Damage Patterns Research Articles

Tool skill impacts the archaeological evidence across technological primates

The archaeological record offers insights into our evolutionary past by revealing ancient behaviour through stone and fossil remains. Percussive foraging is suggested to be particularly relevant for the emergence of tool-use in our lineage, yet early hominin percussive behaviours remain largely understudied compared to flaked technology. Stone tool-use of extant primates allows the simultaneous investigation of their artefacts and the associated behaviours. This is important for understanding the development of tool surface modification, and crucial for interpreting damage patterns in the archaeological record. Here, we compare the behaviour and the resulting material record across stone tool-using primates. We investigate the relationship of nut-cracking technique and stone tool modification across chimpanzees, capuchins, and long-tailed macaques by conducting standardized field experiments with comparable raw materials. We show that different techniques likely emerged in response to diverse nut hardness, leading to variation in foraging success across species. Our experiments further demonstrate a correlation between techniques and the intensity of visible percussive damage on the tools. Tools used with more precision and efficiency as demonstrated by macaques, show fewer use wear traces. This suggests that some percussive techniques may be less readily identified in the archaeological record.

Experimental Investigations on the Application of Natural Plant Fibers in Ultra-High-Performance Concrete.

Due to its high strength, the use of ultra-high-performance concrete (UHPC) is particularly suitable for components subjected to compressive loads. Combined with its excellent durability, UHPC can be used to produce highly resource-efficient components that represent a sustainable alternative to conventional load-bearing structures. Since UHPC fails in a brittle manner without the addition of fibers, it is typically used in conjunction with micro steel fibers. The production of these steel fibers is both expensive and energy-intensive. Natural plant fibers, due to their good mechanical properties, cost-effective availability, and inherent CO2 neutrality, can provide a sustainable alternative to conventional steel fibers. Thanks to the low alkaline environment and dense matrix of UHPC, the use of natural plant fibers in terms of durability and bond is possible in principle. For the application of natural plant fibers in UHPC, however, knowledge of the load-bearing and post-cracking behavior or the performance of UHPC reinforced with natural plant fibers is essential. Currently, there are no tests available on the influence of different types of natural plant fibers on the load-bearing behavior of UHPC. Therefore, five series of compression and bending tensile tests were conducted. Three series were reinforced with natural plant fibers (bamboo, coir, and flax), one series without fibers, and one series with steel fibers as a reference. Under compression loads, the test specimens reinforced with natural plant fibers did not fail abruptly and exhibited a comparable post-failure behavior and damage pattern to the reference specimens reinforced with steel fibers. In contrast, the natural plant fibers did not perform as well as the steel fibers under bending tensile stress but did show a certain post-cracking bending tensile strength. A final life cycle assessment demonstrates the superiority of natural plant fibers and shows their positive impact on the environment.

Dynamic constitutive modeling of steel fiber reinforced concrete considering damage evolution under high strain rate

This study conducted quasi-static compression and splitting tensile tests on steel fiber reinforced concrete (SFRC), as well as dynamic compression tests using the split Hopkinson pressure bar (SHPB). The mechanical properties of SFRC with varying fiber contents and under different loading strain rates were examined separately. Experimental results indicate that the addition of steel fibers effectively enhances the properties of concrete. The dynamic mechanical performance of SFRC specimens (compressive strength, peak toughness, ultimate toughness, and energy absorption capacity) demonstrated a clear strain enhancement effect. The dynamic stress-strain curves of SFRC reveal the material's good viscoelastic properties. Then, a viscoelastic constitutive model for SFRC considering damage under high strain was proposed, with parameter fitting based on SHPB test results. The constitutive model was applied to the numerical simulation by the user-defined material (UMAT) in ABAQUS. The dynamic stress-strain curves and damage patterns obtained by numerical simulation are basically consistent with the test results. This further demonstrates that the proposed constitutive model effectively describes the dynamic characteristics of SFRC.

