Sample Shape Research Articles

Asymmetric sample shapes complicate planar biaxial testing assumptions by intensifying shear strains and stresses

Planar biaxial testing offers a physiologically relevant approach for mechanically characterizing thin deformable soft tissues, but often relies on erroneous assumptions of uniform strain fields and negligible shear strains and forces. In addition to the complex mechanical behavior exhibited by soft tissues, constraints on sample size, geometry, and aspect ratio often restrict sample shape and symmetry. Using simple PDMS gels, we explored the unknown and unquantified effects of sample shape asymmetry on planar biaxial testing results, including shear strain magnitudes, shear forces measured at the sample’s boundary, and the homogeneity of strains experienced at the center of each sample. We used a combination of finite element modeling and experimental validation to examine PDMS gels of varying levels of asymmetry, allowing us to identify effects of sample shape without confounding factors introduced by the nonlinear, spatially variable, and anisotropic properties of soft tissues. Both biaxial simulations and experiments, which showed strong agreement, revealed that sample shape asymmetry led to significantly larger shear strains, shear forces, and overestimation of principal stresses. Excluding these shear forces resulted in an underestimation of shear moduli during inverse mechanical characterizations. Even in the simplest of deformable biomaterials, sample shape asymmetry should be avoided as it can induce drastic increases in shear strains and shear forces, invalidating traditional planar biaxial testing analyses. Alternatively, sample shape asymmetry may be exploited to generate more robust estimates of constitutive parameters in more complex materials, which could lead to a refined understanding and inference of mechanical behavior.

Study on micromechanical behavior and energy evolution of granular material generated by latent diffusion model under rotation of principal stresses

In this study, advanced image processing technology is used to analyze the three-dimensional sand composite image, and the topography features of sand particles are successfully extracted and saved as high-quality image files. These image files were then trained using the latent diffusion model (LDM) to generate a large number of sand particles with real morphology, which were then applied to numerical studies. The effects of particle morphology on the macroscopic mechanical behavior and microscopic energy evolution of sand under complex stress paths were studied in detail, combined with the circular and elliptical particles widely used in current tests. The results show that with the increase of the irregularity of the sample shape, the cycle period and radius of the closed circle formed by the partial strain curve gradually decrease, and the center of the circle gradually shifts. In addition, the volume strain and liquefaction strength of sand samples increase with the increase of particle shape irregularity. It is particularly noteworthy that obvious vortex structures exist in the positions near the center where deformation is severe in the samples of circular and elliptical particles. However, such structures are difficult to be directly observed in sample with irregular particles. This phenomenon reveals the influence of particle morphology on the complexity of the mechanical behavior of sand, providing us with new insights into the understanding of the response mechanism of sand soil under complex stress conditions.

Mechanical textile recycling efficiency: Sample configuration, treatment effects and fibre opening assessment

The mechanical textile recycling process significantly reduces fibre length. Previously, we explored how lubricant pre-treatment before mechanical recycling reduced the fibre length loss. In this study, we added simulated wear to assess its influence on the fibre length output. We also evaluated the influence of sample shape and feed direction on recycling efficiency. We treated plain woven cotton textiles were subjected to either sandpaper grinding or steel needle raising. Finishing treatments with polyethylene glycol 4000 and Afilan CFA 100 were also used in combination. Samples were prepared in two shapes and fed into the recycling machine with warp threads oriented longitudinally, perpendicularly, or diagonally. Recycling efficiency was evaluated based on fibre length and the degree of fibre opening using a novel air flow permeability test. The results showed that sandpaper treatment degraded fibres, while the raising treatment improved recycling efficiency. A previously unreported finding was that the size, shape and feeding direction of woven fabrics showed significant effects on the fibre length output. Material fed with a thread system aligned longitudinally to the recycling machine direction resulted in a higher proportion of opened fibres and fewer unopened fabric pieces. It was further observed that the yarns aligned longitudinally with the feed direction exhibited significant opening, while those oriented perpendicularly remained largely unopened. The new method for measuring the degree of opened fibres proved effective and holds promise for future application. These findings provide tangible guidance on the mechanical recycling protocol and means to improve output assessment procedures.

