIW) were prepared. The critical heat flux (CHF) and heat transfer coefficient (HTC) were systematically analyzed. All nanofluids enhanced boiling performance compared with deionized water. Among the mono nanofluids, GNPs/DIW achieved the highest enhancement, increasing CHF and HTC by 40.55% and 164.8%, respectively. The hybrid nanofluid Ag-GNPs/DIW exhibited the better overall performance, enhancing CHF and HTC by 53.63% and 209.8%, respectively. Conversely, the Al₂O₃-GNPs/DIW hybrid nanofluid exhibited decreasing heat transfer performance compared with Mono-GNPs/DIW, indicating opposite deposition effects caused by the Al₂O₃ added. Characterization of the surface using SEM, EDS, XRD, contact angle, and porosity detects that GNP deposition creates a protective graphitic layer that minimizes copper oxidation and enhances surface porosity and cavity radius, consequently enhancing boiling heat transfer. In contrast, Al₂O₃ encourages oxide formation and partial pore blockage, which reduced HTC. These results provide new insights into synergistic and antagonistic nanoparticle deposition mechanisms that control the enhancement of boiling in mono- and hybrid nanofluids.
Network Intrusion Detection Systems (NIDSs) are deployed and constitute an essential component of modern network defense against adversaries employing more and more advanced cyberattack strategies. Nevertheless, maintaining high detection accuracy in heterogeneous network environments still faces great challenges because of the diversity of traffic patterns and attack behaviors. This paper proposes a new Spatial–Contextual Dual-Feature Fusion (SCDF-CNN-BiGRU) framework in the context of hierarchical network intrusion detection employing multiple benchmark cybersecurity datasets. The proposed framework utilizes a lightweight shared convolutional neural network (CNN) feature extraction stage followed by 2 parallel and complimentary learning branches. The first branch employs Bidirectional Gated Recurrent Unit (BiGRU) to extract temporal dependencies and contextual relationships of network traffic while the second one adopts bidirectional convolutional processing to learn discriminative spatial representations. The features extracted from both branches are then fused via feature aggregation module to create an overall traffic representation. It also establishes hierarchical intrusion analysis through binary attack detection and multi-class attack categorization, along with an attack-level mapping strategy to connect different levels of attack types and the corresponding highly representative fine-grained attack descriptions. The framework was evaluated using six heterogeneous benchmark datasets, including UNSW-NB15, NSL-KDD, NF-ToN-IoT-v3, CICIOT2023, BCCC and CIC-UNSW-NB15. Experimental results showed strong detection performance with binary classification accuracies of up to 0.999 and multi-class accuracies of up to 0.988. These findings indicate that the proposed SCDF-CNN-BiGRU framework gives robust representations and consistent performance across multiple heterogeneous datasets via unified learning and ensemble inference.
In this paper a compact four-port crown-shaped MIMO antenna is proposed for sub-6 GHz wireless applications and fabricated on FR4 substrate. The peak gain is 4.57 dBi, and the radiation efficiency is above 75% at wide impedance bandwidth of 4.0–4.8 GHz, with operation against about 4.5 GHz as expected. The crown geometry allows for improved impedance matching, better structural symmetry and lower mutual coupling when compared to conventional patch antennas. In order to increase practical performance, Nd:YAG laser surface treatment is used as a post-fabrication approach that decreases the RMS surface roughness from 385 nm to 78 nm in order to reach maximum electrical conductivity and minimum conductor losses. As a result, the reflection coefficient below −30 dB is measured, the VSWR reaches values close to unity and provides 50 Ω input impedance. The MIMO system in this case also shows an optimal diversity with ECC near idle (0.01) and a diversity gain of approximately 10 dB. Closer agreement between simulated and measured results, especially after laser treatment, has validated the design and demonstrated the ability of laser post-processing to decrease fabrication tolerances. The antenna is structurally unique in integrating a crown-shaped fractal patch geometry with the complement split-ring resonator, which breaks the surface current symmetry to excite orthogonal modes to realize a significantly wide impedance bandwidth across sub-6 GHz spectrum. This achieves natural decoupling through its inherent spatial diversity and orthogonal port orientations without complex but bulky decoupling networks crucial for the compact form factor needed in dense 5G terminals.
