The practice of operating hydraulic machines and equipment shows that failures can occur earlier than the specified lifespan. At the same time, at the stage of carrying out strength calculations of the designed machines and equipment, significant safety margins are incorporated into parts and units. That is, calculated machine lifespans often exceed actual values. Accurate data require full-scale lifespan testing or observations of operation. However, resource tests are economically expensive, since they require a significant amount of energy, and, as a result, lead to a negative impact on the environment. It is possible to level out the listed shortcomings during resource tests by using energy-efficient and energy-saving technologies, such as energy recovery. This study enhances energy efficiency and assesses engineering systems during equipment design. In particular, we present a hydromechanical drive design for testing reciprocating hydraulic machines. The study analyzes energy-saving and energy recovery methods during operation. On the basis of the analysis and previously conducted studies, we developed a mathematical model for hydraulic equipment testing. The developed model is based on the volumetric stiffness theory, enabling analysis of the design and functional characteristics of test stand components on their dynamic behavior and energy efficiency.

This study focuses on the participation of energy storage in primary frequency regulation of offshore wind farms. A frequency regulation performance evaluation indicator is designed, and the black-start capability of the wind farm after shutdown is also considered. By equivalently processing the black-start time, a black-start capability evaluation indicator is designed. An energy storage strategy is adopted to balance power charging and discharging during the primary frequency regulation cycle. Considering the service life of energy storage batteries and the maximum number of charge/discharge cycles, a multi-objective comprehensive optimization model is proposed, which integrates frequency regulation performance, annual average investment cost of energy storage, black-start capability, and wind energy utilization rate. The designed model is solved using a genetic algorithm. Finally, a case study of an offshore wind farm is given to compare and analyze the primary frequency regulation with energy storage participation and the joint frequency regulation of wind and energy storage, which verifies the effectiveness of the proposed designed model and algorithm.

In a scenario where fuel costs are notably high and the policies that we are currently witnessing tend to limit the fossil fuel resource that powers most heavy goods transport services, the optimization of space in vehicles transporting these goods, such as trucks and shipping containers, becomes an indisputable and urgent need. This urgency is manifested in the need to minimize the costs associated with transport, given its increasing growth. This experiment aims to study and implement an Internet of Things (IoT)-based solution to the problem previously presented. The developed system comprises a computer and a millimeter-wave (mmWave) sensor. The computer processes the data captured by the sensor through code in Python language and displays, through a web page allocated in a cloud/server, the volume occupied by the load, as well as the percentage of occupied and free space, considering the volume provided by the user. The validation tests consisted of checking the results in 2D and 3D, all carried out in a controlled environment focused on the detection of static objects. For the 3D analysis, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm was used to obtain the points for extracting the volume of the detected object. Several objects with different dimensions were used and the error ranged from 0.6% to 7.61%. These results denote the confirmation of the reliability and efficacy of the presented solution. With this, it was concluded that this new solution has significant potential to enter the market and compete with other existing technologies.

Sports activities often carry a high risk of injury, varying in severity, making the use of protective equipment, such as helmets and kneecaps, essential in many cases. Among all potential injuries, head injuries are the most crucial due to their severity. Hence, in the last decades, the scientific interest has been focused on establishing head injury criteria and improving the helmet design with the ultimate goal of the reduction in injury probability and increasing the athlete’s performance. In this context, the current study aims to develop a lightweight sports helmet with increased safety performance, utilizing topology optimization processes and advanced architected materials. In detail, the design of a conventional helmet was developed and modified applying in specific regions advanced architected materials, such as triply periodic minimal surfaces (TPMS) and hybrid structures, with functionally graded configurations to produce sandwich-like structures capable of absorbing mechanical energy from impacts. The developed helmet’s designs were numerically evaluated through dynamic finite element analyses (FEA), simulating the helmet’s impact on a wall with a specific velocity. Through these analyses, the plastic deformation of the designed helmets was observed, coupled with the stress concentration contours. Furthermore, the results of FEAs were utilized in order to calculate the values of the head injury criterion (HIC). Finally, the developed topologically optimized helmet design incorporating the hybrid lattice structure revealed increased energy absorption, reaching a HIC of 1618, improved by around 14% compared to the conventional design configuration.

Ultrasonic power stimulation of polymers has been employed to modify their properties for various industrial applications. It is used to disperse particles in polymers or to impregnate continuous fiber-reinforced filaments. These processes operate under extreme conditions, involving temperatures exceeding 400 °C and pressures reaching up to 60 bars. Traditional sound introduction systems rely on moving horns within cavities, which pose significant challenges in maintaining clean environments. The moving horn makes it inconceivable to seal such sound introduction systems. To address these limitations, an innovative tool that incorporates only sealed components capable of introducing sound energy without employing cavities was developed. This technology focuses on optimizing eigenfrequencies to efficiently transfer motion into the polymer channel while minimizing disturbing vibrations and sealing issues. The simulation results reveal the mode of operation between the fourth and fifth resonance of the tool. The measurements of the tool validate this theory, indicating a range of operation between 18.5 kHz and 19.5 kHz. With an amplitude of 15 μm, resulting in a minimum power introduction of 224.03 W/cm² in PLA, the average flow rate gain is 13.6%. This new design reduces the risk of blockages and damage in the processed goods and minimizes the force required to process the polymer.

