Stress Wave Velocity Research Articles

Growth characteristics and stress-wave velocity of standing trees of three Populus tree species in Mongolia

Growth characteristics and stress-wave velocity of standing trees of three <i>Populus</i> tree species in Mongolia

Stiffness and hardness of thermally modified timber assessed with explainable machine learning

Thermal modification is an environmentally friendly practice to enhance the durability of wood. Despite the method's effectiveness in improving wood durability and dimensional stability, the mechanical properties of wood could be compromised following the heat treatment process. While most of the literature has focused on studying the impact of wood modification on stiffness or strength, less attention was given to characterization and nondestructive prediction of wood hardness following thermal treatment. Hardness, an important quality indicator of wood, has been a subject of limited research in the context of developing predictive models for assessing the hardness of thermally modified wood. The existing research in this area has either been scarce or unsuccessful, with poor predictive performance being a common issue. This research studies the impact of thermal modification on the longitudinal and transverse hardness of some common North American softwoods (Douglas-fir, Western hemlock, red cedar) and hardwoods (red alder, paper birch). It also aims to develop an explainable machine-learning (TreeNet gradient boosting machine) predictive model for hardness prediction using stress wave data combined with wood density and information about the type of wood species and heat treatment level. The impact of heat treatment on the stress wave velocity, density, and hardness was studied, and the dependency of the variables was assessed using correlation and clustering analysis. Machine learning modeling showed that the longitudinal and transverse hardness could be predicted by having a maximum R2 (test data) of 70.62 and 72.78, respectively, with a relative importance of the predictors in descending order as wood species > density > wave velocity >MOEdyn> heat treatment. Using the top 3 critical parameters yielded an R2 (test data) of ∼69 % for both models. The developed model could predict the hardness of various wood species treated at different temperatures, having only the type of wood species and its density followed by the stress wave velocity, which can be measured at an industrial scale.

TECHNOLOGICAL PROPERTIES OF Eucalyptus grandis USING DIGITAL IMAGE CORRELATION (DIC)

This study aimed to characterize some technological properties of Eucalyptus grandis wood and evaluate the use of Digital Image Correlation (DIC) to obtain the displacement and the behavior of the samples in deformation and its relationship with tension in tensile and compression tests parallel to the fibers. Samples were produced from 23-year-old wood to determine the basic density, shrinkage coefficient, anisotropy in contraction and swelling, and the mechanical strength to tensile and compression parallel to the fibers. To calculate the Modulus of Elasticity (E), the stress wave velocity was measured in the tensile samples. The measurement of sample elongation during the test was obtained by DIC and then calculating strain and E. The basic density was 0.497 g/cm³ and the anisotropy values of contraction (1.25) and swelling (1.27) indicated that it was a very dimensionally stable wood. The tensile strength (118.50 MPa) was higher than normally obtained for the species. The parallel compression average values (53.06 MPa) were similar to those in the literature. As for E, the average value obtained by DIC was 12,664.24 MPa; by the stress wave timer, it was 11,941.35 MPa. The evaluated wood is indicated for structural uses according to the C40 class (NBR 7190-1997). Finally, DIC was able to adequately provide displacement values that occurred during tests, enabling the modulus of elasticity calculation.Keywords: wood characterization, non-destructive method, physical and mechanical properties, strain.

Dynamic Analysis of 2D FG Porous Thick Cylindrical Shells Under Thermal Shock

In this research, a thick hollow cylindrical shell made of bidirectional functionally graded open cell porous materials under internal thermal shock according to the classical theory of linear thermo-elasticity is examined for the first time. The cylinder is made of a porous cellular material and its porosity varies along both radial and axial directions continuously. The governing motion equations are obtained by using 2D-axisymmetric theory of linear thermo-elasticity rather than shell theories. This theory represents thickness stretching and gives more precise results. Graded finite element method is employed to model the problem. Applying this method rather than conventional FEM leads to more accurate results, especially for dynamic analyses. The cubic higher order element is used for dividing the solution domain. To obtain transient temperatures, Crank–Nicolson algorithm is used and then the Newmark procedure is used to derive time responses of displacement and stress components. The time history of displacements and stress components for different radial and axial power law exponents, porosity coefficient, boundary conditions, length-to-thickness ratio and two different porosity patterns are investigated in detail. The obtained results show that thermal-induced vibration is generally caused by hoop stress, and frequency and amplitude of vibrations and velocity of stress waves are considerably influenced by the porosity distribution, porosity coefficient and power law exponents in both directions.

