Predicting pavement performance is essential for highway planning and construction, considering traffic, climate, material quality, and maintenance. This study’s main objective is to evaluate Baosteel’s Slag Short Flow (BSSF) steel slag as a sustainable aggregate in pavement engineering by means of durability. The research integrates pavement performance prediction using BSSF and assesses its impact on fatigue resistance and percentage of cracked area (%CA). Using the Brazilian mechanistic-empirical design method (MeDiNa), eight scenarios were analyzed with soil–slag mixtures (0%, 25%, 50%, and 75% slag) in base and subbase layers under two traffic levels over 10 years. An asphalt mixture with 15% steel slag aggregate (SSA) was used in the surface layer and compared to a reference mixture. Higher SSA percentages were applied to the base layer, while lower percentages were used in subbase layers, facilitating field implementation. The resilient modulus (MR) and permanent deformation (PD) were design inputs. The results show that 15% SSA does not affect rutting damage, with %CA values below Brazilian limits for traffic of 1 × 106. The simulations confirm BSSF as an effective and sustainable alternative for highway pavement construction, demonstrating its potential to improve durability and environmental impact while maintaining performance standards.

A hyperparameter-optimized Kriging surrogate model was developed for the structural collapse behavior framework presented in this paper. The assessment is conducted on a stiffened panel subject to axial load and lateral pressure, typical of the deck structure of a bulk carrier ship. This behavior is characterized using nonlinear finite element analysis to determine the collapse response. The surrogate model’s hyperparameters were optimized using a Genetic Algorithm to achieve the best performance, and the trained framework can predict ultimate strength. By following this approach, the problem can be reformulated as a multi-objective optimization task. This framework involves associating the Kriging surrogate model with a multi-objective evolutionary optimization algorithm based on Genetic Algorithms to balance the trade-off between the weight and ultimate strength of the stiffened panel. The results confirm the applicability of the Kriging surrogate framework to predict the ultimate strength and assess the collapse analysis of the stiffened panels, ensuring accuracy through GA-based hyperparameter optimization.

A testing method is developed to evaluate the acceleration- and strain-based fatigue life of a thermal interface layer in the high-cycle fatigue regime. The methodology adopts vibration-based fatigue testing, where adhesively bonded beams are excited at their resonant frequency under variable amplitude loading using an electrodynamic shaker. Fatigue failure is monitored through shifts in modal frequency and modal damping. Key findings include the identification of a 4% frequency shift as the failure criterion, corresponding to macro-delamination. The thickness of the thermal interface material influences acceleration-based fatigue life, decreasing by a factor of 0.2 when reduced from 0.3 mm to 0.15 mm and increasing by 5.5 when increased to 0.5 mm. Surface quality has a significant impact on both acceleration-based and strain-based fatigue curves. Beams from chemically etched aluminum–magnesium alloy specimens exhibit a sevenfold increase in fatigue life compared to beams from untreated printed circuit boards. Strain-based fatigue life increases with temperature, with a 0.2 reduction at −40 °C and an eightfold increase at 100 °C relative to 23 °C. The first principal strain ε1,rms is validated as a reliable local damage parameter, effectively characterizing fatigue behavior across varying TIM thicknesses.

Burst pressure is one of the critical strength parameters used in the design and operation of pressure vessels because it represents the maximum pressure that a vessel can withstand before failing. Historically, the Barlow formula was used as a design base for estimating burst pressure. However, it does not consider the plastic flow response for ductile steels and is applicable only to thin-walled cylinders (i.e., the diameter to thickness ratio D/t ≥ 20). A new multiaxial plastic yield theory was developed to consider the plastic flow response, and the associated theoretical (i.e., Zhu–Leis) solution of burst pressure was obtained and has gained extensive applications in the pipeline industry because it was validated by different full-scale burst test datasets for large-diameter, thin-walled pipelines in a variety of steel grades from Grade B to X120. The Zhu–Leis flow theory of plasticity was recently extended to thick-walled pressure vessels, and the associated exact flow solution of burst pressure was obtained and is applicable to both thin and thick-walled cylindrical shells. Many full-scale burst tests are available for thin-walled line pipes in the pipeline industry, but limited pressure burst tests exist for thick-walled vessels. To validate the newly developed exact solutions of burst pressure for thick-walled cylinders, this paper conducts a series of burst pressure tests on small-diameter, thick-walled pipes. In particular, six burst tests are carried out for three thick-walled pipes in Grade B carbon steel. These pipes have a nominal diameter of 2.375 inches (60.33 mm) and three nominal wall thicknesses of 0.154, 0.218, and 0.344 inches (3.91, 5.54, and 8.74 mm), leading to D/t = 15.4, 10.9, and 6.9, respectively. With the burst test data, comparisons show that the Zhu–Leis flow solution of burst pressure matches well the burst test data for thick-walled pipes. Thus, these burst tests validate the accuracy of the Zhu–Leis flow solution of burst pressure for thick-walled cylindrical vessels.