Research on a Photovoltaic Panel Dust Detection Algorithm Based on 3D Data Generation

With the rapid advancements in AI technology, UAV-based inspection has become a mainstream method for intelligent maintenance of PV power stations. To address limitations in accuracy and data acquisition, this paper presents a defect detection algorithm for PV panels based on an enhanced YOLOv8 model. The PV panel dust dataset is manually extended using 3D modeling technology, which significantly improves the model’s ability to generalize and detect fine dust particles in complex environments. SENetV2 is introduced to improve the model’s perception of dust features in cluttered backgrounds. AKConv replaces traditional convolution in the neck network, allowing for more flexible and accurate feature extraction through arbitrary kernel parameters and sampling shapes. Additionally, a DySample dynamic upsampler accelerates processing by 8.73%, improving the frame rate from 87.58 FPS to 95.23 FPS while maintaining efficiency. Experimental results show that the 3D image expansion method contributes to a 4.6% increase in detection accuracy, an 8.4% improvement in recall, a 5.7% increase in mAP@50, and a 15.1% improvement in mAP@50-95 compared to the original YOLOv8. The expanded dataset and enhanced model demonstrate the effectiveness and practicality of the proposed approach.

Locking Alignment of Liquid Crystal Actuators Using Hydrogen Bonds to Enable Room‐Temperature Shape Programmability and Enhanced Work Capacity

AbstractSoft actuators that mimic the softness and deformability of living organisms have great potential for use in various fields. For most soft actuators, achieving both reprogrammable shape and high work capacity is crucial but challenging. These properties are mutually exclusive for liquid crystal elastomers (LCEs), an important type of soft actuators. Herein, a room‐temperature shape‐programmable LCE capable of high‐energy actuation is developed. Our approach utilizes hydrogen bonds to stabilize the aligned liquid crystal phases. The slow recovery of H‐bonds at room temperature provides a specific processing window, during which the sample shape can be programmed after the thermal treatment. The temperature‐dependent rearrangement of hydrogen bonds allows for fabrication of actuators with customized shapes in a facile do‐it‐yourself manner. Additionally, the integration of strong covalent cross‐links is vital for holding structural integrity. The combination of non‐covalent and covalent cross‐linking significantly improves the mechanical properties, enabling the actuators to perform reversible actuation with a work capacity (440 kJ m−3) higher than that of traditional LCEs (<100 kJ m−3). This study provides a turnkey strategy to address the conflict between shape reprogrammability and work capacity, advancing the development of soft actuators.

Analysis of Thermal Isotropy of Parallelepiped Shape of Bronze Samples for Mechanical Engineering Applications

Objective: The need to find out whether the specimens are ‘thermally thin’ or not is the basis for applying the law of conservation of energy or the Fourier differential equation of heat conduction in finding the time dependence of the specimen temperature. The aim of this study is to find out the thermal field distribution in a parallelepiped shaped bronze specimen and to verify the Bio number. Methods: A number of external variables make it difficult to maintain a monotonic change in sample temperature during the ‘heating’ stage. These factors led to the use of the cooling method to study tiny samples with low inertia of the thermal process. We used the cooling method to experimentally verify the isotropy of the thermal field in the sample and to study the kinetics of cooling relative to the sample axes over a wide range of temperatures. Results: It was found out that in natural air cooling the main mechanisms are conductive, convective and radiative heat transfer. The contribution of thermal radiation to the cooling process is noticeable at high temperatures. It was found that the typical cooling time increases with sequential radiative, conductive and convective heat transfer. By extending the temperature study area to, for the first time, we were able to observe each component of the heat transfer process independently. The values of the typical cooling time on all axes correspond to the experimental error bounds. It was found that the temperature value of the sample is independent of the coordinates and depends only on time. In this case, the law of conservation of energy can be used to explain the dependence of body temperature on cooling time. Conclusion: It is shown that the sample under study is ‘thermally thin’, i.e. the thermal field is constant in all directions. In this situation, the thermal balance equation should be applied rather than the Fourier differential equation of heat conduction, since the temperature gradient inside the body is practically zero. The results obtained are of great importance for the study of cooling processes of metallic products in thermal power engineering, heat engineering and thermophysics.

