Damage State Research Articles

Integrating Building- and Site-Specific and Generic Fragility Curves into Seismic Risk Assessment: A PRISMA-Based Analysis of Methodologies and Applications

Fragility curves are fundamental tools in seismic risk assessments, providing insights into the vulnerability of structures to earthquake-induced damages. These curves, which plot the probability of a structure reaching or exceeding various damage states against earthquake intensity, are critical for developing effective modification strategies. This review aims to present the characteristics between building- and site-specific fragility curves, which incorporate detailed local characteristics, and generic fragility curves that apply broader, more generalized parameters. We utilize the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology to systematically review the literature to address key research questions about the methodological differences, applications, and implications of these curve types in assessing seismic risks. The methods involved a comprehensive search and combination of existing studies on the topic, focusing on how these curves are developed and applied in real-world scenarios. The results from this review show that building- and site-specific curves, while more precise, require extensive data and are therefore more complex and costly to develop. In contrast, generic curves, though less accurate, offer a cost-effective solution for preliminary risk assessments over large areas. The conclusions drawn from this review suggest that while each type has its merits, the choice between building- and site-specific and generic fragility curves should be guided by the specific requirements of the seismic risk assessment task, including available resources and the need for precision in the vulnerability estimations.

Research on damage identification of simply supported bridge based on effect size method for vehicle-bridge coupled vibration

Abstract This paper presents a novel bridge damage identification method employing Cohen's d as an effect size indicator, predicated on the detection of bridge damage through the coupled vibration between a vehicle and the bridge. By analyzing the dynamic response of the bridge as a vehicle passes over, this method effectively extracts the modal parameters of the bridge and facilitates the identification of bridge damage. Numerical models of the bridge under various damage conditions, including no damage, mid-span damage, and damage at the 1/4 and 3/4 span locations, have been constructed to substantiate the efficacy and precision of the effect size as a damage indicator. Furthermore, to address the challenge of accurately identifying damage at boundaries, which is often confounded by boundary effects, a boundary subdivision method has been defined for the detection of boundary damage. Through the implementation of a real-bridge test based on indirect measurement technology, the self-vibration frequency of the bridge was successfully extracted. This empirical data was then compared and analyzed against results from ANSYS numerical simulations, thereby validating the practicality and accuracy of the proposed method. In the final analysis, the influence of random traffic flow on the bridge damage identification results was examined. The findings indicate that the vibrations in simply supported beam bridges are intensified due to the impact of random traffic flow, which aids in enhancing the accuracy of damage identification. The introduction of this method provides a new quantitative tool for bridge health monitoring, enabling the rapid and accurate identification of bridge damage without interrupting traffic. It holds significant value for engineering applications in bridge maintenance and safety assessment.

Understanding Electric Current Effects on Tribological Behaviors of Instantaneous Current-Carrying Pair With Recurrence Plot

Abstract Armature–rail instantaneous current-carrying friction in electromagnetic launchers refers to a sliding electric-mechanical impact friction and transition-induced arc erosion on a millisecond time scale. To reveal the electric current (50–300 A) effects on friction behavior and wear mechanism, the instantaneous current-carrying friction tests were performed with Al 1060 and Brass H62. Given the short nonlinear friction-induced signals, the friction behavior, including the time-domain information and system state, was comprehensively analyzed via frictional sound pressure (FSP), recurrence plot (RP), and recurrence quantification analysis (RQA). The wear topography was observed and characterized by the multifractal spectrum. Recurrence analyses demonstrate that as the current increases, the nonstationarity of the system state weakens, and the complexity and unpredictability enhance. Higher currents reduce the FSP amplitude, i.e., enhance the interfacial lubrication effect, but intensify electrical wear and surface roughness. This signifies a wear mechanism transition from abrasive wear and slight adhesive wear to arc ablation, fatigue wear, and severe adhesive wear. The widening spectrum width implies that the irregularity and fluctuation of the topography are enhanced with the current. RP patterns and RQA quantifiers correlate with the wear damage state. The results provide a reference for antiwear design and online degradation tracking of the rail.

