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1 |
In-situ optimization of thermoset composite additive manufacturing via deep learning and computer vision
بهینه سازی درجای تولید افزودنی کامپوزیت ترموست از طریق یادگیری عمیق و بینایی کامپیوتری-2022 With the advent of extrusion additive manufacturing (AM), fabrication of high-performance thermoset com-
posites without the need of tooling has become a reality. However, finding an optimal set of printing parameters
for these thermoset composites during extrusion requires tedious experimentation as composite ink properties
can vary significantly with respect to environmental parameters such as temperature and relative humidity.
Addressing this challenge, this study presents a novel optimization framework that utilizes computer vision and
deep learning (DL) to optimize the calibration and printing processes of thermoset composite AM. Unlike
traditional DL models where printing parameters are determined prior to printing, our proposed framework
dynamically and autonomously adjusts the printing parameters during extrusion. A novel DL integrated extrusion
AM system is developed to determine the optimal printing parameters including print speed, road width, and
layer height for a given composite ink. This closed loop system is consisted of a computer communicating with an
extrusion AM system, a camera to perform in-situ imaging and several high accuracy convolution neural net-
works (CNNs) selecting the ideal process parameters for composite AM. The results show that our proposed
process optimization framework was able to autonomously determine these parameters for a carbon fiber-
composite ink. Consequently, specimens with complex geometries could be fabricated without visible defects
and with maximum fiber alignment and thus enhancing the mechanical performance of the specimen’s com-
posite material. Moreover, our proposed framework minimizes a labor-intensive procedure required to additively
manufacture thermoset composites by optimizing the extrusion process without any user intervention. keywords: یادگیری عمیق | بینایی کامپیوتر | اکستروژن | پرینت سه بعدی کامپوزیت | Deep learning | Computer vision | Extrusion | Composite 3D printing |
مقاله انگلیسی |
2 |
3D-printable conductive materials for tissue engineering and biomedical applications
مواد رسانای قابل چاپ سه بعدی برای مهندسی بافت و کاربردهای زیست پزشکی-2021 Many patients that undergo autografting suffer from donor site morbidity and risk of immune rejection. Tissue
engineering is receiving considerable attention as engineered tissues could help overcome the drawbacks of
autografts and achieve better performance on tissue repair, replacement and regeneration. Conductivity is one of
the desired properties of engineered scaffolds and tissue constructs as bioelectricity plays an important role in the
native physiological environment. Hence, conductive materials have been extensively used in the making of
biosensors, tissue engineering scaffolds and drug delivery systems to elicit electrically-mediated signals, thus
mimicking the natural cellular environment. Conductive polymers, carbon-based materials, and metal nanoparticles are the main categories of conductive materials used. Ionic liquids, especially biocompatible ionic
liquids, is currently being explored as a competitive filler composite to greatly improve the conductivity of
polymers with little to zero cytotoxicity. The effects of electrical stimulation on cell alignment, migration,
proliferation, and differentiation as well as detailed properties of different types of conductive materials are
briefly yet succinctly reviewed. Furthermore, 3D printing of conductive scaffolds and hydrogels, and their corresponding biomedical applications are also discussed.
Keywords: Conductive biomaterials | Bioprinting | Tissue engineering | Ionic liquids | Electrical stimulation |
مقاله انگلیسی |
3 |
Knowledge-Based Management of Virtual Training Scenarios
مدیریت دانش محور سناریوهای آموزش مجازی-2021 Virtual reality (VR) gains increasing attention as a method of implementing training systems in different domains, in particular,
when real training is potentially dangerous for the trainees or the environment, or requires expensive equipment. The essential
element of professional training is domain-specific knowledge, which can be represented using the semantic web approach. It
enables reasoning as well as complex queries against the representation of training scenarios, which can be valuable for teaching
purposes. However, the available methods and tools for creating VR training systems do not use semantic knowledge representation.
Currently, the creation, modification, and management of training scenarios require skills in programming and computer graphics.
Hence, they are unavailable to domain experts without expertise in IT. In this paper, we propose an ontology-based representation
and a method of modeling VR training scenarios. In our approach, trainees’ activities, potential mistakes as well as equipment
and its possible errors are represented using domain knowledge understandable to domain experts. We illustrate the approach by
modeling VR training scenarios for electrical operators of high-voltage installations.
