Browse Topic: Fabrication

Items (2,771)
With the increasing complexity of traffic conditions, the computational burden of multi-object tracking algorithms has grown, making it difficult to meet the requirements for tracking accuracy and real-time performance. In this paper, we proposed a road vehicle multi-object tracking method by improving and optimizing the YOLOv5 detection algorithm and the DeepSORT tracking algorithm. A Channel Attention(CA) mechanism is introduced into the existing YOLOv5 algorithm to construct the fusion algorithm CA-YOLOv5, and the feature extraction network structure of YOLOv5 is reconstructed by adding a prediction layer to improve the accuracy of vehicle detection. The ReID (Re-identification) network in DeepSORT algorithm is adopted as ResNet neural network to construct the fusion algorithm ResNet-DeepSORT. And it combined with data and feature enhancement, as well as high accuracy detection results of road vehicles. Thus, it improves the tracking accuracy and reduces the number of ID jumps to
Bo, LiuJing, WuYanping, ZhouJing, Li
The rapid development of civil aviation industry makes it difficult for traditional flight scheduling methods to cope with the increasingly complex air transport demand. In this study, an AI-based civil aviation transportation scheduling optimisation system is designed, integrating a novel deep reinforcement learning framework with a validated multimodal fusion algorithm (MMFA) to address spatiotemporal dependencies in aviation data to construct the core architecture of the system. Measurement results show that the system effectively reduces the average flight delay time by 58.1%, improves the slot utilisation rate by 21.3%, increases the flight punctuality rate to 93.7%, and shortens the response time to emergencies by 62.5%. The high performance and significant economic benefits demonstrated by the system in the real environment provide a feasible solution for the intelligent upgrading of civil aviation transport.
Li, Mohan
Objective:Methods:Conclusion:
Dai, HongzhouLi, JianZhao, DiLiu, Haoran
In order to better understand the development level and the degree of development of the transportation network in different areas of the Hexi Corridor, the accessibility of the transportation network in the Hexi Corridor is studied. Firstly, calculate the road density of each county and district in the Hexi Corridor. Then, in view of the topographic characteristics of the Hexi Corridor, introduce the shortest travel time and travel cost into the gravity model, consider the accessibility of both road and railway transportation modes between nodes, construct a comprehensive accessibility model, and analyze the spatial characteristics of the comprehensive accessibility of each county and district in the Hexi Corridor. Secondly, the gravitational model is used to analyze the economic connection intensity among the counties and districts in the Hexi Corridor. Finally, calculate the Gini coefficient, draw the Lorenz curve, and analyze the fairness of the comprehensive accessibility of the
Jiang, PingMu, HaiboPeng, Zhiwei
The market-oriented reform of railway coal transport price is a key initiative to optimize the transport structure and enhance the railway’s market share in coal transport. Based on the competitive relationship between road and railway, this paper explores the impact of the floating pricing mechanism of railway coal transport on the allocation of capacity and enterprise benefits. Firstly, we construct a model to consider the selection behaviour of highway and railway freight transport modes to reveal shippers’ choice of coal transport modes, and analyse shippers’ preference for highway and railway based on transport cost, timeliness and price elasticity; secondly, we combine railway coal transport clearing rules with market-oriented floating pricing policy, establish a pricing decision model with the goal of optimizing transport volume and carrier revenue, and quantify the full railway tariff, transport time and volume, surplus and so on. Secondly, we establish a pricing decision model
Liu, LiYang, LeiCai, Zhenghong
Railway is a key component driving innovation and sustainability in transportation systems. Aiming at solving the problems of metal reflection, oil contamination and complex background interference in railway wheel tread defect detection, this paper will focus on the railway wheel tread defect detection method, SEN-YOLO, based on the YOLOv5s and the comparison between different generations of YOLO detection. To better adapt the model to actual detection scenarios, multi-stage dynamic data augmentation strategy combining illumination robustness optimization and motion blur simulation is designed to construct a railway wheel dataset that closely mirrors real-world conditions. In terms of model architecture, the YOLOv5s-based approach integrates the Squeeze-and-Excitation Networks (SENets) module to enhance the capture of minor defect features and employs an adaptive feature fusion strategy to mitigate background noise. To further improve detection accuracy and generalization, the YOLOv5s
You, LijieMo, YayelinTu, JingjieZhou, Hang
In order to determine the ranking of factors affecting passengers’ evaluation of the aircraft cabin, a cabin evaluation system for aircraft was constructed by studying domestic and foreign literature. Taking the aircraft cabin as the research object, the Analytic Hierarchy Process (AHP) is used to construct an aircraft cabin evaluation system consisting of 3 primary indicators and 15 secondary indicators. The comprehensive weights of each indicator are determined through a combination of qualitative and quantitative research methods, providing important references for aircraft cabin design.