Identifying the parameters of a triple-diode electrical circuit structure in PV modules is a critical issue, and it has been regarded as an important research area. Accordingly, in this study, a differential evolution algorithm (DEA) is hybridized with an electromagnetism-like algorithm (EMA) in the mutation stage to enhance the reliability and efficiency of the DEA. A new formula is presented to adapt the control parameters (mutation factor and crossover rate) of the DEA. Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). The results of the proposed PV modeling method are evaluated with other state-of-the-art approaches. According to different statistical criteria, the DEIMA demonstrates superiority in terms of root mean square error and main bias error by at least 5.4% and 10%, respectively, as compared to other methods. Furthermore, the DEIMA has an average execution time of 27.69 s, which is less than that of the other methods.

This article provides a comparative analysis of pendulum and radial micro-hydropower plants. The novelty of this study lies in the comparative analysis of units that are fundamentally different in design to achieve the most rational option for low-speed rivers. It has been established that a pendulum micro-hydropower plant has a high torque with relatively small dimensions but operates cyclically. At a diameter of 1 m and a blade area of 0.3 m2, the peak torque was 140 N·m. At the same time, the design is sensitive to the blade area and at 0.6 m2 and a lever length of 1.5 m, the torque reached 430 N·m. A radial micro-hydropower plant has lower torque but operates constantly. At an area of 1.23 m2 and a diameter of 1 m, the torque was 40.4 N·m. Accordingly, in terms of specific area with a diameter of 1 m, a pendulum micro-hydropower plant has up to 12 times more torque. It has been established that the pendulum hydropower plant best satisfies the requirements for converting a low river speed into high revolutions of a current generator.

Technological progress is leading to the incorporation of digital twinning and artificial intelligence, causing engineering design and scientific procedures to transition into an AI-driven age. Digital twinning and modeling have been increasingly included into engineering design optimization, particularly via processes like topology optimization and generative design, to provide modern design solutions efficiently. The integration of topology optimization with additive manufacturing is revolutionizing the design optimization process in the automotive industry, where there is a pressing demand for lightweight design and improving production efficiency. A design optimization methodology has been developed to optimize an Automotive Seatbelt Bracket subjected to dynamic load and fatigue. The innovative design is lighter and consolidates the entire assembly into a single body that can be manufactured using additive manufacturing.

Agrivoltaic agrotunnels are currently designed for high-density grow walls that are not amenable to bush berries or root crops. Commercial grow bins provide deeper substrates for produce with more root systems but have high costs per unit growing area. To overcome the economic limitations of grow bins, this study applies the distributed manufacturing open-source design paradigm to develop four designs for low-cost open-source structures. The designs target root vegetables and bush fruit specifically to be adopted by remote communities with limited or no outdoor growing environment to offset the market price for imported fresh produce. The indoor growing designs provide the necessary structure for supporting grow lights and grow bins and enable the transplanted berry plants to flower and produce fruits. They provide a comparable amount (110 L) or more of grow volume from 106 to 192 L. The water reservoir volume for the commercial system (62 L) and grow area (0.5 m3) is surpassed by all new designs that range from 64 to 192 L and 0.51 to 0.76 m3, respectively. These superior properties are possible with material costs for all four designs that save more than 90% of the economic cost of the commercial systems.

The present paper is devoted to the seismic design of steel frames constituted by multistep I-shaped cross-section beam elements. The proposed design problem formulation is aimed at protecting the connections among beams and columns. In particular, reference is made to beams welded at their ends to appropriate steel plates connected by bolts to the columns. Therefore, the protection against brittle failure of the beam end sections is ensured by appropriate constraints of the optimal design problem. A useful comparison is made between the adoption of the so-called Reduced Beam Sections (RBS) and the use of multistep beam elements. In particular, the RBS approach here considered is the well-known dogbone technique consisting of reducing the width of the beam cross-sections in correspondence with suitably located beam portions, while the typical multistep beam element is constituted by a factory-made I-shaped uniform piecewise profile. To perform the necessary comparison, reference is made to a three-story, two-span plane steel frame constituted by elastic, perfectly plastic material and subjected to static and seismic loads. The load conditions and the relevant combinations have been imposed in compliance with the Italian structural code. The frame is first studied as constituted by European standard steel profiles on sale, and the related design is obtained using the optimization tool contained in SAP2000 software. A linear dynamic analysis is performed to determine the response of the frame. Later, the same frame, either equipped with dogbone and constituted by multistep beam elements, subjected to serviceability load conditions, is studied in terms of inter-story drifts and beam deflections. The geometry of the multistep beam elements is obtained by the solution to the proposed optimization problem. Furthermore, a nonlinear static analysis is performed to evaluate the capacity curves of the same frames. The results obtained for the frames equipped with the described different devices, compared with those related to the original frame, provide very interesting information on the sensitivity of the seismic response of the structure, showing the full reliability of the multistep beam element approach.