جستجوی مقالات مرتبط با کلیدواژه « 3D F?E?M » در نشریات گروه « فنی و مهندسی »

The surface texture depth is an important indicator for evaluating the skid resistance capabilities and providing suitable surface drainage conditions for asphalt pavement, which has a direct effect on the safety and comfort of road users. Texture evaluation is one of the main goals of the pavement management system. Three-dimensional evaluation is the most accurate method of measuring pavement texture characteristics. In this paper, a three-dimensional automatic device based on a hybrid imaging technique is presented. In this device, a system consisting of two-dimensional digital cameras is designed to provide the required image data. The proposed system has a tool for reducing surface friction. This system also makes it possible to evaluate the texture in rainy conditions. Based on the two-dimensional images taken from the pavement surface, the three-dimensional models of the pavement texture are presented. A method for calculating the mean texture depth is presented. Measuring the depth of pavement texture in different directions is a the capability of this method, which makes it possible to uniformly evaluate the depth of the texture in different directions and find the critical direction for texture drainage capacity. The proposed system has been used to measure the depth of texture in different sections of pavement and the results in have been compared with the results of the standard sand patch method. This comparison shows a high correlation between the results of the proposed method and the standard pavement texture evaluation method.

With the increasing development of technology and the emergence of smart devices in today’s life, interactive communication with these smart devices has become inevitable. Among the many methods of interactive communication, which include the use of voice and clothes equipped with motion sensors, as well as image-based methods, each of which is focused on identifying and monitoring a specific part of the body, human hand-based methods due to their characteristics Especially the hand is of double importance in this field, and therefore the estimation of the three-dimensional state of the hand using image processing has become one of the most attractive and challenging research fields related to human-machine interaction. In this article, different methods of estimating the three-dimensional state of the hand are reviewed with an emphasis on methods based on image processing, and their strengths and weaknesses are stated and compared. This comparison is based on traditional methods as well as methods related to deep learning. Also, the databases used in hand posture estimation have been introduced and the characteristics of each of them have been investigated in different applications.

The use of 3D printing concrete in construction applications is one of the most innovative and challenging fields, combining traditional construction knowledge with digital technologies. The focus on this area has increased due to removing the molds, reducing the cost, needed human resources, and other important advantages. There are many challenges such as rheological requirements, bonding between layers, materials used, their reinforcement, and anisotropic behaviors in this industry which has a special potential in fast and mass construction, and complex architectures. Throughout history up to current times, the performance of the built structures has always been the result of the interaction between steel and concrete. According to the practical applications of this technology, manufacturing compatible materials, using reinforcing systems such as fibers and steel rebars, and maintaining proper interaction between them, are fascinating subjects that attract the attention of researchers in this field. The examples of the research processes along with their analysis are reviewed in this article. since this article was written to introduce this technology and its challenges, it provides a source of inspiration, for getting to know the audience as much as possible, with conflict goals of producing suitable concrete to improve the ability of printing and its quality.

A composite structure is a non-uniform solid that consists of two or more different materials with different kinds that are mechanically bonded together. These structures have completely different chemical and physical properties and they merge together to make a substance that is not similar to any of these materials. In previous studies, the construction and investigation of sandwich structures of polymer materials were done with two materials with similar physical properties (two hard materials), but in this research, two polymers with completely different physical properties were combined and a new sandwich structure was made. This study aims to investigate and try to increase the mechanical performance of single-layer and multi-layer composite (sandwich) structures printed from hard (ABS) and soft (TPU) polymer materials and comparing these samples by preparing different composite structures from these polymers. The method of making polymer materials used in this research is the use of 3D printing technology (incremental layering). The results have been obtained in the form of laboratory tensile test and simulation in the Abaqus software environment. These results indicate that with the change of layers and materials, the amount of strain to failure of the composite samples has increased up to about 4 times. It should be noted that the construction of the tensile test samples in this project was done according to the standard of the American Association of Materials and Testing.

To design an open pit mine, geological operations must be conducted, followed by the preparation of a three-dimensional model and mineral block model. The ultimate pit limit can be determined through accurate methods and artificial intelligence techniques. The problem of determining the ultimate pit limit is considered to be NP-hard, making it challenging to solve. While exact methods provide better and optimal results, they may require significant time to answer the problem due to the large number of blocks involved. In such cases, it is more suitable to use collective algorithms or a planned approach to determine the final range. Optimizing the determination of the ultimate pit limit is similar to other optimization problems that can be addressed using logical algorithms in MATLAB software. In this study, Keshtel algorithm, implemented in MATLAB, is utilized to optimize the final range. Initially, Keshtel algorithm is employed to solve the problem. Subsequently, the Songun copper mine is chosen as a case study for the two-dimensional and three-dimensional implementation, and the results of determining the ultimate pit limit are compared with both Keshtel algorithm and NPV Scheduler software. The findings reveal that Keshtel algorithm, used to determine the final limits of the Songun copper mine, differs by only 0.47% compared to the NPV Scheduler software. Moreover, the comparison of Keshtel algorithm with the results of Lerch Grossman in determining the two-dimensional final range, as well as the comparison with NPV Scheduler software in three-dimensional problems, demonstrates its efficiency in solving these issues effectively.