Research on extreme value estimations and dynamic coefficients of wheel load for high-speed railway based on generalized Pareto distribution theory

The design value of wheel load is one of the key design parameters for high-speed railway ballastless track structure, which essentially belongs to the extreme estimation of wheel load. Based on the generalized Pareto distribution theory, this article carries on the research on the extreme value estimations of wheel load excited by whole wavelength range irregularity, which provides a basis for the design of ballastless track structure. When using automatic threshold selection method, sample declustering can improve the independence between data. The shape parameter screening method is proposed for the extreme value estimations of wheel load, and the corresponding sample size and shape parameter range for each cluster are determined. A reasonable sample size is determined, and the mean of the extreme estimations of wheel load is used as the final extreme estimation of wheel load. The dynamic coefficients that match the design life of the ballastless track structure are obtained.

An evaluation of six techniques for measuring porosity of ribbons produced by roller compaction

Ribbon porosity is a critical parameter to monitor in the roller compaction process. In this study, six techniques for measuring the porosity of solid compacts, i.e., manually by caliper (Caliper), X-ray microtomography (µCT), off-line near-infrared spectroscopy (NIR), laser triangulation (Laser), mercury intrusion porosimetry (MIP), and GeoPyc, were compared using a set of rectangular ribblets of microcrystalline cellulose (MCC). These ribblets, which were compressed at 8–––130 MPa on a compaction simulator, exhibited porosities over the range of 0.09 – 0.52. Subsequently, porosities of MCC ribbons made on a roller compactor at specific roll forces of 1.8 kN/cm and 8.8 kN/cm were measured. The Caliper method is convenient for samples with a simple shape but not suitable for real ribbons. The accuracy of GeoPyc measurement relies on accurate conversion factor (unit in cm3/mm), sample shape and size, and sufficient sample volume percentage in the medium. The µCT data is more accurate at lower porosities (< 0.2), while the MIP data is more accurate at higher porosities (> 0.4). The Laser method has good accuracy and is more reproducible compared to other methods in the ribblets measurement. The NIR method is fast, which makes it suitable for in-line monitoring of changes in ribbon quality, but porosity quantification is sensitive to sample presentation, such as surface curvature and roughness. These insights could assist in the choice of the most appropriate method for monitoring ribbon porosity to guide the development and optimization of a roller compaction process for a given formulation.

Self-exothermic reaction behavior and pore structures of Ni-Al intermetallics with more than 70% porosity

Abstract In this study, high-porosity Ni-Al alloys with complete shape and controllable pore structures were prepared by combining the self-exothermic reaction with the space holder method. The observations show that porous Ni-Al sintered discs appeared to melt and deform after a violent reaction without adding space holder particles. The link between the volume content of urea particles and macroscopic morphology, combustion behavior, phase composition and pore structures of porous Ni-Al compounds were studied. The space holder pores acts as a heat absorber, greatly increasing the open porosity to 76.0% when adding 50 vol% urea particles. This leachable space holder method can be an effective strategy to regulate the sample shape and pore characteristics of porous Al-containing intermetallics.

Characterisation Analysis of Sulphur and Phosphorous Doped and Co-doped Graphitic Carbon Nitride (g-C3N4) Materials

Graphitic carbon nitride (g-C3N4) is tailored with doping of different non-metals (Sulphur and Phosphorus). For synthesis through thermal condensation method, the mixtures of urea and dopant with diverse concentrations have been added for preparation of materials. The basic effect of doping and its concentration on the structural morphology and absorption spectra of the samples is investigated in detail. Pure g-C3N4 suffers from high recombination rate of photogenerated electron-hole pairs resulting in low photocatalytic activity. Different techniques like X-ray diffraction (XRD), Scanning electron microscopy (SEM), Fourier transforms infrared (FTIR) spectroscopy, and Photoluminescence spectroscopy (PL) have been used for the characterization. X-ray diffraction studies confirm the formation of the g-C3N4 structure and SEM images reveal crumpled sheets and irregular plate like shapes of the doped graphitic nitride samples. FTIR analysis identify the presence of surface amino (N-H) and water (O-H) groups, cyano terminal group (C≡N), (C≡C), C–N) and (C=N) bonds and breathing mode of the tri-s-triazine units in the samples. PL spectra shows that the sulphur and phosphorus co-doped PSGCN (8 wt.%) sample is better for photocatalytic activity.