Steel fiber reinforced concrete (SFRC) can enhance post-cracking tensile resistance through fiber bridging across cracks; however, the torsional contribution of fibers is still not explicitly addressed in most design provisions. This study develops a three-dimensional nonlinear finite element (FE) model in ABAQUS to evaluate the response of SFRC beams subjected to pure torsion. The concrete response was simulated using the Concrete Damage Plasticity (CDP) model, while the tensile softening behavior of SFRC was represented using stress–crack opening displacement relationships derived from experimental material characterization data. The FE model was validated against two independent experimental programs reported in the literature, covering beams with different fiber contents and transverse reinforcement ratios. The validation was performed through comparisons of torque–twist response, ultimate torsional capacity, and crack patterns. Following validation, a parametric study was conducted to examine the effects of SFRC post-cracking tensile softening behavior, concrete compressive strength, stirrup bar diameter, and stirrup spacing. The results showed that SFRC tensile softening behavior significantly influenced residual torsional resistance, deformation capacity, and post-cracking response. Increasing concrete compressive strength improved both cracking torque and ultimate torsional capacity, although the improvement was not directly proportional to the strength increase. Reducing stirrup spacing was more effective than increasing stirrup bar diameter because closer stirrups improved crack control and enhanced the torsion-resisting mechanism. The findings confirm that steel fibers and transverse reinforcement provide complementary contributions to torsional resistance under pure torsion.
This study investigates reactive social responsibility (RSR) in architecture as an approach to assessing the deterioration of historic fabrics and their revitalization process. The paper focuses on Al-Rasheed Street in Baghdad, which has experienced several revitalization efforts in response to prolonged neglect, socio-political instability, and the decline of public life. It adopts a quantitative case study methodology supported by two field surveys targeting architects and public users who visited the site before. The survey (of public users) evaluated spatial perception, social interaction, and user satisfaction; meanwhile, the specialist survey evaluated the effectiveness of the architectural and spatial interventions. By integrating expert assessment and user experience, this approach offers an overall assessment of the revitalization process. The findings suggest that the interventions exemplify the concept of reactive social responsibility by responding to major challenges, including fading spatial character, limited social interactions and declining pedestrian activity, also the comparative analysis identified differences in how the publics and experts perceive the interventions, where publics expressed higher levels of satisfaction towards visual identity and spatial experience, while architects expressed more concerns towards participatory mechanisms and long-term sustainability. Through enhanced pedestrian walkability, facade renovation, and the upgrading of cultural activity, the street’s social vitality and public interaction were restored. A theoretical framework was also developed based on indicators such as participation, adaptability, contextual responsiveness, and social sustainability. The results, however, suggest that while these interventions achieve noticeable and measurable short-term improvements, their long-term impact remains limited without integrated policies, stakeholder involvement, and sustained proactive planning strategies. This empirical study offers a framework for systematic analysis based on clear measurement indicators and field data.
Efficient reservoir operation is an important aspect of sustainable water resources management in monsoon-driven river basins such as India, where hydrological variability and competing water demands present complex operating challenges. The present study is aimed to evaluate the comparative performance of evolutionary and nature inspired metaheuristic optimization approaches for the optimal operation of Indira Sagar Reservoir. The reservoir operation problem is formulated as a constrained multi-objective optimization problem to minimize water-supply deficits and improve hydropower related performance under the constraints of storage, dead-storage, release, spillway-capacity and storage-change. The selected algorithms represent different population-based evolutionary and nature-inspired search mechanisms and are evaluated under a common modelling framework using representative hydrological years. Performance is assessed based on deficit reduction, convergence behavior, reliability, resilience, vulnerability, and sustainability indicators. The existing operating policy exhibited low time-based reliability (0.4627) and volumetric reliability (0.6854), while resilience reached 1.0000, indicating rapid recovery following detected failures but frequent shortage occurrence. The comparative results showed that CSA achieved the lowest mean deficit of 966.8 MCM among the evaluated approaches, compared with approximately 14,220.14 MCM for the existing policy, followed by IWO and CA. The observed ranking was CSA > IWO > CA > TV-EM-MOPSO > EM-MOPSO > MO-PSO. These findings identify CSA as the most promising candidate among the evaluated approaches for further development and validation of an improved operating policy for Indira Sagar Reservoir.
