Three-dimensional Computer-aided Design Model Research Articles

Evaluation and Improvement of a Prosthetic Hand Product Using Biomechanics and Empathy Map Approach

The Panangan Prosthetic Hand is a transradial prosthesis that can be operated with both amputated and non-amputated arms. Several users have reported some degree of exhaustion and discomfort when using this prosthesis. Users may also be dissatisfied because this product has not met some of their specific needs and desires. To evaluate the product, tests were conducted by measuring muscle activity using an electromyography (EMG) sensor and assessing discomfort levels using the Borg CR10 scale during specific activities performed with the prosthesis. Additionally, interviews were conducted using an empathy map to profile the participants. The test results showed high muscle activities and discomfort levels in certain tasks, such as pouring water from a drink box. Based on these findings and the participants' profiles, their needs were identified, and solutions for improving the product were designed. Subsequently, these solutions were developed into a three-dimensional computer-aided design (3D CAD) model prototype.

Design and analysis of serviceable cantilever fit snap in automotive plastic parts

Purpose Snap fits are crucial in automotive applications for rapid assembly and disassembly of mating components, eliminating the need for fasteners. This study aims to focus on designing and analyzing serviceable cantilever fit snap connections used in automobile plastic components. Snap fits are classified into permanent and semi-permanent fittings, with permanent fittings having a snap clipping angle between 0° and 5° and semi-permanent fittings having a clipping angle between 15° and 45°. Polypropylene random copolymer is chosen for its exceptional fatigue resistance and elasticity. Design/methodology/approach The design process includes determining dimensions, computing assembly, disassembly pressures and creating three-dimensional computer-aided design models. Finite element analysis (FEA) is used to evaluate the snap-fit mechanism’s stress, deformation and general functionality in operational scenarios. Findings The study develops a modified snap-fit mechanism with decreased bending stress and enhanced mating force optimization. The maximum bending stress during assembly is 16.80 MPa, requiring a mating force of 7.58 N, while during disassembly, it is 37.3 MPa, requiring a mating force of 16.85 N. The optimized parameters significantly improve the performance and dependability of the snap-fit mechanism. The results emphasize the need of taking into account both the assembly and disassembly processes in snap-fit design, because the research demonstrates greater forces during disassembly. The approach developed integrates FEA and design for assembly (DFA) concepts to provide a solution for improving the efficiency and reliability of snap-fit connectors in automotive applications. Originality/value The research paper’s distinctiveness comes from the fact that it presents a thorough and realistic viewpoint on snap-fit design, emphasizes material selection, incorporates DFA principles and emphasizes the specific requirements of both assembly and disassembly operations. These discoveries may enhance the efficiency, reliability and sustainability of snap-fit connections in plastic automobile parts and beyond. In conclusion, the idea that disassembly needs to be done with a lot more force than installation in a snap-fit design can have a good effect on buzz, squeak and rattle and noise, vibration and harshness characteristics in automobiles.

Application of Pathfinding Algorithms in Partial Discharge Localization in Power Transformers.

The introduction of artificial intelligence (AI) to ultra-high-frequency (UHF) partial discharge (PD) monitoring systems in power transformers for the localization of PD sources can help create a robust and reliable system with high usability and precision. However, training the AI with experimental data or data from electromagnetic simulation is costly and time-consuming. Furthermore, electromagnetic simulations often calculate more data than needed, whereas, for localization, the signal time-of-flight information is the most important. A tailored pathfinding algorithm can bypass the time-consuming and computationally expensive process of simulating or collecting data from experiments and be used to create the necessary training data for an AI-based monitoring system of partial discharges in power transformers. In this contribution, Dijkstra's algorithm is used with additional line-of-sight propagation algorithms to determine the paths of the electromagnetic waves generated by PD sources in a three-dimensional (3D) computer-aided design (CAD) model of a 300 MVA power transformer. The time-of-flight information is compared with results from experiments and electromagnetic simulations, and it is found that the algorithm maintains accuracy similar to that of the electromagnetic simulation software, with some under/overestimations in specific scenarios, while being much faster at calculations.

