The increased demand for superior materials has highlighted the need of investigating the mechanical properties of composites to achieve enhanced constitutive relationships.Fiber-reinforced polymer composites have eme...The increased demand for superior materials has highlighted the need of investigating the mechanical properties of composites to achieve enhanced constitutive relationships.Fiber-reinforced polymer composites have emerged as an integral part of materials development with tailored mechanical properties.However,the complexity and heterogeneity of such composites make it considerably more challenging to have precise quantification of properties and attain an optimal design of structures through experimental and computational approaches.In order to avoid the complex,cumbersome,and labor-intensive experimental and numerical modeling approaches,a machine learning(ML)model is proposed here such that it takes the microstructural image as input with a different range of Young’s modulus of carbon fibers and neat epoxy,and obtains output as visualization of the stress component S11(principal stress in the x-direction).For obtaining the training data of the ML model,a short carbon fiberfilled specimen under quasi-static tension is modeled based on 2D Representative Area Element(RAE)using finite element analysis.The composite is inclusive of short carbon fibers with an aspect ratio of 7.5that are infilled in the epoxy systems at various random orientations and positions generated using the Simple Sequential Inhibition(SSI)process.The study reveals that the pix2pix deep learning Convolutional Neural Network(CNN)model is robust enough to predict the stress fields in the composite for a given arrangement of short fibers filled in epoxy over the specified range of Young’s modulus with high accuracy.The CNN model achieves a correlation score of about 0.999 and L2 norm of less than 0.005 for a majority of the samples in the design spectrum,indicating excellent prediction capability.In this paper,we have focused on the stage-wise chronological development of the CNN model with optimized performance for predicting the full-field stress maps of the fiber-reinforced composite specimens.The development of such a robust and efficient algorithm would significantly reduce the amount of time and cost required to study and design new composite materials through the elimination of numerical inputs by direct microstructural images.展开更多
Objective To observe the effects of repeated subconvulsive electrical stimuli to the hippocampus on the emotional behavior and spatial learning and memory ability in rats.Methods One hundred and eight male Wistar rats...Objective To observe the effects of repeated subconvulsive electrical stimuli to the hippocampus on the emotional behavior and spatial learning and memory ability in rats.Methods One hundred and eight male Wistar rats were randomized into 3 groups. Animals in group SE (n = 42) were given subconvulsive electrical stimulation to the hippocampus through a constant pulsating current of 100 μA with an intratrain frequency of 25 Hz, pulse duration of 1 millisecond, train duration of 10 seconds and interstimulus interval of 7 minutes, 8 times a day, for 5 days. In the electrode control group or CE group (n = 33), animals were implanted with an electrode in the hippocampus, but were not stimulated. Group NC (n =33) animals received no electrode or any stimulation. The emotional behavior of experimental rats was examined by activity in an unfamiliar open field and resistance to capture from the open field, while the spatial learning and memory ability was measured during training in a Morris water maze.Results The stimulated rats tested 1 month after the last round of stimulation displayed substantial decreases in open field activity (scale: 10. 4±2. 3, P<0. 05) and increases in resistance to capture (scale: 2. 85±0. 56, P < 0. 01 ). The amount of time for rats in group SE to find the platform (latency) as a measurement for spatial bias was prolonged (29±7) seconds after 15 trials in the water maze, P<0. 05). The experimental rats swam aimlessly in all four pool quadrants during the probe trial in the Morris water maze.Conclusions Following repeated subconvulsive electrical stimuli to the hippocampus, rats displayed long-lasting significant abnormalities in emotional behavior, increased anxiety and defensiveness, enhanced ease to and delayed habituation to startlement, transitory spatial learning and memory disorder, which parallels many of the symptoms in posttraumatic stress disorder patients.展开更多
基金financial support received from DST-SERBSRG/2020/000997,Indiathe initiation grant received from IIT Kanpur。
文摘The increased demand for superior materials has highlighted the need of investigating the mechanical properties of composites to achieve enhanced constitutive relationships.Fiber-reinforced polymer composites have emerged as an integral part of materials development with tailored mechanical properties.However,the complexity and heterogeneity of such composites make it considerably more challenging to have precise quantification of properties and attain an optimal design of structures through experimental and computational approaches.In order to avoid the complex,cumbersome,and labor-intensive experimental and numerical modeling approaches,a machine learning(ML)model is proposed here such that it takes the microstructural image as input with a different range of Young’s modulus of carbon fibers and neat epoxy,and obtains output as visualization of the stress component S11(principal stress in the x-direction).For obtaining the training data of the ML model,a short carbon fiberfilled specimen under quasi-static tension is modeled based on 2D Representative Area Element(RAE)using finite element analysis.The composite is inclusive of short carbon fibers with an aspect ratio of 7.5that are infilled in the epoxy systems at various random orientations and positions generated using the Simple Sequential Inhibition(SSI)process.The study reveals that the pix2pix deep learning Convolutional Neural Network(CNN)model is robust enough to predict the stress fields in the composite for a given arrangement of short fibers filled in epoxy over the specified range of Young’s modulus with high accuracy.The CNN model achieves a correlation score of about 0.999 and L2 norm of less than 0.005 for a majority of the samples in the design spectrum,indicating excellent prediction capability.In this paper,we have focused on the stage-wise chronological development of the CNN model with optimized performance for predicting the full-field stress maps of the fiber-reinforced composite specimens.The development of such a robust and efficient algorithm would significantly reduce the amount of time and cost required to study and design new composite materials through the elimination of numerical inputs by direct microstructural images.
基金This study was supported by grants from the National Natural Science Foundation of China (No. 39870284) and the Tenth Five-Year Plan for Medical Projects of PLA (No. 01L028).
文摘Objective To observe the effects of repeated subconvulsive electrical stimuli to the hippocampus on the emotional behavior and spatial learning and memory ability in rats.Methods One hundred and eight male Wistar rats were randomized into 3 groups. Animals in group SE (n = 42) were given subconvulsive electrical stimulation to the hippocampus through a constant pulsating current of 100 μA with an intratrain frequency of 25 Hz, pulse duration of 1 millisecond, train duration of 10 seconds and interstimulus interval of 7 minutes, 8 times a day, for 5 days. In the electrode control group or CE group (n = 33), animals were implanted with an electrode in the hippocampus, but were not stimulated. Group NC (n =33) animals received no electrode or any stimulation. The emotional behavior of experimental rats was examined by activity in an unfamiliar open field and resistance to capture from the open field, while the spatial learning and memory ability was measured during training in a Morris water maze.Results The stimulated rats tested 1 month after the last round of stimulation displayed substantial decreases in open field activity (scale: 10. 4±2. 3, P<0. 05) and increases in resistance to capture (scale: 2. 85±0. 56, P < 0. 01 ). The amount of time for rats in group SE to find the platform (latency) as a measurement for spatial bias was prolonged (29±7) seconds after 15 trials in the water maze, P<0. 05). The experimental rats swam aimlessly in all four pool quadrants during the probe trial in the Morris water maze.Conclusions Following repeated subconvulsive electrical stimuli to the hippocampus, rats displayed long-lasting significant abnormalities in emotional behavior, increased anxiety and defensiveness, enhanced ease to and delayed habituation to startlement, transitory spatial learning and memory disorder, which parallels many of the symptoms in posttraumatic stress disorder patients.
