Damage Assessment Tool Research Articles

A neural network-based multivariate seismic classifier for simultaneous post-earthquake fragility estimation and damage classification

A scalar intensity measure (IM) could be insufficient to represent the earthquake intensity and variety in fragility estimation. Introducing multiple IMs to conventional regression of fragility functions can be computationally demanding and require priori assumptions of functional forms. In this study, multivariate seismic classifiers with multiple IMs as inputs are developed based on artificial neural networks (ANNs) to address the above disadvantages of traditional regression approaches. Case studies of a four-story code-conforming benchmark building indicate that fragility estimates from multi-IM ANN classifiers lead to higher accuracy (5.0% to 7.7%) in system-level and element-level damage classification than the single-IM traditional fragility curves. Further studies of IM combinations show that the ANN performance can be improved by more IMs correlated with structural responses while compromised by redundant irrelevant IMs. The optimal IM set should be determined by correlation ranking and ANN predictive performance together. Moreover, the ANN configuration of the case-study building is optimized with five readily available IMs as inputs, which enable a near real-time (within 0.3 ms) prediction of future earthquake damage while maintain high predictive performance. Overall, the multivariate ANN seismic classifier can be a promising tool for simultaneous seismic fragility estimation and damage assessment.

Use of UAV-based photogrammetry products for semi-automatic detection and classification of asphalt road damage in landslide-affected areas

Transportation networks are severely affected by natural hazards, including landslides. The prioritization of maintenance works is required to preserve the efficiency and functionality of road infrastructure. To overcome the subjectivity of traditional visual inspections for road pavement condition assessment, advanced (semi-)automatic approaches have been emerging. Still, the quantitative and objective description of damage typology and extent, and its severity classification remain the major issues for the assessment of landslide impacts on transportation routes. The objective of this work is to provide a ready-to-use tool for semi-automatic damage assessment of asphalt-paved roads in landslide-affected areas to support risk analysis and planning of mitigation measures. The use of 3D models and 2D images as reconstructed from UAV-based photogrammetry is investigated to detect longitudinal and transverse cracks on the road pavement and assess their severity in landslide areas, as a rapid, systematic, objective and less laborious alternative to traditional field surveys. A semi-automatic procedure is proposed to i) select asphalt-paved roads exposed to landslides, ii) rapidly map distresses on selected road sections, iii) quantitatively detect and describe longitudinal and transverse cracks, and iv) classify their severity according to the International Roughness Index (IRI). The procedure is applied to the Province of Como (northern Italy), where three test sites are selected for detailed analyses. The results indicate that the proposed procedure is useful for road management purposes at different levels of details by providing four outputs: i) a road damage hotspot map to detect deformations, ii) a multi-criteria binary classifier to detect pavement damage, iii) an IRI-based criterion to rate the pavement quality, and iv) a road damage severity map.

Detection and Localization of Multiple Damages through Entropy in Information Theory

According to recent works, entropy measures, and more specifically, spectral entropies, are emerging as an efficient method for the damage assessment of both mechanical systems and civil structures. Specifically, the occurrence of structural system alterations (intended in this work as stiffness reduction) can be detected as a localized change in the signal entropy. Here, the Wiener Entropy (also known as the Spectral Flatness) of strain measurements is proved as a viable tool for single and multiple damage assessment, including damage detection, localization, and severity assessment. A case study from oil & gas engineering, i.e., a finite element model of a buried steel pipeline, is utilized for this aim.

A Data-Driven Damage Assessment Tool for Truss-Type Railroad Bridges Using Train Induced Strain Time-History Response

ABSTRACT In this paper, a non-parametric damage detection method for truss-type railroad bridges is presented. The method uses operational strain time-history responses to detect damage in truss elements, and change in support behaviour. Dynamic strain time-history responses obtained under baseline and unknown-state bridge conditions are used to compute the magnitudes of differences in strain values between two successive time-steps. A new damage-sensitive feature (DSF) is proposed as the change in percentage of the square root of the sum of squared values of these magnitudes. After establishing a threshold DSF based on the baseline bridge, further structural change or damage in the bridge could be detected and located by observing the values of the DSFs. The validity of the method is investigated through finite element analysis of a steel-truss railway bridge. It is demonstrated that the proposed method yields promising results for identifying, locating, and relatively assessing the damage, and could be useful even when different operational conditions (i.e. different train speeds and loads) and measurement noise influence the strain data. Therefore, the proposed method has the potential to assist in developing effective maintenance strategies for railway bridges.