Machine learning based tomographic image reconstruction technique to detect hollows in wood

A new technique based on machine learning algorithms was introduced to detect internal wood defects. This technique relies on analyzing segmented propagation rays of stress waves and successfully generates the tomographic images of the defects by using the stress wave velocity. Utilizing a dual-stage methodology, the initial phase involves ray segmentation for the precise delineation of stress wave propagation, while the subsequent stage integrates advanced classification and clustering algorithms to facilitate the generation of tomographic images. This approach effectively tackles the inherent challenges associated with accurate segmentation and classification of stress wave velocity rays. The effectiveness of the proposed method was evaluated using both synthetic and experimental data. The results showed that the proposed method, when compared with some state-of-the-art methods, has a superior ability to accurately detect defective regions in the wood. The success of the proposed method is evaluated with four different evaluation metrics. It determined that over 90% success is achieved for all metrics. In comparison with related studies, it determined that the results are improved by 7–22% compared to the literature.

Optimizing Sensor Positions in the Stress Wave Tomography of Internal Defects in Hardwood

Stress wave tomography technology uses instruments to collect stress wave velocity data via sensors, visualizes those velocity data, and reconstructs an image of internal defects using estimated velocity distribution. This technology can be used to detect the size, position, and shape of internal defects in hardwood, and it has increasingly attracted the attention of researchers. In order to obtain enough stress wave signals, 12 sensors are usually equidistantly positioned around the cross-section of trunks like a clock. Although this strategy is reasonable and convenient, it is obviously not the optimal signal acquisition strategy for all defects. In this paper, a novel sensor position’s optimization method for high-quality stress wave tomography is proposed. The relationship between the shape of defects and the planar distribution of sensors is established by taking the ray penetration ratio and degree of equidistant distribution of sensors as indicators. Through the construction of the fitness function and optimization conditions, the optimal strategy for the planar distribution of sensors was determined using the Genetic Algorithm. Seven samples containing simulated defects and real tree trunks were used to test the proposed algorithm, and the comparison results show that the image of internal defects in hardwood can be reconstructed with high accuracy after optimizing the sensor positions.

Effective wave velocity in rock masses with double-scale discontinuities under in-situ stresses

The effective velocity of stress wave in rock masses with double-scale discontinuities subjected to in-situ stresses was investigated in the present study. An improved model that comprehensively considers the deformation of macrojoint and wave velocity of microdefected rock mass under in-situ stress was proposed to study the effective velocity of stress wave. The effect of in-situ stress on effective velocity was systematically analyzed using the presented model. The effect of the propagation distance, incident wave amplitude and incident wave frequency on effective velocity under in-situ stresses were further discussed and compared with the results of traditional study that disregards the influence of in-situ stress. The findings demonstrate that the small in-situ stresses have a substantial effect on the effective velocity. The effective velocity shows a trend of rapid increase followed by slow increase as increases of in-situ stress. Additionally, the effective velocity increases with propagation distance and amplitude. In the low and high-frequency regions, the effective velocity remains approximately at minimum and maximum values. A significant increase in the effective velocity is observed as the frequency increases in the mid-frequency region. However, it is noted that the effective velocity does not change significantly with increasing amplitude for sufficiently large in-situ stresses, and the influence of amplitude on the effective velocity can be disregarded. Furthermore, it is found that the effective velocity resulting from the present study is consistently larger than that resulting from the traditional study due to the effect of the in-situ stress. The findings of this investigation offer useful theoretical guidance for research into the effective velocity in deep rock mass.

