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This paper presents an alternative approach to the Transformer Assessment Index (TAI) by proposing a relatively simple rating method called the Exploitation Perspective Index (EPI). The method provides two numerical indicators: the first reflects the overall technical condition of the particular unit, and the second shows the condition of the unit in the context of the entire fleet. The objective of the EPI method is to support the decision-making process regarding the technical condition assessment of each of the transformers in the target population, considering not only technical but also economic aspects of transformer maintenance. Application of the method is described step by step, including input data, parametrization of the weights, and interpretation of the output results it provides. The proposed method is evaluated by two representative use cases and compared with two other methods. As a result, EPI confirms its applicability, and it has already been successfully implemented by the electric power industry. EPI can be potentially freely adopted for any transformer fleet, as well as for the specific situation of the utility, by adjusting the relevant parameters.

This paper presents a fuzzy logic approach, a simplified and adaptable method, to determine the health index of gas-insulated switchgear (GIS) bay and their compartments. Since the traditional weighting and scoring method (WSM) is a subjective method, the fuzzy logic approach has been applied to enhance the accuracy of the health index (HI) determination by evaluating the detectable degradation and the incorporated conditional factor (CF) considering actual operating conditions and invisible ageing. The input data are first obtained from routine inspection and time-based testing and then converted to numerical values as the fuzzy logic model input to compute the component HI. The bay HI values are further calculated by applying the WSM using the obtained component of the HI. Then, the accuracy of the obtained HI of the bay has been improved by multiplying with the CF to obtain the overall bay HI values. The proposed methodology was implemented in an independent power producer in a large industrial estate in Thailand to evaluate 175 GIS bays with actual data. The results were compared against other HI evaluation techniques with a satisfactory outcome. Finally, the overall bay HI is used to prioritize maintenance activity, to effectively allocate human resources, to prevent unplanned outages, and to achieve cost-effective, condition-based maintenance.

Development of innovative solutions for the maintenance of transport infrastructure facilities is needed in order to ensure a more rational, planned and lower-cost maintenance of transport infrastructure, and to ultimately minimise the risk of catastrophic consequences. A system for an autonomous inspection of structures, based on advanced measuring methods integrated on a wall-climbing robot and an unmanned aerial vehicle, is currently developed in the scope of the ASAP project. The objective of this paper is to provide an overview and draw attention to disadvantages of conventional methods for testing materials and structures in order to assess their condition. This objective was the main motivation for forming a multidisciplinary team through the ASAP project. Possibilities and challenges in the development of an autonomous structural-assessment system are also presented in the paper, with the purpose of increasing the reliability and efficiency of systemic assessment of structures.

Aiming at the problem of randomness and uncertainty in the selection of missile in combat mission, a missile condition evaluation decision method based on test data and extended TOPSIS-grey correlation is proposed. In order to solve the problem of establishing the index system in missile condition evaluation, the state parameter space with missile degradation as the index is established based on missile test data. The extended TOPSIS and grey relational combination method is used to evaluate the missile state sequencing, which overcomes the problem that the single method is not detailed enough. In this process, the determination of index weight is considered, and the combination of fuzzy analytic hierarchy process (FAHP) and entropy weight method is used to determine the index weight, which overcomes the problem that the determination of index weight is too subjective. The method flow of missile condition assessment decision based on test data and extended TOPSIS-grey correlation is given, and the practicability and effectiveness of the method are verified by a case.

A novel strategy for condition assessment of concrete piers subjected to impact load is presented in this article. The method of estimating residual displacement (lateral displacement and rotation angle) of concrete piers using long-gauge fiber optic sensing is firstly established. Theoretical derivation reveals that there exists linear relationship between the residual average strain and lateral displacement or rotation angle of the concrete piers. Then, a scaled concrete pier subjected to impact load was designed to verify the condition assessment strategy. The damages of the pier gradually increase by changing the impact velocity of the moving vehicle. Experimental results show that the residual average strain can well reflect the location and severity of random crack damages of the pier under impact load. Meanwhile, residual lateral displacement and rotation angel distribution along the specimen can be identified using the residual average strain measured by long-gauge fiber optic sensors. In addition, hammer excitation was also conducted on the pier after each impact in order to obtain structural dynamic properties. The extracted natural frequencies can reflect global performance (boundary condition and global stiffness) of the pier at each damage state. Therefore, the presented strategy could be a new alternative for condition assessment of concrete piers or columns in civil engineering.

