Damage Patterns Research Articles

Shaking up the Neolithic - Tracing seismic impact at Neolithic Göbekli Tepe/Southeast-Türkiye

Neolithic societies were inherently vulnerable. In addition to the challenges of a changing climate and evolving subsistence strategies and social identities, Neolithic societies were also confronted with a range of natural hazards, including extreme weather events, unstable building grounds, and earthquakes. In particular, earthquakes appear to have had a significant impact on early Neolithic communities and their settlements across the Middle East. This contribution presents the findings of recent combined building archaeological and archaeoseismological research in relation to the various damage patterns observed in the built environment at Göbekli Tepe, Türkiye. Of particular interest here are the damages and anthropogenic reactions that can be linked to seismic activities during the Neolithic.

An Experimental Study and Result Analysis on the Dynamic Effective Bond Length of a Carbon Fiber-Reinforced Polymer Sheet Attached to a Concrete Surface

A carbon fiber-reinforced polymer (CFRP) is a common material utilized for the enhancement in reinforced concrete (RC) constructions. Previous research indicates that the bonding performance between a CFRP sheet and concrete determines whether the bonding of CFRP material is effective. However, the majority of existing research on the bonding performance of the CFRP–concrete interface is concentrated on static loading conditions. In order to clarify the effect of dynamic load on the bonding performance of the CFRP sheet–concrete interface, this study adopts the double-sided shear test method to carry out dynamic experimental research. The test findings reveal that the damage pattern of the CFRP sheet–concrete interface remains consistent across different loading rates. The ultimate bearing capacity increases as the strain rate increases. As the strain rate increases from 10−5 s−1 to 10−2 s−1, the effect of bond length on ultimate bearing capacity increases by about 7%. As the strain rate increases, both the maximum strain of CFRP and the maximum interfacial shear stress demonstrate a corresponding increase, with respective increase rates of 60% and 20%. The effective bond length decreases by about 20% when the strain rate rises from 10−5 s−1 to 10−2 s−1. Finally, a formula for calculating the dynamic effective bond length of a CFRP sheet, grounded in the Chen and Teng formula, has been proposed and verified.

A Disparate Disaster: Spatial Patterns of Building Damage Caused by Hurricane Ian and Associated Socio-Economic Factors

The literature shows that communities under different socio-economic conditions suffer different levels of damage in disasters. In addition to the physical intensity of hazards, such differences are also related to the varying abilities of communities to prepare for and respond to disasters. This study analyzes the spatial patterns of building damage in Hurricane Ian in 2022 and investigates the socio-economic disparities related to the damage. Specifically, this study employs NASA’s Damage Proxy Map (DPM2) to analyze spatial patterns of building damage caused by the hurricane. Then, it uses statistical analysis to assess the relationships between building damage and hurricane intensity, building conditions, and socio-economic variables at the building and census tract levels. Furthermore, the study applies geographically weighted regression (GWR) to examine the spatial variation of the damage factors. The results provide valuable insights into the potential factors related to building damage and the spatial variation in the factors. The results also reveal the uneven distribution of building damage among different population groups, implying socio-economic inequalities in disaster adaptation and resilience. Moreover, the study provides actionable information for policymakers, emergency responders, and community leaders in formulating strategies to mitigate the impact of future hurricanes by identifying vulnerable communities and population groups.

Study on Mechanical Properties of Steel-Strengthened Bamboo Beams with Webbing Opening

Bamboo beams are often reinforced with built-in steel sections to enhance their strength and load-bearing capacity. In this paper, we studied the effect of different parameters, including the location of the hole, the hole size, and the thicknesses of the steel and bamboo, on the mechanical properties of reinforced beams. The damage patterns, deformation characteristics, and force-transfer mechanisms, as well as the mechanical properties of reinforced beams with different hole shapes, underwent non-linear finite element analysis. The damage sustained by the reinforced bamboo beam differed from that of the traditional bamboo beam; two diagonal points formed a plastic hinge, mainly during the process of shear damage to the hole. It was determined that the hole size and the thickness of the bamboo have the greatest influence on the mechanical properties of the reinforced beam. The damage characteristics of the composited beams with different holes are similar; the bearing capacity of reinforced beams with open square holes is reduced by 10%–25%compared with circular holes.