Effects of pulsed laser processing on structural evolution of diamonds - A molecular dynamics and experimental study

The pulsed laser processing has been used for machining ultrahard diamonds. However, structural evolutions, along with microscopic mechanisms, have hardly been clarified. In the present study, a molecular dynamics model for describing the pulsed laser processing of diamonds was developed, and the calculation results were verified through corresponding experiments, by using the typical nanosecond pulsed laser processing. At first, the temporal evolution of the temperature field was calculated, establishing the correlation between the temperature distribution and material ablation phenomena. Besides, intricacies of dislocation generation mechanism were elaborately explained, indicating that stress waves played prominent roles in formation and propagation of dislocations. In order to understand the phase transition phenomena, including the graphitization, vaporization and solidification, variations in coordination numbers based on calculations, together with Raman and XPS characterizations on diamond samples before and after laser processing, were examined and compared. Moreover, different effects of the pulsed laser processing on polycrystalline and monocrystalline diamonds were compared. It was found that the polycrystalline diamond shows lower rate of temperature fall and lower velocity of stress waves. This study provides valuable insights into the microscopic mechanisms governing pulsed laser processing of diamonds, thereby broadening the scope for optimizing laser machining processes.

Improved deep artificial neural network-powered prediction of extreme mechanical performances of fractal architectures with high hierarchical rank

This work explores the mechanical performances, including anisotropy, wave propagation, and buckling resistance capability of the Menger sponge and Jerusalem fractal structures, with the high rank, using an improved deep artificial neural network (ANN) model inserted by a loop with multiple conditions. Where, the effective mechanical attributes, including Young’s modulus, shear modulus, and Poisson’s ratio of the Menger sponge structure with rank 4 are attained using high-performance computer cluster (HPCC) that are then used to train and also validate the ANN model. The accuracy of the deep ANN model trained by data of fractal structures with and without rank 4 is verified by the numerical model and experiment with the good agreement found or the maximum percent difference being 15.6% where the numerical and experimental data don’t belong to its training samples. Remarkably, the deep ANN model demonstrates an extremely low cost, but very fast compared with the numerical and experimental works. Namely, the improved deep ANN model implemented by a regular computer can accurately predict the mechanical attributes of Menger sponge fractal structures with full ranks in 3 min. While it takes a week for numerical work using HPCC or experiment method to produce the same mechanical properties of the Menger sponge with only rank 4, displaying at least thousands of times slower than the ANN model. The ANN results indicate that the onset of anisotropy of considered fractal structures is from rank 1, and the reversal of anisotropy will take place upon an increase in the rank while such reversal is not seen for the case of lattice structure. The anisotropy reversal could be one of main reasons why the fractal structure tends to have a high rank in nature. In addition, the buckling stress and phase wave velocity are observed to decrease with rising rank, with a nonlinear pattern.

Effect of Improved Planting Stock on Tree Growth, Wood Properties, and Soil Fertility of Teak Plantations 10 Years After Planting

Teak (Tectona grandis Linn. f.) is one of the most economically valuable types of tropical forest because teak wood has high durability, resilience and good aesthetic qualities. Teak tree improvement in Indonesia was initiated in 1983 producing planting stock for reforestation, i.e. clonal seed orchards (CSO) to produce seedling as sexual reproduction (referred to seedling), and hedge orchards to produce shoot cuttings as asexual (vegetative) reproductive (referred to shoot cuttings). Teak plantations established using seedling and shoot cuttings should improve forest productivity. The objectives of this study were to compare the growth rate, wood properties, and soil fertility of teak plantations propagated using seedling and shoot cuttings. Three square plots of 100 trees (10 × 10 trees; 1,000 m2) were established on both types of plantation and tree growth characteristics, wood properties, and soil fertility were monitored. The tree growth characteristics were diameter at breast height (DBH), tree height (H), clear bole height (CB), and volume of standing stock (Vss), and the wood properties included pilodyn penetration (PP) and stress wave velocity (SWV). Soil fertility was assessed from soil samples collected from three soil depths, with three replicates in each plot: 0–5 cm (top layer), 6–30 cm (middle layer), and 31–60 cm (bottom layer). Soil samples were analysed for total nitrogen, total phosphorus, total potassium, total calcium, and total magnesium. The results showed that the mean DBH, H, CB, and Vss differed significantly between the type of planting stock. The DBH, H, CB, and Vss values were 28.4%, 46.8%, 49.1%, and 130.1% higher, respectively, in teak plantations from shoot cuttings than from seedling. Moreover, the SWV of shoot cuttings planting stock plantation was 3.6% higher than from seedling. The mean PP did not differ significantly between teak plantations from shoot cuttings (22.00 mm) and seedling (21.80 mm). Furthermore, the planting stock did not affect soil fertility, which was highest in the top layer in all treatments. Our results suggest that teak plantations from shoot cuttings would increase growth, forest productivity, maintaining wood quality and soil fertility. Thus, it can maintain sustainable teak forest plantations.