Cai, Ruihong
This paper integrates the theoretical models of Transformer and BiGRU to construct the Transformer BiGRU Global Attention model, with the aim of enhancing the model’s ability to extract key information. Through the implementation of a cross-attention mechanism to amalgamate features and enhance feature representation, the model attains exact prediction of main engine fuel consumption for vessels. Compared to the Transformer and BiGRU models, our model achieves 86% higher prediction accuracy, enabling more accurate prediction of ship main engine fuel consumption. This furnishes data support for the purpose of comparison with original factory data, thereby facilitating the assessment of engine fault conditions.
Liu, ZicongZhang, DefuLv, HongbinZhu, Wei
With the rapid development of metro network operation, metro passenger flow congestion propagation occurs frequently. Accurately modeling passenger flow congestion propagation is crucial for alleviating metro passenger flow congestion and formulating corresponding control strategies. Traditional modeling methods struggle to effectively capture the complex spatiotemporal dependency relationships in metro networks. To improve the accuracy of congestion propagation modeling, this paper proposes a Dynamic Spatiotemporal Graph Convolutional Network (DSTGCN). The model integrates node attributes and temporal encoding through a dynamic adjacency matrix generation module, uses multi-head attention mechanisms to adaptively learn the time-varying propagation intensity between nodes, and combines static topology to construct dynamic adjacency matrices. A multi-scale spatiotemporal feature extraction module is designed, employing temporal convolution and spatial attention mechanisms to mine
Chen, BeijiaWang, JunhangShao, Jiayu
NASA has developed a novel approach for macroscale biomaterial production by combining synthetic biology with 3D printing. Cells are biologically engineered to deposit desired materials, such as proteins or metals, derived from locally available resources. The bioengineered cells build different materials in a specified 3D pattern to produce novel microstructures with precise molecular composition, thickness, print pattern, and shape. Scaffolds and reagents can be used for further control over material product. This innovation provides modern design and fabrication techniques for custom-designed organic or organic-inorganic composite biomaterials produced from limited resources.
In the electrical machines, detrimental effects resulted often due to the overheating, such as insulation material degradation, demagnetization of the magnet and increased Joule losses which result in decreased lifetime, and reduced efficiency of the motor. Hence, by effective cooling methods, it is vital to optimize the reliability and performance of the electric motors and to reduce the maintenance and operating costs. This study brings the analysis capability of CFD for the air-cooling of an Electric-Motor (E-Motor) powering on Deere Equipment's. With the aggressive focus on electrification in agriculture domain and based on industry needs of tackling rising global warming, there is an increasing need of CFD modeling to perform virtual simulations of the E-Motors to determine the viability of the designs and their performance capabilities. The thermal predictions are extremely vital as they have tremendous impact on the design, spacing and sizes of these motors.
