Search Results (6,833)

Purpose: Despite significant attention being paid to compression garments (CG) in the sports field, there remains ongoing debate regarding their actual effectiveness in enhancing athletic performance and expediting post-exercise recovery. This article examines their various aspects, with a focus on CG design and the materials they are made of, aiming to analyze the importance of personalized compression strategies based on individual anthropometric measurements and non-linear compression designs. Methods: Using anthropometric analysis of 40 healthy participants, this study examines the morphological characteristics of the lower limb and their implications for CG design. Results: Measurements of limb length and circumferences revealed complex interactions among anatomical variables, emphasizing the need for customized and adaptable device design. Finite element simulations clarified the challenges in achieving uniform pressure gradients along the lower limb, highlighting the limitations of one-piece devices and suggesting tailored segmented designs for individual limb segments. Conclusion: The results demonstrate that one-piece devices often fail to provide optimal compression due to non-linear variations in limb dimensions. Conversely, segmented devices, particularly those with bilinear progression, exhibited superior performance in applying targeted compression across different limb segments. This more detailed approach to customization could significantly contribute to optimizing outcomes and user comfort. Full article

This paper considers a heterogeneous queuing system with an unlimited number of servers, where the parameters are determined by a random environment. A distinctive feature is that the parameters of the exponential distribution of the request processing time do not change their values until the end of service. Thus, the devices in the system under consideration are heterogeneous. For the study, a method of asymptotic analysis is proposed under the condition of extremely rare changes in the states of the random environment. We consider the following problem. Cloud node accepts requests of one type that have a similar intensity of arrival and duration of processing. Sometimes an input scheduler switches to accept requests of another type with other intensity and duration of processing. We model the system as an infinite-server queue in a random environment, which influences the arrival intensity and service time of new requests. The random environment is modeled by a Markov chain with a finite number of states. Arrivals are modeled as a Poisson process with intensity dependent on the state of the random environment. Service times are exponentially distributed with rates also dependent on the state of the random environment at the time moment when the request arrived. When the environment changes its state, requests that are already in the system do not change their service times. So, we have requests of different types (serviced with different rates) present in the system at the same time. For the study, we consider a situation where changes of the random environment are made rarely. The method of asymptotic analysis is used for the study. The asymptotic condition of a rarely changing random environment (entries of the generator of the corresponding Markov chain tend to zero) is used. A multi-dimensional joint steady-state probability distribution of the number of requests of different types present in the system is obtained. Several numerical examples illustrate the comparisons of asymptotic results to simulations. Full article

Partial Discharge (PD) measurement is one of the effective methods for assessing the internal insulation condition of power transformers in factories and substations. The pulse current signals generated by PD within transformer windings are significantly influenced by the winding structure during their propagation from the discharge source to the external measurement system. This influence may lead to misinterpretation of the insulation status, particularly in the analysis of PD measurement results. Such effects are closely related to the signal transmission path and distance and exhibit a strong correlation with the winding transfer function, manifesting as attenuation, distortion, or delay of the measured signals compared to the original PD waveforms. Therefore, it is essential to investigate the impact of the discharge path on the propagation characteristics of transformer windings and its effect on PD waveforms. This paper establishes a simplified distributed parameter model of a 180-turn single-winding multi-conductor transmission line using the finite element method and mathematical modeling, deriving the transfer functions between the winding head or winding end and various internal discharge positions. By injecting different types of PD waveforms collected in the laboratory at various discharge locations within the winding, the alterations of PD signals propagated to the winding head and winding end are simulated, and clustering analysis is performed on the propagated PD signals of different types. Full article

This article aims to perform system identification of a nearly 30-year-old cable-stayed steel footbridge over the Wisłok River in Rzeszów (Poland). The design documentation of the bridge has been lost, and since its construction, the footbridge has been subject to renovations. The structure is highly susceptible to pedestrian traffic, and before any actions are taken to improve the comfort of use, it is necessary to create and validate a numerical model and assess the force distribution in the structure. Models are often built as mappings of an ideal structure. However, real structures are not ideal. The comparison of numerical and measured data can allow for an indication of potential damage areas. Two main purposes of the article have been formulated: (1)Development of a numerical model of an old footbridge, whose components have been degraded due to long-term use. Changes, compared to the ‘original’, focused on elongation of the cables due to rheology and a decrease in their tension. (2) Demonstrate the challenges in modeling and validating this type of bridge. In the article, the result of the numerical simulation (Finite Element Method and Ansys2024 R2 was applied, the verification was made in RFEM6) for models with different boundary conditions and varied pre-tension in cables was compared with the results of static and dynamic examination of a real object. The dynamic tests showed an uneven distribution of pre-tension in cables. The ratio of the first natural frequencies of inner cables on the north side is as high as 16%. The novelty demonstrated in the article is that static tests are insufficient for proper system identification; the same value of vertical displacement can be obtained for a selected static load, with varied tension in cables. Therefore, dynamic testing is essential. Full model updating requires a multicriteria approach, which will be made in the future. Full article

