A novel approach to the dynamic response analysis of Euler-Bernoulli beams resting on a Winkler soil model and subjected to impact loads

This work presents a novel approach to the dynamic response analysis of a Euler-Bernoulli beam resting on a Winkler soil model and subjected to an impact loading.The approach considers that damping has much less importance in controlling the maximum response to impulsive loadings because the maximum response is reached in a very short time,before the damping forces can dissipate a significant portion of the energy input into the system.The development of two sine series solutions,relating to different types of impulsive loadings,one involving a single concentrated force and the other a distributed line load,are presented.This study revealed that when a simply supported Euler-Bernoulli beam,resting on a Winkler soil model,is subject to an impact load,the resulting vertical displacements,bending moments and shear forces produced along the span of the beam are considerably affected.In particular,the quantification of this effect is best observed,relative to the corresponding static solution,via an amplification factor.The computed impact amplification factors,for the sub-grade moduli used in this study,were in magnitude greater than 2,thus confirming the multiple-degree-of-freedom nature of the problem.

A Galaxy Image Augmentation Method Based on Few-shot Learning and Generative Adversarial Networks

Galaxy morphology classifications based on machine learning are a typical technique to handle enormous amounts of astronomical observation data,but the key challenge is how to provide enough training data for the machine learning models.Therefore this article proposes an image data augmentation method that combines few-shot learning and generative adversarial networks.The Galaxy10 DECaLs data set is selected for the experiments with consistency,variance,and augmentation effects being evaluated.Three popular networks,including AlexNet,VGG,and ResNet,are used as examples to study the effectiveness of different augmentation methods on galaxy morphology classifications.Experiment results show that the proposed method can generate galaxy images and can be used for expanding the classification model’s training set.According to comparative studies,the best enhancement effect on model performance is obtained by generating a data set that is 0.5–1 time larger than the original data set.Meanwhile,different augmentation strategies have considerably varied effects on different types of galaxies.FSL-GAN achieved the best classification performance on the ResNet network for In-between Round Smooth Galaxies and Unbarred Loose Spiral Galaxies,with F1 Scores of 89.54%and 63.18%,respectively.Experimental comparison reveals that various data augmentation techniques have varied effects on different categories of galaxy morphology and machine learning models.Finally,the best augmentation strategies for each galaxy category are suggested.

Functionally graded structure of a nitride-strengthened Mg_(2)Si-based hybrid composite

The ex-situ incorporation of the secondary SiC reinforcement,along with the in-situ incorporation of the tertiary and quaternary Mg_(3)N_(2) and Si_(3)N_(4) phases,in the primary matrix of Mg_(2)Si is employed in order to provide ultimate wear resistance based on the laser-irradiation-induced inclusion of N_(2) gas during laser powder bed fusion.This is substantialized based on both the thermal diffusion-and chemical reactionbased metallurgy of the Mg_(2)Si–SiC/nitride hybrid composite.This study also proposes a functional platform for systematically modulating a functionally graded structure and modeling build-direction-dependent architectonics during additive manufacturing.This strategy enables the development of a compositional gradient from the center to the edge of each melt pool of the Mg_(2)Si–SiC/nitride hybrid composite.Consequently,the coefficient of friction of the hybrid composite exhibits a 309.3%decrease to–1.67 compared to–0.54 for the conventional nonreinforced Mg_(2)Si structure,while the tensile strength exhibits a 171.3%increase to 831.5 MPa compared to 485.3 MPa for the conventional structure.This outstanding mechanical behavior is due to the(1)the complementary and synergistic reinforcement effects of the SiC and nitride compounds,each of which possesses an intrinsically high hardness,and(2)the strong adhesion of these compounds to the Mg_(2)Si matrix despite their small sizes and low concentrations.

Galaxy Morphology Classification Using a Semi-supervised Learning Algorithm Based on Dynamic Threshold

Machine learning has become a crucial technique for classifying the morphology of galaxies as a result of the meteoric development of galactic data.Unfortunately,traditional supervised learning has significant learning costs since it needs a lot of labeled data to be effective.FixMatch,a semi-supervised learning algorithm that serves as a good method,is now a key tool for using large amounts of unlabeled data.Nevertheless,the performance degrades significantly when dealing with large,imbalanced data sets since FixMatch relies on a fixed threshold to filter pseudo-labels.Therefore,this study proposes a dynamic threshold alignment algorithm based on the FixMatch model.First,the class with the highest amount has its reliable pseudo-label ratio determined,and the remaining classes'reliable pseudo-label ratios are approximated in accordance.Second,based on the predicted reliable pseudo-label ratio for each category,it dynamically calculates the threshold for choosing pseudo-labels.By employing this dynamic threshold,the accuracy bias of each category is decreased and the learning of classes with less samples is improved.Experimental results show that in galaxy morphology classification tasks,compared with supervised learning,the proposed algorithm significantly improves performance.When the amount of labeled data is 100,the accuracy and F1-score are improved by 12.8%and 12.6%,respectively.Compared with popular semisupervised algorithms such as FixMatch and MixMatch,the proposed algorithm has better classification performance,greatly reducing the accuracy bias of each category.When the amount of labeled data is 1000,the accuracy of cigar-shaped smooth galaxies with the smallest sample is improved by 37.94%compared to FixMatch.