Singh, BhuvaneshwarTirumala, BhaskarBadgujar, SwapnilHK, Shashikiran
With the global increase in demand for construction equipment, companies face immense pressure to produce more products in a competitive and sustainable way by utilizing advanced manufacturing technologies. Additionally, the need for data analytics and Industry 4.0 is increasing to take better decisions early in the development cycles and during the production phase. Advanced manufacturing processes & adopting Industry 4.0 is the only viable solution to address these challenges. However, the implementation of advanced manufacturing processes in heavy fabrication and construction equipment factories has been slow. A significant challenge is that the products being produced were originally designed for conventional manufacturing processes. When factories are becoming smart and connected through Industry 4.0 solutions, companies must reconsider many established assumptions about advanced manufacturing processes and their benefits. To maximize efficiency gains, improve safety standards
Bhorge, PankajSaseendran, UnnikrishnanRodge, Someshwar
Innovators at NASA Johnson Space Center have developed additively manufactured thermal protection system (AMTPS) comprised of two printable heat shield material formulations. These formulations are directly applied by 3D printer or other robotic extrusion system and bonded to a spacecraft to devise a heat shield suitable for atmospheric entry. This technology could significantly decrease heat shield or thermal protection system (TPS) fabrication cost and time.
Target tracking is an important component of intelligent vehicle perception systems, which has outstanding significance for the safety and efficiency of intelligent vehicle driving. With the continuous improvement of technologies such as computer vision and deep learning, detection based tracking has gradually become the mainstream target tracking framework in the field of intelligent vehicles, and target detection performance is the key factor determining its tracking performance. Although remarkable progress has been made in current 3D object detection networks, a single network still struggles to provide stable detection for distant and occluded targets. Besides, traditional tracking methods are based on single-stage association matching, which can easily lead to identity jumps and target loss in case of missed detections, resulting in poor overall stability of the tracking algorithm. To solve the above problem, a hierarchical association matching method using a dual object
Wu, ShaobinChu, YunfengLi, YixuanSu, ShengjieLiu, ZhaofengLi, XiaoanSi, Lingrui
The assessment of collision risks is crucial for effective risk control and scientific management of maritime safety. To prevent maritime transportation accidents, an accident causation model has been proposed to analyze risks in maritime transportation systems. The 24-model further analyzes the impact pathways of accident factors in the accident chain and calculates the fit of HOF-related factors. Using Bayesian Networks as a foundation and the 24-model as a tool, a Bayesian Network model for collision risk is constructed by identifying risk factors and determining their correlations, utilizing accident data from Chinese maritime authorities. Utilizing a Bayesian Network to construct a ship collision risk model that couples HOF and calculates conditional probabilities of relevant node occurrences. To explore the coupled relationships between nodes in a network, this study employs the N-K model to construct a safety risk coupling model for ship collision accidents, calculating risk
Li, JianminZhang, XiaochuanJia, DaweiZang, RuLyu, Hongguang
A research team led by scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) has developed a new fabrication technique that could improve noise robustness in superconducting qubits, a key technology for enabling large-scale quantum computers.
Through the Artemis campaign, NASA will send astronauts on missions to and around the Moon. The agency and its international partners report progress continues on Gateway, the first space station that will permanently orbit the Moon, after visiting the Thales Alenia Space facility in Turin, Italy, where initial fabrication for one of two Gateway habitation modules is nearing completion.
The scope of this SAE Aerospace Recommended Practice (ARP) is to establish the procedure for creating titles of aerospace tubing and clamp installation documents generated by SAE Subcommittee G-3E.
G-3, Aerospace Couplings, Fittings, Hose, Tubing Assemblies
Aqueous zinc-ion batteries (ZIBs) have attracted extensive attention due to their high safety, abundant reserves, and environmental friendliness. Iodine with high abundance in seawater (55 μg L-1) is highly promising for fabricating zinc-iodine batteries due to its high theoretical capacity (211 mAh g-1) and appropriate redox potential (0.54V). However, the low electrical conductivity of iodine hinders the redox conversion for an efficient energy storage process with zinc. Additionally, the formed soluble polyiodides are prone to migrate to the Zn anode, leading to capacity degradation and Zn corrosion.