Effect of build orientation on the green tribological properties of multi-jet fusion manufactured PA12 parts

Additive manufacturing (AM) is a newly developed technology for manufacturing parts from three-dimensional (3D) computer-aided design (CAD) models by depositing a material layer on layer. Multi-jet fusion (MJF) is one of the AM technologies that can be used for manufacturing functional parts like gear, linear, bearing, etc., by polymers. In various applications, technical processes, design of tribological systems, optimum lubrication, and reduction of wear and friction are significant performance criteria to provide energy and material conservation. The development of green tribological applications offers essential solutions to problems of ecosystem pollution and energy from a global point of view to increase sustainability. In this article, the green tribological behavior of Polyamide 12 (PA12) parts, manufactured by MJF with different build orientations was evaluated by ball-on-disc tribological tests under different normal loads and lubricated environments. Mechanical profilometer and digital microscope were used to evaluate surface quality and morphology. Scanning electron microscope (SEM) was used to determine the samples’ wear characteristics. The maximum surface roughness was measured for the part having a build orientation of 45°. The maximum coefficient of friction value was determined as 0.355 for the sample with 45° orientation under 5 N load and dry environment. The maximum wear rate value was determined as 2.3249 × 10−4 mm3/Nmm for the sample with 0° orientation under 10 N load and dry state. The differences between build orientations should be considered when evaluating tribological properties. This article provides a new perspective to researchers and practitioners toward green tribology of polymer AM parts.

Open NASA Blade Models for Nonlinear Dynamics Simulations

Abstract This contribution presents a catalogue of open turbomachinery blade models dedicated to nonlinear dynamics simulations. Based on a specifically developed in-house computer code, three-dimensional computer-aided design (CAD) models and finite element (FE) models of multiple-circular-arc (MCA) NASA airfoils are generated. Both the in-house code and the models are made freely accessible online. To cover a wide range of geometries, 39 blades are considered from different stages and with different aspect ratios. It is expected that this blade catalogue will provide an opportunity for the direct comparison of recently developed methodologies relative to nonlinear vibration phenomena in turbomachines, including rubbing events and blade-tip/casing contacts. To this end, the paper also contains original results for some of the most emblematic NASA blades, with an emphasis on nonlinear interaction maps and a detailed presentation of redesign operations to mitigate high amplitude of vibrations when blade-tip/casing contacts occur.

Assessment of Intramural Segment Compression in Anomalous Coronary Arteries through Patient-Specific Finite Element Modeling

Background: Anomalous Aortic Origin of a Coronary Artery (AAOCA) is a congenital condition that can lead to ischemia and sudden cardiac death. Current diagnostic tools are unable to fully quantify the pathological behavior that occurs mainly with physical effort. Methods: Patients’ computed tomography scans and centerline-based geometric quantities were used to develop three-dimensional computer-aided design models of the main anatomical variants of AAOCA. Blood pressure ranging from rest to extreme effort was simulated through structural finite element analyses, and the pressurized geometries were analyzed to evaluate coronary lumen cross-sectional areas and variations at the different loading conditions. Results: We simulated 39 subjects, demonstrating the ability to reproduce accurately the patient-specific anatomy of different AAOCA variants and capture pathological behaviors. AAOCAs with intramural courses showed compression along the proximal segment with a caliber reduction ranging from 0.14% to 18.87% at different pressure levels. The percentage of proximal narrowing relative to the distal segment was greater than any other type of anomalous course and exceeded 50% with simulated exertion. Conclusions: The present study proposes a computational pipeline to investigate conditions not reproducible in clinical practice, providing information to support decision-making in the management of AAOCA patients.

Simplification of 3D CAD Model in Voxel Form for Mechanical Parts Using Generative Adversarial Networks

Most three-dimensional (3D) computer-aided design (CAD) models of mechanical parts, created during the design stage, have high shape complexity. The shape complexity required of CAD models reduces according to the field of application. Therefore, it is necessary to simplify the shapes of 3D CAD models, depending on their applications. Traditional simplification methods recognize simplification target shape based on a pre-defined algorithm. Such algorithm-based methods have difficulty processing unusual partial shapes not considered in the CAD model. This paper proposes a method that uses a network based on a generative adversarial network (GAN) to simplify the 3D CAD models of mechanical parts. The proposed network recognizes and removes simplification target shapes included in the 3D CAD models of mechanical parts. A 3D CAD model dataset was constructed to train the 3D CAD model simplification network. 3D CAD models are represented in voxel form in the dataset. Next, the constructed training dataset was used to train the proposed network. Finally, a 3D voxel simplification experiment was performed to evaluate the performance of the trained network. The experiment results showed that the network had an average error rate of 3.38% for the total area of the mechanical part and an average error rate of 14.61% for the simplification target area.

