Accelerometers are extensively utilized in various applications to measure vibrations (in the form of acceleration) across different vibrational structures. Researchers have already been exploring different mechanisms to interpret acceleration values. In this regard, over the past decades, Microelectromechanical Systems (MEMS) accelerometers have been prominently describing the interconnectivity between the generated electrical signal and the accelerated motion. However, there has been a major gap in the comparative assessments of the different transduction mechanisms. Therefore, in this research work, a classical dynamics approach is utilized to mathematically model the MEMS accelerometer by incorporating three different designing mechanisms: Piezoelectric, Electro-Capacitive, and Electromagnetic transductions. The transfer functions of all three designs of the MEMS accelerometer are developed by incorporating different structural parameters, material properties, and external input conditions. The piezoelectric accelerometer relies on the inherent compliance of the piezoelectric material, the electric field generated, and the material’s dimensions. The electro-capacitive model’s key parameters include the number of rows of capacitive plates in a comb-like structure, the area of each plate, and the voltage produced by these capacitive elements. On the other hand, the electromagnetic accelerometer depends mainly on the change in flux produced by the magnet in the coil, the coil length, and the magnetic field strength. MATLAB has been utilized to investigate the electrical response of the designed MEMS accelerometers by considering several controllable factors of each modeled system. The tangible findings highlight that under the same environmental as well as external input conditions, the Piezoelectric accelerometer produces the highest output voltage as compared to the electro-capacitive and electromagnetic MEMS accelerometers. Therefore, this article provides a well-established theoretical, mathematical, and semi-numerical interpretation of the MEMS accelerometers for multipurpose engineering applications.

Trapezoidal sheet metal is widely used in construction due to its high strength-to-weight ratio. However, optimizing its shape for both bending stiffness and coverage area poses a significant challenge. This study focuses on optimizing the shape of trapezoidal sheet metal to achieve maximum bending stiffness and coverage area, with the constraint of fixed working length. Using Pareto front analysis, we identified the optimal shape incorporating stiffeners on the flanges and web. The dual objectives of maximizing stiffness and coverage area often conflict, making the optimization problem complex. The proper formulation and selection of optimization algorithms are crucial. We employed both global and local minimization algorithms with multistart methods to effectively explore the design space.

We utilized Pareto front analysis to balance the conflicting objectives of maximizing bending stiffness and coverage area. The shape of the sheet metal, including stiffeners on the flanges and web, was optimized using both global and local minimization algorithms. Multistart methods were applied to ensure comprehensive exploration of the design space. The optimization revealed that achieving an optimal shape for trapezoidal sheet metal requires careful consideration of the trade-offs between bending stiffness and coverage area. The Pareto front provided a range of optimal solutions, highlighting the importance of selecting appropriate algorithms for different aspects of the optimization problem.

This research demonstrates that the shape optimization of trapezoidal sheet metal is a complex yet feasible task when using advanced optimization techniques. The findings emphasize the critical role of problem formulation and algorithm selection in achieving effective results. Future work will explore further refinements in the optimization process and application to other structural components. This study provides a robust framework for engineers to optimize the design of trapezoidal sheet metal, enhancing its performance and efficiency in construction applications.

Water and sewer manholes are prone to chemical degradation, resulting in concrete erosion and structural weakening. Traditional repair methods often fail to restore the original load-bearing capacity adequately. This study investigates an innovative method for renovating water and sewer manholes using a three-layer coating of polyurea and closed-cell rigid foam. The chemical degradation of manholes leads to significant concrete loss, necessitating robust repair methods. Finite Element Method (FEM) analyses were conducted on axisymmetric manhole structures subjected to soil pressure and tanks with internal water pressure, considering existing concrete damage.

This study employed FEM to simulate the structural behavior of damaged manholes under various loading conditions. A three-layer repair coating comprising polyurea and closed-cell rigid foam was applied to address these damages. Numerical homogenization was used to reduce the complex cross-section of the repaired manhole to a single equivalent layer, facilitating simplified yet accurate structural analysis. The homogenization process enabled the transformation of the geometrically complex cross-section into an effective single layer with equivalent properties. This approach allowed for the re-evaluation of the manhole's load-bearing capacity, demonstrating significant improvements due to the innovative repair method.

This research underscores the efficacy of using a three-layer polyurea and closed-cell rigid foam coating for manhole renovation. The combination of FEM and homogenization techniques provided a reliable framework for assessing and enhancing the structural integrity of repaired manholes. This study's findings support the adoption of this innovative repair method, promising improved durability and performance of water and sewer infrastructure. This work contributes to the field of civil engineering by presenting a practical and effective solution for extending the lifespan of critical infrastructure elements.