Impact of Aggregation Pheromone Traps on Spatial Distribution of Halyomorpha halys Damage in Apple Orchards.

Halyomorpha halys (Stål) (Hemiptera: Pentatomidae) is an invasive pest causing significant damage to tree crops. Our study examined the impact of newly designed aggregation pheromone-baited 'mini-sailboat' (MSB) traps for controlling H. halys and its effect on the spatial distribution of fruit damage. Four replicates of four traps, with a total of 16 MSB traps, were placed along a 1.3 km border of apple orchards, concentrating the traps on one side of the orchards. A fruit damage assessment for incidence and severity was conducted at increasing distances from the orchard border where the traps were placed, encompassing 107 assessment points. Our study showed that deploying MSB traps along the orchard border significantly increased fruit damage within the first 45 m compared to control plots without traps. However, beyond the first 45 m from the border, there was a significant reduction in damage incidence. In the treated plots, 50% of the damage occurred within 26 m of the traps, while in control plots, within 85 m. Shifting the fruit damage pattern means restricting the pests lingering in a narrow strip near the MSB traps, which paves the way for improved techniques to restructure the crop perimeter.

Damage evolution and acoustic emission characteristics of sandstone under different true triaxial cyclic loading and unloading modes

In the process of deep coal mining, the cyclic mining disturbance behavior produces significant cyclic loading and unloading effects, to ensure safe production in the mining area, it is necessary to study the damage characteristics and acoustic emission characteristics of the rock body under different cyclic loading and unloading effects. This study developed a TAWZ-5000/3000 rock true triaxial (disturbance) test system and used it to carry out true triaxial cyclic loading and unloading tests in different modes, with acoustic emission (AE) monitoring of the deformation and damage processes. The test results proved that a large number of cycles weakens the rock’s ability to control deformation, and this weakening ability is also related to the types of cyclic loading and unloading modes. The hysteresis loop characteristics and mechanical parameters show obvious path dependence. Based on the damage equivalence method, it is found that the absolute damage parameter increases with the increase of the number of cycles in the same mode, and the accumulation rate of the cumulative damage parameter is faster; the cumulative damage parameter in the equal amplitude cyclic loading and unloading (EAC) mode is always higher than that in the other two modes. The normalized AE ring count rate in the rock samples under cyclic loading and unloading has a significant relationship with the damage percentage, and the crack extension scale function (b-value) shows the “steady increase – strong fluctuation − significant decline” trend. By analyzing the AE characteristic parameters, namely rise time/amplitude (RA) and ringing count/duration (AF), it is found that the sandstones in EAC, graded cyclic loading and unloading (GC), and stepped cyclic loading and unloading (SC) modes are mainly damaged by tension-shear and shear, respectively. By analyzing the values of the acoustic emission parameters RA-AF, it is found that the sandstone is mainly damaged by tensile shear, tensile tension, and shear under EAC, GC, and SC modes, respectively, corresponding to the rock samples’ damage patterns. The study results have important guiding significance for preventing and controlling disasters in deep mines.