Mainshock-aftershock building fragility methodology for community resilience modeling

This study introduces a methodology for developing fragility functions that enable the assessment of seismic vulnerability and resilience at the community level for buildings subjected to mainshock-aftershock sequences. To date, this has been assessed at a single structural level or through statistical combinatorial approaches. This paper provides a solution for a suite of archetypes including ductile and non-ductile reinforced concrete frames as well as woodframe buildings. The findings highlight the central role of aftershocks in exacerbating damage states and increasing economic losses, emphasizing the importance of including these events in accurate assessments of community resilience and seismic risk. The suite of archetypes is applied at the community level using the IN-CORE platform to quantify the effect of incorporating aftershocks into community-level seismic vulnerability analyses. The ability to accurately include the effect of aftershocks within community-level risk and resilience analyses will be key to planning for earthquakes.

Research on Damage Detection of Dual-Rotor Synchronous Excitation Mine Screen Beams Based on Strain Mode Difference Vibration Mode Analysis

The frame beam structure of the mine screen, subjected to various excitations, is a critical component of mining machinery. Its stress is intricate, the operational environment is severe, and damage can lead to catastrophic failures resulting in machinery destruction and fatalities. Based on the characterization of the vibration response of mine screen frame beams with varying degrees of damage at the same location and with the same degree of damage but at different locations, this paper develops a method of strain modal difference vibration pattern analysis and damage feature extraction for the detection of structural damage in beams. This method is based on the sensitivity of the sudden change in vibration strain modal difference to small deformations. This method solves the problem of using the conventional structural finite element analysis or experimental modal analysis methods to obtain the displacement mode, intrinsic frequency, and other characteristics, which make it difficult to effectively identify the actual engineering, with the damage conditions of the damage state and damage location of the mine screen frame beam problems. The feasibility and validity of the engineering application of the concept are demonstrated through instances.

Damage Diagnostics of Miter Gates Using Domain Adaptation and Normalizing Flow-Based Likelihood-Free Inference

Miter gates are vital civil infrastructure components in inland waterway transportation networks. To provide risk-informed insights for decisions related to repair and maintenance, sensors have been installed on some miter gates for monitoring. Despite the monitoring system's ability in collecting a large volume of monitoring data, accurately diagnosing damage state in such large structures remains challenging due to the lack of labeled monitoring data, since these structures are designed with high reliability and for a long operation life. This paper addresses this challenge by proposing a damage diagnostics approach for miter gates based on domain adaptation. The proposed approach consists of two main modules. In the first module, Cycle-Consistent generative adversarial network (CycleGAN) is employed to map monitoring data of a miter gate of interest and other similar yet different miter gates into the same analysis domain. Subsequently, a normalizing flow-based likelihood-free inference model is constructed within this common domain using data from source miter gates whose damage states are labeled from historical inspections. The trained normalizing flow model is then used to predict the damage state of the target miter gate based on the translated monitoring data. A case study is presented to demonstrate the effectiveness of the proposed method. The results indicate that the proposed method in general can accurately estimate the damage state of the target miter gate in the presence of uncertainty.

Structural Damage Detection Using PZT Transmission Line Circuit Model

Arrangements of piezoelectric transducers, such as PZT (lead zirconate titanate), have been widely used in numerous structural health monitoring (SHM) applications. Usually, when two or more PZT transducers are placed close together, significant interference, namely crosstalk, appears. Such an effect is usually neglected in most SHM applications. However, it can potentially be used as a sensitive parameter to identify structural faults. Accordingly, this work proposes using the crosstalk effect in an arrangement of PZT transducers modeled as a multiconductor transmission line to detect structural damage. This effect is exploited by computing an impedance matrix representing a host structure with PZTs attached to it. The proposed method was assessed in an aluminum beam structure with two PZTs attached to it using finite element modeling in OnScale® software to simulate both healthy and damaged conditions. Similarly, experimental tests were also carried out. The results, when compared to those obtained using a traditional electromechanical impedance (EMI) method, prove that the new approach significantly improved the sensitivity of EMI-based technique in SHM applications.