An adaptive convolutional neural network based on transmissibility grayscale image for online identification of offshore platform damage pattern

In response to the challenges in offshore platform damage pattern recognition, where traditional methods lack adaptability owing to relying on feature extraction and expert knowledge, a novel method for online recognition of offshore platform damage patterns using an improved convolutional neural network (CNN) based on transmissibility grayscale image is proposed. The original transmissibility function is converted into a two-dimensional grayscale image to capture the essential features in the original signal, which is then used as the input for the deep learning model. Subsequently, an attention mechanism is introduced to enable the CNN to focus on key areas of the image, emphasize important feature channels, dynamically adjust feature representations, and enhance its overall performance. Meanwhile, the model is optimized by virtue of variational Bayesian algorithm and early stopping criteria, and finally, the trained offline model is applied to online damage pattern recognition of offshore platforms. Through on indoor vibration monitoring experiments, seven different damage patterns of the platform model are recognized accurately, which show that the accuracy of the improved CNN model is increased by an average of 8.5 % as compared to traditional intelligent methods. Furthermore, the proposed method is applied to the online damage identification of offshore platforms in the field, and the corresponding prediction accuracy reaches 98.9 %, demonstrating the feasibility and generalizability of the proposed method in adaptive feature extraction and precise identification of damage patterns.

Analysis of crumb rubber content influence on damage evolution and pattern recognition of rubberised epoxy asphalt mixture using acoustic emission techniques

ABSTRACT The application of coarse crumb rubber (CR) to toughen the epoxy asphalt mixture has emerged as a viable choice. However, the evolution rule of strength and damage modes of mixtures with different crumb rubber contents remains elusive. The objective of this study is to clarify the failure mechanisms in rubberized epoxy asphalt mixture combined acoustic emission (AE) data and k-means clustering theory. Four types of epoxy asphalt mixture samples are tested with the monitor of AE sensors. Based on the temporal and frequential features of AE signals, damage evolution is evaluated by the Weibull function, b-value, and the relationship between the raise angle and average frequency at the peak loading. Moreover, the k-means algorithm is conducted to cluster the AE events and damage characteristics after pre-processing the data. The test results indicate that CR particles enhance the toughness of epoxy asphalt mixtures and the mixtures with fewer CR are susceptible to occur sudden fracture due to brittle coarse aggregates. The k-means method effectively identifies AE events into four types of damaged behaviours. The findings offer valuable insights into the strength attenuation, modification characteristics, damage evolution and damage modes of rubberized epoxy asphalt mixtures, contributing to the development of more durable and resilient asphalt materials.

Different patterns of structural network impairments in two amyotrophic lateral sclerosis subtypes driven by 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid imaging.

The structural network damages in amyotrophic lateral sclerosis patients are evident but contradictory due to the high heterogeneity of the disease. We hypothesized that patterns of structural network impairments would be different in amyotrophic lateral sclerosis subtypes by a data-driven method using 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid imaging. The data of positron emission tomography, structural MRI and diffusion tensor imaging in fifty patients with amyotrophic lateral sclerosis and 23 healthy controls were collected by a 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid. Two amyotrophic lateral sclerosis subtypes were identified as the optimal cluster based on grey matter volume and standardized uptake value ratio. Network metrics at the global, local and connection levels were compared to explore the impaired patterns of structural networks in the identified subtypes. Compared with healthy controls, the two amyotrophic lateral sclerosis subtypes displayed a pattern of a locally impaired structural network centralized in the sensorimotor network and a pattern of an extensively impaired structural network in the whole brain. When comparing the two amyotrophic lateral sclerosis subgroups by a support vector machine classifier based on the decreases in nodal efficiency of structural network, the individualized network scores were obtained in every amyotrophic lateral sclerosis patient and demonstrated a positive correlation with disease severity. We clustered two amyotrophic lateral sclerosis subtypes by a data-driven method, which encompassed different patterns of structural network impairments. Our results imply that amyotrophic lateral sclerosis may possess the intrinsic damaged pattern of white matter network and thus provide a latent direction for stratification in clinical research.