Evaluation of some physical and mechanical properties of Acacia hybrid BV10 planted in Quy Chau, Nghe An

This study aimed to evaluate some major physical and mechanical properties of 7 year old Acacia hybrid BV10 planted in Quy Chau district, Nghe An province. Small specimens with dimensions of 20 (Radial) × 20 (Tangential) × 320 (Longitudinal) mm3 were cut near the pith and near the bark at breast height from each sample tree, then placed in a standard laboratory setting until their weights reached a constant value. The resulting mean air-dry density (AD), stress wave velocity (SWV), static modulus of elasticity (MOE) and modulus of rupture (MOR) were 0.53 g/cm3, 4,241 m/s, 10.00 GPa, and 82.17 MPa, respectively. Statistical analysis showed that SWV and these wood properties examined near the bark were always higher than those values measured near the pith. Stress wave technology can be used to predict MOE and MOR; however, AD is still a more reliable indicator for predicting mechanical properties since it showed a strong correlation with MOE (r = 0.86; P &lt; 0.001) and MOR (r = 0.80; P &lt; 0.001).

Multi-scale simulation study on the evolution of stress waves and dislocations in Ti alloy during laser shock peening processing

This study investigates the effect of laser shock peening (LSP) on the evolution of stress waves and dislocations in Ti-6Al-4V alloy by multi-scale simulation. The finite element model on the macroscale and molecular dynamics model on the microscale were built, and multi-scale simulations based on the finite element and molecular dynamics were performed. Under the high pressure on material induced by LSP, elastic deformation and plastic deformation are generated. With the increase of stress wave traveling distance, its intensity gradually decays. The stress wave in the material completely vanishes eventually. The macroscale simulation shows that the average velocity of the stress wave equals 6.0 km/s and does not change much with the loading pressure. The microscale simulation shows that the average velocity of the stress wave in single crystal α-Ti is in the range of 7.1∼7.8 km/s. The average velocity of stress wave in polycrystals is always lower than that in the single crystal and has a trend to decrease with the increase of grain number until a stable value of around 6.0 km/s. Considering the induced shock pressure, the piston velocity should be below 0.4 km/s to recreate the LSP process. This paper provides a comprehensive understanding of the effect of LSP on the evolution of stress waves and dislocations and also provides a new numerical method to further study laser shock peening processing.

Assessment of residual stresses in railway rails using ultrasonic and Barkhausen noise techniques

Residual stress, a factor affecting the fatigue and fracture characteristics of rails, is formed during the processes of fabrication and heat treatment, and is also generated by shrinkage/tension due to the temperature differences and vertical loads on wheels due to the weight of vehicles. Moreover, damage to rails tends to accelerate due to residual stress caused by the continuous increase in the number of passes and the high speed of passing vehicles. Because this can have a direct effect on safety accidents on railroad rails, having a technique to evaluate and analyse the residual stresses in rails accurately is very important. In this paper, firstly, residual stresses applied in rails were evaluated using longitudinal critically refracted (LCR) wave. Non-destructive stress measurement using ultrasonic techniques is based on calculation of the acoustoelastic coefficient obtained from the relationship between material stress and LCR wave velocity. This is because LCR waves exhibit a relatively large change in flight time in relation to a change in stress compared to other ultrasonic modes. Barkhausen noise technique is also very suitable for measuring residual stresses on railway rails, which are ferromagnetic materials. Tensile and compression tests were performed with the specimens extracted from the inspection object, and the difference between the ultrasonic speed and the magnetization amplitude according to the applied stress was measured. Then, the feasibility of calculating the internal stresses in railway rails using the reference data obtained from the extracted specimens was determined, and the reliability of each method was verified. Furthermore, based on these results, the difference in the results for the loads asymmetrically applied according to the wheel shape was analysed by measuring for each part of new and used rails.

