Explore the vast range of titles available.

This paper introduces new mixed formulations and discretizations for mth-Laplace equations of the form (-1)m ∆mu = f for arbitrary m = 1,2,3,... based on novel Helmholtztype decompositions for tensor-valued functions. The new discretizations allow for ansatz spaces of arbitrary polynomial degree and the lowest-order choice coincides with the nonconforming FEMs of Crouzeix and Raviart for m = 1 and of Morley for m = 2. Since the derivatives are directly approximated, the lowest-order discretizations consist of piecewise affine and piecewise constant functions for any m = 1,2,... Moreover, a uniform implementation for arbitrary m is possible. Besides the a priori and a posteriori analysis, this paper proves optimal convergence rates for adaptive algorithms for the new discretizations.

This contribution studies failure by elastic buckling and plastic collapse of wall structures during extrusion-based 3D printing processes. Results obtained from the parametric 3D printing model recently developed by Suiker (Int J Mech Sci, 137: 145–170, 2018), among which closed-form expressions useful for engineering practice, are validated against results of dedicated FEM simulations and 3D concrete printing experiments. In the comparison with the FEM simulations, various types of wall structures are considered, which are subjected to linear and exponentially decaying curing processes at different curing rates. For almost all cases considered, the critical wall buckling length computed by the parametric model turns out to be in excellent agreement with the result from the FEM simulations. Some differences may occur for the particular case of a straight wall clamped along its vertical edges and subjected to a relatively high curing rate, which can be ascribed to the approximate form of the horizontal buckling shape used in the parametric model. The buckling responses computed by the two models for a wall structure with imperfections of different wavelengths under increasing deflection correctly approaches the corresponding bifurcation buckling length. Further, under a specific change of the material properties, the parametric model and the FEM model predict a similar transition in failure mechanism, from elastic buckling to plastic collapse. The experimental validation of the parametric model is directed towards walls manufactured by 3D concrete printing, whereby the effect of the material curing rate on the failure behaviour of the wall is explored by studying walls of various widths. At a relatively low curing rate, the experimental buckling load is well described when the parametric model uses a linear curing function. However, the experimental results suggest the extension of the linear curing function with a quadratic term if the curing process under a relatively long printing time is accelerated by thermal heating of the 3D printing facility. In conclusion, the present validation study confirms that the parametric model provides a useful research and design tool for the prediction of structural failure during extrusion-based 3D printing. The model can be applied to quickly and systematically explore the influence of the individual printing process parameters on the failure response of 3D-printed walls, which can be translated to directives regarding the optimisation of material usage and printing time.

In the use of implants, a particularly important role is played by the instrumentation. It is primarily designed to fulfill its functional role. During its design phase, an important step is the strength verification calculation. For this, frequently a finite element method analysis realized with one of the established software is used. In the present work, a verification of the component identified as the most stressed is performed for the critical areas in terms of stresses.

Historic masonry buildings are characterised by uniqueness, which is intrinsically present in their building techniques, morphological features, architectural decorations, artworks, etc. From the modelling point of view, the degree of detail reached on transforming discrete digital representations of historic buildings, e.g., point clouds, into 3D objects and elements strongly depends on the final purpose of the project. For instance, structural engineers involved in the conservation process of built heritage aim to represent the structural system rigorously, neglecting architectural decorations and other details. Following this principle, the software industry is focusing on the definition of a parametric modelling approach, which allows performing the transition from half-raw survey data (point clouds) to geometrical entities in nearly no time. In this paper, a novel parametric Scan-to-FEM approach suitable for architectural heritage is presented. The proposed strategy uses the Generative Programming paradigm implementing a modelling framework into a visual programming environment. Such an approach starts from the 3D survey of the case-study structure and culminates with the definition of a detailed finite element model that can be exploited to predict future scenarios. This approach is appropriate for architectural heritage characterised by symmetries, repetition of modules and architectural orders, making the Scan-to-FEM transition fast and efficient. A Portuguese monument is adopted as a pilot case to validate the proposed procedure. In order to obtain a proper digital twin of this structure, the generated parametric model is imported into an FE environment and then calibrated via an inverse dynamic problem, using as reference metrics the modal properties identified from field acceleration data recorded before and after a retrofitting intervention. After assessing the effectiveness of the strengthening measures, the digital twin ability of reproducing past and future damage scenarios of the church is validated through nonlinear static analyses.

This work is a continuation of the author’s previous research on modeling a piezoelectric sensor–actuator hybrid. It presents the results of vibration and structural sound reduction for a plate with attached piezoelectric elements. The models consist of a steel plate with two piezoelectric actuators attached on one side and a hemispherical air volume on the other side. One of the actuators is used to excite the plate’s vibration and has the same shape and size in all models. The second actuator is used for vibration and structural sound reduction and varies between a standard square-based full actuator and a sensor–actuator hybrid with different sizes and shapes of the sensor component (either square- or disc-based). Harmonic analyses were performed for the first four mode shapes (skipping the third mode since it is a square plate). Optimization was performed using internal ANSYS functions, with the objective of minimizing the sum of displacement vectors at a number of nodes corresponding to either the full plate or the sensor placed on the said plate.