Human-machine collaboration framework for structural health monitoring and resiliency

Post-earthquake damage assessment can be significantly expedited when machine learning (ML) algorithms supported by sensing technologies are used. ML has some limitations when it comes to seismic damage assessment. ML tools require data from each class while training but in the case of seismic structural health monitoring, vibration data are usually available from the undamaged structures. In this paper, a framework called the human-machine collaboration (H-MC) is proposed. The H-MC framework combines the ML tools and human (domain) expertise for damage assessment of real instrumented buildings with only data from undamaged cases. It uses novelty detection as the ML tool and structure-specific analytical model to enable rapid damage detection. Subsequently, the framework is applied to detect damage in real instrumented buildings. The results showed that the H-MC algorithm correctly detected the damaged cases. It also labeled all the undamaged events accurately eliminating false positive detection. Furthermore, it is revealed that the resiliency of a building can be improved when the H-MC method is implemented over traditional field inspection. The proposed framework can be a viable tool for rapid post-earthquake damage assessment which is essential for improving community resiliency.

PROTOTYPING A SYSTEM OF AN EARLY BUILDING DAMAGE ASSESSMENT EFFECTED BY AN EARTHQUAKE

The main purpose of this research is to identify a level of a building damage caused by an earthquake early and in detail by utilizing an information system. Early identification of the building damage will be categorized based on three categories, namely minor damage, moderate damage and major damage. Each classification has standards and calculations set up by the government. To find out the damage categories, a current study was carried out on how to develop an information system that could be used by evaluators in determining conclusions according to observation results. Related to the research and development method, and adapting the Analysis, Design, Development, Implementation and Evaluation (ADDIE) development model, researchers collaborate between the ADDIE model and the standard building damage values decided by the government in a real time. The design of the early damage assessment tool for buildings is still under development and is still a prototype system.Keywords: Buliding Damage, Information System, ADDIE

The clock drawing test as a cognitive screening tool for assessment of hypertension-mediated brain damage

IntroductionHypertension (HTN) is the most frequent cause of subcortical vascular brain injury (VBI) and its cognitive consequences. The aims were to show the usefulness of the Clock Drawing Test (CDT) to detect cognitive impairment in hypertensive patients and to compare it with the Mini-Mental Test (MMSE). MethodsA subset of hypertensive patients of the Heart-Brain Study in Argentina was included. Demographic characteristics, vascular risk factors, blood pressure (BP) and schooling level were recorded. The MMSE and CDT tests were used for neurocognitive assessment and Hospital Anxiety Depression scale (HAD) for mood disorder evaluation. Results1414 hypertensive patients (age 59.7±13.8 years, female (62.3%). The prevalence of cognitive impairment was 20.7% (using MMSE) and 36.1% (using CDT). Among hypertensive patients with normal MMSE (>24) 29.3% had cognitive impairment (abnormal CDT). The CDT was associated with level of education but not with age or mood status. ConclusionsThe CDT is a useful screening tool to detect hypertension-mediated brain damage earlier (especially in midlife) and is more sensitive than MMSE.

Medium-Resolution Multispectral Data from Sentinel-2 to Assess the Damage and the Recovery Time of Late Frost on Vineyards

In a climate-change context, the advancement of phenological stages may endanger viticultural areas in the event of a late frost. This study evaluated the potential of satellite-based remote sensing to assess the damage and the recovery time after a late frost event in 2017 in northern Italian vineyards. Several vegetation indices (VIs) normalized on a two-year dataset (2018–2019) were compared over a frost-affected area (F) and a control area (NF) using unpaired two-sample t-test. Furthermore, the must quality data (total acidity, sugar content and pH) of F and NF were analyzed. The VIs most sensitive in the detection of frost damage were Chlorophyll Absorption Ratio Index (CARI), Enhanced Vegetation Index (EVI), and Modified Triangular Vegetation Index 1 (MTVI1) (−5.26%, −16.59%, and −5.77% compared to NF, respectively). The spectral bands Near-Infrared (NIR) and Red Edge 7 were able to identify the frost damage (−16.55 and −16.67% compared to NF, respectively). Moreover, CARI, EVI, MTVI1, NIR, Red Edge 7, the Normalized Difference Vegetation Index (NDVI) and the Modified Simple Ratio (MSR) provided precise information on the full recovery time (+17.7%, +22.42%, +29.67%, +5.89%, +5.91%, +16.48%, and +8.73% compared to NF, respectively) approximately 40 days after the frost event. The must analysis showed that total acidity was higher (+5.98%), and pH was lower (−2.47%) in F compared to NF. These results suggest that medium-resolution multispectral data from Sentinel-2 constellation may represent a cost-effective tool for frost damage assessment and recovery management.