Rapid positioning test method for cylindrical structure penetration based on machine learning

Focusing on the requirements of rapid damage location test for multi-layer steel plates penetration of cylindrical structure in the complex and harsh environment, this paper studies the propagation characteristics of high-speed impact stress waves in steel plates. Also, the measurement effects of impact stress in the near zone of penetration hole are compared with different sensors, so as to select appropriate PZT sensors to measure the velocity of impact stress wave in the actual steel plates. Then the array layout scheme is designed, and the corresponding damage location algorithm is determined. Finally, the deep learning algorithm is used to improve the accuracy and efficiency of damage location.

Density Estimation by Drilling Resistance Technique to Determine the Dynamic Modulus of Elasticity of Wooden Members in Historic Structures

(1) The assessment of the mechanical properties of old timber is essential for the proper maintenance of wooden structures. (2) Among the non-destructive properties, the dynamic modulus of elasticity is one of the best predictors of the mechanical characteristics of the members, but it requires the determination of wood density to be determined. (3) Thus, wood density was estimated by drilling resistance measurements, developing species-specific prediction equations for silver fir, chestnut and poplar. (4) The estimated density was combined with the stress wave velocity propagating longitudinally through the wooden piece, and the dynamic modulus of elasticity was calculated. (5) Medium-high coefficient determinations (R2 from 0.79 to 0.94) were found for density estimation, and medium coefficient determinations (R2 from 0.53 to 0.60) were found for the estimation of the static modulus of elasticity using the dynamic modulus.

Coarse-grained numerical simulation for compressible fluid–particle two-phase flows

Compressible fluid–particle two-phase flows broadly exist in engineering problems, and the Eulerian–Lagrangian method is a popular branch of simulation studies. Usually, the coarse-grained strategy is adopted to reduce computational costs, and the coarse-grained criterion becomes critical for maintaining accuracy. In this study, a coarse-grained criterion was proposed for simulating compressible particulate two-phase flows by considering similarity invariants and regime transition behaviors. Based on our developed computation framework, in which the particle phase is solved using the discrete element method, a series of benchmark cases, including shock impacting granular column, shock impacting granular layer, and shock impacting granular ring cases, were considered to investigate the validity of the proposed criterion. It was proven that the stiffness coefficient should be scaled to the parcel size to maintain the invariance of the spreading velocity of the particle stress wave and the restitution coefficient should be reduced to help recover the internal energy dissipation inside the parcels. Furthermore, to describe more accurately the regime transition behaviors, which are common phenomena in compressible particulate two-phase flows, an adaptive interpolation operator was introduced to adjust the influencing range of the Lagrangian parcels dynamically.

Rheological behavior of zein biopolymer and stiffness characteristic of biopolymer treated soil

The modification of polymeric biomolecules to achieve improved cementation is important for their potential applications. This study presents the rheological behaviors of eco-friendly zein biopolymer and stiffness characteristics of biopolymer-treated soil under various solvent and curing conditions. The rheological and stiffness characteristics of zein biopolymer are evaluated in terms of shear stress, viscosity, and shear wave velocity. The time sensitivity, flow index, and microstructure of biopolymer gel are analyzed. The biopolymer gel generally exhibits a weakly non-Newtonian shear-thickening behavior, except for the specimen cured for 24 h under chamber condition. At a constant shear rate, the biopolymer gel shows a rheopexy behavior, which is characterized by an increase in viscosity over time. The shear wave velocity of biopolymer-treated soil increases with the curing period, up to 50 and 96 % under atmospheric and chamber conditions, respectively. The peak absorption values for the hydroxyl functional group decrease significantly as the curing period and ethanol content increase. Furthermore, the microparticle sizes of the zein biopolymer gel decrease with increasing ethanol content. Therefore, understanding the stiffness characteristics of biopolymer-treated soil specimens for potential soil stabilization can be improved based on the rheological properties of zein biopolymer.