Today, nanotechnology is used in various fields. One of the practical tools of this new technology is the Atomic Force Microscope (AFM). AFM is used in imaging, making microscale equipment, extracting the properties of biological tissues and manipulation. Manipulation of particles using AFM is considered in two phases. The first phase is before the movement of the target particle and the second phase is during the movement of the target particle. Determining the exact path of the particle in the second phase of nanomanipulation is of great importance. One of the important parameters in the simulation of the second phase is the friction model used. In this research, for the first time, three exact friction models of LuGrr, Leuvn and Greenwood-Williamson have been used to investigate the 3D second phase of nanomanipulation. The target particle under investigation is a gold nanoparticle, whose dimensions and geometry were obtained experimentally by imaging with an AFM. The obtained results have shown that the LuGre model predicts the lowest amount of displacement and the Greenwood-Williamson model predicts the highest amount of displacement.

Three dimensional printing (3D) is a process of fabricating 3D objects through depositing layers of materials (such as polymers) on previous layers. Currently is considered one of the most important research fields in academic and industrial research centers. Among the various approaches to 3D printing, photopolymerization is of great interest due to the wide range of monomers/oligomers prone to photopolymerization reactions (photopolymers). Photoinitiators and monomers/oligomers are two important components of resins applied for 3D process, which affect not only the possibility of resin printing, but also the functional properties of the part such as mechanical strength, dimensional accuracy, transparency, modulus and others. In this article, the most important group of photopolymers used in the 3D printing process is reviewed from the point of view of reaction chemistry and their advantages and disadvantages. It is obvious that the design and manufacture of photocurable resins requires knowledge about the types of resins available and the challenges associated with them. Therefore, this article can be a good source for active researchers in this field.

In this study, the distribution of the fracture intensity in the Sarvak carbonate Formation in an oilfield located in the Dezful embayment and its relationship with geomechanical parameters were investigated. Therefore, fracture intensity data, reservoir data such as porosity, along with rock elastic properties were imported into Petrel software. In this software, after providing several seismic attributes, such as variance attributes, they were merged together using the neural network approach and converted to one driver (representative attribute) to be applied for fracture intensity modeling. After constructing the 3D grid, the imported data such as fracture intensity, porosity, and geomechanical parameters were scaled up and prepared for modeling. Therefore, all related logs including porosity, Young’s modulus, Poisson's ratio, and uniaxial compressive strength along with the fracture intensity logs were distributed in three dimensions using geostatistical algorithms, in order to investigate the relationship between geomechanical parameters and fracture network distribution. Based on this study, there is a notable relationship between geomechanical parameters and porosity while there is no logical relationship between geomechanical parameters and fracture intensity. Also, the parts with high fracture intensity in the upper and lower Sarvak do not show a clear relationship with the effective porosity distribution, indicating the effect of diagenesis processes in porosity variation during the geological time.

In the Emarat Pb-Zn deposit located in the Markazi province, underground exploration and exploitation activities have been carried out at the various elevation levels through drilling tunnels and cross-cuts. In the present research, 2D and 3D modeling of surveyed faults at the variety of levels were performed studying their relationship with ore-bearing in the region qualitatively and quantitatively. To achieve the goal, a complete statistical study was done, first. Afterward, 2D strike and dip map with rose diagram, 2D grid-based map, 3D strike and dip diagram and solid model of the faults surveyed at the various elevation levels were drawn and analyzed using methods and different mathematical algorithms applied in geosciences. In addition, a stratified iso-grade map of total Pb-Zn for different elevation levels was also produced. The qualitative comparison of 2D grid-based maps and iso-grade maps for each elevation level peer to peer shows that in general, trend of mineral depositing follows the trend of faults frequency but frequency of the faults number in each zone does not much affect on the deposit grade. Also, the linear correlation coefficient between the faults number and deposit grade at the various elevation levels was obtained 0.157 on average, equaling to "very low" correlation. In fact, the results of the quantitative correlation at the different elevation levels, confirm the results of the qualitative correlation study.