Purpose: This study aimed to evaluate the effect of different coronal restoration methods on stresses in immature central incisors with regenerative endodontic treatment and excessive loss of coronal structure. Methods: A three-dimensional (3D) Finite Element Analysis (FEA) model of a maxillary central incisor treated with a 3 mm MTA coronal plug after regenerative endodontic treatment was created. Six different models were simulated: (1) intact immature tooth (control), (2) direct composite resin build-up, (3) fibre-reinforced composite build-up, (4) hybrid ceramic endocrown, (5) LiSi ceramic endocrown, and (6) endocore and ceramic crown restoration. Analyses were performed with SolidWorks/CosmosWorks, and a 150 N load was applied at a 135° angle. Results: Maximum tensile stresses were concentrated in the cervical region (4.577 MPa). Direct composite and fibre-reinforced restorations showed high stress in root dentin (3.891 and 3.841 MPa, respectively). The endocore/ceramic crown restoration (1.578 MPa) provided the closest stress distribution to the natural tooth (1.322 MPa). Conclusions: The biomechanical performance of the restoration–tooth complex depends on both the restorative material and the restoration design. In immature teeth undergoing regenerative endodontic treatment, the most biomechanically favourable restoration option was an endocore/ceramic crown. Full article

As a pivotal component of the single-gear reducer, the casing of the miniature car reducer not only safeguards the internal transmission system but also interfaces seamlessly with the external structure. Currently, the structural design of domestic single-stage reducers primarily leans on experience and standardized specifications. To guarantee the reliable and stable operation of the casing, a high safety factor is often incorporated, which inevitably results in increased weight and necessitates secure bolting connections. This study presents an innovative scheme to design the flange with the box and realize the lightweight nature of the box by finite element analysis to reduce the manufacturing cost. Based on the working state of maximum torque and maximum speed, this study obtains the stress distribution of each bearing seat under different working conditions and carries out static and dynamic analysis combined with other coupling constraints. The analysis results show that the structure has high stiffness and strength, which is suitable for lightweight design, and that the first ten spontaneous vibration frequencies are far away from the excitation frequency of the inner and outer boundary, avoiding the resonance phenomenon. Moreover, this study proposes a new structure design method, which effectively improves the stiffness of the structure. Through the calculation of volume ratio before and after three optimizations, the optimal volume ratio of 30% is selected, unnecessary materials around the bearing seat are removed, and the layout of ribs is determined. After structural optimization, the weight of the shell is reduced by 10.2%, and both the static and dynamic characteristics meet the design requirements. Full article

This paper presents the application of conic programming methods to the limit analysis of plane rigid-plastic problems in structural and geotechnical engineering. The approach is based on the formulation of yield criteria as second-order cone constraints and on the dual optimization problem, which directly provides collapse mechanisms and limit loads. Two benchmark examples are investigated. The first concerns a deep beam under uniform top pressure, analyzed with linear and quadratic finite elements. The results confirm the ability of the method to reproduce realistic collapse mechanisms and demonstrate the effect of mesh refinement and element type on convergence. The second example addresses the ultimate bearing capacity of a strip footing on cohesive-frictional soil. The numerical implementation was carried out in MATLAB using CVX with MOSEK as the solver, which ensures practical applicability and efficient computations. Different soil models are considered, including Mohr–Coulomb and two Drucker–Prager variants, and the results are compared with the classical Terzaghi solution. Additional elastoplastic FEM simulations carried out in a commercial program are also presented. The comparison highlights the differences between rigid-plastic optimization and incremental elastoplastic analyses, showing that both conservative and liberal estimates of bearing capacity can be obtained. The study shows that conic programming is an efficient and flexible framework for limit analysis of plane rigid-plastic problems, providing engineers with complementary tools for assessing ultimate loads, while also ensuring good computational efficiency. Full article

In offshore drilling and geological exploration, the stability of jack-up rigs is predominantly determined by the bearing capacities of spudcan foundations during seabed penetration. The penetration depth of spudcans is relatively shallow in hard clay. The formation of a cavity on the top surface of a spudcan often complicates accurate estimation of its capacity. This study employs the finite element method, in conjunction with the Swipe and Probe loading techniques, to examine the failure surfaces of soils of varying strengths. Numerical simulations that consider different gradients of undrained shear strength and cavity depths demonstrate that cavity depth significantly influences the failure envelope. The findings indicate that higher soil strength increases the bearing capacity and reduces the area of soil displacement at failure. Moreover, an enhanced theoretical equation for predicting the vertical-horizontal-moment (V-H-M) failure envelope in hard clay strata is proposed. The equation’s accuracy has been verified against numerical simulation results, revealing an error margin of 3–10% under high vertical loads. This model serves as a practical and valuable tool for assessing the stability of jack-up rigs in hard clay, providing critical insights for engineering design safety and risk assessment. Full article