Satellite measurement of forest disturbance, recovery and deposit distribution following explosive volcanic eruptions

The characteristics and extent of forest damage, and the subsequent patterns of recovery, reflect the intensity of an explosive volcanic eruption and have the potential to be a novel proxy for eruption magnitude and impact. Using satellite measurements of vegetation damage and recovery patterns, following the 2015 explosive eruption of Calbuco, Chile, we assess the impact on surrounding temperate forests and how areas impacted by different deposit types recover post-eruption. The Calbuco eruption resulted in tephra deposition over hundreds of square kilometres, pyroclastic flows extending 6 km and lahars extending 15 km. We explore NDVI derived from optical imagery (June 2013–May 2023) as well as radar backscatter and phase coherence (October 2014–June 2023) through time series analysis, clustering and estimation of recovery timescales to find patterns in forest disturbance and recovery. We find that forest damage and recovery correspond primarily with deposit type, thickness and dispersal directions. The thickest tephra deposits (> 40 cm) correlate with the most vegetation loss, so our vegetation impact maps allow us to refine the spatial mapping of tephra fall-deposit isopachs to give a revised eruption volume of 0.28 km3. Vegetation recovery rates relate to initial impact type and intensity, but also local topography, aspect and altitude. Our results demonstrate a novel application of optical and radar satellite remote sensing to determine eruption extents and magnitudes through vegetation disturbance. We show that measuring vegetation disturbance, particularly in remote and densely vegetated environments, can help refine field-based analyses in inaccessible or intensely damaged zones.

Hyperspectral imaging for pest symptom detection in bell pepper

BackgroundThe automation of pest monitoring is highly important for enhancing integrated pest management in practice. In this context, advanced technologies are becoming increasingly explored. Hyperspectral imaging (HSI) is a technique that has been used frequently in recent years in the context of natural science, and the successful detection of several fungal diseases and some pests has been reported. Various automated measures and image analysis methods offer great potential for enhancing monitoring in practice.ResultsIn this study, the use of hyperspectral imaging over a wide spectrum from 400 to 2500 nm is investigated for noninvasive identification and the distinction of healthy plants and plants infested with Myzus persicae (Sulzer) and Frankliniella occidentalis (Pergande) on bell peppers. Pest infestations were carried out in netted areas, and images of single plants and dissected leaves were used to train the decision algorithm. Additionally, a specially modified spraying robot was converted into an autonomous platform used to carry the hyperspectral imaging system to take images under greenhouse conditions. The algorithm was developed via the XGBoost framework with gradient-boosted trees. Signals from specific wavelengths were found to be associated with the damage patterns of different insects. Under confined conditions, M. persicae and F. occidentalis infestations were distinguished from each other and from the uninfested control for single leaves. Differentiation was still possible when small whole plants were used. However, application under greenhouse conditions did not result in a good fit compared to the results of manual monitoring.ConclusionHyperspectral images can be used to distinguish sucking pests on bell peppers on the basis of single leaves and intact potted bell pepper plants under controlled conditions. Wavelength reduction methods offer options for multispectral camera usage in high-grown vegetable greenhouses. The application of automated platforms similar to the one tested in this study could be possible, but for successful pest detection under greenhouse conditions, algorithms should be further developed fully considering real-world conditions.

Multivariate and network lesion mapping reveals distinct architectures of domain-specific post-stroke cognitive impairments

BackgroundThe purpose of this study was to identify patterns of structural disconnection and multivariate lesion-behaviour relationships associated with post-stroke deficits across six commonly impacted cognitive domains: executive function, language, memory, numerical processing, praxis, and visuospatial attention. MethodsStroke survivors (n = 593) completed a brief domain-specific cognitive assessment (the Oxford Cognitive Screen (OCS)) during acute hospitalisation. Network-level and multivariate (sparce canonical correlation) lesion mapping analyses were conducted to identify focal neural correlates and distributed patterns of structural disconnection associated with impairment on each of the 16 OCS measures. ResultsNetwork-level and multivariate lesion mapping analyses identified significant correlates for 12/16 and 10/16 OCS measures, respectively which were largely consistent with correlates reported in past work. Language impairments were reliably localised to network- and voxel-level correlates centred in left fronto-temporal regions. Memory impairments were associated with disconnection in a large network of left hemisphere regions. Number processing deficits were associated with damage to voxels centred in the left insular/opercular cortex, as well as disconnection within the surrounding white matter tracts. Within the domain of attention, different subtypes of visuospatial neglect were linked to distinct but partially overlapping patterns of disconnection and voxel-level damage. Praxis impairment was not linked to any voxel-level regions but was significantly associated with disconnection within the left hemisphere dorsal attention network. ConclusionThese results highlight the utility of routine, domain-specific cognitive assessment and imaging data for theoretically-driven lesion mapping analyses, while providing novel insight into the complex anatomical correlates of common and debilitating post-stroke cognitive impairments.