Application of vibration wave CT technology in the dynamic prediction of shock hazards

The vibration wave CT detection technology could be used for forecasting dynamic disasters such as coal and gas outburst and rock burst in coal mines as well as for dynamic monitoring and warning of impact risks. Based on the positive correlation between stress and vibration wave velocity and the positive abnormal distribution of vibration wave velocity, the impact danger area could be determined. Two evaluation indexes on the impact risk were constructed: the anomalous coefficient An and abnormal value Am of the gradient variation coefficient (VG) of wave velocity. The critical values of the two indexes corresponding to the impact risk degree were given. In addition, the field engineering practice was carried out by using the inversion results of vibration wave CT detection technology. Combined with the field engineering geological conditions, the impact risk area of the F15-24080 working face was defined comprehensively. The results showed high precision of this CT detection technology. Vibration wave CT detection technology could make dynamic prediction and evaluation of the impact risk on a site and provide guidance and test for the formulation and implementation effect of pressure relief measures in high-impact danger areas.

On the In Situ Cyclic Resistance of Natural Sand and Silt Deposits

This study presents cyclic resistances of an instrumented medium dense sand (i.e., the Sand Array) and medium plastic silt (i.e., the Silt Array) deposit deduced from in situ dynamic testing using the controlled blasting test method. Particle velocity records were used to calculate the cyclic resistance ratios, CRRs, and convert the transient blast-induced ground motions into their equivalent number of shear stress cycles, Neq, through consideration of the cyclic resistance observed from stress-controlled, constant–volume, cyclic direct simple shear (DSS) tests. The CRR-Neq relationship developed for the medium dense sand deposit demonstrated that the in situ cyclic resistance is larger than that (1) expected from cyclic DSS test specimens reconstituted to the in situ vertical effective stress, relative density, and shear wave velocity, Vs; and (2) calculated using case history-based, penetration-, and Vs-based deterministic formulations of liquefaction triggering models. Differences between the in situ cyclic resistance and that computed using probabilistic liquefaction triggering models reduced somewhat when considering probabilities of liquefaction exceeding 50% and 85%, depending on the model. Partial drainage during dynamic loading of the Sand Array appears to have contributed to the cyclic resistance of the sand deposit, with an increase of 6% to 27% compared to that estimated for fully undrained conditions. Differences between the cyclic failure criteria used to interpret the cyclic resistance of intact laboratory specimens of silt result in significantly different interpretations of the in situ CRR; the use of maximum excess pore pressure-consistent criteria appears to provide the best representation of the in situ, stress-based cyclic resistance when high quality, intact silt specimens form the basis for conversion of transient seismic waveforms to uniform shear stress loading cycles. The investigation described herein suggests that the reduction of cyclic resistance for plastic soils to account for multidirectional shaking ranges from 0% to 7% over Neq of 1 to 100.

Nanosecond laser-induced multi-focusing damage in the bulk of fused silica

A time-resolved imaging system was utilized in this work to study the focusing behavior during laser-induced filamentary damage in the bulk of fused silica. The results show that focusing behavior has a significant dependence on laser energy. With the increased laser energy, single focusing is changed into multi-focusing. The probability of multi-focusing appearances also increases. During this process, the plasma distribution interval increases, which expands the area affected by the damage. The difference in the stress wave velocity indicates that the multi-focusing formation has temporal and spatial order. Finally, the multi-focusing damage’s physical mechanism and formation process are discussed. The results provide a reference for the mechanism of nanosecond laser-induced multi-focusing damage to transparent media.