Study of unidirectional torsion of samples with different internal structures manufactured in the MEX process

PurposeManufacturing of products loaded with torque in an incremental process should take into account the strength in relation to the internal structure of the details. Incremental processes allow for obtaining various internal structures, both in the production process itself and as a result of designing a three-dimensional computer-aided design model with programmable strength. Finite element analysis (FEA) is often used in the modeling process, especially in the area of topological optimization. There is a lack of data for numerical simulation processes, especially for the design of products loaded with torque and manufactured additive manufacturing (AM). The purpose of this study is to present the influence of the internal structure of samples produced in the material extrusion (MEX) technology on the tested parameters in the process of unidirectional torsion and to present the practical application of the obtained results on the example of a spline connection.Design/methodology/approachThe work involved a process of unidirectional torsion of samples with different internal structures, produced in the MEX technology. The obtained results allowed for the FEA of the spline connection, which was compared with the test of unidirectional torsion of the connection.FindingsThe performance of the unidirectional torsion test and the obtained results allowed us to determine the influence of the internal structure and its density on the achieved values of the tested parameters of the analyzed prototype materials. The performed FEA of the spline connection reflects the deformation of the produced connection in the unidirectional torsion test.Originality/valueThere are no standards for the torsional strength of elements manufactured from polymeric materials using MEX methods, which is why the industry often does not use these methods due to the need to spend time on research, which is associated with high costs. In addition, the industry is vary of unknown solutions and limits their use. Therefore, it is important to determine, among others, the strength parameters of components manufactured using incremental methods, including MEX, so that they can be widely used because of their great potential and thus gain trust among the recipient market. In addition, taking into account the different densities of the applied filling structure of the samples made of six prototype materials commonly available from manufacturers allowed us to determine its effect on the torsional strength. The presented work can be the basis for constructors dealing with the design of elements manufactured in the MEX technology in terms of torsional strength. The obtained results also complement the existing material base in the FEA software and perform the strength analysis before the actual details are made to verify the existing irregularities that affect the strength of the details. The analysis of unidirectional torsion made it possible to supplement the material cards, which often refer to unprocessed material, e.g. in MEX processes.

Lightweight Model-Based Weld Line Generation and Its Applications to Support the Construction of Ships and Offshore Plants

Welding is the most expensive process in building ships and offshore plants. Therefore, the quantity of welding material should be calculated for the subsections (cells) of the blocks for efficient work planning, and welding paths must be generated for welding automation. Three-dimensional (3D) computer-aided design (CAD) models have been used for this work. However, relevant information regarding welding is often omitted, and a separate database and interface to this database must be developed. In this study, a method of lightweight model-based weld line generation is proposed, followed by the calculation of bead length for welding material quantity estimation and welding path generation. Experiments were performed on various test cases of curved parts and blocks. The proposed method accurately generated weld lines, calculated bead length, and generated welding paths in a short time of approximately 1 s.

Radiation Damage Analysis of FNSF Components Using McCad and MCNP

The Fusion Energy System Studies Fusion Nuclear Science Facility (FESS-FNSF) concept represents a transitional step between ITER and a commercial fusion power plant. The FNSF is a conceptualized D-T fueled tokamak with 518 MW of fusion power that has been extensively used to explore and optimize design features. The energetic 14.1-MeV neutrons can produce significant localized heating and activations, and can cause damage to plasma-facing components, which can determine maintenance/outage scheduling needs and also impact the lifetime of the device as a whole. This study illustrates a neutronics analysis that was conducted on a 22.5-degree symmetric sector of the FNSF with the goal of understanding the neutron heating and radiation damage that can be characterized by quantifying the displacements per atom (dpa). Concurrently, this study also focused on the development of analysis capabilities by converting a three-dimensional computer-aided design model of the FNSF into MCNP6.2 input using the McCad code. Accordingly, some confirmatory results on tritium production and the tritium breeding ratio (TBR) are provided to support model validation. The results produced by MCNP6.2 simulations showed that the highest heating and damage occurred in the outboard region, which concentrated approximately 290 MW of the total nuclear heating, in contrast to 97 MW within the inboard region. These results are consistent with previous studies that employed earlier versions of the FNSF concept and different modeling approaches. This study also provides additional details on neutron wall loading, as well as total heating from neutrons and gammas, results which show the total heating of the device (16 sectors) is approximately 477.83 ± 0.80% MW, indicating a neutron energy multiplication factor of 1.15. Additionally, the capability to calculate hydrogen and helium production, as well as dpa, is illustrated. Finally, the neutronics effects of using alternative materials to tungsten carbide were evaluated for the vacuum vessel, low-temperature shield, and structural ring components, which showed that compounds like YH2, Mg(BH4)2, and ZrH2 could reduce the total heating on the magnet and also reduce the TBR.