Quantitative evaluation on the effects of the spatial variability in concrete materials on seismic damage of concrete gravity dams

The influencing mechanism of the spatial variability in concrete materials on the seismic damage of concrete gravity dams is still unclear, and existing methods for evaluating the seismic damage are insufficient. In this work, the effects of concrete’s spatial variability on the seismic damage distribution, energy dissipation, and deformation in concrete gravity dams are performed based on the damaged plastic model of concrete. Prior to the seismic damage analysis, the method for seismic inputting and the correlation function for realizing random fields of concrete materials are carefully determined. Based on the seismic damage analysis of the Koyna gravity dam, the tensile strength has the greatest influence on the seismic damage, followed by the elastic modulus and fracture energy. Aiming at the parameter of tensile strength, the decrease of correlation distance and the increase of the coefficient of variation increase the damage degree and complicate the damage distribution. A convenient and comprehensive damage profiling indicator is proposed to avoid the one-sidedness and evaluation error caused by using a single scalar damage value. The triangular area enclosed by the three individual damage indexes represents the comprehensive damage degree, and the shape change of the damage triangle indicates the change in the damage pattern of the dam. This damage profiling indicator is specifically designed to quantitatively distinguish and evaluate the damage degrees between a series of damage cases.

Fragility analysis of high arch dam against far-field underwater blast

The security assessment of high arch dams is a significant topic that has been researched in recent years. It is troublesome to develop a security assessment for high arch dams under far-field underwater blasts because the high arch dam is a sophisticated statically indeterminate spatial shell structure, and the underwater blasting shock wave has the characteristics of a large peak value and high frequency. Hence, the fragility analysis of a 300-m-high arch dam against a far-field underwater blast based on the probabilistic method is conducted for safety evaluation with the index of downstream peak displacement (and Downstream Peak Displacement-Span ratio). The fragility analysis process of the high arch dam under the far-field underwater blast is proposed for the first time. The impact of foundation plasticity on the high arch dam under far-field underwater blast is discussed regarding dynamic response and damage patterns with the coupled acoustic-structural (CAS) method first. The damage limit states are presented based on different damage patterns and index values from enormous computational schemes. The fragility curves with different indexes of downstream peak displacement, upstream peak displacement, and damage volume ratio are also compared. The fragility curves of the high arch dam against the far-field underwater blast with different explosive distances of 50 to 200 m are established with the Artificial Neural Network method. The results demonstrate that the non-linear dynamic response and damage of the high arch dam under the far-field underwater blast are significantly influenced by the foundation plasticity, especially for vibration upstream and damage of the foundation face. The explosive situations with an explosive distance of 50–100 m and explosive weight of more than 12000 kg cause a greater threat to the security of the high arch dam with the probability of severe damage approaching 100 %. The explosive situations with an explosive distance of more than 150 m or explosive weight of less than 3000 kg have a small effect. The research results can be used as a reference when conducting safety assessments of high arch dams to blasting loads.

MRI in Postero-Lateral Corner Injuries of the Knee Joint: Clinical-Radiological Correlation

Abstract Background The posterolateral corner (PLC) was once regarded as the “dark side of the knee” owing to the complex and variable anatomy superimposed on the inconsistent terminology used in the literature to describe the structures in this region. Aim of the Work To describe the role of MRI in assessment of posteriolateral corner injury of knee joint. Patients and Methods This cross sectional study was conducted in department of Radiology in Ain Shams University, the data collected from database to reach sample size number and enrolled data of 20 patients in period was 18-24 months. Results We were able to show that the MRI procedure we gave accurately visualises the majority of the complex individual components of the posterolateral knee, as well as damage to these structures, in this investigation. When the diagnosis of grade III injuries to the posterolateral knee is in doubt, we believe that MRI of the posterolateral knee is a useful complement to the surgeon. In our capacity to correctly diagnose damaged structures on MRI, there were no clear differences between acute and chronic knee injuries. On MRI, avulsions or tears of the direct arm or anterior arm insertion off the fibular styloid show focal discontinuity, nonvisualization, increased signal intensity, or proximal retraction, often with a contemporaneous bone avulsion. The damage pattern can also be seen in axial and sagittal views. Conclusion When posterolateral rotatory instability is suspected, the MRI approaches that described for visualizing particular injuries to the posterolateral knee will almost always reveal the bulk of the affected structures. When a posterolateral knee injury is assessed on MRI, using a special MRI protocol that covers the full fibular head and styloid on all imaging sequences will help in identifying these structures.