Since the behavior of people in the videos are in 3D signals format and they are long, it is difficult to search for a specific action. Therefore, a suitable technique in live security videos is required to detect ongoing armed thieves to reduce the occurrence of crime and theft. The innovation of this paper is to provide a rapid and efficient method for detecting guns in frames of images taken from videos without deleting the main points. The hierarchy of object recognition is that in order to extract frames from images derived from videos, the separation algorithm will be applied at a specified frame rate and all images will be placed in a folder. Then, video samples are divided into three categories of training, validation and testing, and using Haar Cascade (HC) classification, the frames of whole body images are extracted and the rest of the backgrounds are removed from the images. The reason for choosing this method is that the HC classification is resistant to rotation of images and also this algorithm has shown good performance compared to complex calculations. Therefore, in our proposed model, we will use this algorithm as a whole body diagnosis. This is done by detecting the Region of Interest (ROI) area by cutting the selected areas, followed by subtracting the background to eliminate unwanted backgrounds. All key points of selection and extraction are stored inside a folder. Finally, all images are sent to 3D convolutional Neural Networks (3DCNNs) to detect weapons in the images. Finally, in order to evaluate the performance of the system in terms of accuracy, it is used with correct positive rate parameters, false positive rate, positive prediction value and false detection rate. As can be seen in the results of the tests, the highest gun detection rate is related to the 3DCNNs model with a detection rate of 96.1%, followed by the best detection model rate related to YOLO V3 and with a detection rate of 95.6%.

light-based three dimensional (3D) printing processes which are based on the use of light-sensitive monomers or oligomers, are the most versatile and interesting technique due to the unique potential to design structures with complex geometry, the ease of the process, the availability of the required compounds as well as the feasibility of tailoring materials to achieve the required properties. In this approach, photoinitiators are considered the key elements in the success of this process, and several types of research have been performed to introduce initiators with enhanced efficiencies. This article reviews the types of photoinitiators used in 3D printing technology and highlights the research carried out to transfer the absorption region of the compounds from the ultraviolet region to the visible region. In addition, water-soluble photoinitiators are also of great interest for use in the bioprinting of hydrogel systems, which are reviewed in this article. Obviously, success in the development of the 3D printing process and fabrication of constructs with suitable mechanical properties as well as resolution requires familiarity with the key elements involved in the process, therefore, one of the most important factors is investigated

In this study, a 3D bioactive glass composite scaffold containing 2 mol% silver/polycaprolactone (PCL) was synthesized by a 3D printer with the advantages of reproducibility and high flexibility in shape and size. The effective parameters (printer parameters, ratio of glass-phase, polymer phase, and solvent in printer ink) were determined for printing of nanocomposite scaffold by Taguchi method. Characterization of printed scaffolds was performed using X-ray diffraction, scanning electron microscope, infrared spectroscopy, bioactivity test, atomic emission spectroscopy, toxicity test, and cell proliferation. The results related to the synthesis of silver-containing bioglass by sol-gel method and heat treated at 550°C offered nanoparticles with an average diameter of less than 15 nm and a homogeneous distribution of silver in the matrix. Ratio of polymer phase to glass powder equivalent to 0.5, concentration of polymer in solvent of 50%, retraction of 1.5, and drive gear of 1200 are obtained as the optimum conditions for scaffold printing with acceptable quality (percentage, size and distribution of holes, regular structure of layers, and repeatability). The fabricated scaffold in optimal conditions revealed significant antibacterial properties, good bioactivity, acceptable cell viability, and high ALP activity. 3D printed BG/PCL nanocomposite scaffolds with macro (up to 500 µm) and micro size of holes and porosity percentage up to 64% in the structure can be a promising candidate for bone tissue engineering.

One of the serious challenges in remote sensing is extracting suitable features. With the presence of a new generation of deep neural networks, automatic and accurate feature extraction and classification of crops have become possible. On the other hand, appropriate features can partially reduce the effects of spectral similarity in the detection of different crops while improving classification accuracy. Also, the use of time-series data during the crop growth period provides useful information about crops to researchers. In this regard, this research aimed to investigate and evaluate three methods, three-dimensional convolutional neural network (3D-CNN), long short-term memory (LSTM), and gated recurrent unit (GRU), to extract appropriate features from time-series optical images. In the architecture of 3D-CNN, an attempt was made to design a structure so that the optimal spatial-temporal features could be extracted from time series images, and then the results were evaluated and compared with two other methods (i.e. LSTM, GRU). Finally, according to the results, 3D-CNN, with an overall accuracy (OA) of 90.70% and a kappa coefficient (KC) of 89.37%, which were about 3.50% and 4.00% higher than the OA and KC of LSTM, respectively, demonstrated a greater capability to identify crops. Moreover, the OA of the results of the classification by GRU was close to the OA of 3D-CNN, and only the OA of this method was 1.48% better than GRU. Therefore, the results confirmed the efficiency and suitability of 3D-CNN for crop classification.