Research on Polyurethane Creep Prediction Model Based on BWO-BP

Abstract Polyurethane foam materials can creep under the influence of temperature, humidity, and pressure during use, which seriously affects their safety and state of use. Therefore, studying the creep behavior of polyurethane foam materials and developing corresponding creep mechanism models have significant scientific value for understanding their damage patterns. As a type of machine learning, Backpropagation (BP) neural network can be used for data analysis. However, there are many issues when determining the network structure. Whale Optimization (BWO) algorithm, as a type of swarm intelligence algorithm, can efficiently determine the framework of the BP model. BP which has been optimized through the BWO algorithm, has been utilized to construct a model for the prediction of polyurethane’s creep failure. The optimization process has significantly lowered the mean squared error from 0.30 in the non-optimized BP model to 0.07 in the enhanced BWO-BP model, which validates the effectiveness of the proposed algorithm.

A systemic approach for assessing infrastructure component importance in hazard-prone communities

Investing in pre-event disaster mitigation interventions for physical infrastructure, such as structural retrofits and enhancements, can be costly due to limited resources. To prioritize investments, infrastructure components are ranked by their criticality within the overall system. To be effective in real-world deployment, this approach must account for the complex interactions between components, as failures can occur simultaneously across large geographical areas due to the hazard footprint. As a result, hazard-specific uncertainties and spatial correlations may lead to distinctive failure patterns. In this study, we propose a novel data-driven framework leveraging Monte Carlo simulation, that harnesses the individual realizations to capture and model realistic component damage patterns under a specified hazard scenario. This framework addresses a gap in literature by moving beyond traditional methods that often treat component failures as independent events. By capturing the interdependence between bridges, primarily through failure interactions, and system-wide effects, our method provides a more comprehensive criticality assessment. The simulation data provides a foundation for the framework, which applies to a wide variety of infrastructure networks and performance metrics. To demonstrate the method's effectiveness, a simplified transportation network from Shelby County, TN subjected to an earthquake event is analyzed. The proposed framework provides an effective approach for component ranking, suitable for decision-making where human intuition and simple methods are insufficient. Its broad applicability suggests a potential for large-scale and interdependent network problems.

Development of Johnson-Cook-Distinct Lattice Spring Model and its application in projectile penetration into metal targets

Projectile penetration into metal targets plays an important role in modern protective structure engineering, damage assessment in terrorist attacks, and car clash accident analysis, etc. The penetration process of metal target has been characterized by large deformation, high temperature, high pressure, and dynamic damage, which can be classified as a continuous-discontinuous dynamical process. To capture the dynamic responses of metal materials subjected to high-speed penetration, Johnson-Cook model has been implemented in a continuum-discrete model, namely, Distinct Lattice Spring Model (DLSM). This is achieved by redefining the constitutive model in DLSM, with plasticity hardening (plastic strain effects), strain rate, temperature, damage evolution, equation of state, etc., being taken into account, thus developing a new numerical model called JC-DLSM model. This model is validated through studying Taylor rod high-speed impact experiments, thin metal plate penetration experiments, and projectile impact experiments on titanium alloy targets. Good agreement between numerical modelling and experimental data has been achieved for all cases considered, thereby demonstrating the capability of JC-DLSM to reproduce the damage characteristics and ballistic limits of metals under high-speed impact/penetration. Then, the impacts of projectile shape, metal target surface configuration on the characteristics of penetration damage patterns have been investigated. This contributes to a better understanding of the damage mechanisms of metal targets upon penetration or impact, facilitating the computational means for analysing and optimizing the penetration resistance of protective engineering structures.