In this work, Genetic Algorithm (GA) optimized Proportional Integral Derivative (PID) controller is employed in the active suspension. The PID gain values are optimally tuned based on the objective function by the Integral Time Absolute Error (ITAE) criteria of various suspension measures like vehicle body displacement, suspension and tire deflections. The proposed GAPID controller is experimentally validated through the 3-DOF quarter-car (QC) test rig model. The fabricated model with passive suspension system (PASS) and active suspension system (ACSS) with an electrical actuator is presented. The schematic representation of the fabricated test set-up with and without ACSS is also illustrated. Further, simulation and experimental response of the fabricated model with and without ACSS are compared. It is identified that the proposed GAPID controller attenuates the sprung mass acceleration by about 41.64 % and 29.13 % compared with PASS for the theoretical as well as experimental cases
A, ArivazhaganKandavel, Arunachalam
The mass production of conventional silicon chips relies on a successful business model with large “semiconductor fabrication plants” or “foundries.” New research by KU Leuven and imec shows that this “foundry” model can also be applied to the field of flexible, thin-film electronics. Adopting this approach would give innovation in the field a huge boost.
MEMS is a more complex technology than traditional semiconductors. They are 3D structures with moving parts, making them much more difficult to fabricate. If you’re designing a semiconductor, you may be able to take advantage of an existing process development kit (PDK), which your foundry can provide to you. There is no equivalent approach in MEMS. It’s a “one process, one product” paradigm that requires a high level of customization. That takes time, money, and resources.
The metal inert-gas (MIG) welding technique employed for aluminum alloy automotive bumpers involve a complex thermo-mechanical coupling process at elevated temperatures. Attaining a globally optimal set of model parameters continues to represent a pivotal objective in the pursuit of reliable constitutive models that can facilitate precise simulation of the welding process. In this study, a novel piecewise modified Johnson-Cook (MJ-C) constitutive model that incorporates the strain-temperature coupling has been proposed and developed. A quasi-static uniaxial tensile model of the specimen is constructed based on ABAQUS and its secondary development, with model parameters calibrated via the second-generation non-dominated sorting genetic algorithm (NSGA-II) method. A finite element simulation model for T-joint welding is subsequently established, upon which numerical simulation analyses of both the welding temperature field and post-welding deformation can be conducted. The results
Yi, XiaolongMeng, DejianGao, Yunkai
3D-printed microscopic particles, so small that to the naked eye they look like dust, have applications in drug and vaccine delivery, microelectronics, microfluidics, and abrasives for intricate manufacturing. However, the need for precise coordination between light delivery, stage movement, and resin properties makes scalable fabrication of such custom microscale particles challenging. Now, researchers at Stanford University have introduced a more efficient processing technique that can print up to 1 million highly detailed and customizable microscale particles a day.
Purdue University material engineers have created a patent-pending process to develop ultrahigh-strength aluminum alloys that are suitable for additive manufacturing because of their plastic deformability.
Since the rapid development of the shipping and port industries in the second half of the twentieth century, the introduction of container technology has transformed cargo management systems, while simultaneously increasing the vulnerability of global shipping networks to natural disasters and international conflicts. To address this challenge, the study leverages AIS data sourced from the Vessel Traffic Data website to extract ship stop trajectories and construct a shipping network. The constructed network exhibits small-world characteristics, with most port nodes having low degree values, while a few ports possess extremely high degree values. Furthermore, the study improved the PageRank algorithm to assess the importance of port nodes and introduced reliability theory and risk assessment theory to analyze the failure risks of port nodes, providing new methods and perspectives for analyzing the reliability of the shipping network.