Characteristics of the Fault Damage Zone From High‐Resolution Seismic Imaging Along the Palos Verdes Fault, California

AbstractThe distribution and intensity of fault damage zones provides insight into fault activity and its relationship to fluid flow in the crust. Presently, measures of the in‐situ distribution of fault damage remain limited and along‐strike studies are rare. This study focuses on an offshore section Palos Verdes Fault damage zone that spans 28 km, near Los Angeles, California. To investigate the previously unresolved shallow (∼400 m below the seafloor) fault damage zone we use densely spaced (∼500 m line separation) newly collected sparker multichannel seismic lines and sub‐bottom profiles. The combination of high‐resolution acquisition methods and specialized seismic processing workflows provide improved imaging of shallow faulting. We apply a multi‐trace similarity technique to identify discontinuities in the seismic data that may be attributed to faults and fractures. This fault detection approach reveals diverse fault damage patterns on adjacent seismic profiles. However, a discernible damage zone pattern emerges by stacking multiple damage detection profiles along strike. We find that peak damage identified in this way corresponds to the active main fault strand, confirmed in this study, and thus the technique may be useful for identifying active fault strands elsewhere. Additionally, we observe that the variable width of the damage zone along strike is controlled by fault obliquity. Furthermore, our observations reveal a correlation between fault damage and seafloor fluid seeps visible in the water column, suggesting that damage plays a role in controlling fluid flow around the fault.

Physics-guided deep learning based on modal sensitivity for structural damage identification with unseen damage patterns

Recently, wide attention has been paid to develop deep learning-based models for structural damage identification. However, in most of the studies, the pure deep learning-based structural damage identification methods lack physical interpretability and scientific consistency for generalization. Therefore, although such methods can achieve good damage identification results when data with similar damage patterns used for training and testing the network model, they usually give poor predictions in the unseen domain, i.e., the network’s extrapolation ability is limited. In this research, a physics-guided deep learning neural network (PGDLNN) is proposed by incorporating the physical loss constructed by structural modal parameters sensitivity analysis into the original Convolutional Neural Network (CNN) for structural damage identification. The model’s physical interpretability is improved, which can lead to more accurate damage identification results, especially in the domain with unseen damage patterns in training the network model. Numerical and experimental studies on simply supported beams are carried out to demonstrate the feasibility and effectiveness of the proposed method. The influences of measurement noise and incomplete measurements are also investigated. The results show that the incorporation of physical knowledge to deep learning model can enhance the generalization of the network, and hence improve the accuracy of damage severity quantification. This study not only performs damage localization and quantification simultaneously using the physics-guided deep learning neural network, but also demonstrates the superiority of incorporating physical knowledge into data-driven deep learning models for structural health monitoring.

Investigating food production-associated DNA methylation changes in paleogenomes: Lack of consistent signals beyond technical noise.

The Neolithic transition introduced major diet and lifestyle changes to human populations across continents. Beyond well-documented bioarcheological and genetic effects, whether these changes also had molecular-level epigenetic repercussions in past human populations has been an open question. In fact, methylation signatures can be inferred from UDG-treated ancient DNA through postmortem damage patterns, but with low signal-to-noise ratios; it is thus unclear whether published paleogenomes would provide the necessary resolution to discover systematic effects of lifestyle and diet shifts. To address this we compiled UDG-treated shotgun genomes of 13 pre-Neolithic hunter-gatherers (HGs) and 21 Neolithic farmers (NFs) individuals from West and North Eurasia, published by six different laboratories and with coverage c.1×-58× (median = 9×). We used epiPALEOMIX and a Monte Carlo normalization scheme to estimate methylation levels per genome. Our paleomethylome dataset showed expected genome-wide methylation patterns such as CpG island hypomethylation. However, analyzing the data using various approaches did not yield any systematic signals for subsistence type, genetic sex, or tissue effects. Comparing the HG-NF methylation differences in our dataset with methylation differences between hunter-gatherers versus farmers in modern-day Central Africa also did not yield consistent results. Meanwhile, paleomethylome profiles did cluster strongly by their laboratories of origin. Using larger data volumes, minimizing technical noise and/or using alternative protocols may be necessary for capturing subtle environment-related biological signals from paleomethylomes.