The corrosion of steel bars in reinforced concrete structures subjected to harsh environments remains a significant challenge. Fiber-reinforced polymer (FRP) composites have been investigated as potential alternatives to conventional steel reinforcement. While basalt fiber-reinforced polymer (BFRP) bars exhibit high tensile strength, durability, and sustainability, they are characterized by linear elastic behavior and a brittle failure mode. Hybrid reinforcements of steel and BFRP bars combine the ductility of steel with the corrosion resistance of BFRP. This study presents the development and validation of a three-dimensional nonlinear finite element (FE) model in ABAQUS to simulate the flexural behavior of high-strength concrete (HSC) beams reinforced with a hybrid (steel/BFRP) system under repeated loading. Six beam specimens with a compressive strength of 86.5 MPa were modeled and validated against experimental results. The FE model predicted ultimate load capacity with an average error of 4.97%, while deflection predictions showed an average error of 17.44%. The beams failed when the concrete cracked before the BFRP bars reached their full tensile capacity. A parametric study investigated the effects of increasing the concrete compressive strength from 86.5 MPa to 120 MPa on BFRP stress utilization, ultimate load capacity, and failure mode. Numerical results predict that increasing the concrete strength to 120 MPa significantly enhances structural performance, suggesting a shift in failure mode as indicated by the model. These findings provide valuable insights into optimizing hybrid reinforcement systems for improved structural efficiency and durability.
This paper introduces a rigorous dynamic modeling and control platform of the electromechanical energy conversion systems of single-shaft, heavy-duty gas turbines. As contemporary power grids become increasingly volatile with the integration of intermittent renewable power sources, traditional fixed-gain Proportional-Integral-Derivative (PID) controllers are becoming less effective in maintaining a stable frequency and protecting the thermomechanical limits of the turbines. To address this limitation, a non-linear dynamic model was developed incorporating governor droop, valve actuator inertia, combustion thermodynamics, and rotor swing dynamics. Then, a synthesized PID-based Model Reference Adaptive Control (MRAC) algorithm that dynamically adjusts control gains in real-time using the MIT rule was developed. Three critical operational stress tests applied to the proposed MRAC-PID architecture included a 20% step load disturbance, high-frequency load tracking, and parameter uncertainty with half the grid inertia. Quantitative analysis demonstrates that the MRAC-PID controller shows significant improvements in comparison with the classical PID, reducing the maximum frequency undershoot from -0.018 p.u. to (a 61.1% improvement), reducing thermal overshoots by 88.8%, and decreasing transient settling time by 63.8%. Moreover, the adaptive algorithm effectively eliminated valve chattering during stochastic load operation and mitigated severe torsional resonance during low-inertia operation.
Hydraulic jumps are a fundamental phenomenon in open channel hydraulics, playing a critical role in energy dissipation and stilling basin design. Experimental research was conducted to investigate the hydraulic jump controlled with a thin-crested sill of varying heights and positions, which has not been previously investigated. Therefore, this experimental study was conducted to investigate hydraulic jump control using a thin-crested sill of varying heights and positions. The exact location of the hydraulic jump within the horizontal open channel should be known to prevent any damage to the surrounding structures. In total, 130 experiments were performed with initial Froude numbers ranging from 3.42 to 8.93. Measurements included the basic variables, such as initial and sequential depths, jump lengths, energy losses for sluice gate openings, and different discharge rates. Findings indicate that although the sill placement had minimal effect on the sequent depth ratio, it had a significant reduction in jump length, jump position, and energy dissipation in the stilling basin. The experimental sequent depth ratio (y₂/y₁) showed close agreement with the values predicted by Bélanger's equation. In addition, regression models developed to estimate the sequent depth ratio, jump length, energy loss, and optimal sill location achieved coefficients of determination ranging from 0.82 to 0.98. These results provide practical design guidance for selecting appropriate sill dimensions and locations to ensure complete hydraulic jump formation and effective energy dissipation in stilling basins.