Gully erosion mapping susceptibility in a Mediterranean environment: A hybrid decision-making model

Gully erosion is one of the main natural hazards,especially in arid and semi-arid regions,destroying ecosystem service and human well-being.Thus,gully erosion susceptibility maps(GESM)are urgently needed for identifying priority areas on which appropriate measurements should be considered.Here,we proposed four new hybrid Machine learning models,namely weight of evidence-Multilayer Perceptron(MLP-WoE),weight of evidence–K Nearest neighbours(KNN-WoE),weight of evidence-Logistic regression(LR-WoE),and weight of evidence-Random Forest(RF-WoE),for mapping gully erosion exploring the opportunities of GIS tools and Remote sensing techniques in the El Ouaar watershed located in the Souss plain in Morocco.Inputs of the developed models are composed of the dependent(i.e.,gully erosion points)and a set of independent variables.In this study,a total of 314 gully erosion points were randomly split into 70%for the training stage(220 gullies)and 30%for the validation stage(94 gullies)sets were identified in the study area.12 conditioning variables including elevation,slope,plane curvature,rainfall,distance to road,distance to stream,distance to fault,TWI,lithology,NDVI,and LU/LC were used based on their importance for gully erosion susceptibility mapping.We evaluate the performance of the above models based on the following statistical metrics:Accuracy,precision,and Area under curve(AUC)values of receiver operating characteristics(ROC).The results indicate the RF-WoE model showed good accuracy with(AUC=0.8),followed by KNN-WoE(AUC=0.796),then MLP-WoE(AUC=0.729)and LR-WoE(AUC=0.655),respectively.Gully erosion susceptibility maps provide information and valuable tool for decision-makers and planners to identify areas where urgent and appropriate interventions should be applied.

Realizing high thermoelectric performance flexible free-standing PEDOT:PSS/Bi_(0.5)Sb_(1.5)Te_(3)composite films for power generation

Flexible thermoelectrics provide a distinct solution for developing sustainable and portable power supplies.Inorganic/organic material compositing is an effective strategy to induce a significant enhancement of thermoelectric(TE)performance.However,the poor electrical performance of inorganic/organic material is attributed to the poor carrier transport between organic/inorganic interfaces induced by the low contribution of composited inorganic materials.Herein,we prepared a high room temperature figure-of-merit(ZT)value of~0.19 and high bending resistance(surviving 1200 bending cycles at the bending radius of 16.5 mm)of p-type poly(3,4-ethylenedioxy thiophene):poly(4-styrenesulfonate)(PEDOT:PSS)/Bi_(0.5)Sb_(1.5)Te_(3)free-standing composite film via a facile vacuum-as sis ted filtration approach.Compositing Bi_(0.5)Sb_(1.5)Te_(3)nano-spherical particles into PEDOT:PSS results in the optimized interfacial contact and carrier concentration,leading to a high Seebeck coefficient of~43.79μV·K^(-1).Accordingly,a high-power factor of~1.52μW·cm^(-1)·K^(-2)is achieved in the PEDOT:PSS/Bi_(0.5)Sb_(1.5)Te_(3)composite film at room temperature.In addition,the PEDOT:PSS/Bi_(0.5)Sb_(1.5)Te_(3)interfaces with phase boundaries,nanograins and point defects could further decrease the thermal conductivity to~0.20 W·m^(-1)K^(-1),leading to a high ZT value.Furthermore,a 6-leg freestanding film device was assembled,which provided an output power of 44.94 nW.This study demonstrates that free-standing organic/inorganic composite films are effective power sources for wearable electronic products.

Sand transport in multiphase flow mixtures in a horizontal pipeline:An experimental investigation

An inherent problem with both oil and natural gas production is the deposition of sand particles in pipeline,which could lead to problems such as excessive pressure drops,equipment failure,pipeline erosion,and production decline.The characterization of sand particles transport and sedimentation in different flow systems such as sandemultiphase mixtures is vital to predict the sand transport velocity and entrainment processes in oil and gas transportation pipelines.However,it seems that no model exists able to accurately characterize the sand transport and deposition in multiphase pipeline.In fact,in the last decade several researchers tried to extend the modeling of liquid-solid flow to gas-liquid-solid flow,but no significant results have been obtained,especially in slug flow condition due to the complexity of the phenomenon.In order to develop and validate a mathematical model properly formulated for the calculation of the sand critical deposition velocity in gas-liquid flow,more and more experimental data are necessary.This paper presents a preliminary experimental study of three phase flows(air-water-sand)inside a horizontal pipe and the application of the sand-liquid models present in literature.Significant observations were made during the experimental study from which several conclusions were drawn.Different sand flow regimes were established by physical observation and data analysis:fully dispersed solid flow,moving dunes and stationary bed.The critical deposition velocities were determined at different sand concentrations.It was concluded that sand transport characteristics and the critical deposition velocity are strongly dependent on the gas-liquid flow regime and on sand concentration.

Drought Stress Induces Flowering and Enhances Carbohydrate Accumulation in Averrhoa Carambola

Star fruit(Averrhoa carambola)is an important fruit tree in tropical and subtropical Asia.The tree blooms several times and fruits accordingly within one year.Controlling the flowering time and understanding the physiological mechanism of the induction of floral buds in A.carambola are indispensable to the industry.In this study,A.carambola potted trees were subjected to drought stress in a growth chamber.To avoid excessive drought stress and leaf abscission,trees were watered every 7 d and were sprayed with water every 2 d.The flowering rate was recorded,and the carbohydrate contents of the leaves,phloem,and xylem tissues were determined during the treatment and after re-watering.The results showed that drought stress increased the flowering rate in both drooping and water shoots,increased the relative conductivity,decreased the relative water content(RWC)of leaves.The total soluble sugar,sucrose,fructose,and glucose in leaves of the drooping shoots were increased.The starch contents in the xylem of both drooping and water shoots were also increased by the treatment.The results indicated that drought stress enhances carbohydrate accumulation in A.carambola.This study provides a potential way by water control to induce flowering without chemical in A.carambola.