Neurotrophic and synaptic effects of GnRH and/or GH upon motor function after spinal cord injury in rats

Thoracic spinal cord injury (SCI) profoundly impairs motor and sensory functions, significantly reducing life quality without currently available effective treatments for neuroprotection or full functional regeneration. This study investigated the neurotrophic and synaptic recovery potential of gonadotropin-releasing hormone (GnRH) and growth hormone (GH) treatments in ovariectomized rats subjected to thoracic SCI. Employing a multidisciplinary approach, we evaluated the effects of these hormones upon gene expression of classical neurotrophins (NGF, BDNF, and NT3) as well as indicative markers of synaptic function (Nlgn1, Nxn1, SNAP25, SYP, and syntaxin-1), together with morphological assessments of myelin sheath integrity (Klüver-Barrera staining and MBP immunoreactivity) and synaptogenic proteins (PSD95, SYP) by immunohystochemistry (IHC) , and also on the neuromotor functional recovery of hindlimbs in the lesioned animals. Results demonstrated that chronic administration of GnRH and GH induced notable upregulation in the expression of several neurotrophic and synaptogenic activity genes. Additionally, the treatment showed a significant impact on the restoration of functional synaptic markers and myelin integrity. Intriguingly, while individual GnRH application induced certain recovery benefits, the combined treatment with GH appeared to inhibit neuromotor recovery, suggesting a complex interplay in hormonal regulation post-SCI. GnRH and GH are bioactive and participate in modulating neurotrophic responses and synaptic restoration under neural damage conditions, offering insights into novel therapeutic approaches for SCI. However, the intricate effects of combined hormonal treatment accentuate the necessity for further investigation that conduce to optimal and novel therapeutic strategies for patients with spinal cord lesions.

Seismic Collapse Risk Assessment and Fragility Analysis of Reinforced Masonry Core Walls with Boundary Elements Using the FEMA P695 Methodology

In the past, the primary objective of structural design codes was centred around ensuring human life safety, with a strong focus on preventing structural collapse. This approach predominantly relied on force- or strength-based criteria as the basis for design. Nevertheless, a notable shift has occurred recently, transitioning the design philosophy from 'strength' towards a 'performance'-based approach. This shift signifies a growing recognition that strength and performance are not identical. However, to adopt the performance-based seismic design approach, it is essential to develop precise models for estimating damage and potential losses associated with various seismic force-resisting systems (SFRSs). Fragility functions are widely interpreted among the most prevalent damage and loss models. They establish a crucial link between specific demand parameters and the likelihood of exceeding various damage states. Although reinforced masonry (RM) structures have recently gained popularity, the seismic design of mid- to high-rise RM structures is still challenging because it requires a reliable SFRS capable of providing the needed ductility and capacity. Therefore, the main objective of this study is to evaluate the key seismic performance parameters (i.e., system overstrength and ductility) and to perform a collapse capacity risk assessment of reinforced masonry core walls with boundary elements (RMCW+BEs) as the main SFRS in RM structures. The current study utilizes the applied element method (AEM) implemented in the Extreme Loading for Structures software (ELS) to model three RM structures with various heights (10-, 15-, and 20-story buildings). Nonlinear pseudo- static pushover analysis was performed to quantify the ductility and overstrength of the proposed RM system following the FEMA P695 guidelines. In addition, an incremental dynamic analysis (IDA) was carried out to assess the seismic collapse risk of RMCW+BEs by generating system-level-based fragility curves. The results showed that the proposed RM system provides the needed ductility, overstrength and deformation capacity for a ductile SFRS for typical mid- and high-rise RM buildings. Furthermore, the developed collapse fragility curves verified excellent seismic performance, negligible collapse probability values and high reserved collapse capacity at the maximum considered earthquake (MCE) design level. The findings of this study significantly contribute toward adopting RMCW+BEs as an effective SFRS for typical RM buildings in the next generations of North American masonry design standards.