The research aims at studying the wind-induced pressure on an 8° low-slope gable roof by means of wind tunnel tests and ANSYS Fluent simulation analysis. Direct pressure measurements were obtained from the experimental tests, and the resulting pressure distribution and aerodynamic flow were interpreted by the numerical model. The four roof configurations examined were a closed roof, a single opening, two openings and four openings. These cases were then tested experimentally under the same conditions in an open-circuit wind tunnel at the College of Engineering at the University of Baghdad with a fixed wind velocity of 38 m/s. Pressure coefficients were calculated from the pressure taps located over the windward wall, leeward wall and the gable roof surfaces. A steady, incompressible RANS formulation numerical model was then constructed in ANSYS Fluent 2025 R1 with the standard k–ε turbulence model. Increasing the number of openings on the roof resulted in improved interaction between the external separated flow and the internal air volume, and resulted in a noticeable redistribution of the pressure over the roof surface. The CFD results were compared with the experimental measurements, and the results were very good, with a high , an and a . Based on the results, it can be concluded that the openings of a roof can have a significant impact on the aerodynamic pressure response of low-rise gable roofs and that the openings should be taken into account when assessing roof pressures due to wind.
Acute lymphoblastic leukemia (ALL) is the most malignant form of leukemia. This form of leukemia is considered the most prevalent kind of cancer in both adults and children. Leukemia is typically identified by analyzing blood and bone marrow smears under a microscope. Advanced cytochemical testing can also be performed to confirm and categorize leukemia. However, these approaches are expensive, time-consuming, and dependent on the skill and knowledge of the relevant specialists. In recent decades, deep learning with convolutional neural networks (CNNs) has generated sophisticated methods for image classification by analyzing microscopic smear images to detect the presence of leukemic cells. These techniques are easy to use, quick, affordable, and free from expert bias. Nevertheless, the majority of these approaches are unable to quantify the uncertainty in their results, which can have devastating consequences. This research implemented hybrid models that merged InceptionV3-GRU, EfficientNetB3-GRU, and MobileNetV2-GRU for detecting and classifying ALL. Following this, to identify an optimal set of hyperparameters and enhance the model's performance, Bayesian optimization is utilized. Then, we use a deep ensemble uncertainty quantification approach to deal with uncertainty during ALL image classification. The outcomes of three different hybrid deep learning models were then aggregated at the score level using the sum rule after they had been trained on the two publicly available ALL patient blood sample datasets: ALL-IDB1 and ALL-IDB2. Herein, a parallel architecture was considered, which offers a high degree of confidence in discriminating between ALL and not ALL. The proposed system has managed to correctly and accurately diagnose the ALL patients, respectively, with a detection accuracy rate of 100% for the ALL-IDB1 dataset, 98.07% for the ALL-IDB2 dataset, and 98.64% for the combined dataset using our proposed method.