Researchers are currently conducting several studies in the field of navigation systems and sensors. Even in the past, there was a lot of research regarding the field of velocity sensors for unmanned underwater vehicles (UUVs). UUVs have various services and significance in the military, scientific research, and many commercial applications due to their autonomy mechanism. So, it’s very crucial for the proper maintenance of the navigation system. Reliable navigation of unmanned underwater vehicles depends on the quality of their state determination. There are so many navigation systems available, like position determination, depth information, etc. Among them, velocity determination is now one of the most important navigational criteria for UUVs. The key source of navigational aids for different deep-sea research projects is water currents. These days, many different sensors are available to monitor the UUV’s velocity. In recent times, there have been five primary types of sensors utilized for UUV velocity forecasts. These include Doppler Velocity Logger sensors, paddlewheel sensors, optical sensors, electromagnetic sensors, and ultrasonic sensors. The most popular sensing sensor for estimating velocity at the moment is the Doppler Velocity Logger (DVL) sensor. DVL sensor is the most fully developed sensor for UUVs in recent years. In this work, we offer an overview of the field of navigation systems and sensors (especially velocity) developed for UUVs with respect to their use with tidal current sensing in the UUV setting, including their history, evolution, current research initiatives, and anticipated future.

This paper analyzes the surface quality characteristics, such as arithmetic average roughness (Ra), maximum peak-to-valley height (Rt), and average peak-to-valley height (Rz), in hard turning of AISI 52100 steel using a (TiN/TiCN/Al2O3) coated carbide insert under a minimal cutting fluid environment (MCFA). MCFA, a sustainable high-velocity pulsed jet technique, reduces harmful effects on human health and the environment while improving machining performance. Taguchi’s L27 orthogonal array was used to conduct the experiments. The findings showed that surface roughness increases with feed rate, identified as the most influential parameter, while the depth of cut shows a negligible effect. The main effects plot of signal-to-noise (S/N) ratios for the combined response of Ra, Rt, and Rz revealed the optimal cutting conditions: cutting speed of 140 m/min, feed rate of 0.05 mm/rev, and depth of cut of 0.3 mm. Feed rate ranked highest in influence, followed by cutting speed and depth of cut. The lower values of surface roughness parameters were observed in the ranges of Ra ≈ 0.248–0.309 µm, Rt ≈ 2.013–2.186 µm, and Rz ≈ 1.566 µm at a feed rate of 0.05–0.07 mm/rev. MCFA-assisted hard turning reduces surface roughness by 35–40% compared to dry hard turning and 10% to 24% when compared to the MQL technique. Moreover, this study emphasizes the significant environmental benefits of MCFA, as it incorporates minimal eco-friendly cutting fluids that minimize ecological impact while enhancing surface finish.

Micropiles, small-diameter-drilled and grouted piles, are often used to provide foundation support in challenging ground conditions. This research seeks to understand the behavior of Type D micropiles (pressure-grouted) within layered soil profiles. Layered soils frequently create complexity because of differences in stiffness, strength, and permeability, which impact load transfer and the interaction between the micropiles and the surrounding soil. Type D micropiles use pressure injection, which results in enhanced skin friction, better grout–soil contact, and a greater capacity to carry loads. A set of numerical simulations was conducted to analyze the behavior of the micropile Type D under axial loading, which was evaluated by considering factors such as micropile diameter, spacing, and inclination. The results indicated that increasing the diameter of a micropile significantly improves its performance by enhancing load transfer and structural stiffness, as well as reducing soil deformation and settlement. In addition, for vertical micropiles and those with inclination angles of 10° and 20°, stiffness increased with diameter, while axial displacement remained constant at a 45° inclination. Furthermore, larger diameters reduced lateral displacements up to 20° inclination angles by increasing stiffness, but lateral deflection increased at 45° due to greater lateral load components. The bending moment increased with inclination angle, driven by higher horizontal loads and increased eccentricity, while spacing had little effect for angles greater than 20° due to effective load redistribution.