Laminated and sandwich plates are widely used in engineering applications due to their high strength-to-weight ratio. However, the presence of delamination can significantly affect their structural performance, particularly under bending loads. This study addresses the numerical homogenization of multilayer laminated and sandwich plates, incorporating the effects of compliance and a lack of integrity between layers, in particular, delamination. Previous research has described the homogenization process, but this study focuses on the impact of delamination on bending stiffness without affecting tensile stiffness.

We employed numerical homogenization techniques, incorporating interplay delamination or partial delamination to model these effects. The Finite Element Method (FEM) was utilized to simulate the behavior of delaminated plates, ensuring accurate boundary conditions through using periodic boundary conditions to capture the correct stiffness reductions. The analysis revealed that delamination leads to significant reductions in bending stiffness, while tensile stiffness remains largely unaffected. The correct implementation of periodic boundary conditions was crucial in accurately estimating stiffness reductions in delaminated plates.

This research highlights the importance of accurate boundary condition assumptions in numerical models for predicting the structural performance of partially delaminated multilayered and sandwich plates. The findings provide a basis for more reliable design and analysis of such structures, promoting better understanding and mitigation of the effects of delamination. This study underscores the potential of advanced numerical methods to enhance the analysis and design of complex laminated and sandwich structures, contributing to more resilient and efficient engineering solutions.

The stability of palletized corrugated board packaging is crucial for safe transportation and storage. Offset stacking, where packages are slightly shifted relative to those in lower rows, is a common technique to enhance pallet stability. However, this method can compromise the load-bearing capacity of the packaging. This study investigates the impact of offset stacking on the load-bearing capacity of cardboard packaging during palletization. While offsetting packages on a pallet can enhance stability, it adversely affects the load-bearing capacity of the packages. This is particularly critical as the load from upper packages is primarily transferred through the walls, and their misalignment can significantly reduce their structural integrity. Our research indicates that such reductions in load-bearing capacity can reach up to several percent.

Advanced numerical modeling using the Finite Element Method (FEM) was employed to estimate the decrease in load-bearing capacity due to offset stacking. This method allows for a detailed analysis of how misaligned walls affect structural performance under a load. The FEM analysis revealed that offset stacking leads to a notable reduction in the load-bearing capacity of the packaging. The structural integrity of the corrugated board is compromised, with load-bearing capacity reductions reaching up to 25% in some configurations.

This study highlights the trade-off between stability and load-bearing capacity in offset stacked cardboard packaging. The findings underscore the need for careful consideration in packaging design and palletization strategies to balance these competing factors. Future work will focus on optimizing stacking patterns and developing guidelines to mitigate the adverse effects on load-bearing capacity. This research provides valuable insights for the packaging industry, promoting safer and more efficient palletization practices while maintaining structural integrity.

Bubble Deck slabs are an innovative construction technology designed to optimize material usage and reduce slab weight through strategically placed elliptical voids. Traditional analysis methods struggle to accurately model these complex geometries and their nonlinear behavior under load. This study explores the numerical homogenization of bubble deck slabs, which incorporate elliptical voids to reduce weight and material usage while maintaining structural integrity. These slabs, characterized by lower and upper mesh reinforcement, present a complex cross-sectional geometry that benefits from advanced numerical methods for accurate modeling.

This study employs numerical homogenization techniques based on the finite element method to transform the complex geometry of bubble deck slabs into an equivalent homogeneous layer. To account for the nonlinear (plastic) behavior of the material, the General Nonlinear Constitutive Law (GNCL) is integrated into the homogenization process. The combination of these methods enables a detailed representation of the slabs' structural response. The homogenization process successfully reduced the complex bubble deck geometry to a simplified model that retains the critical nonlinear characteristics. The results indicate that this approach can accurately predict the structural behavior under various loading conditions, including those leading to nonlinear deformation (due to cracking, etc.).

This research demonstrates that combining numerical homogenization with the GNCL provides a robust framework for analyzing bubble deck slabs. The methodology allows for accurate and efficient structural analysis, promoting material efficiency and structural performance. Future research will focus on extending this approach to other complex slab geometries and incorporating additional loading scenarios. This study underscores the potential for advanced numerical methods to enhance the design and analysis of innovative structural elements, contributing to more sustainable and economical construction practices.

This study focuses on optimizing the cross-sections of free-standing concrete rectangular water tanks. The primary goal is to minimize material usage while maintaining structural integrity. Traditional design methods often lead to conservative estimates of material requirements. By employing evolutionary and global gradient-free algorithms, this research aims to find more efficient design parameters. Water tanks are essential structures in civil engineering, and their design requires careful consideration to ensure safety and cost-effectiveness. The design challenge increases with the aspect ratio of the tank, as walls behave more like cantilevers with higher width-to-height ratios.