Integration of Dynamic Models and Virtual Reality for the Training of Steam Generator Operators

Abstract The goal of the PITSTOP (Immersive platform for structured operator training) project is to overcome the limits of traditional workplace training on dangerous systems and reduce the related risks, using an innovative integration of engineering simulation models and virtual reality (VR) tools. This article specifically presents the first VR platform for training on small-scale industrial steam generators, representative of a vast class of hazardous industrial equipment. The dynamic model of the steam generator was developed in matlab-simulink using a mixed physics-based and data-driven approach. The generator model includes the main engineering components, actuators and measuring equipment, as well as control logic and emergency procedures. It can simulate normal operations and emergency situations. The model was calibrated using experimental data collected from the real system at various operating conditions to align simulated performance with the real behavior. The VR environment was developed in Unity, a graphics engine widely adopted by the videogame industry, using three-dimensional computer-aided design models of the steam generator and its surroundings. The user can access this immersive system wearing an HTC Vive headset. Unlike most existing training systems, learners can interact with the actuators using bare hands gestures, without controllers, making the experience intuitive and easily accessible. By connecting the dynamic model with the VR environment, the user's interactions are directly provided to the steam generator model, which in turn directly outputs the steam generator response to the VR environment, providing audio and visual feedback to the user, as if they were actually acting on the real generator. The results from this study could boost the further development of training platforms to safely train operators and certify their competence.

A Pose-Normalization Method for Casting Voxel Models Using Second-Order Central Moment Matrix

Within the framework of casting process design, the efficient retrieval of three-dimensional (3D) computer-aided design (CAD) models could result in significant time and cost savings. However, this technique still suffers from inefficiency and inaccuracy because of the wide variety of casting models’ poses. In this study, a method for normalizing the poses of casting models is proposed. This method constructs the transformation matrix through the eigendecomposition of the second-order central moment matrix calculated from the voxel casting model. Then the transformation matrix is applied to the casting model to get a normalized pose. An assessment approach for pose normalization is also suggested in the study, which measures the distance between poses normalized based on multiple poses of the same model. The study demonstrates that the pose-normalization approach reliably transforms distinct poses of the same model into a unified pose. The mean distance between normalized poses is 0.016 and the minimum distance is 0.010. The method’s effects improve when the voxel size reduces.

Influence of the femoral entry point for intramedullary alignment in total knee arthroplasty: A computer-aided design approach.

Objectives The aim of this study was to simulate different entry points and investigate potential angulation errors of the intramedullary device and resulting changes in the distal femoral cut using a computer-aided design (CAD) approach.Materials and methods We used a CAD approach to simulate various distal femoral entry points for intramedullary instrumentation. Simulations were performed on (i) a commercially available three-dimensional (3D) CAD model of a human femur (DigitalFemur) and (ii) a digital 3D model of an analogue large femur model produced using a coordinate measuring machine (FaroFemur). Divergent insertion points medial, lateral, anterior and posterior to the ideal position were simulated. Angulation deviations of the resulting positions of the intramedullary rod were measured and changes in the anatomical-mechanical axis angle were calculated. Differences between the two simulation models were quantified.Results The ideal entry point in the FaroFemur was 9.9 mm anterior and 4.3 mm medial to the apex of the intercondylar notch, and 9.2 mm anterior and 3.6 mm medial in the DigitalFemur. A medial entry point increased the angle between the anatomical femoral axis and the alignment rod in the FaroFemur and DigitalFemur (with 5 mm displacement 2.510° and 2.363°, respectively; with 10 mm displacement 3.239° and 3.283°, respectively). In contrast, a lateral entry point decreased the angle between the anatomical femoral axis and the alignment rod (with 5 mm displacement 2.267° and 2.262°, respectively; with 10 mm displacement 3.158° and 3.731°, respectively). An anterior entry point changed the angle between the anatomical femoral axis and the alignment rod towards extension (1.802° in the FaroFemur; 2.142° in the DigitalFemur), while a posterior entry point generated a deviation toward flexion (2.045° in the FaroFemur; 2.055° in the DigitalFemur). The mean difference between the two models was 0.108±0.121° with the highest difference for anterior displacement.Conclusion Minor deviations of the entry point for intramedullary instrumentation during total knee arthroplasty can result in malalignment of several degrees.