Understanding the response and damage evolution of structures subjected to multiple impact events is essential for designing resilient structures capable of withstanding complex loading scenarios, such as impacts from hail, gravel or foreign object debris. This article presents the development and characterization of a novel test bench, the “Compressed air multi-cannon”, designed specifically for studying the multi-impact behavior of composite materials. This test bench offers advantages over traditional impact testing methods by enabling controlled and adjustable impact parameters, including number of impacts, spatial and temporal lag, energy, angle and impactor dimensions. The primary objective of this work is to provide a detailed description of the test bench design, construction, and validation procedures. Key components such as the pressurized air system, projectile launch mechanism, target mounting arrangement, and data acquisition system are discussed. Experimental methodologies for assessing multi-impact response, specimen preparation, instrumentation, and data analysis techniques are outlined. Through a series of single-impact and multi-impact tests, distinctive damage mechanisms and energy absorption characteristics were observed in composite structures, revealing significant differences in how composites respond under single- and multi-impact conditions. It was found that the single-impact configuration remains particularly critical compared to multi-impact configurations with a high number of impacts. However, further testing is required to determine whether this result holds true under varying impact parameters, highlighting the unique value of this machine for exploring new, realistic questions in the literature.

The performance of the porous gas bearing depends on the geometric characteristics, material, fluid properties, and the properties of the porous media, which is a restrictor that controls the gas flow. Its application in industrial environments must support higher loads, higher supply pressure, and, consequently, higher pressure in the lubricant fluid film. Because porous media has a relatively low elastic modulus, it is necessary to consider its deformation when designing porous gas bearings. The design of porous gas bearings is a multi-objective problem in engineering because the optimization objectives commonly are to maximize the load capacity or static stiffness coefficient and minimize the airflow; these objectives conflict. This work presents a multi-objective optimization algorithm based on the nature-inspired Flower Pollination Algorithm enhanced with Non-Dominated Sorting Genetic Algorithm II. The algorithm is applied to optimize the design of a porous gas bearing, maximizing the resultant force and the static stiffness coefficient and minimizing the airflow. The results indicate a better performance of the Multi-Objective Flower Pollination Algorithm than the Multi-Objective Cuckoo Search. The results show a relatively short running time of 6 min for iterations and a low number of iterations of 50.

Aluminium alloys are used for the fabrication of the fuel clad of research-grade nuclear reactors as well as for several types of core components of high-flux research reactors. In order to carry out design and safety analysis of these components, their mechanical and fracture properties are required by the designer. In this work, experiments have been conducted on tensile specimens machined from an aluminium alloy block to evaluate the material stress-strain curve. Experiments have also been conducted on disc-shaped compact tension specimens in order to determine the fracture toughness of aluminium alloy. Numerical simulations of both tensile and fracture specimens have been carried out using the crystal plasticity model. Initially, the slip system level parameters of the crystal plasticity material model have been calibrated using experimental stress-strain data for single as well as polycrystalline aluminium. For the prediction of crack initiation toughness, Rice and Tracey’s damage model has been used. The critical damage parameter has been evaluated for a fractured specimen with a crack length-to-width (a/W) ratio of 0.6. The attainment of the critical damage parameter in the analysis corresponds to the instance of experimentally observed ductile crack initiation in the specimen. Later, this model was applied to other fracture specimens with different a/W ratios with values ranging from 0.39 to 0.59. It was observed that the critical damage parameter corresponding to crack initiation in the material has a very small variation, even if the specimens have different crack lengths. It is well-known in the literature that Rice and Tracey’s critical damage parameter is a material constant. Hence, we have applied the same model to predict crack initiation for single crystal fracture specimens with two different orientations of the crack plane. It was observed that the <111> orientation is more susceptible to crack initiation and propagation compared with the <100> orientation, as the damage parameter is high in the ligament of the specimen ahead of the crack tip for the same level of applied loading. As the [111] crack plane is more closely packed compared with the [100] plane, the distance between atomic planes is greater for the former, and hence, it is more susceptible to ductile damage. The results of the experiments and the material damage parameter are helpful for the integrity analysis of the fuel clad of research reactors as well as components of high-flux research reactors.