The most important strategy in tissue engineering is the relationship between the three components of biomaterials, living cells, and biologically active molecules suitable for tissue regeneration. To be clinically effective, these environments must replicate, as closely as possible, the main characteristics of the native Extracellular Matrix (ECM) on a cellular scale. Tissue engineering is generally employed to create hybrid scaffolding to support cartilage tissue regeneration using fabrication 3D printing techniques. The current study designed a three-dimensional scaffold using FDA-approved Polycaprolactone/Poly Lactic-co-Glycolic Acid (PCL/PLGA) polymers. Then, 40 and 45 (w/w) alginate nanoparticles were added to the bio-ink to improve the printability, mechanical properties, and biocompatibility of the scaffolds. Finally, 3D-printed scaffolds were evaluated using mechanical properties, surface hydrophilicity, water absorption, biodegradability, surface morphology, and cell viability. The results showed that increasing the percentage of alginate nanoparticles in the bio-ink would increase the percentage of porosity, surface hydrophilicity, mechanical properties, cell viability, and printability. In addition, water absorption and compression modules of PCL/PLGA 3D-printed scaffolds containing 45 % alginate were optimized, compared to those of other groups, hence used as bio-ink in 3D printing of scaffolds in tissue engineering defects.

Nowadays using 3D printing for prototyping is well known in industrial applications and there are efforts to make functional parts with this technology to reach low volume production markets. By using pellets rather than filaments, the limitations caused by lack of variety of materials can be conquered. Also there will be no need to make a massive part as several divided parts and then glue them together.In this article pellets of ABS, that are well known and functional in industry, are analysed for an extruder to investigate the ability of pellet material extruding. Characteristic specifications of extruder such as operating pressure, screw rotational speed and required torque for rotating the screw are achieved for they are important factors to find out the mechanism for experimental tests and selecting suitable operating parts such as motor and gearbox. At the end, the experimental tests on designed system are done and the result approved the trends of theoretical data.

چکیده انگلیسی Polymer 3D printing is an emerging technology that further research in this field will lead to continuous improvement of polymer 3D printing design performance, which is necessary to push the boundaries in engineering and medicine. Polymer 3D printing provides the possibility of printing low-cost functional parts with various properties and capabilities. Here, by reviewing research on materials, processes and related strategies applied for medical applications, it is presented. Research in materials has led to the development of polymers with useful properties for mechanics and biocompatibility, by tuning the mechanical properties achieved by changing the parameters of the printing process. Polymer 3D printing technologies include extrusion, sheet lamination, Vat photo polymerization, additive layer, powder-based fusion, material projection, direct energy deposition. Thermal and laser inkjet techniques are more common. The two technologies of sheet exfoliation and direct energy deposition have limited medical applications. Which enables the direct deposition of design materials for useful and customized architectures. Design strategies, such as the hierarchical distribution of materials, make it possible to balance contrasting properties. The most investigated medical applications include tissue scaffolds, dental implants, medical education, delivery systems, and drug safety devices. And finally, the challenges and obstacles of polymer 3D printing were studied.

Although ECG signals contain rich enough information about the heart function, neither the clinical cardiologists nor researchers and engineers with their developed algorithms can illustrate all of this hidden information without some ECG pre-processing attempts. The standard 12- lead ECG signals represent the magnitudes of the heart's electrical activity at any instant in a cardiac cycle. Still, the direction of these signals is not clearly shown in ECG leads. On the other hand, in VCG, we have both the magnitude and direction of the heart's electrical signal, but the time is hidden. In this paper, a new approach has been proposed that, without requiring complicated calculations, represents and visualizes the magnitude and direction of the heart's electrical activity as a function of time. Unlike the normal 2-dimensional ECG for several leads, in this new 3-dimensional proposed ECG(Time Vector Electrocardiogram), any two arbitrary frontal leads are shown versus time. The resulting curve is independent of the selected leads; thus, only a single 3-dimensional curve is obtained, which contains and illustrates more information about the heart function. Some applications of the proposed method are presented in this paper by using the ECG data for patients from the G12EC database. If this new approach is welcomed by cardiologists and field experts, we believe that it would greatly assist them in diagnosing heart behavior and its possible abnormalities more clearly and much faster.