The paper presents results of numerical analysis of the gabion retaining wall stability. A real, complicated object is analysed. Gabions are modelled using a homogenized Mohr-Coulomb model for mesh and filling. Interface elements are used to allow discontinuous deformation field between adjacent gabions and between gabions and subsoil. A parametric study of the influence of the mesh and joints between gabions strength on the stability of the structure is performed. Different modelling approaches are compared. Numerical simulations were performed using ZSoil v25 Finite Element Method (FEM) system. Efficiency of the proposed approach is shown.

This paper generalizes the non-conforming FEM of Crouzeix and Raviart and its fundamental projection property by a novel mixed formulation for the Poisson problem based on the Helmholtz decomposition. The new formulation allows for ansatz spaces of arbitrary polynomial degree and its discretization coincides with the mentioned non-conforming FEM for the lowest polynomial degree. The discretization directly approximates the gradient of the solution instead of the solution itself. Besides the a priori and medius analysis, this paper proves optimal convergence rates for an adaptive algorithm for the new discretization. These are also demonstrated in numerical experiments. Furthermore, this paper focuses on extensions of this new scheme to quadrilateral meshes, mixed FEMs, and three space dimensions.

In this paper, an approach for a two-and-half-dimensional (2.5D) finite element method (FEM)-based analysis, or quasi-three-dimensional (3D) FEM analysis, of an axial flux machine is discussed. By cutting the 3D model laterally and thereby creating cylindrical surface cuts, the 3D model can be split into several cylindrical surfaces. Transforming those cylindrical cuts into planes leads to a layer-based two-dimensional (2D) model with different radii for each layer. By integrating over all lateral surface cuts, the results for the entire axial flux machine can be determined. In comparison to the simulation of a full 3D FEM model, the simulation of the proposed 2.5D model is much faster. To validate the approach, the two main types of axial flux machines are simulated with both 3D-FEM-based model and 2.5D-FEM-based approach, and the results are presented in this paper.

With the increasing complexity of industrial products, the requirements for environmental protection, and resource conservation, new manufacturing technologies have become necessary. 3D printing or additive manufacturing (AM) can be used to create parts by adding material layer by layer. The analysis of the data obtained by applying finite element method (FEM) on gears produced from polylactic acid (PLA), thermic treated PLA and Acrylonitrile Butadiene Styrene (ABS) shows the equivalent stress values obtained numerically in comparison with those obtained experimentally through tensile testing. Thus, there is a positive percentage difference between tensile strength σeq,max for PLA material of 18.32%, for ABS material of 15.98%, and for treated PLA material of 18.39%. Thus, the contact stresses identified by the numerical method in the contact area of the gear teeth flanks were compared with the average compressive stresses obtained experimentally for specimens made from PLA, ABS, and treated PLA materials, printed with a 100% infill percentage. There is a percentage difference between these values of 64.4% for PLA material, 63.18% for ABS material, and 48.21% for treated PLA material. This indicates that the gears made from the considered materials can operate without issues if no other loads are applied. The integration of numerical simulation results with experimental data validates the accuracy of the analysis methods, providing a solid basis for decision-making in the design and improvement of gear wheels.

A tomato automatic detection method based on an improved YOLOv8s model is proposed to address the low automation level in tomato harvesting in agriculture. The proposed method provides technical support for the automatic harvesting and classification of tomatoes in agricultural production activities. The proposed method has three key components. Firstly, the depthwise separable convolution (DSConv) technique replaces the ordinary convolution, which reduces the computational complexity by generating a large number of feature maps with a small amount of calculation. Secondly, the dual-path attention gate module (DPAG) is designed to improve the model’s detection precision in complex environments by enhancing the network’s ability to distinguish between tomatoes and the background. Thirdly, the feature enhancement module (FEM) is added to highlight the target details, prevent the loss of effective features, and improve detection precision. We built, trained, and tested the tomato dataset, which included 3098 images and 3 classes. The proposed algorithm’s performance was evaluated by comparison with the SSD, faster R-CNN, YOLOv4, YOLOv5, and YOLOv7 algorithms. Precision, recall rate, and mAP (mean average precision) were used for evaluation. The test results show that the improved YOLOv8s network has a lower loss and 93.4% mAP on this dataset. This improvement is a 1.5% increase compared to before the improvement. The precision increased by 2%, and the recall rate increased by 0.8%. Moreover, the proposed algorithm significantly reduced the model size from 22 M to 16 M, while achieving a detection speed of 138.8 FPS, which satisfies the real-time detection requirement. The proposed method strikes a balance between model size and detection precision, enabling it to meet agriculture’s tomato detection requirements. The research model in this paper will provide technical support for a tomato picking robot to ensure the fast and accurate operation of the picking robot.