Construction project performance in developing economies is consistently hindered by complex, interdependent challenges, often managed in isolation. This study addresses this systemic gap by developing and validating a novel Integrated Multidimensional Performance Optimization Framework (IMPOF). Applying multivariate regression models to empirical data from 50 projects in Ethiopia’s Amhara Region, the research quantifies synergies and trade-offs among six core performance dimensions: cost, schedule, quality, safety, environmental sustainability, and logistics. Diagnostic evaluation confirms that all models meet key OLS assumptions, with no harmful multicollinearity, normally distributed residuals, linear relationships, and constant error variance. The analysis reveals a “Productivity–Quality–Cost Paradox,” where intense pressure for labor productivity (β = −3.068 for Quality; −5.402 for Cost) leads to corner-cutting, rework, and waste, challenging foundational industry norms. Crucially, logistics emerges as a strategic linchpin, with metrics like Delivery Route Efficiency (β = 28.344 for Schedule) delivering cascading benefits across all performance domains. The findings advocate for firms to institutionalize preventive maintenance, implement GIS-based logistics systems, and adopt adaptive scheduling. The framework redefines success as achieving “Constrained Optimization” across the entire project ecosystem, advocating for adaptive scheduling and positioning environmental sustainability as a core indicator of operational efficiency. For practitioners and policymakers, this research provides an actionable roadmap: investing in logistics digitization, reforming contracts with integrated incentives, redefining onsite productivity around quality and safety, and formalizing skills development. Ultimately, the study underscores the need for integrated leadership and a collective mindset shift toward holistic project management to enhance efficiency, resilience, and sustainability in developing regions. Future research should integrate machine learning and dynamic simulation to further refine predictive accuracy.
Concrete, among the most commonly applied materials, has drawn considerable attention in building construction and road making. However, the extensive use of cement, which forms the majority of the concrete, leads to environmental pollution. In addition, with enhanced population and country growth, particularly in certain road constructions, improved quality at even greater construction costs seems to be an essential requirement. The application of advanced technologies, such as nanomaterials and new materials like shape memory alloy (SMA) in this context, needs to be investigated. This research examines the compressive, splitting tensile, flexural, and secondary compressive strength, as well as ultrasonic pulse velocity (UPV) of concrete specimens. The specimens are composed of SMA at percentages of 0.1%, 0.2%, and 0.3%, nano-silica (NS) at percentages of 1%, 3%, and 5%, and a combined mix design incorporating both materials simultaneously in a 28-day curing period. The results are compared with a control sample made with ordinary Portland cement (OPC). The findings demonstrate that, in addition to achieving a 17% increase in compressive strength and a 4% increase in both splitting tensile and flexural strength, the addition of 3% NS is also more cost-effective than the addition of 5% NS. Furthermore, the use of 0.3% SMA enhances the strength parameters, but the combination of SMA and NS improves compressive strength by up to 20%, splitting tensile strength by up to 7%, and flexural strength by up to 12%, exhibiting the best performance. In addition, SMA can prevent the drop in compressive strength during reloading due to its stress control behavior after cracking. Additionally, NS-containing samples exhibit the highest dynamic modulus of elasticity (MOE). It is worth mentioning that a strong correlation exists between the compressive strength of NS-containing specimens and their secondary compressive strength, splitting tensile strength, MOE, and UPV. Similarly, specimens containing SMA show a high correlation with their secondary compressive, flexural, and splitting tensile strengths. These findings highlight the potential of incorporating SMA and NS in concrete to improve its mechanical characteristics while reducing environmental impact significantly.
We investigate the performance limits of spectral amplitude coding optical code-division multiple access (SAC-OCDMA) systems from a receiver-centric perspective. Existing approaches have focused largely on code design and uniform receiver architectures; however, these measures provide only partial mitigation and lead to rapid BER saturation as the number of active users increases. We develop an incoherent SAC-OCDMA framework using a block-shifted circulant matrix XOR (BSCM-XOR) code and examine both uniform and multiple detection schemes. We also developed a modified direct detection (MDD) receiver, which performs interference redistribution in the optical domain prior to photodetection. The different detection schemes used in our heterogeneous step-up are MDD, Direct-AND, and AND-subtraction. Simulation results obtained using OptiSystem 15.0 demonstrate that heterogeneous detection reshapes the noise hierarchy by suppressing PIIN accumulation. This effectively shifts the system operation from an interference-limited to a noise-limited regime. At a benchmark of BER (10−9), the proposed MDD scheme extends transmission reach by up to ∼28 km compared with the AND-subtraction detection scheme under identical conditions. Our results show that SAC-OCDMA performance limits are not determined by code correlation alone but are strongly receiver-defined, establishing receiver heterogeneity as a practical and low-complexity design for robust multiuser optical access network.