Li, DingCheng, ChengZhao, XingxiLi, Zengshuang
Shared autonomous vehicles systems (SAVS) are regarded as a promising mode of carsharing service with the potential for realization in the near future. However, the uncertainty in user demand complicates the system optimization decisions for SAVS, potentially interfering with the achievement of desired performance or objectives, and may even render decisions derived from deterministic solutions infeasible. Therefore, considering the uncertainty in demand, this study proposes a two-stage robust optimization approach to jointly optimize the fleet sizing and relocation strategies in a one-way SAVS. We use the budget polyhedral uncertainty set to describe the volatility, uncertainty, and correlation characteristics of user demand, and construct a two-stage robust optimization model to identify a compromise between the level of robustness and the economic viability of the solution. In the first stage, tactical decisions are made to determine autonomous vehicle (AV) fleet sizing and the
Li, KangjiaoCao, YichiZhou, BojianWang, ShuaiqiYu, Yaofeng
This study investigates the fabrication and characterization of overhanging structures using the Cold Metal Transfer (CMT) pulse based Wire Arc Additive Manufacturing (WAAM) technique, specifically targeting automotive applications on commercial aluminum components. Focusing on optimal welding strategies for overhanging structures, components are fabricated by providing offsets during consecutive deposition of layers, thus producing parts with angles of 45°, 60° and 90° inclinations from the substrate. Three specimens undergo around twenty-five layers of deposition, resulting in structurally sound joints within this specified angle range. AA 4043 electrode is utilized, and welding parameters are optimized through trials by verifying with bead on plate deposition. Successful outcomes are achieved within the specified angle range, though challenges arise beyond 60°, complicating the maintenance of desired weld quality. The study further evaluates the microstructure, microhardness, and
A, AravindS, JeromeA, Rahavendran
Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has emerged as a revolutionary method for fabricating complex geometries using a variety of materials. Polyethylene terephthalate glycol (PETG) is a thermoplastic material that is biodegradable and environmentally friendly, making it a preferred choice in additive manufacturing (AM) due to its affordability and ease of use. This study aims to optimize the FDM settings for PETG material and investigate the impact of key process parameters on printing performance. An experimental study was conducted to evaluate the influence of crucial factors in FDM, including layer thickness, infill density, printing speed, and nozzle temperature, on significant outcomes such as dimensional accuracy, surface quality, and mechanical properties. The use of the Grey Relational Analysis (GRA) approach enabled a systematic assessment of multi-performance characteristics, facilitating the optimization of the FDM process. The findings
Pasupuleti, ThejasreeNatarajan, ManikandanKumar, VKiruthika, JothiKatta, Lakshmi NarasimhamuSilambarasan, R
Soft-bending actuators are gaining considerable attention in robotics for handling delicate objects and adapting to complex shapes, making them ideal for biomimetic robots. Soft pneumatic actuators (SPAs) are preferred in soft robotics because to their safety and compliance characteristics. Using negative pressure for actuation, it enhances stability by reducing the risk of sudden or unintended movements, crucial for delicate handling and consistent performance. Negative pressure actuation is more energy-efficient, safe and are less prone to leakage, increasing reliability and durability. This paper involves development of a new soft pneumatic actuator design by comparing various designs and to determine its performance parameters. This paper depicts on designing, and fabricating flexible soft pneumatic actuators working under negative pressure for soft robotic applications. The material used for fabrication was liquid silicone rubber and uniaxial tensile tests were conducted to
Warriar J S, SreejithSadique, AnwarGeorge, Boby
A novel sintering method of bridging the two mechanically polished and oriented single-crystals together face-to-face in a non- environmental controlled atmosphere to fabricate the bicrystal substrate of NaCl of macroscopic thickness, with a common zone axis and having planarity over large areas, has been developed. Epitaxial [001] bicrystalline thin face-centered cubic (fcc) metal film of surface-reactive metal-containing tilt grain boundary across the interface is first grown in high vacuum directly by flash deposition on initially fabricated [001] oriented bicrystalline substrate of NaCl. The [001] tilt boundary, thus produced, and is examined by electron microscopy to characterize grain boundary morphology and structure. The findings of some preliminary investigations are then presented. A distinct atomic structure is observed for 310 and 210 inclination. Both HAADF-STEM and Diffraction images reveal that such fabricated high-angle grain boundary accommodates minor deviations from
Dish, NilabhGautam, AbhayBehera, RakeshBanka, HemasunderChavan, Pradeep
Nowadays, there are many technologies emerging like firefighting robots, quadcopters, and drones which are capable of operating in hazardous disaster scenarios. In recent years, fire emergencies have become an increasingly serious problem, leading to hundreds of deaths, thousands of injuries, and the destruction of property worth millions of dollars. According to the National Crime Records Bureau (NCRB), India recorded approximately 1,218 fire incidents resulting in 1,694 deaths in 2020 alone. Globally, the World Health Organization (WHO) estimates that fires account for around 265,000 deaths each year, with the majority occurring in low- and middle-income countries. The existing fire-extinguishing systems are often inefficient and lack proper testing, causing significant delays in firefighting efforts. These delays become even more critical in situations involving high-rise buildings or bushfires, where reaching the affected areas is particularly challenging. The leading causes of
Karthikeyan, S.Nithish, U.Sanjay, S.Sibiraj, T.Vishnu, J.