In-situ X-ray micro-CT quantitative analysis and modelling the damage evolution in granite rock

Micro-cracking of rock is important mechanism in underground engineering and subsurface energy extraction. Understanding and modeling microcrack evolution and coalescence, and the eventual macroscopic fracture propagation is still a challenge. A micro-mechanically motivated fracture model is developed based on observation and quantitative analysis of in-situ X-CT uniaxial compression test on brittle intact rock with the resolution of 11.98 μm. We performed uniaxial compression test on a micro-granite and acquired real-time X-CT images of crack development under different loadings to investigate cracking pattern, evolution of the crack network and geometric characteristics of the cracks. The experimental results show that the nucleation of isolated microcracks is the main damage pattern before failure. The evolution of damage is subtle under moderate loading but grows stably in density until the unstable coalescence of microcracks, followed by macro-scale failure. Moreover, the damage process is initially dominated by the development of inclined cracks; when failure is approached, the development of relatively more parallel cracks gradually become predominant, indicating the damage transition nature from shear mechanism to tensile mechanism. Based on the X-CT analysis, an improved physics-informed micro-mechanical sliding model is proposed. Compared with previous sliding models, the crack-crack interaction is improved so that this model can well characterize the abrupt failure process. The total surface area of cracks is used to quantify the damage evolution and a relative calibration method is presented. The simulation results show the stress–strain curve and damage evolution are consistent with the experimental results.

Graph theoretical analysis of limestone fracture network damage patterns based on uniaxial compression test

The topological attributes of fracture networks in limestone, subject to intense hydrodynamics and intricate geological discontinuities, substantially influence the mechanical and hydraulic characteristics of the rock mass. The dynamical evolution of fracture networks under stress is crucial for unveiling the interaction patterns among fractures. However, existing models are undirected graphs focused on stationary topology, which need optimization to depict fractures' dynamic development and rupture process. To compensate for the time and destruction terms, we propose the damage network model, which defines the physical interpretation of fractures through the ternary motif. We focus primarily on the evolution of node types, topological attributes, and motifs of the fracture network in limestone under uniaxial stress. Observations expose the varying behavior of the nodes' self-dynamics and neighbors' adjacent dynamics in the fracture network. This approach elucidates the impact of micro-crack behaviors on large brittle shear fractures from a topological perspective and further subdivides the progressive failure stage into four distinct phases (isolated crack growth phase, crack splay phase, damage coalescence phase, and mechanical failure phase) based on the significance profile of the motif. Regression analysis reveals a positive linear and negative power correlation between fracture network density and branch number to the rock damage resistance, respectively. The damage network model introduces a novel methodology for depicting the interaction of two-dimensional (2D) projected fractures, considering the dynamic spatiotemporal development characteristics and fracture geometric variation. It helps dynamically characterize properties such as connectivity, permeability, and damage factors while comprehensively assessing damage in rock mass fracture networks.

Radiation-induced DNA damage by proton, helium and carbon ions in human fibroblast cell: Geant4-DNA and MCDS-based study

Background. Radiation-induced DNA damages such as Single Strand Break (SSB), Double Strand Break (DSB) and Complex DSB (cDSB) are critical aspects of radiobiology with implications in radiotherapy and radiation protection applications. Materials and Methods. This study presents a thorough investigation into the effects of protons (0.1–100 MeV/u), helium ions (0.13–100 MeV/u) and carbon ions (0.5–480 MeV/u) on DNA of human fibroblast cells using Geant4-DNA track structure code coupled with DBSCAN algorithm and Monte Carlo Damage Simulations (MCDS) code. Geant4-DNA-based simulations consider 1 μm × 1 μm × 0.5 μm water box as the target to calculate energy deposition on event-by-event basis and the three-dimensional coordinates of the interaction location, and then DBSCAN algorithm is used to calculate yields of SSB, DSB and cDSB in human fibroblast cell. The study investigated the influence of Linear Energy Transfer (LET) of protons, helium ions and carbon ions on the yields of DNA damages. Influence of cellular oxygenation on DNA damage patterns is investigated using MCDS code. Results. The study shows that DSB and SSB yields are influenced by the LET of the particles, with distinct trends observed for different particles. The cellular oxygenation is a key factor, with anoxic cells exhibiting reduced SSB and DSB yields, underscoring the intricate relationship between cellular oxygen levels and DNA damage. The study introduced DSB/SSB ratio as an informative metric for evaluating the severity of radiation-induced DNA damage, particularly in higher LET regions. Conclusions. The study highlights the importance of considering particle type, LET, and cellular oxygenation in assessing the biological effects of ionizing radiation.