A physics-based acoustic emission energy method for mixed-mode impact damage prediction of composite laminates

In-service composite laminates are susceptible to impact-induced damage, which can substantially reduce its integrity and service life. The damage prediction remains a great challenge due to mixed damage modes and varying damage patterns. This study develops a novel acoustic emission (AE) energy method for predicting damage areas under three typical damage modes. Laboratory testing of composite laminate specimens subject to quasi-static indentation is performed in conjunction with in-situ AE monitoring to acquire AE data. By bridging two sets of energy formulations developed, namely, the one that correlates the damage area and the released strain energy of each damage mode and another that relates the released strain energy to the AE energy, an analytical model for predicting damage areas using AE energy components is derived. Proper signal procedure procedures are established to extract the energy components from AE monitoring data, and numerical and testing data are used to calibrate the model parameters. The effectiveness of the proposed model is further validated by comparing the prediction results of the damage areas with the actual damage areas of specimens tested under different indentation depths. The result indicates that the proposed AE energy method can yield reliable predictions of the damage area under mixed damage modes.

Game-Based Assessment of Peripheral Neuropathy Combining Sensor-Equipped Insoles, Video Games, and AI: Proof-of-Concept Study.

Detecting peripheral neuropathy (PNP) is crucial in preventing complications such as foot ulceration. Clinical examinations for PNP are infrequently provided to patients at high risk due to restrictions on facilities, care providers, or time. A gamified health assessment approach combining wearable sensors holds the potential to address these challenges and provide individuals with instantaneous feedback on their health status. We aimed to develop and evaluate an application that assesses PNP through video games controlled by pressure sensor-equipped insoles. In the proof-of-concept exploratory cohort study, a complete game-based framework that allowed the study participant to play 4 video games solely by modulating plantar pressure values was established in an outpatient clinic setting. Foot plantar pressures were measured by the sensor-equipped insole and transferred via Bluetooth to an Android tablet for game control in real time. Game results and sensor data were delivered to the study server for visualization and analysis. Each session lasted about 15 minutes. In total, 299 patients with diabetes mellitus and 30 with metabolic syndrome were tested using the game application. Patients' game performance was initially assessed by hypothesis-driven key capabilities that consisted of reaction time, sensation, skillfulness, balance, endurance, and muscle strength. Subsequently, specific game features were extracted from gaming data sets and compared with nerve conduction study findings, neuropathy symptoms, or disability scores. Multiple machine learning algorithms were applied to 70% (n=122) of acquired data to train predictive models for PNP, while the remaining data were held out for final model evaluation. Overall, clinically evident PNP was present in 247 of 329 (75.1%) participants, with 88 (26.7%) individuals showing asymmetric nerve deficits. In a subcohort (n=37) undergoing nerve conduction study as the gold standard, sensory and motor nerve conduction velocities and nerve amplitudes in lower extremities significantly correlated with 79 game features (|R|>0.4, highest R value +0.65; P<.001; adjusted R2=0.36). Within another subcohort (n=173) with normal cognition and matched covariates (age, sex, BMI, etc), hypothesis-driven key capabilities and specific game features were significantly correlated with the presence of PNP. Predictive models using selected game features achieved 76.1% (left) and 81.7% (right foot) accuracy for PNP detection. Multiclass models yielded an area under the receiver operating characteristic curve of 0.76 (left foot) and 0.72 (right foot) for assessing nerve damage patterns (small, large, or mixed nerve fiber damage). The game-based application presents a promising avenue for PNP screening and classification. Evaluation in expanded cohorts may iteratively optimize artificial intelligence model efficacy. The integration of engaging motivational elements and automated data interpretation will support acceptance as a telemedical application.