Learning deep domain-agnostic features from synthetic renders for industrial visual inspection

Deep learning has resulted in a huge advancement in computer vision. However, deep models require an enormous amount of manually annotated data, which is a laborious and time-consuming task. Large amounts of images demand the availability of target objects for acquisition. This is a kind of luxury we usually do not have in the context of automatic inspection of complex mechanical assemblies, such as in the aircraft industry. We focus on using deep convolutional neural networks (CNN) for automatic industrial inspection of mechanical assemblies, where training images are limited and hard to collect. Computer-aided design model (CAD) is a standard way to describe mechanical assemblies; for each assembly part we have a three-dimensional CAD model with the real dimensions and geometrical properties. Therefore, rendering of CAD models to generate synthetic training data is an attractive approach that comes with perfect annotations. Our ultimate goal is to obtain a deep CNN model trained on synthetic renders and deployed to recognize the presence of target objects in never-before-seen real images collected by commercial RGB cameras. Different approaches are adopted to close the domain gap between synthetic and real images. First, the domain randomization technique is applied to generate synthetic data for training. Second, domain invariant features are utilized while training, allowing to use the trained model directly in the target domain. Finally, we propose a way to learn better representative features using augmented autoencoders, getting performance close to our baseline models trained with real images.

Identification of particular hydrodynamic parameters for a modular type 4 DOF underwater vehicle by means of CFD method

PurposeThe development of robust control algorithms for the position, velocity and trajectory control of unmanned underwater vehicles (UUVs) depends on the accuracy of their mathematical models. Accuracy of the model is determined by precise estimation of the UUV hydrodynamic parameters. The purpose of this study is to determine the hydrodynamic forces and moments acting on an underwater vehicle with complex body geometry and moving at low speeds and to achieve the accurate coefficients associated with them.Design/methodology/approachA three-dimensional (3D) computer-aided design (CAD) model of UUV is designed with one-to-one dimensions. 3D fluid flow simulations are conducted using computational fluid dynamics (CFD) software programme in the solution of Navier Stokes equations for laminar and turbulent flow analysis. The coefficients depending on the hydrodynamic forces and moments are determined by the external flow analysis using the CFD programme. The Flow Simulation k-ε turbulence model is used for the transition from laminar flow to turbulent flow. Hydrodynamic properties such as lift and drag coefficients and roll and yaw moment coefficients are calculated. The parameters are compared with the coefficient values found by experimental methods.FindingsAlthough the modular type UUV has a complex body geometry, the comparative results of the experiments and simulations confirm that the defined model parameters are accurate and close to the actual experimental values. In the proposed k-ε method, the percentage error in the estimation of drag and lifting coefficients is decreased to 4.2% and 8.39%, respectively.Practical implicationsThe model coefficients determined in this study can be used in high-level control simulations which leads to the development of robust real-time controllers for complex-shaped modular UUVs.Originality/valueThe Lucky Fin UUV with 4 degrees of freedom is a specific design and its CAD model is first extracted. Verification of simulation results by experiments is generally less referenced in studies. However, it provides more precise parameter identification of the model. Proposed study offers a simple and low-cost experimental measurement method for verification of the hydrodynamic parameters. The extracted model and coefficients are worthwhile references for the analysis of modular type UUVs.

Machining feature recognition based on deep neural networks to support tight integration with 3D CAD systems

Recently, studies applying deep learning technology to recognize the machining feature of three-dimensional (3D) computer-aided design (CAD) models are increasing. Since the direct utilization of boundary representation (B-rep) models as input data for neural networks in terms of data structure is difficult, B-rep models are generally converted into a voxel, mesh, or point cloud model and used as inputs for neural networks for the application of 3D models to deep learning. However, the model’s resolution decreases during the format conversion of 3D models, causing the loss of some features or difficulties in identifying areas of the converted model corresponding to a specific face of the B-rep model. To solve these problems, this study proposes a method enabling tight integration of a 3D CAD system with a deep neural network using feature descriptors as inputs to neural networks for recognizing machining features. Feature descriptor denotes an explicit representation of the main property items of a face. We constructed 2236 data to train and evaluate the deep neural network. Of these, 1430 were used for training the deep neural network, and 358 were used for validation. And 448 were used to evaluate the performance of the trained deep neural network. In addition, we conducted an experiment to recognize a total of 17 types (16 types of machining features and a non-feature) from the B-rep model, and the types for all 75 test cases were successfully recognized.