Estimation of Earthquake-Induced Direct Economic Losses of Portfolio Buildings Based on Seismic Fragility Surface

Regional seismic loss assessment is crucial for developing earthquake emergency plans, which can significantly reduce casualties and socioeconomic losses in urban communities. Due to the complex types of building structures in a region, it is not possible to accurately measure the damage state of building structures using a single scalar ground motion intensity measure (IM). To more accurately reflect the responses of structures under earthquake excitations, the seismic fragility surface models for 4 typical RC frame structures are developed based on the vector ground motion IMs. The results indicate that the fragility surface model offers a superior level of precision in capturing the inherent uncertainty of ground motion and subsequently determines a more precise probability of structural failure, outperforming traditional single scalar ground motion IM fragility curve models. This enhanced accuracy holds significant implications for regional loss assessment. To fully consider the spatial cross-correlation of vector ground motion IMs, based on the established ground motion database of 8778 records, principal component analysis (PCA) and geostatistical analysis methods are used to construct a spatial cross-correlation influence field that simultaneously considers multiple ground motion IMs to simulate more realistic earthquake scenarios. Considering the impact of uncertainty in loss ratio on earthquake-induced direct economic loss estimation results, the maximum entropy technique is used in conjunction with an improved Latin Hypercube Sampling (LHS) to achieve spatially uniform sampling of loss ratio (LR). This study proposes an assessment framework for regional seismic direct economic loss for portfolio buildings based on the seismic fragility surface model considering spatial cross-correlation and uncertainty of loss ratio. The proposed framework is verified by numerical examples, and it is proven that the regional portfolio buildings considering multiple ground motion IMs is more reliable and robust than those merely considering a single ground motion IM, and when spatial cross-correlation is not considered, the probability of serious economic losses will be underestimated.

PEMELIHARAAN KONSTRUKSI JALAN DENGAN METODE SDI

The Dawan-Pesinggahan Road section is one of the sections that has the status of a district road in Klungkung Regency. The Dawan Pesinggahan Road section is located in Dawan District, Dawan Village and Pesinggahan Village, which has a length of 3,300 km and an average width of 4.5 m. The Dawan – Pesinggahan Road section has existing conditions in 2021, namely 3,300 km in good condition, 0.9 km in moderate condition and there are conditions of light and heavy damage. In 2022, there will be a lot of road damage which will cause the condition of the road to decline and it is very necessary to assess the condition of the road so that we can find out what measures will be taken to restore road stability on the Dawan-Pesinggahan Road Section. Assessment of road conditions using the SDI method in Klungkung Regency was carried out on the Jl. Dawan – Stopover. The selection of this section as a sample was due to time constraints and the district road section used as a travel center in Klungkung Regency which needs to receive more attention through road management. Apart from that, the section used is a road section that visually has road damage. This research was carried out because there are still damaged roads that need to be treated quickly. This research aims to analyze road conditions, analyze the type of treatment and obtain costs for handling the road section. The data used in the research are primary data and secondary data. Primary data was obtained through a survey of road conditions by measuring road damage, while secondary data was obtained from the community development sector of the Klungkung Regency PUPRPKP Service, namely Klungkung Regency road decrees, Klungkung Regency road maps and basic Klungkung Regency road data. The research stages are, identifying road damage by taking measurements, data recapitulation by processing surveys, data analysis using the SDI method and estimating costs to repair the road. Assessment results for the Jl. Dawan – Pesinggahan Crocodile cracks at 13.54%, random cracks 18.71%, transverse cracks 17.06%, patches 14.66%, holes 12.03% and subsidence 13.24% and the estimated cost required to maintain this road section is IDR. 3,864,775,688.95

Investigation on the failure mechanism of friction-based self-centering timber beam-column joint considering bolt bearing effect: Experimental study and theoretical analyses