Development of a targeted method for DNA adductome and its application as sensitive biomarkers of ambient air pollution exposure

DNA adducts are widely recognized as biomarkers of exposure to environmental carcinogens and associated health effects in toxicological and epidemiological studies. This study presents a targeted and sensitive method for comprehensive DNA adductome analysis using ultra-high-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry (UHPLC-QqQ-MS/MS). The method was developed using calf thymus DNA, with careful optimization of mass spectrometric parameters, chromatographic separation conditions, and pretreatment methods. Ultimately, a targeted method was established for 41 DNA adducts, which showed good linearity (R2 ≥0.992), recovery (80.1–119.4 %), accuracy (81.3–117.8 %), and precision (relative standard deviation <14.2 %). The established method was employed to analyze DNA adducts in peripheral blood cells from pregnant women in Shanxi and Beijing. Up to 23 DNA adducts were successfully detected in samples of varying sizes. From 2 μg of maternal DNA samples, seven specific adducts were identified: 5-methyl-2'-deoxycytidine (5-MedC), 5-hydroxymethyl-2'-deoxycytidine (5-HmdC), N6-methyl-2'-deoxyadenosine (N6-MedA), 8-hydroxy-2'-deoxyguanosine (8-OHdG), 5-hydroxy-2'-deoxycytidine (5-OHdC), 1,N6-etheno-2'-deoxyadenosine (1,N6-εdA), and N2-methyl-2'-deoxyguanosine (N2-MedG). This study reveals that exposure to higher concentrations of ambient air pollutants may elevate the levels of DNA methylation and oxidative damage at different base sites, highlighting the application potential of DNA adducts as sensitive biomarkers of air pollution exposure.

Comparison of simplified bone-screw interface models in materially nonlinear μFE simulations

Micro finite-element (μFE) simulations serve as a crucial research tool to assist laboratory experiments in the biomechanical assessment of screw anchorage in bone. However, accurately modelling the interface between bone and screw threads at the microscale poses a significant challenge. Currently, the gold-standard approach involves employing computationally intensive physical contact models to simulate this interface. This study compared nonlinear μFE predictions of deformations, whole-construct stiffness, maximum force and damage patterns of three different computationally efficient simplified interface approaches to the general contact interface in Abaqus Explicit, which was defined as gold-standard and reference model. The μCT images (resolution: 32.8 μm) of two human radii with varying bone volume fractions were utilized and a screw was virtually inserted up to 50% and 100% of the volar-dorsal cortex distance. Materially nonlinear μFE models were generated and loaded in tension, compression and shear. In a first step, the common simplification of using a fully-bonded interface was compared to the general contact interface, revealing overestimations of whole-construct stiffness (19% on average) and maximum force (26% on average), along with inaccurate damage pattern replications. To enhance predictions, two additional simplified interface models were compared: tensionally strained element deletion (TED) and a novel modification of TED (TED-M). TED deletes interface elements strained in tension based on a linear-elastic simulation before the actual simulation. TED-M extends the remaining contact interface of TED by incorporating neighboring elements to the contact area. Both TED and TED-M reduced the errors in whole-construct stiffness and maximum force and improved the replication of the damage distributions in comparison to the fully-bonded approach. TED was better in predicting whole-construct stiffness (average error of 1%), while TED-M showed lowest errors in maximum force (1% on average). In conclusion, both TED and TED-M offer computationally efficient alternatives to physical contact modelling, although the fully-bonded interface may deliver sufficiently accurate predictions for many applications.