Automatic detection of seismic damages from very high monoscopic spatial images

Remote sensing technology is increasingly becoming well recognized as a valuable post-earthquake damage assessment tool. In this study, this tool is used to derive an automatic determination of building height, using the advantage of shadow appearance in a very high-resolution imagery produced by QuickBird satellite. In fact, the changes of building structures caused by an earthquake could affect the orientation, shape and size of its shadow and then its height. This characteristic is used to detect damages in buildings, and a classification under these damages is proposed, through the use of two panchromatic images, before and after the quake. A validation of the determination of building height has been performed through several examples. Then, building classification is performed and results obtained by this automatic procedure were in adequacy with in situ conclusion.

Non-Destructive Assessment of Heated Rc Columns Cooled by Two Cooling Methods

Fire constitutes a major hazard to the buildings. The structural members exposed to high temperatures during fire accidents. The phenomenon observed was the structural members undergo dehydration of concrete, thermal distress in the form of cracking and spalling due to excessive heating. This leads to cause degradation of concrete strength. After tackle the fire hazard, the next step is to find the suitability of the building for repair or restoration, which involves assessment of fire severity and fire damage. Nondestructive testing (NDT) is the most practical and widely used methods to obtain in place strength or even for new structure strength. It is an effective tool for damage assessment and quality assurance, as well. In this paper, reinforced concrete (RC) columns made with OPC mix and HVFA mix, exposed to high temperatures ranging from 100 to 800°C. After heating, the specimens were brought to room temperature by air cooling and water quenching methods. The specimens were tested for residual compressive strengths and material integrity of concrete columns, by non-destructive testing methods, to understand how parameters like cooling condition and exposure duration influence the mechanical properties of conventional concrete mix and fly ash concrete mix. OPC concrete mix columns performed better strengths over HVFA mix columns when they cooled by air. Whereas water quenched HVFA mix columns upkeep the concrete quality grading on comparing the OPC mix specimens.

Assessment of fatigue damage in a fully pearlitic ductile cast iron by evaluation of Acoustic Emission Entropy

The paper presents the preliminary results of Acoustic Emission (AE) tests on a peralitic ductile cast iron (DCI) subjected to fatigue tensile loading. The focus is on the evaluation of the information Entropy of the AE data, as an innovative tool for a reliable assessment of fatigue damage in DCIs. Two damage indexes are proposed for the identification of the damage evolution and for the prediction of the fracture failure.

In-Situ Dynamic Response Measurement for Damage Quantification of 3D Printed ABS Cantilever Beam under Thermomechanical Load.

Acrylonitrile butadiene styrene (ABS) offers good mechanical properties and is effective in use to make polymeric structures for industrial applications. It is one of the most common raw material used for printing structures with fused deposition modeling (FDM). However, most of its properties and behavior are known under quasi-static loading conditions. These are suitable to design ABS structures for applications that are operated under static or dead loads. Still, comprehensive research is required to determine the properties and behavior of ABS structures under dynamic loads, especially in the presence of temperature more than the ambient. The presented research was an effort mainly to provide any evidence about the structural behavior and damage resistance of ABS material if operated under dynamic load conditions coupled with relatively high-temperature values. A non-prismatic fixed-free cantilever ABS beam was used in this study. The beam specimens were manufactured with a 3D printer based on FDM. A total of 190 specimens were tested with a combination of different temperatures, initial seeded damage or crack, and crack location values. The structural dynamic response, crack propagation, crack depth quantification, and their changes due to applied temperature were investigated by using analytical, numerical, and experimental approaches. In experiments, a combination of the modal exciter and heat mats was used to apply the dynamic loads on the beam structure with different temperature values. The response measurement and crack propagation behavior were monitored with the instrumentation, including a 200× microscope, accelerometer, and a laser vibrometer. The obtained findings could be used as an in-situ damage assessment tool to predict crack depth in an ABS beam as a function of dynamic response and applied temperature.