Keywords: semantic web | knowledge representation | ontologies | training | virtual reality | 3D content |
مقاله انگلیسی |
4 |
Dynamic resilience for biological wastewater treatment processes: Interpreting data for process management and the potential for knowledge discovery
انعطاف پذیری پویا برای فرآیندهای تصفیه بیولوژیکی فاضلاب: تفسیر داده ها برای مدیریت فرآیند و پتانسیل برای کشف دانش-2021 Climate change, population growth and increasing regulation are causing wastewater treatment plants to become
increasingly stressed, especially in countries like the UK, where many of these systems date back to the early part
of the 20th century. Understanding resilience dynamics for these ageing wastewater assets represents a funda-
mental step in classifying multi-dimensional water stressors toward preventing severe pollution incidents. This
paper explores the potential of a novel dynamic resilience approach to assess and predict the dynamic resilience
of biological wastewater treatment based on the separation of stressor events (cause) and process stress (effect) to
consider the deviation from reference conditions. The approach presented provides a fundamental link between
(1) conventional activated sludge modelling methodologies, (2) actual biological wastewater process instrument
data (potential for knowledge discovery) and (3) the characterisation of dynamic resilience in wastewater
treatment processes. Results first present the dynamic resilience approach by modelling simulated shock flow
conditions on an activated sludge plant, then incorporates ten years of wastewater process instrument data to
demonstrate the actual dynamic resilience. The aim is to represent the “dynamic resilience” as self-ordering
windows, a visual knowledge base (three dimensional, heat map), which operational staff can easily interpret.
The outcomes presented suggest that such an approach is feasible and has the potential for real-time identifi-
cation of conditions that result in pollution incidents based on actual historical process instrument data
(knowledge discovery). Also, the methods presented could be extended to develop an improved understanding of
wastewater system resilience under a range of future stressor scenarios. keywords: انعطاف پذیری پویا | مدل سازی تاثیر فرآیند | استرس فرایند | مدل سازی پویا | مدل سازی فاضلاب | Dynamic resilience | Process impact modelling | Process stress | Dynamic modelling | Wastewater modelling |
مقاله انگلیسی |
5 |
Dynamic 3D image simulation of basketball movement based on embedded system and computer vision
شبیه سازی تصویر پویا سه بعدی حرکت بسکتبال بر اساس سیستم تعبیه شده و بینایی ماشین-2021 Traditional empirical basketball teaching methods can be repeated, affecting serious basketball training efficiency and the acquisition of technical essentials. Based on this problem, the basketball training reproduction framework is built utilizing augmented reality innovation. The framework sets up a virtual reenactment model ofa ballplayer planning a player’s track. Simultaneously, as a helping player, it captures the basketball player’sactual situation, compares them with the simulated trajectories, and provides more targeted training. Based on virtual reality-based Virtual Data Augmentation Technology (VDRT), basketball technology’s teaching mode allows players to acquire key points of sports skills and significantly improve basketball players’ training efficiency as soon as possible. With the quick improvement of current science and innovation, for example, center, science and innovation, and electronic data innovation, more educational activities are being applied. However, modern educational methods’ important content is to master and use modern educational equipment and processes. This article uses basic concepts, characteristics, and virtual reality techniques and literature and information methods to explain the types of role play in basketball lessons. Finally, it analyzes the application programs of basketball theory education, technical education, tactical instruction and educational competitions that provide scientific standards for future basketball education reform. Keywords: Basketball movement | virtual data reinforcement technique (VDRT) | Field Programmable Gate Array (FPGA) |
مقاله انگلیسی |
6 |
Stereo disparity optimization with depth change constraint based on a continuous video
بهینه سازی اختلاف استریو با محدودیت تغییر عمق بر اساس یک فیلم مداوم-2021 Three-dimensional reconstruction based on stereo vision technology is an important research direction in the field of computer vision, and has a wide range of applications in industrial measurement, medical image reconstruction, cultural relic preservation, robot navigation, virtual reality and other fields. However, the three- dimensional reconstruction of moving objects usually has poor accuracy, low efficiency and poor visualization effect due to the image noise, motion blur, complex and time-consuming calculation etc. In this article, a disparity optimization method based on depth change constraint is proposed, which utilizes the correlation of the adjacent frames in the continuous video sequence to eliminate mismatches and correct the wrong disparity values by introducing a depth change constraint threshold. The experiments on the video images which are taken by a binocular stereo vision system demonstrate that our method of removing incorrect matches bears satisfactory results and it can greatly improve the effect of the three-dimensional reconstruction of the moving objects. Keywords: Disparity optimization | Three-dimensional reconstruction | Depth change constraint | Video images |
مقاله انگلیسی |
7 |
Stereo disparity optimization with depth change constraint based on a continuous video
بهینه سازی اختلاف استریو با محدودیت تغییر عمق بر اساس یک فیلم مداوم-2021 Three-dimensional reconstruction based on stereo vision technology is an important research direction in the field of computer vision, and has a wide range of applications in
industrial measurement, medical image reconstruction, cultural relic preservation, robot
navigation, virtual reality and other fields. However, the three-dimensional reconstruction of moving objects usually has poor accuracy, low eciency and poor visualization
eect due to the image noise, motion blur, complex and time-consuming calculation
etc. In this article, a disparity optimization method based on depth change constraint is
proposed, which utilizes the correlation of the adjacent frames in the continuous video
sequence to eliminate mismatches and correct the wrong disparity values by introducing a depth change constraint threshold. The experiments on the video images which
are taken by a binocular stereo vision system demonstrate that our method of removing
incorrect matches bears satisfactory results and it can greatly improve the eect of the
three-dimensional reconstruction of the moving objects.