Aluminum Matrix Composites (AMCs) are gaining traction in aerospace, automotive, and marine industries due to their superior mechanical properties. By integrating hard ceramic particles such as silicon carbide (SiC) and aluminum oxide (Al₂O₃) into aluminum matrices, these composites exhibit enhanced wear resistance and strength-to-weight ratios. This study explores the fabrication and characterization of 6061-T6 aluminum alloy matrix composites, reinforced individually with SiC and Al₂O₃ particles through the squeeze casting technique. The research includes a comprehensive analysis of microstructures and mechanical properties, focusing on compressive strength, Brinell hardness, and tribological behavior. Findings reveal that SiC and Al₂O₃ reinforcements boost compressive strength by up to 27% and 47%, respectively, and increase hardness by up to 29% and 20%, respectively, compared to unreinforced aluminum.
Thirumavalavan, R.Santhosh, V.Sugunarani, S.Regupathi, S.Sundaravignesh, S.
From biology, to genetics, and paleontology, these fields share the DNA as a common and time-proven tool. In science, pressure may be such a tool, shared by thermodynamics, material science, and astrophysics, but not by aerodynamics. Pressure is a shorthand for a force acting perpendicular to a surface. When this surface is reduced to zero, so should the pressure. The wing area of an aircraft acts as a reference area to calculate its parasite drag coefficient. In this scenario, the parasite drag acts as a force over the wing area. If the wing area is reduced to zero, its parasite drag does not, as the fuselage is still generating parasite drag. The ratio of the parasite drag and wing area is an example of a pressure construct that uses a physically irrelevant reference area and has no absolute zero. Pressure constructs, more frequently used than pressures in aerodynamics, are a math-based parameter that preserve dimensional propriety according to the Buckingham Pi theorem but lacks a
Burgers, Phillip
Our energy future may depend on high-temperature superconducting (HTS) wires. This technology’s ability to carry electricity without resistance at temperatures higher than those required by traditional superconductors could revolutionize the electric grid and even enable commercial nuclear fusion.
This work pioneers the development of eco-friendly brake pads using coconut fiber and sawdust as reinforcement materials, combined with abrasives and friction modifiers. The innovation lies in the utilization of these natural fibers, which are not only cost-effective and abundantly available but also contribute to the sustainability of brake pad manufacturing. The study aims to explore the feasibility and performance of these organic fibers in brake pad applications. Coconut fiber and sawdust were chosen for their unique properties, such as high strength-to-weight ratio and thermal stability, making them ideal candidates for enhancing brake pad performance. The inclusion of abrasives and friction modifiers further optimizes the braking efficiency and durability of the pads. Comprehensive testing was conducted, including hardness, compression, wear (using a pin-on-disc apparatus), and thermogravimetric analysis (TGA), to thoroughly evaluate the mechanical properties and thermal
Ajay Devan, V.Gunasekar, N.Ravikumar, K.Balaguru, B. A.Deepak, S.