Aluminum alloys under long-term service or repetitive stress are prone to small fatigue cracks (FCs) with arbitrary orientations, necessitating eddy current probes with focused magnetic fields and directional selectivity for reliable detection. This study presents a flexible printed circuit board (FPCB) probe with a double-layer planar excitation coil and a double-layer differential receiving coil. The excitation coil employs a reverse-wound design to enhance magnetic field directionality and focusing, while the differential receiving coil improves sensitivity and suppresses common-mode noise. The probe is optimized by adjusting the excitation coil overlap and the excitation–receiving coil angles to maximize eddy current concentration and detection signals. Finite element simulations and experiments confirm the system’s effectiveness in detecting surface cracks of varying sizes and orientations. To further characterize these defects, two time-domain features are extracted: the peak-to-peak value ($\Delta$P), reflecting amplitude variations associated with defect size and orientation, and the signal width ($\Delta$W), primarily correlated with defect angle. However, substantial overlap in their value ranges for defects with different parameters means that these features alone cannot identify which specific parameter has changed, making prior defect classification using a Transformer-based approach necessary for accurate quantitative analysis. The proposed method demonstrates reliable performance and clear interpretability for defect evaluation in aluminum components. Full article

Background: The implant–abutment interface has been thoroughly examined due to its impact on the success of implant healing and longevity. Removing the abutment is advantageous, but it changes the biomechanics of the implant fixture and restoration. This in vitro three-dimensional finite element analytical (FEA) study aims to evaluate the distribution of von Mises stress (VMS) in abutment-free and three additional implant abutment connections composed of various titanium alloys. Materials and methods: A three-dimensional implant-supported single-crown prosthesis model was digitally generated on the mandibular section using a combination of microcomputed tomography imaging (microCT), a computer-assisted designing (CAD) program (SolidWorks), Analysis of Systems (ANSYS), and a 3D digital scan (Visual Computing Lab). Four digital models [A (BioHorizons), B (Straumann AG), C abutment-free (Matrix), and D (TRI)] representing three different functional biomaterials [wrought Ti-6Al-4Va ELI, Roxolid (85% Ti, 15% Zr), and Ti-6Al-4V ELI] were subjected to simulated static/cyclic static loading in axial/oblique directions after being restored with highly translucent monolithic zirconia restoration. The stresses generated on the implant fixture, abutment, crown, screw, cortical, and cancellous bones were measured. Results: The highest VMSs were generated by the abutment-free (Model C, Matrix) implant system on the implant fixture [static (32.36 Mpa), cyclic static (83.34 Mpa)], screw [static (16.85 Mpa), cyclic static (30.33 Mpa), oblique (57.46 Mpa)], and cortical bone [static (26.55), cyclic static (108.99 Mpa), oblique (47.8 Mpa)]. The lowest VMSs in the implant fixture, abutment, screw, and crown were associated with the binary alloy Roxolid [83–87% Ti and 13–17% Zr]. Conclusions: Abutment-free implant systems generate twice the stress on cortical bone than other abutment implant systems while producing the highest stresses on the fixture and screw, therefore demanding further clinical investigations. Roxolid, a binary alloy of titanium and zirconia, showed the least overall stresses in different loadings and directions. Full article

Background/Objectives: The process of designing and fabricating bone tissue engineering scaffolds is a multi-faceted and intricate process. The scaffold is designed to attach cells to the required volume of regeneration to subsequently migrate, grow, differentiate, proliferate, and consequently develop tissue within the scaffold which, in time, will degrade, leaving just the regenerated tissue. The fabrication of tissue scaffolds requires adapting the properties of the scaffolds to mimic, to a large extent, the specific characteristics of each type of bone tissue. However, there are some significant limitations due to the constrained scaffolds’ architecture and structural features that inhibit the optimization of bone scaffolds. Methods: To overcome these shortcomings, new computational approaches for scaffold design have been adopted through currently adopted computational methods such as finite element analysis (FEA), computational fluid dynamics (CFD), and fluid–structure interaction (FSI). Results: This paper presents a narrative review of the state of the art in the field of parametric numerical modeling and computational fluid dynamics geometry-based models used in bone tissue engineering. Computational methods for scaffold design improve the process of constructing scaffolds and contribute to tissue engineering. Conclusions: This paper highlights the benefits of computational methods on employing scaffolds with different architectures and inherent characteristics that can potentially contribute to a favorable environment for hosting cells and predict their behavior and response. By recognizing these benefits, researchers can enhance and optimize scaffold properties for future advancements in tissue engineering research that will lead to more accurate and robust outcomes. Full article