Confidence Intervals for the Mean and Difference of Means of Birnbaum-Saunders Distributions with Application to Wind Speed Data

This paper proposes the confidence intervals for the mean and difference of means of Birnbaum-Saunders (BirSau) distributions based on the Bootstrap confidence interval (BCI), Percentile bootstrap confidence interval (PBCI), Generalized confidence interval (GCI), Bayesian credible interval (BayCrI) and the highest posterior density (HPD). The simulation study used R statistical software to evaluate the coverage probabilities and average lengths. The concerning results of the mean suggest that HPD is the recommended method for constructing confidence intervals in the BirSau distributions, except for small sample sizes where the GCI method proves more efficient. For the difference of means, PBCI emerges as the preferred way to construct confidence intervals, except in some cases where small sample sizes with the HPD method are more efficient. Moreover, the average lengths of these proposed confidence intervals decreased as both sample size and shape parameters increased. To illustrate the effectiveness of the suggested confidence intervals, we applied them to wind speed datasets collected in Ayutthaya and Ratchaburi provinces, Thailand.

Dynamic Mechanical Spectroscopy with Cylindrical Geometry: Application to the Comparison of Various Plasticizers of Thermoplastic Starch

AbstractDynamic mechanical spectroscopy is a common analysis for polymers. Rectangular specimens are usually used for measurement in the solid state due to their easy designing. However, in reason of the non‐symmetric shape of sample, rectangular specimens do not experience linear stress on their all body, leading to overestimation of shear modulus. Corrections are required to determine the right shear modulus. In this present work, straight shear modulus determination is carried out using specimens with a cylindrical shape. The reliability of the technique is described on a biosourced polymer materials made of thermoplastic starch, plasticized by glycerol, choline chloride/urea mixture (ChCl/U), 1‐ethyl‐3‐methylimidazolium chloride ([EMIM]Cl) and 1‐ethyl‐3‐imidazolium acetate ([EMIM]Ac). The technique is shown to be particularly interesting to avoid any additional shaping of the specimens prior to measurements, that can be detrimental to their properties (evaporation, degradation). A comparison between cylinder and rectangular specimen has also been made to illustrate the interest of cylinder clamping on biosourced polymer material.

High Stability and Low Power Nanometric Bio-Objects Trapping through Dielectric-Plasmonic Hybrid Nanobowtie.

Micro and nano-scale manipulation of living matter is crucial in biomedical applications for diagnostics and pharmaceuticals, facilitating disease study, drug assessment, and biomarker identification. Despite advancements, trapping biological nanoparticles remains challenging. Nanotweezer-based strategies, including dielectric and plasmonic configurations, show promise due to their efficiency and stability, minimizing damage without direct contact. Our study uniquely proposes an inverted hybrid dielectric-plasmonic nanobowtie designed to overcome the primary limitations of existing dielectric-plasmonic systems, such as high costs and manufacturing complexity. This novel configuration offers significant advantages for the stable and long-term trapping of biological objects, including strong energy confinement with reduced thermal effects. The metal's efficient light reflection capability results in a significant increase in energy field confinement (EC) within the trapping site, achieving an enhancement of over 90% compared to the value obtained with the dielectric nanobowtie. Numerical simulations confirm the successful trapping of 100 nm viruses, demonstrating a trapping stability greater than 10 and a stiffness of 2.203 fN/nm. This configuration ensures optical forces of approximately 2.96 fN with an input power density of 10 mW/μm2 while preserving the temperature, chemical-biological properties, and shape of the biological sample.

Mass insulation enhancement of cork stoppers through heat treatment: experimental measurements, modeling, and optimization

Natural cork stoppers, used as bottle sealers for high-end products such as ingredients and flavorings, belong to the highest class in terms of cork quality. Various studies have been carried out to examine the solute diffusion in cork using conventional methods. However, the investigations were limited to natural cork stoppers that had been boiled and cut in a single direction. In this study, the anisotropic cylindrical shape of cork samples was modeled, considering various cutting directions. Additionally, we subjected the stoppers to boiling then to an optimal THT cycle to improve the cork's mechanical qualities. The optimal thermal cycle is determined using TGA analysis. IR and SEM tests are employed to verify the enhancements in the cork. The apparent mass diffusion coefficient (Dapp) is determined by the calibration of the model with the experimental data acquired via the conductometric method. The coefficient values are optimized using the Bat algorithm with a relative error of 10–5. The Dapp was found to be better for the treated cork grown in the Jijel region than for the cork Medea, which is better than of Skikda cork. Regarding the impact of the cutting direction on the Jijel's cork, the results indicate that the mass insulation is higher when the treated stoppers are cut in the tangential-longitudinal direction (DJTLt=4,12.10-13m2s-1) compared to the tangential-radial direction (DJTRt=7,75.10-13m2s-1) and the longitudinal-radial direction (DJLRt=8,53.10-13m2s-1). The treatment, which serves as a solution for the cork industry, showed an improvement in mass insulation 13-fold greater than the natural cork.