Visual perception systems for autonomous vehicles are exposed to a wide variety of complex weather conditions, among which rainfall is one of the weather conditions with high exposure. Therefore, it is necessary to construct a model that can efficiently generate a large number of images with different rainfall intensities to help test the visual perception system under rainfall conditions. However, the existing datasets either do not contain multilevel rainfall or are synthetic images. It is difficult to support the construction of the model. In this paper, the natural rainfall images of different rainfall intensities were first collected and produced a natural multilevel rain dataset. The dataset includes no rain and three levels (light, medium and heavy) of rainfall with the number of 629, 210, 248 and 193 respectively, totaling 1280 images. The dataset is open source and available online via: https://github.com/raydison/natural-multilevel-rain-dataset-NMRD. Subsequently, a
Liu, ZhenyuanJia, TongXing, XingyuWu, JianfengChen, Junyi
One of the most common materials in the fabrication sectors, especially in the auto sector, is Aluminum alloy. Owing to its low strength to weight ratio, it could be a good fit for a number of applications. The cold working procedure may strengthen the 5XXX series Aluminum alloy, which is not heat treatable and it is also challenging to fuse these alloys together using fusion welding processes. In Recent days, a solid-state welding procedure, Friction Stir Welding (FSW) is used to join this alloy. The impact of FSW process parameters on tensile strength of the joint is examined in this study. Based on the outcomes of the experiment, the highest tensile strength is observed at 900 RPM tool rotation, 100 mm/min welding speed, 1.5-degree tilt angle, and 3.0 tool diameter ratio. Superior strength (246 MPa) of this parameter over its competitors can be attributed to the balanced material flow and the formation of finer grains in the weld region.
Maram, Sreenivasulu ReddyKumar, M. VinothHariram, V.
Hybrid reinforcement-made polypropylene (PP) composites are beneficial over monolithic PP and utilized for various engineering and non-engineering applications. The present investigation of PP hybrid composites is developed with 10 percentages of weight (wt%) of E-glass fiber embedded with 0–6 wt% of silicon carbide via compression technique associated with hot press. E-glass fiber and SiC influencing wear rate, tensile strength, and microhardness behavior of PP and its composites are experimentally investigated. The peak loading of SiC as 6 wt% into PP/10 wt% E-glass fiber is recorded as better wear resistance (0.021 mm3/m), maximum tensile strength value (54.9 MPa), and highest hardness (68 HV). Moreover, the investigation results of hybrid PP composite are better resistance to wear and hiked tensile and hardness behavior compared to monolithic PP. This PP/10 wt% E-glass fiber/6 wt% of SiC hybrid composite is adopted for high-strength to lightweight sports goods applications.
Venkatesh, R.
United States microchip fab plants can cram billions of data-processing transistors onto a tiny silicon chip, but the “clock,” which times the transistors’ operations, must be made separately, which creates a flaw in chip security as well as the supply line. However, a new approach uses commercial chip fab materials and techniques to fabricate specialized transistors to serve as the building block of the timing device.
Human body models have been used for decades to inform efforts in promoting automobile occupant and pedestrian safety. However, many of these models fail to capture the intricacies of individual variability. Cadaveric subjects typically exceed representative age ranges and hence mechanics. Animal subjects typically require specific setups that stray from that which is representative of human crash scenarios. Computational models can only consider so many practical real-world variables. Artificial surrogates, dummies being popular among them, are very popular for reusability and robust data collection. However, even the biomechanically accurate skeletal surrogates available commercially are limited in that they do not consider human variability and skeletal microstructure local variability. The objective of the work herein is to assess computational methods of metastructural variability mimicry by fabrication material. We implement mimicry approaches focusing on bulk isotropic
Hezrony, Benjamin S.C. F. Lopes, PedroBrown, Philip J.
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