Evaluation of the Major Steps in the Conventional Protocol for the Alkaline Comet Assay.

Single cell gel electrophoresis, also known as the comet assay, has become a widespread DNA damage assessment tool due to its sensitivity, adaptability, low cost, ease of use, and reliability. Despite these benefits, this assay has shortcomings, such as long assay running time, the manipulation of multiple slides, individually, through numerous process steps, the challenge of working in a darkened environment, and reportedly considerable inter- and intra-laboratory variation. All researchers typically perform the comet assay based upon a common core approach; however, it appears that some steps in this core have little proven basis, and may exist, partly, out of convenience, or dogma. The aim of this study was to critically re-evaluate key steps in the comet assay, using our laboratory’s protocol as a model, firstly to understand the scientific basis for why certain steps in the protocol are performed in a particular manner, and secondly to simplify the assay, and decrease the cost and run time. Here, the shelf life of the lysis and neutralization buffers, the effect of temperature and incubation period during the lysis step, the necessity for drying the slides between the electrophoresis and staining step, and the need to perform the sample workup and electrophoresis steps under subdued light were all evaluated.

Tracking fluids in multiple scattering and highly porous materials: Toward applications in non-destructive testing and seismic monitoring

Seismic and ultrasonic waves are sometimes used to track fluid injections, propagation, infiltrations in complex material, including geological and civil engineered ones. In most cases, one use the acoustic velocity changes as a proxy for water content evolution. Here we propose to test an alternative seismic or acoustic observable: the waveform decorrelation.We use a sample of compacted millimetric sand as a model medium of highly porous multiple scattering materials. We fill iteratively the sample with water, and track changes in ultrasonic waveforms acquired for each water level. We take advantage of the high sensitivity of diffuse coda waves (late arrivals) to track small water elevation in the material. We demonstrate that in the mesoscopic regime where the wavelength, the grain size and the porosity are in the same order of magnitude, Coda Wave Decorrelation (waveform change) is more sensitive to fluid injection than Coda Wave Interferometry (apparent velocity change). This observation is crucial to interpret fluid infiltration in concrete with ultrasonic record changes, as well as fluid injection in volcanoes or snow melt infiltration in rocky glaciers. In these applications, Coda Wave Decorrelation might be an extremely interesting tool for damage assessment and alert systems.

A virtual logbook for the documentation of a continuously changing archaeological site: the San Clemente site in Albenga (Italy)

<p>Cultural and built heritage is nowadays recognized as a value not only in the socio-cultural field but also as an important economic driver. However, this non-renewable resource is more and more threatened by both external and internal factors and only by raising awareness on the vulnerability of cultural heritage we can lead to a real involvement of citizen to heritage site protection. In this sense, Virtual Museums (VMs), and more in general virtual technologies, can have a primary role to attract tourists and citizens. Indeed, VMs by presenting cultural concepts by using amusing and engaging techniques may reach younger generations in an easier way. In this paper, the specific case of the San Clemente archaeological site (Albenga, Italy) is addressed. Being the site in the riverbed of the Centa, it undergoes frequent flooding events causing continuously new damages to the archaeological site. The development of a virtual logbook of the site is presented along with the pre-processing steps that are necessary for the preparation of the published material. The logbook is addressed on one side to professionals (i.e. archaeologists and practitioners in cultural heritage) with the main aim of providing a tool for quick damage assessment. On the other side, a mobile app is on development for tourists and citizens allowing virtual exportation of the site and providing informative contents about it.</p><p><strong>Highlights:</strong></p><ul><li><p>Virtual museums and virtual environments are fundamental tools to raise awareness about the vulnerability of archaeological sites.</p></li><li><p>This paper presents the development of a virtual logbook, that can be used by experts and tourists, for the archaeological site of San Clemente (Albenga).</p></li><li><p>Integration of data coming from different sources is rendered into a web environment that can be easily accessed from both desktop and mobile devices.</p></li></ul>

Energy based load-impulse diagrams with multiple failure modes for blast-loaded reinforced concrete structural elements

An energy based load-impulse diagram is an alternative of damage assessment tool for protective structures. By defining energy flow relationships, the entire domain of structural responses and corresponding damage can be characterized. The damage level or failure type of a reinforced concrete element under a specific threat or hazard (e.g. impact and blast) can be determined by examining the corresponding combination of energy input and its rate. An energy balance approach for deriving energy based load-impulse diagrams with multiple failure modes for structural elements are presented in this paper. Two different structural behaviors of reinforced concrete elements subjected to blast loads were considered (i.e. flexure and direct shear), and the energy flow in a structural system were described by proposing an energy tank analogy. The application of these approaches to the damage assessment of tested structural elements is illustrated.