Cold sintering of complex-shaped ceramic materials

The present work explores for the first time the production of ceramic bodies with complex shape through the cold sintering process. Inspired by previous works on spark plasma sintering, a spacer accessory was designed to act as a removable mold. This proof-of-concept was tested with four different ceramic systems: biogenic hydroxyapatite, zinc oxide, diatomaceous earth and construction/demolition waste materials. In all cases, the density is comparable to that obtained by cold sintering of simpler disks. Moreover, the microstructure of the complex-shaped materials is substantially homogeneous in the entire component. Some distortions can be detected when comparing the spacer and sample shape, their control and modeling being a key challenge for future works.

LDConv: Linear deformable convolution for improving convolutional neural networks

Neural networks based on convolutional operations have achieved remarkable results in the field of deep learning, but there are two inherent flaws in standard convolutional operations. On the one hand, the convolution operation is confined to a local window, so it cannot capture information from other locations, and its sampled shapes is fixed. On the other hand, the size of the convolutional kernel is fixed to k × k, which is a fixed square shape, and the number of parameters tends to grow squarely with size. Although Deformable Convolution (Deformable Conv) address the problem of fixed sampling of standard convolutions, the number of parameters also tends to grow in a squared manner, and Deformable Conv do not explore the effect of different initial sample shapes on network performance. In response to the above questions, the Linear Deformable Convolution (LDConv) is explored in this work, which gives the convolution kernel an arbitrary number of parameters and arbitrary sampled shapes to provide richer options for the trade-off between network overhead and performance. In LDConv, a novel coordinate generation algorithm is defined to generate different initial sampled positions for convolutional kernels of arbitrary size. To adapt to changing targets, offsets are introduced to adjust the shape of the samples at each position. LDConv corrects the growth trend of the number of parameters for standard convolution and Deformable Conv to a linear growth. Compared to Deformable Conv, LDConv provides richer choices and can be equivalent to deformable convolution when the number of parameters of LDConv is set to the square of K. Differently, this paper also explores the effect of neural networks by using LDConv with the same size and different initial sampling shapes. LDConv completes the process of efficient feature extraction by irregular convolutional operations and brings more exploration options for convolutional sampled shapes. Object detection experiments on representative datasets COCO2017, VOC 7 + 12, and VisDrone-DET2021 fully demonstrate the advantages of LDConv. LDConv is a plug-and-play convolutional operation that can replace the convolutional operation to improve network performance. The code for the relevant tasks can be found at https://github.com/CV-ZhangXin/LDConv.

Determination and study of correlations of relative sensitivity factors in metal and metal oxide samples by glow discharge mass spectrometry

The determination of relative sensitivity factor (RSF) plays a crucial role in achieving accurate quantitative analysis in glow discharge mass spectrometry (GD-MS). In this study, the RSF of typical elements in 14 metal and metal oxide matrices were determined, and their correlation with discharge parameters, matrix effects, the first ionization energies and sample shapes were investigated. It was found that discharge gas flow exerted a minor influence on RSF values in a nickel (Ni) metal sample, whereas discharge current significantly affected RSF, with variations up to 57.00 % for cobalt (59Co). The results revealed that matrix effects were more pronounced in metal oxides, with the relative standard deviation (RSD) of RSF for typical elements ranging from 25.17 % to 101.04 %. RSF values for the same element across different metal oxides showed a correlation with lattice binding energy (U0). Particularly, RSF values for 12 elements including 23Na, 27Al, 28Si, 45Sc, 52Cr, 56Fe, 59Co, 88Sr, 130Te, 138Ba, 139La and 140Ce within 7 metal oxides showed a significant correlation with U0 of the metal oxides. In terms of sample shape, pin samples generally yielded higher RSF values than flat samples in both metals and oxides. RSF accuracy was confirmed with standard samples of zirconium (Zr 73 MR10002 and Zr IARM 705–18) and iron oxides (Fe2O3-1 and Fe2O3-2) with relative errors within 17.50 % except for 12C. Subsequently, these RSF values were effectively utilized for the quantitative analysis of samples collected from the China Space Station (CSS). This comprehensive analysis elucidates the multifaceted influences on RSF values, enhancing the precision of trace element quantification in GD-MS.