For friction-based self-centering timber structures, the bearing between friction bolts and the edge of holes is inevitable, due to machining inaccuracies and significant deformations at the beam-column joints. However, this issue has yet to be addressed in existing research. A limit state investigation was conducted on these friction-based self-centering timber beam-column joints under extensive deformation to analyze the failure mechanism and the loss of pretension force throughout the loading process. The influence of bolt bearing behavior on the residual deformation, loading capacity, energy dissipation capacity, and stiffness of the joint was studied. Finally, a theoretical prediction model considering single bolt and multi bolts bearing was proposed incorporating theoretical analysis and experimental results. The results indicate that the damage of the joint is concentrated on the compression deformation at the edge of bolt holes in friction pads and timber beams. The joint ultimately fails due to the end face of the column being crushed by the anchor used to fix post-tensioned (PT) strands. The joint exhibits good hysteresis characteristics within a 4 % drift and still demonstrates good recoverability within a 6 % drift. The loss rate of pretension force is below 15 % when the drift is lower than 4 %, but it increases significantly after the drift exceeds 5 %. When the drift is less than 4 %, the joints primarily exhibit single bolt bearing mode, resulting in only a slight increase in stiffness for the joints. When the drift exceeds 8 %, the joints primarily exhibit a multi bolt bearing mode, resulting in a maximum increase of approximately 64.5 % in joint stiffness. The theoretical bolt bearing model derived can better predict the position of bolts bearing the edge of holes and the damage state of friction-based self-centering timber beam-column joints.

Research on tool wear and breakage state recognition of heavy milling 508III steel based on ResNet-CBAM

Milling water chamber head material 508 III steel belongs to extreme manufacturing, and the tool failure is very serious in the process of machining. How to monitor and identify the tool wear damage state in time and effectively is a key problem to be solved urgently. Identifying chip morphology changes under machining conditions plays a very important role in characterizing tool wear and breakage. Tool wear has an important influence on the chip morphology during the process of milling 508III steel, and changes in chip morphology can also reflect the tool wear and breakage state. Therefore, this paper takes the chip morphology image as an important feature for tool wear and breakage recognition, and uses Gaussian fuzzy estimation morphology method to preprocess the chip morphology image. Build a ResNet network combined by convolutional block attention module (ResNet-CBAM) tool wear and breakage recognition model, and explore the selection of the model backbone network, determination of the ResNet backbone network depth, and fusion methods of different attention mechanisms. Through the ablation experiment and visual analysis of the attention mechanism module, it is verified that the ResNet-CBAM model proposed in this paper has an accuracy rate of 96.67% in tool wear and breakage state recognition, especially in the stage of severe tool wear and breakage. This study realizes the prediction and early warning of tool life, and provides effective guarantee for the efficient cutting of large parts of high-end equipment and the stable operation of manufacturing system.

Sub‐assemblage testing and fragility analysis of connections of continuous‐plasterboard suspended ceiling systems

AbstractPast earthquake reconnaissance reports highlighted extensive seismic damages to suspended ceiling components and connections, including instances of complete ceiling failures. The seismic qualification of these nonstructural elements typically requires comprehensive evaluation through full‐scale shake table testing. However, such experimental evaluation is ordinarily not possible for every change made in various components and connections of ceiling systems due to the cost and effort involved. A feasible alternative is to obtain the behavior of components and connections from sub‐assemblage testing and incorporate them in appropriate numerical ceiling models to derive mechanical responses for developing alternative or new installation schemes. This paper considers critical connections of three continuous‐plasterboard suspended ceiling systems that were evaluated using shake table‐generated motions. The connections were classified according to their attachment to typical floors and walls of building structures, and sub‐assemblage testing was conducted using both monotonic and cyclic displacement loading. The observed failure modes in each connection were detailed, and appropriate damage states were assigned as the basis for constructing connection fragility curves. The results of the sub‐assemblage testing were presented in terms of the hysteresis responses, envelope curves, nonlinear backbone curves, and cumulative energy dissipation curves. Additionally, multilinear models of the connections were derived by approximating nonlinear backbone curves’ initial‐ and post‐yield behaviors. These multilinear models were further idealized to derive three equivalent linearized models for simplified yet reasonably accurate results for linear structural analyses. Finally, fragility curves were derived for all connections, considering their cyclic displacement failure capacities.