Assessment of Fatigue Damage and Crack Propagation in Ceramic Matrix Composites by Infrared Thermography

The initiation and propagation of damage in SiC fiber-reinforced ceramic matrix composites under static and fatigue loads were assessed by infrared thermography (IRT). The proposed thermographic technique, operating in lock-in mode, enabled early prediction of the residual life of composites, and proved vital in the rapid determination of the materials’ fatigue limit requiring testing of a single specimen only. IRT was also utilized for quantification of crack growth in the materials under cyclic loads. The paper highlights the accuracy and versatility of IRT as a state-of-the art damage assessment tool for ceramic composites.

Ex-Vivo Porcine Skin Model for Estimation of Trapped Occupant Burn Risk in Pre- and Post-suppression Fire Environments

There are currently important questions in the fire service as to the efficacy of various fire attack methods, both in terms of rapidly suppressing the fire and for potentially impacting the burn risk for occupants in the structure. A series of 24 full-scale residential fire experiments were performed to investigate the influence of fire size and fire service water application (interior only vs exterior-to-interior fire attack) on relative risk for skin burns in trapped occupants. A novel skin damage assessment tool utilizing ex vivo porcine skin samples was developed allowing measurement of temperatures at the surface of the porcine skin and at the subcutaneous fat surrogate interface. This tool allowed, for the first time, observation that typical fire attack methods resulted in short-lived transient increases in skin surface temperatures for a simulated occupant just outside the fire room that were typically around 5°C but ranged from 0°C to 15°C for rapid fire service intervention. Minimal differences were observed between the effects of interior or exterior fire streams immediately outside of the fire room. However, these values were markedly lower than when water application was delayed. This new tool provides novel information regarding trapped occupant skin burn risk that compliments traditional fire measurement tools and may provide a platform for future study on the impact of clothing as well as model based interpretation of experimental data that more accurately captures relevant physiology.

Paediatric and adolescent rheumatic diseases: measures of disease activity.

Juvenile idiopathic arthritis, juvenile systemic lupus erythematosus and juvenile dermatomyositis are rare, chronic, multi-systemic rheumatic disorders that can be associated with significant morbidity, not only during childhood, but lifelong. Dedicated disease activity and damage assessment tools are essential to guide clinical management and perform multicentre clinical trials to ensure the best possible care and outcome for children with rheumatic diseases using an evidence-based, treat-to-target approach. This article summarizes the outcome measures most commonly used in paediatric rheumatology.

The Comet Assay: Assessment of In Vitro and In Vivo DNA Damage.

Anthropogenic activities, indiscriminate and rapid industrialization as well as pursuance of a better life has led to an increase in the concentration of chemicals, like pesticides, automobile exhausts, and new chemical entities, in the environment, which have an adverse effect on all living organisms including humans. Sensitive and robust test systems are thus required for accurate hazard identification and risk assessment. The Comet assay has been used widely as a simple, rapid, and sensitive tool for assessment of DNA damage in single cell from both in vitro and in vivo sources as well as in humans. The advantages of the in vivo Comet assay are its ability to detect DNA damage in any tissues, despite having non-proliferating cells, and its sensitivity to detect genotoxicity. The recommendations from the international workshops held for the Comet assay have resulted in establishment of guidelines, and the OECD has adopted a guideline for the in vivo Comet assay as a test for assessing DNA damage in animals. The in vitro Comet assay conducted in cultured cells can be used for screening large number of compounds and at very low concentrations. The in vitro assay has also been automated to provide a high throughput screening method for new chemical entities, as well as in environmental samples. This chapter details the in vitro Comet assay using the 96-well plate and in vivo Comet assay in multiple organs of the mouse.