Application of Modal Strain Energy Analysis to Localize an Added Mass on an Aluminium Plate.

The modal strain energy method is a vibration-based damage detection method that allows the use of passive measurements. The method is based on the measurement and analysis of the modal response of the structure under investigation. The aim of this work is to investigate the application of this method to detect and localise a local change in a structure using acoustic measurements in a fluid around the structure. Firstly, the modal strain energy is presented. The technique is based on the analysis of the modal shapes of undamaged and damaged samples obtained by operational modal analysis. The application of modal strain energy to off-contact acoustic measurements is then discussed. The method is used to detect and locate a local change (an additional mass) in an aluminium plate subjected to a mechanical force. The study begins with numerical simulation using finite element models, followed by experiments on the aluminium plate.

Assessment of fishes, sediment and water from some inland rivers across the six geopolitical zones in Nigeria for microplastics.

In Nigeria, limited research has been conducted on Microplastics (MPs) in inland rivers, necessitating a comprehensive assessment to understand the extent of contamination. This study aimed to assess the abundance, distribution, and composition of MPs in fishes, sediment, and water from inland rivers across Nigeria's six geopolitical zones. Samples were collected from selected rivers in each geopolitical zone (Rivers Yauri, Benue, Argungu, Jamare, Ogun, Ethiope and Orashi). MPs were isolated using a combination of filtration, density separation, and visual identification. MPs abundance, distribution, shapes, colors, and chemical composition were determined using microscopy and Fourier-transform infrared spectroscopy. The study presents the first report of MPs in six in land rivers in Nigeria and found that MPs were present in all the fishes, sediments and river waters studied across all the rivers. The abundance and composition of MPs varied among the different sample types, with fibers being the most abundant shape in both water and fish samples. PET, PP, and PE were the most prevalent types of plastics found in fish samples, while PE/PA/Nylon, PVA, and PVC were predominant in water samples. PA/Nylon, PUR, PVC, and PET were the most common in sediment samples. Source analysis by Principal component analysis (PCA) and Hierarchical Cluster Analysis (HCA) indicated that the presence of MPs was mainly influenced by local anthropogenic activities. However, estimated daily intakes are generally low, indicating that daily consumption of the samples is not likely to be harmful. The widespread presence of MPs in inland rivers across Nigeria highlights the urgent need for effective waste management strategies and environmental conservation efforts to mitigate plastic pollution.

Head shape divergence between parthenogenetic and their paternal bisexual rock lizards in sympatry

Head shape plays a crucial role in ecological and evolutionary processes in lizards, and scientists have studied head shape using traditional and 3D geometric morphometrics. Lizards are classic subjects for ecological studies because closely related and ecologically similar species coexist. Sympatric species tend to show higher levels of morphological divergence compared to allopatric species.In this study, we focus on two parthenogenetic Darevskia species (Darevskia dahli and Darevskia armeniaca) that share a maternal species, Darevskia mixta, but have different paternal species (Darevskia portschinskii and Darevskia valentini). We aim to assess the relative importance of morphologically inheritable traits and environmental conditions on head shape in these parthenogenetic species. Specifically, we aim to determine whether local adaptations or intermediate phenotypes between parental species drive head shape variation in parthenogens. To accomplish this, we analyze the head shapes of samples from both parthenogens, their paternal species, and their common maternal species from 3 sites in Georgia. Our study shows that certain aspects of head shape are associated with body size and habitat climate, with high mountain species exhibiting larger and deeper heads with stronger jaws regardless of breeding mode. In addition, both parthenogens exhibit narrower and more elongated jaw areas, flatter mandibles, and thus weaker jaws compared to females of their maternal and paternal species.