Experiments for the Assessment of the Probabilistic Multistage Algorithm for Damage Detection in Flat and Curved CFRP Panels

The Probabilistic Multistage (PM) algorithm was developed by authors for identifying and localizing damages in isotropic plates. More specifically, PM algorithm consists of a fully automated probabilistic damage imaging methodology based on ultrasonic guided wave propagation and a 5-sensor array working in a pitch-catch approach. The algorithm processes the gathered data in three steps to identify key features associated with damage. The aim of this work is to assess the effectiveness of the PM algorithm on more complex structures. Specifically, the study investigates three cases of study, made of Carbon Fiber Reinforced Plastic (CFRP) composite, characterized by different geometries and layups. The algorithm is initially tested on panels with artificial damage in the form of a Teflon disk located in a specific location between the middle laminae of the panels, which is used to replicate the effect of delamination. In order to expand the experimental dataset without incurring additional costs or waste, new damage conditions are simulated by adding masses on the upper surface of the panels. Each plate is investigated considering three different damage sizes and 16 different damage locations. The proposed algorithm successfully detects damages both within and outside the sensor network. The PM algorithm produces a clear damage positioning map and a positioning (probabilistic field) range for the identified damage. This information can be used to assist operators in conducting inspections more efficiently by focusing on the highlighted areas, which may potentially lead to reduced maintenance and repair expenses.

Preharvest salicylic acid and chitosan treatments reduce red drupelet reversion and enhance antioxidant capacity in blackberry fruit

Red drupelet reversion (RDR) is a postharvest physiological disorder affecting fresh blackberries during commercialization. The drupelets revert from fully black to red, causing detriments of the commercial value. The specific mechanism is still being investigated, some reports suggest that the occurrence of RDR is associated with pigment degradation in the fruit, and can be caused or aggravated by mechanical damage and storage conditions. Even, though studies report no significant alteration in blackberry organoleptic properties caused by RDR, the visual aspect of it affects the consumer perception of the fruit quality reducing marketability and ultimately generating economic losses. In this regard, preharvest treatments have been recently reported to have positive effects in reducing RDR in blackberries. In this study, we investigated the effects of chitosan (COS) and salicylic acid (SA) as preharvest treatments on the phenolic compound content and antioxidant capacity of blackberry fruit. The results showed that SA 3 mM and COS 0.25% treatments increased the total phenolic and flavonoid content while also enhancing the antioxidant capacity of blackberries. We also observed that the content of specialized metabolites and the activity of antioxidant enzymes have a negative correlation with the occurrence of RDR in blackberries.

Transfer learning for probabilistic localization of hidden cracks in concrete structures

AbstractThe utility of discriminative supervised learning models built using multiple training-data sources is investigated for hidden crack localization in concrete. Feed-forward neural network (FFNN) is chosen as the model architecture, and transfer learning is used to assimilate the information obtained from different sources (computational physics simulations and laboratory experiments). The labeled training data consists of values of a damage index and the known locations of hidden cracks. The classification models need to learn how the presence of damage (hidden cracks) affects the damage index at different sensors for different test conditions. To this end, diagnostic FFNN models are built by sequentially adding and training new hidden layers to assimilate labeled information from computer models (different model geometries, test conditions, crack lengths, crack locations) and laboratory experiments on a plain cement slab. These transfer learning-based models are then used to localize damage in concrete specimens that reflect real-world conditions (i.e., specimens with steel reinforcement and randomly distributed aggregate). The actual damage state in these specimens is determined by extracting cores and performing petrographic studies on the extracted cores. The damage probability estimated by transfer learning-based models is compared with the petrographic damage rating index (DRI) to identify the most suitable approach to train the diagnostic models. The transfer learning-based diagnostic methodology shows promise and could be used in various structural health monitoring applications, where sufficient labeled data are typically not available from a single data source.