Ground failures and foundation performances in Adıyaman–Gölbaşı following the 6 February 2023 Kahramanmaraş–Türkiye Earthquake Sequence

The 6 February 2023 Kahramanmaraş–Türkiye earthquake sequence (M7.8 and M7.6) presents an exceptional opportunity to investigate both the effects of local soil conditions on damage patterns under strong shaking conditions and the performance of building foundations in areas that experienced ground failure. The significant ground failure and structural damage in Adıyaman–Gölbaşı triggered an intensive series of detailed reconnaissance and field surveys. This article aims to present the resulting database of observations on ground failures, building, and foundation performances. The field reconnaissance of ground failures and their effects on building performances involved aerial and walk-down surveys, including high-quality photographs taken across the town. In addition, data on building damage statistics compiled by the Ministry of Environment, Urbanization, and Climate Change were accessed and analyzed. The subsurface characteristics of the town were characterized using available data from pre-earthquake site investigation campaigns employed for town planning purposes. It is concluded that the ground failures in the town primarily resulted from soil liquefaction and cyclic softening. Most of the poor building and foundation performances and ground failures were documented in the northern part of Atatürk Boulevard, closer to the lake of Gölbaşı, where soil site characteristics were unfavorable. This revealed once again the significant effects of local soil site conditions, particularly soil liquefaction, on the intensified ground failures, foundation, and structural damage levels.

Разработка прогностической математической модели травматических повреждений печени

Intra-abdominal bleeding is a leading cause of adverse outcomes in liver trauma, underscoring the critical importance of timely surgical intervention and optimal hemostasis strategies. This study investigates the impact of liver model segmentation on the distribution of mechanical stresses during impact simulation using the finite element method. By discretizing a computer-aided design (CAD) model into finite elements of two types – 4-node linear isoparametric elements for the parenchyma and 3-node Kirchhoff plate elements for intersegmental partitions – we developed a computational liver model adequately captures the organ's anatomy. Our results show that incorporating segmentation significantly affects the simulation outcomes, enabling a more realistic assessment of tissue damage patterns upon impact. This approach facilitates the simulation of a wide range of real-world traumatic effects, allowing for arbitrary specification of impact direction, speed, and affected area. By accounting for liver segmentation, our study provides a more accurate and comprehensive understanding of traumatic liver injuries, ultimately informing clinical decision-making and improving patient outcomes.

Estimated Disease Progression Trajectory of White Matter Disruption in Unilateral Temporal Lobe Epilepsy: A Data-Driven Machine Learning Approach.

Although the involvement of progressive brain alterations in epilepsy was recently suggested, individual patients' trajectories of white matter (WM) disruption are not known. We investigated the disease progression patterns of WM damage and its associations with clinical metrics. We examined the cross-sectional diffusion tensor imaging (DTI) data of 155 patients with unilateral temporal lobe epilepsy (TLE) and 270 age/gender-matched healthy controls, and we then calculated the average fractional anisotropy (FA) values within 20 WM tracts of the whole brain. We used the Subtype and Stage Inference (SuStaIn) program to detect the progression trajectory of FA changes and investigated its association with clinical parameters including onset age, disease duration, drug-responsiveness, and the number of anti-seizure medications (ASMs). The SuStaIn algorithm identified a single subtype model in which the initial damage occurs in the ipsilateral uncinate fasciculus (UF), followed by damage in the forceps, superior longitudinal fasciculus (SLF), and anterior thalamic radiation (ATR). This pattern was replicated when analyzing TLE with hippocampal sclerosis (n = 50) and TLE with no lesions (n = 105) separately. Further-progressed stages were associated with longer disease duration (p < 0.001) and a greater number of ASMs (p = 0.001). the disease progression model based on WM tracts may be useful as a novel individual-level biomarker.

Seasonal host shifts based on midgut residues of Protaetia brevitarsis (Coleoptera: Scarabaeidae).