Microscopic deformation mechanism and characteristics of carbonaceous slate during the creep process

Carbonaceous slate exhibits a significant creep deformation that seriously affects the construction and operation of underground projects. To investigate the microstructural changes characteristics and reveal the microscopic deformation mechanism of the carbonaceous slate during the creep process, multiple methods were performed, including the triaxial creep test, SEM and MIP. The following conclusions were drawn: The rock samples underwent three stages during the creep test: microporosity closure at a low-stress level, material densification at an intermediate stress level, and microcracks emerging and expanding to failure at the high stress. The creep deformation was particularly significant in the first and third processes. The lamellar particles are compressed or bent under stress in parallel and vertical directions, showing the anisotropic properties of deformation. The deformation of the rock sample is related to the angle between the bedding and the orientation of major principal stress, and the effect of the anisotropy decreases with the increased stress level. The sprouting and expansion of microfractures occur at high-stress levels, showing pressure dissolution of mineral particles, migration of very fine particles, and cement damage between lamellar particles. Finally, the horizontal samples formed a combined rupture surface composed of the laminar surface and the fracture surface intersecting it, showing brittle damage, while the vertical samples formed a fracture surface parallel to the laminar surface, showing a ductile damage pattern. Those results could provide the basis for a further understanding of the mechanical properties of carbonaceous slate and the improvement of its creep model and parameters. It was significant for the stability analysis and deformation prediction of engineering structures using numerical simulation.

Numerical Integration Study of Penetration and Blasting Damage for Composite Underground Protective Structure with Reinforcement Layers

In response to the increasing threat of powerful earth-penetrating weapons, underground protective structures typically employ composite structural systems with reinforced steel layers. However, current numerical studies often simplify the entire structural system to plain concrete when assessing damage effects, and penetration and blasting processes are treated separately using a restart method. In this paper, we adopt an integrated simulation approach to analyze the resistance performance of composite protective structures with reinforcement layers. The results reveal significant differences in failure modes between plain concrete and reinforced concrete protective structures. The diameter of the steel bars and the spacing between mesh layers notably impact the penetration and blasting damage. Based on the results of a parameter analysis, we propose a method for optimizing the design of reinforcements in composite underground protective structures. The results of the study show the following: (1) The penetration and blast damage patterns of EPWs on plain concrete and composite protective structures with reinforcing mesh are significantly different. Compared to the plain concrete layer, the composite protection structure can effectively resist the damage of EPWs. (2) With the increase in reinforcement diameter, the decrease in reinforcement mesh spacing, and the increase in reinforcement dosage, the penetration depth gradually decreases; the amount and range of the blast damage also decrease accordingly. (3) Under the condition of the same reinforcement ratio, reducing the number of layers of reinforcement mesh, increasing the diameter of reinforcement, and configuring the reinforcement on the top of the protective structure as much as possible can improve the performance of the protective layer against penetration. At the same time, the reasonable arrangement of the reinforcement mesh can also enhance the ability of the protective structure to resist blasting damage.

An MRI evaluation of white matter involvement in paradigmatic forms of spastic ataxia: results from the multi-center PROSPAX study

BackgroundAutosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS) and Spastic Paraplegia Type 7 (SPG7) are paradigmatic spastic ataxias (SPAX) with suggested white matter (WM) involvement. Aim of this work was to thoroughly disentangle the degree of WM involvement in these conditions, evaluating both macrostructure and microstructure via the analysis of diffusion MRI (dMRI) data.Material and methodsIn this multi-center prospective study, ARSACS and SPG7 patients and Healthy Controls (HC) were enrolled, all undergoing a standardized dMRI protocol and a clinimetrics evaluation including the Scale for the Assessment and Rating of Ataxia (SARA). Differences in terms of WM volume or global microstructural WM metrics were probed, as well as the possible occurrence of a spatially defined microstructural WM involvement via voxel-wise analyses, and its correlation with patients’ clinical status.ResultsData of 37 ARSACS (M/F = 21/16; 33.4 ± 12.4 years), 37 SPG7 (M/F = 24/13; 55.7 ± 10.7 years), and 29 HC (M/F = 13/16; 42.1 ± 17.2 years) were analyzed. While in SPG7, only a mild mean microstructural damage was found compared to HC, ARSACS patients present a severe WM involvement, with a reduced global volume (p < 0.001), an alteration of all microstructural metrics (all with p < 0.001), without a spatially defined pattern of damage but with a prominent involvement of commissural fibers. Finally, in ARSACS, a correlation between microstructural damage and SARA scores was found (p = 0.004).ConclusionIn ARSACS, but not SPG7 patients, we observed a complex and multi-faced involvement of brain WM, with a clinically meaningful widespread loss of axonal and dendritic integrity, secondary demyelination and, overall, a reduction in cellularity and volume.