Reverse arch beam string-inclined column structures have been applied in large-scale event venues due to their unique load-bearing characteristics. However, ensuring their resistance to progressive collapse remains a critical challenge. To investigate the structural robustness of reverse arch beam string-inclined column structure in practical engineering applications, a simplified finite element model is developed herein using ANSYS APDL. The natural frequencies of the actual engineering structure are measured through the hammering method to validate the accuracy of the simulation model. Based on the component removal method, different structural components are removed and finite element analysis is carried out. The dynamic response of the overall structure and the importance coefficients of individual components after removal are examined. The results demonstrate good agreement between the natural frequencies measured by the impact hammer test and those predicted by the finite element simulations, with the difference being only 1.67%. It is found that upper beam failure is fatal to this structure; the outer inclined columns significantly affect the robustness of the structure, while the failure of a single strut has a negligible impact. According to the component division, the importance of the overall robustness of the structure is in the following order: upper beam > column end > column base > strut. The maximum stress is mostly located in beam 7, beam 8, beam 28, and beam 107, which needs to be focused on. Full article

In recent years, inverse reinforcement learning algorithms have garnered substantial attention and demonstrated remarkable success across various control domains, including autonomous driving, intelligent gaming, robotic manipulation, and automated industrial systems. Nevertheless, existing methodologies face two persistent challenges: (1) finite or non-optimal expert demonstration and (2) ambiguity in which different reward functions lead to same expert strategies. To improve and enhance the expert demonstration data and to eliminate the ambiguity caused by the symmetry of rewards, there has been a growing interest in research on developing inverse reinforcement learning based on the maximum entropy method. The unique advantage of these algorithms lies in learning rewards from expert presentations by maximizing policy entropy, matching expert expectations, and then optimizing the policy. This paper first provides a comprehensive review of the historical development of maximum entropy-based inverse reinforcement learning (ME-IRL) methodologies. Subsequently, it systematically presents the benchmark experiments and recent application breakthroughs achieved through ME-IRL. The concluding section analyzes the persistent technical challenges, proposes promising solutions, and outlines the emerging research frontiers in this rapidly evolving field. Full article

We consider optimization for different production requirements from the viewpoint of a bio-inspired framework for system flexibility that allows us to study the ability of an algorithm to transfer solutions from previous optimization tasks, which also relates to dynamic evolutionary optimization. Optimizing manufacturing process parameters is typically a multi-objective problem with often contradictory objectives, such as production quality and production time. If production requirements change, process parameters have to be optimized again. Since optimization usually requires costly simulations based on, for example, the Finite Element method, it is of great interest to have a means to reduce the number of evaluations needed for optimization. Based on the extended Oxley model for orthogonal metal cutting, we introduce a multi-objective optimization benchmark where different materials define related optimization tasks. We use the benchmark to study the flexibility of NSGA-II, which we extend by developing two variants: (1) varying goals, which optimizes solutions for two tasks simultaneously to obtain in-between source solutions expected to be more adaptable, and (2) active–inactive genotype, which accommodates different possibilities that can be activated or deactivated. Results show that adaption with standard NSGA-II greatly reduces the number of evaluations required for optimization for a target goal. The proposed variants further improve the adaption costs, where on average, the computational effort is more than halved in comparison to the non-adapted baseline. We note that further work is needed for making the methods advantageous for real applications. Full article

The present work numerically investigates the mechanical behavior of six 6061-T6 aluminum profiles during roll bending, considering, in two specific cases, the application of the process in different bending directions (vertical and horizontal), totaling eight cases analyzed, with emphasis on the influence of multiple bending radii. Notably, two of the profiles are characterized by high geometric complexity, making their analysis particularly relevant within the scope of this study. Using the finite element method in ANSYS^® (version 2022 R2) (SOLID187 element), the study expands the previously validated model to a broader range of geometries and includes an additional validation and verification stage. The results reveal: (i) an inverse relationship between bending radius and von Mises stress, with critical values close to the material’s strength limit at smaller radii; (ii) characteristic displacement patterns for each profile, quantified through specific curve fittings; and (iii) a systematic comparison among the six profiles, highlighting stress concentrations and deformations differentiated by geometry. The simulations provide criteria for predicting forming defects and optimizing process parameters, expanding the database for industrial designs with multiple extruded profiles. Full article