Manufacturability evaluation of parts using descriptor-based machining feature recognition

ABSTRACT Manufacturability validation refers to activities to evaluate the manufacturing cost of parts, manufacturing methods, and manufacturing difficulty, and to determine whether parts can be manufactured from three-dimensional (3D) computer-aided design (CAD) models. To automate the manufacturability evaluation process, it is important to first recognize the machining features of an input 3D CAD model. Thereafter, various pieces of information required for manufacturability evaluation are extracted from the recognized features, and whether manufacturing can be realized according to the predefined manufacturability criteria is determined. This study proposes a method to evaluate manufacturability according to 19 criteria, after automatic recognition of the machining features of turning, milling, and drilling from boundary representation (B-rep) 3D CAD models, which are widely used in work sites. In addition, this study implements a prototype system, and discusses the results of an experiment involving recognition of the features of two test cases, and their manufacturability evaluation.

Comparison of different fidelity mass analyses

Purpose Aircraft structure mass estimation is a very important issue in aerospace. Multiple methods of different fidelity are available, which give results with varying accuracy. Sometimes these methods are giving a high discrepancy of estimated mass compared to the real mass of the structure. The discrepancy is especially noticeable in the case of small aircraft with a composite structure. Their mass properties highly depend not only on the material but also on technology and the human factor. Moreover, methods of mass estimation for unmanned aerial vehicle (UAV) platforms are even less established and examined. The purpose of this paper is to present and discuss various methods of mass estimation. Design/methodology/approach The paper presents different procedures of mass estimation for small UAVs with a composite structure. Beginning from the simplest one, where mass is estimated basing on a single equation and finishing with a mass estimation based on finite element method model and three-dimensional computer-aided design model. The results from all methods are compared with the airworthy aircraft and conclusions are discussed. Findings Mass of flying aircraft was estimated with different methods and compared. It revealed levels of accuracy of the investigated methods. Moreover, the influence on structure mass of human factor, glueing and painting is underlined. Practical implications Mass of the structure is a key factor in aerospace, which influences the performance of the aircraft. Thorough knowledge about the accuracy of the mass estimation methods and possible sources of discrepancies in mass analyses provides an essential tool for designers, which can be used with confidence and allows for the development of new cutting-edge constructions. Originality/value There are very few comparisons of mass estimation methods with an actual mass of manufactured and functional airframes. Additionally, mass estimation inaccuracies based on technological issues are presented, which is seldom done.

Computational methods for the investigation of ski boots ergonomics

Ski boots are known to cause vasoconstriction in the wearer’s lower limbs and, thus, cause a “cold leg” phenomenon. To address this problem, this work provides a computational framework for analysing interactions between the ski boot and the lower limb. The geometry of the lower limb was derived from magnetic resonance imaging and computed tomography techniques and anthropometric data. The geometry of the ski boot shell was obtained by means of three-dimensional computer aided design models from a manufacturer. Concerning the ski boot liner, laser scanning techniques were implemented to capture the geometry of each layer. The mechanical models of the ski boot and the lower limb were identified and validated by means of coupled experimental investigations and computational analyses. The computational models were exploited to simulate the buckling process and to investigate interaction phenomena between the boot and the lower limb. Similarly, experimental activities were performed to further analyse the buckling phenomena. The obtained computational and experimental results were compared regarding both interaction pressure and displacements between the buckle and the corresponding buckle hooks. These comparisons provided reasonable agreement (mean value of discrepancy between the model and mean experimental results in the tibial region: 20%), underlining the model’s capability to correctly interpret results from experimental measurements. Results identified the critical areas of the leg, such as the tibial region, the calcaneal region of the foot and the anterior sole, which may suffer the most due to the hydrostatic pressure and compressive strain exerted on them. The results highlight that computational methods allow investigation of the interaction phenomena between the lower leg and ski boot, potentially providing an effective framework for a more comfortable and ergonomic design of ski boots.

Automatized Evaluation of Students’ CAD Models

The article describes an attempt to address the automatized evaluation of student three-dimensional (3D) computer-aided design (CAD) models. The driving idea was conceptualized under the restraints of the COVID pandemic, driven by the problem of evaluating a large number of student 3D CAD models. The described computer solution can be implemented using any CAD computer application that supports customization. Test cases showed that the proposed solution was valid and could be used to evaluate many students’ 3D CAD models. The computer solution can also be used to help students to better understand how to create a 3D CAD model, thereby complying with the requirements of particular teachers.