Efficient Structural Damage Detection with Minimal Input Data: Leveraging Fewer Sensors and Addressing Model Uncertainties

In the field of structural damage detection through vibration measurements, most existing methods demand extensive data collection, including vibration readings at multiple levels, strain data, temperature measurements, and numerous vibration modes. These requirements result in high costs and complex instrumentation processes. Additionally, many approaches fail to account for model uncertainties, leading to significant discrepancies between the actual structure and its numerical reference model, thus compromising the accuracy of damage identification. This study introduces an innovative computational method aimed at minimizing data requirements, reducing instrumentation costs, and functioning with fewer vibration modes. By utilizing information from a single vibration sensor and at least three vibration modes, the method avoids the need for higher-mode excitation, which typically demands specialized equipment. The approach also incorporates model uncertainties related to geometry and mass distribution, improving the accuracy of damage detection. The computational method was validated on a steel frame structure under various damage conditions, categorized as single or multiple damage. The results indicate up to 100% accuracy in locating damage and up to 80% accuracy in estimating its severity. These findings demonstrate the method’s potential for detecting structural damage with limited data and at a significantly lower cost compared to conventional techniques.

A novel immunopharmacological biocompound

The publication is devoted to topical issues of experimental study of new biocompounds, based on the creation of a consortium of biological composite compounds – biological active substances (metabiotics) produced by strains 59T and 60T of saprophytic compounds of the genus Bacillus subtilis. These strains are very promising for the creation of hepatopicts, new medicinal substances, in the creation and development of a new pharmacological class of hepatoprotectors. Previous studies have shown the safety and hepatoprotective effect of biologically active drugs. It is worth noting that the very effective compounds are the produced biologically active substances – metabolites of bacterial origin, on the basis of which it seems appropriate to create a new class of drugs – metabiotics. The absence of vegetative probiotic cells in such compounds will reduce the additional immune load on the body. The combined use of these compounds provides a potentiated pharmacological effect. In this regard, it seemed appropriate, under the conditions of modeling toxic liver damage by carbon tetrachloride, to conduct an experimental assessment of the immunotropic effect of biologically active substances (BAS) on laboratory animals in order to confirm the effect on cellular factors of immunity. The purpose of the study was to study the effect of the combined use of dietary supplements produced by Bacillus subtilis microorganisms on indicators of cellular immunity in laboratory animals with toxic liver damage. Acute toxic hepatitis was reproduced in white laboratory rats with repeated intragastric administration of carbon tetrachloride. The comparison drug was a registered hepatoprotective drug – ursosan. The immunotropic effect was assessed using factors such as: phagocytic activity of macrophages and neutrophils (FA), NBT test, quantitative assessment of antibody-forming cells, T and B lymphocytes. As a result of the studies performed, reliable data were obtained on an increase in the number of T and B lymphocytes, antibody-forming cells, as well as an increase in FA, which confirms the activation of all parts of cellular immunity in conditions of acute toxic liver damage. The data obtained allow us to recommend the studied biocompound for the creation of new drug candidates of microbiological origin, hepatoprotective agents with immunotropic effects.

Monitoring performance of a new smart geosynthetic under drawing test

Geosynthetics are widely used in civil engineering reinforcements owing to their high strength, acceptable toughness, and ease of transportation. However, traditional geosynthetics do not have the capability to monitor damage inside the soil. Therefore, in this paper, a new sensor-enabled piezoelectric geobelt (SPGB) is developed to measure the deformation of reinforced-soil structures. In-soil drawing tests are conducted to investigate the sensing performance of the SPGB. Variations in the voltage and impedance signals of the SPGB with the drawing displacement under different damage conditions are investigated. The results show that with the increase of drawing displacement, SPGB undergoes tensile deformation followed by pullout damage. In tensile deformation, the signal response of SPGB is related to strain. As the strain increases, the output voltage first increases and then decreases, and the impedance gradually decreases. In the pullout damage phase, the signal response of SPGB is related to the contact area between SPGB and soil. As the drawing displacement increases, the contact area between SPGB and soil gradually decreases, the output voltage gradually decreases, and the impedance gradually increases. Therefore, the SPGB, as a sensor-enabled geosynthetic, provides a reinforcing function to the soil body and simultaneously performs in-soil catastrophe identification.