We employed evolutionary algorithms, specifically genetic algorithms, to optimize the thickness of the tank walls and the placement of vertical ribs. These algorithms are well suited for this application due to their ability to handle complex non-linear optimization problems without the need for gradient information. The optimization variables included wall thickness, which varies with height, and rib placement, considering different tank dimensions. For the modeling of wall behavior, the finite difference method was utilized, incorporating an orthotropic description of the material to accurately represent the directional properties of reinforcing ribs. The optimization process demonstrated that evolutionary algorithms could effectively identify optimal cross-sectional parameters.

The results indicated a potential material saving of 10-15% compared to traditional design methods. The optimized designs maintained structural integrity while using less concrete, making them more economical and sustainable. This research validates the effectiveness of evolutionary algorithms in optimizing the design of reinforced concrete water tanks. The findings suggest significant material savings, contributing to more cost-effective and environmentally friendly construction practices. Future work will extend these methods to other structural elements and consider additional constraints such as seismic loads. This study provides a robust framework for engineers to adopt advanced optimization techniques, enhancing the efficiency and sustainability of civil engineering projects.

The optimal management of manufacturing processes can be achieved through a set of optimal decisions, which must be made to choose the best methodto follow every time the process planner is in a point at which several potential manufacturing paths branch off. A dedicated method, namely the Holistic Optimization Method (HOM), has already been developed for this purpose and was validated in several studies based on artificial and real instances databases. The HOM consists of two algorithms: i) the causal identification of a manufacturing process and ii) the comparative assessment with already performed, similar manufacturing cases, recorded in an instances database. The two algorithms can be used to estimate the values of the different performance indicators of the manufacturing processes. Their application for processing cost estimation in the case of manufacturing processes of bearing components has already shown good results. In this paper, it is presented as a solution to predict the timespan needed for grinding roller bearings rings, applying the specific algorithms of the HOM, grounded on the use of a database with data collected from the industrial environment. The cause variables selected to describe the grinding process of roller bearing rings are the inner and outer diameter of the ring, its width and weight, the machined surface roughness, the grinding stone rotation speed, the feedrate and the cutting depth, while the effect variable to be used by the process planner as decision criterion is the timespan.

A canned motor pump is a type of turbopump that features a non-leakage structure that integrates the pump and the motor. It differs from a typical turbopump in that the pumping liquid also serves as the cooling liquid for the motor and the lubricating liquid for the sliding surfaces. Grooved plain bearings are generally used in canned motor pumps to supply sufficient cooling liquid to the motor. However, there is no external lubricant supply system for canned motor pumps, which means that the design guidelines for standard grooved plain bearings cannot be applied without modification. The purpose of this study is to obtain knowledge to develop design guidelines for helical grooved plain bearings for canned motor pumps. Therefore, the film pressure, which is one of the important indices in bearing design, was analyzed by Computational Fluid Dynamics (CFD). CFD simulation was performed using the steady-state single-phase flow solver implemented in OpenFOAM for analyzing fundamental trends. First, a comparison with the theoretical solution was performed for a plain bearing without grooves to investigate the film pressure. Furthermore, analysis was conducted on a helical grooved plain bearing. This analysis clarified the trend of film pressure generated in the helical grooved plain bearing. The conclusion is that the peak values of positive and negative film pressure tend to be higher in the helical grooved plain bearing than in the plain bearing without grooves, so the effects of material strength and cavitation should be handled appropriately when the bearing is used in industry.

The field of additive manufacturing continues to revolutionize production methods, and 3Dprinting technologies have been at the forefront of this evolution. Among their myriad of applications, conductive 3D-printing filaments hold immense promise in the development of electronics, sensors, and flexible wearable devices. However, the precise characterization of the electrical resistance within structures fabricated using these filaments can be complex, especially when measuring subtle resistance variations. This study embarks on a comparative analysis of the two-probe and four-probe methodologies used for electrical resistance measurement while further investigating the impact of different electrical contact types on experimental specimens. Specimens will be fabricated utilizing a conductive PLA filament and 3D printing technology. The effectiveness of each measurement approach, along with the influence of electrode choice, will be evaluated. Moreover, the flexibility inherent in the four-probe method will be explored further. This research has the potential to significantly refine the measurement of electrical resistance in conductive 3D-printed constructs. In doing so, it could drive further innovation in fields where intricate circuitry, advanced sensors, and seamlessly integrated wearable technology are paramount. Furthermore, by optimizing these measurement techniques, we can gain a deeper understanding of the conductivity behavior of these novel materials, leading to an expansion of their potential applications.