Keywords: Disparity optimization | Three-dimensional reconstruction | Depth change constraint | Video images |
مقاله انگلیسی |
8 |
Revised notched coating adhesion test to account for plasticity and 3D behaviour
تست چسبندگی پوشش بریدگی اصلاح شده برای محاسبه انعطاف پذیری و رفتار سه بعدی-2021 Specialized polyamide-imide coating on a CuSn10Pb10 substrate, a material combination utilized often in
modern bearing applications, is fabricated using the solvent casting method. The coating adhesion is studied
using the well-known notched coating adhesion (NCA) test. Conventionally, the critical strain required to cause
the debond propagation is determined by visual observation and indirectly linked to measured strain data to
calculate fracture toughness. Here, digital image correlation (DIC) is used to systemically study the coating
deformations during testing that enables quantitative determination of the instantaneous debond length. With
the introduced method, the critical strain to induce the debond of the coating and the propagation of the
debond can be determined for non-elastically behaving specimens reliably. The coating’s debond onset is
studied with virtual crack closure technique (VCCT) here. The method can take 3D effects into account in
detail and provides a sophisticated method to determine the critical energy release rate. Additionally, cohesive
zone modelling (CZM) is used to simulate debond progression. Nonlinear stress–strain responses are observed
taking place both with the coating and the substrate materials. The results emphasize that the coating plasticity
has a remarkable role in the test behaviour which needs to be taken into account in the revised analysis.
Keywords: Notched coating adhesion | Fracture toughness | Digital image correlation | Polyamide-imide | Virtual crack closure technique | Cohesive zone model |
مقاله انگلیسی |
9 |
Hybrid simulation models for spare parts supply chain considering 3D printing capabilities
مدل های شبیه سازی ترکیبی برای زنجیره تامین قطعات یدکی با توجه به قابلیت های چاپ سه بعدی-2021 In the era of Industry 4.0, 3D printing unlocks a wide array of solutions to rapidly-produce spare parts for maintenance operations. In this research, we propose a hybrid simulation approach, combining agent-based and discrete event simulation methods, to investigate how the adoption of 3D printing technologies to manufacture spare parts for maintenance operations will improve operational efficiency and effectiveness. Specifically, our framework is applied to the United States Navy’s fighter jet maintenance operations to study various network configurations, where 3D printing facilities may be centralized, decentralized, or hub configured. System performance in terms of the total cost, timeliness of delivery, and vulnerability under disruptions such as cyber- attacks and emergencies are evaluated. Lastly, the impact of 3D printing technological advancements on operational performance is investigated to obtain managerial insights. Keywords: 3D printing | Hybrid simulation | Maintenance operations | Supply chain network configuration |
مقاله انگلیسی |
10 |
A mobile stereo vision system with variable baseline distance for three-dimensional coordinate measurement in large FOV
یک سیستم دید استریو متحرک با فاصله پایه متغیر برای اندازه گیری مختصات سه بعدی در FOV بزرگ-2021 A novel mobile stereo vision system (MSVS) with variable baseline distance for three-dimensional (3D) coordinate measurement in large field of view (FOV) is established herein. Each independent mobile camera can rotate in the horizontal and vertical directions, and the position of the cameras are obtained by differential GPS in real time. In order to achieve rapid camera calibration in large FOV, a simplified model of MSVS based on differential GPS is constructed in this paper. A six-point method is proposed to quickly estimate the camera’s initial parameters (i.e. focal length, initial roll, pitch, and yaw angles) in the situation that the approximate value of the initial yaw angle is unknown. Moreover, the camera’s roll angle is equivalent to its approximate value measured by a high-precision inclinometer during the movement, and the unknown extrinsic parameters of each camera are reduced to the pitch and yaw angles after the camera moves. The refined pitch and yaw angles are eventually estimated by only using a single control point, which makes it possible that the 3D coordinate can be measured online after the camera moves. The computer simulation verifies the effectiveness of the extrinsic parameters calibration method using a single control point. The quantitative results demonstrate that the standard deviation of the focal length of the camera does not exceed 0.028 mm, and the mobile camera’s pitch angle and yaw angle estimated by a single control point is extremely close to the reference values. In addition, the average error of the 3D coordinate on each axis after the camera moves is smaller than 0.08 m in the measuring distance of 100 m, and that on X-axis and Z-axis is comparable and does not exceed 0.35 m. The proposed methods are suitable for the occasions that high accuracy is not required in the field of 3D coordinate measurement in large FOV. Keywords: Mobile stereo vision system | Variable baseline distance | Initial parameters | Extrinsic parameters | Large field of view |
مقاله انگلیسی |