White-spotted flower chafer adult (Protaetia brevitarsis, Coleoptera: Scarabaeidae), a serious omnivorous pest in regions with multiple fruits and crops, was studied to gain a deeper understanding of its damage patterns. DNA molecular tracking technology was used to identify host plant residues in adult P. brevitarsis midgut, and plant species with the most availability were determined during their growing season. Combining the 2019 and 2021 results, it was found that adults in the multi-cropped area fed on 32 plant species from 23 families, with grape (Vitis vinifera, 40%), peach (Prunus perisica, 23%) and mulberry (Morus alba, 14%) making up the majority of their diet. Some adults fed on multiple plant hosts, with four species detected in one adult and two to three species detected in one-third of adults. Adults shifted among host species during the season, moving from mulberry or grape to peach and then back to grape. These results provide a scientific basis for in-depth research to develop green integrated control technologies against P. brevitarsis adults.

Interdisciplinary Management of Traumatic Injuries to the Kidneys and Urinary Tract Caused by Blunt Abdominopelvic Trauma.

Purpose: Blunt abdominopelvic trauma frequently results in injuries to the urinary organs, especially in polytrauma. The urotrauma is rarely an acute life-threatening event; however, it may lead to severe complications. Methods: This review addresses the under-representation of urological trauma management in interdisciplinary medical training and its impact on patient outcomes. It compiles evidence-based recommendations and guidelines from multiple specialties, focusing on common challenges in managing these injuries. The resource is tailored for primary care physicians in radiology, trauma surgery, internal medicine, urology, and nephrology. Results: Urinary tract injuries can occur even if the patient's condition initially appears normal. An exclusion diagnosis is obligatory by contrast medium tomography of the entire urinary tract and, if suspected, an additional uroendoscopic examination. Interventional therapy by catheterisation of the urinary tract is often required. Urosurgical treatment is not commonly needed, but when there is a demand, it must be administered via an interdisciplinary approach with visceral and trauma surgery. Over 90% of life-threatening kidney injuries (usually up to grade 4-5 AAST) are presently treated by interventional radiologists. Acute kidney injury (AKI) as a complication in trauma patients may complicate clinical management and often worsens the outcome. The incidence of trauma-associated AKI in patients admitted to an intensive care unit is high. Conclusions: Patients suffering from blunt abdominopelvic trauma should ideally be referred to certified trauma centres with subspecialised or fully specialised care provided by visceral/vascular surgery, trauma surgery, interventional radiology, urology, and nephrology. This recommendation is based on the complex nature of most damage patterns.

A unified modeling approach for concrete masonry shear walls: Conception, validation and insights

Distinct modeling strategies have been developed to simulate concrete masonry shear walls; however, each is validated with a limited number of specimens tested under identical laboratory conditions and only covers specific detailing scenarios. This research seeks a unified finite element-based modeling approach integrating macro-modeling concepts for grouted masonry (GM) regions and simplified micro-modeling for ungrouted masonry (UGM) regions. The objective is to facilitate accurate simulation of the in-plane behavior of diverse typologies of concrete masonry shear walls: unreinforced masonry (URM), fully grouted reinforced masonry (FGRM), and partially grouted reinforced masonry (PGRM). A smeared crack approach is used to capture the crushing and cracking of grouted masonry (GM) and ungrouted masonry (UGM), and interface elements are incorporated into UGM regions to model the mortar joints, resulting in a combined smeared-discrete model. The validation process comprises two levels. The first-level evaluation focuses on URM and FGRM walls, emphasizing the analysis and comparison of lateral force–displacement curves. Second-level validation is done through simulation of PGRM walls by evaluating lateral force–displacement curves, damage patterns, and reinforcement strains. The implemented modeling approach generally simulates the response of the different experimental masonry shear walls evaluated with good accuracy. A sensitivity analysis was also performed to reveal the influence of some parameters on the numerical results, providing additional perceptions into the reliability of the modeling approach. Relevant insights into the modeling approach were obtained, allowing complex phenomena in the tested walls to be simulated, thus contributing to advances in the simulation of in-plane loaded concrete masonry walls.