In this paper, the model is constructed by measuring the psychological stress condition of employees; the psychological stress condition measurement model analyzes and tests the reasons for reducing human resource turnover in enterprises. In this paper, through the research related to the problem of talent loss in enterprises, we found that enterprises of other ownership often use the talent loss early warning model, to measure the possibility of talent loss in enterprises and issue an early warning, which enables enterprises to solve the talent loss crisis in time and minimize the negative impact of talent loss on enterprises. In this paper, we analyze the causes of human resource attrition risk from a theoretical point of view, construct a system of human resource attrition risk indicators for enterprises, and explain the content of each technical indicator and its measurement method. The PLS structural equation of the HR attrition risk evaluation model is established based on the constructed risk index system. In addition, the analysis of the causes of human resources turnover risk in the company also proposes strategies to avoid and prevent the threat. The PLS structural equation evaluation model of HR turnover risk is applied to various situations of human resource management to analyze the case of the comprehensive evaluation of HR turnover risk to guide the practical application of the model. Therefore, the research results of this paper have significant reference value for enterprises to solve similar human resource attrition problems. At the same time, it will provide a reference for enterprises to improve their human resource diagnostic capability and promote the development of human resource management. [ABSTRACT FROM AUTHOR]

Measuring the furan concentration in transformer oil is one of the most common methods of monitoring and evaluating insulation paper and estimating its degree of polymerization (DP). Here, methods for measuring furan concentration, especially ultraviolet-visible (UV-Vis) spectroscopy method, are reviewed on the old transformers oil. The results show that the excessive turbidity of old oils and noise at low wavelengths are the main disadvantages of this method, which reduce the measurements accuracy. The following solutions are proposed to overcome these disadvantages: 1) diluting insulation oil with hexane to reduce absorption intensity and 2) using average absorption at a given wavelength to reduce noise impact. These solutions are applied to the oil samples of ten old distribution transformer. It is observed that the correlation between 2-furaldehyde (2-FAL) concentration and average absorption intensity in 190–600 nm wavelength range is equal to ${R}^{{2}} =0.98$. A mathematical equation for calculating 2-FAL concentration based on average absorption is presented. It has been shown that to reduce the test time, a 190–400 nm range is the optimal measurement wavelength range. The results show that the average difference between the values of DP in the proposed method and the direct measurement method is equal to 77.5. [ABSTRACT FROM AUTHOR]

The usage of polymeric insulators in transmission and distribution overhead lines for the last few decades has increased extensively. Silicone rubber (SiR) material is used enormously to make high voltage (HV) polymeric insulators. The SiR insulator provides insulation protection for overhead HV lines. The life span of the SiR insulators is shortened due to the aging effect. The progressive aging ultimately leads to the failure of the insulation system as well as the power supply. Therefore, a regular condition assessment of SiR insulators can help prevent the power system’s failures. A comprehensive study of the various types of aging processes of SiR insulators is reported in this article. Also, the comparative analysis of SiR insulators’ physical, chemical, and electrical properties under the influence of aging is reported here. The usefulness, limitation, and difficulties confronted in the existing methodologies are also reported in this article. This review article would be helpful to implement in future research for applying the HV overhead line insulator. [ABSTRACT FROM AUTHOR]

Infrastructural assets such as roads, bridges, and buildings make a considerable contribution to national economies. These assets deteriorate due to aging, environmental conditions, and other external factors. Maintaining the performance of an asset in line with rational repair strategies represents a considerable challenge for decision-makers, who may not pay attention to developing adequate maintenance plans or leave the assets unmaintained. Worldwide, organizations are under pressure to ensure the sustainability of their assets. Such organizations may burden their treasury with random maintenance operations, especially with a limited budget. This research aims to develop a generalized condition assessment approach to monitor and evaluate existing facility elements. The proposed approach represents a methodology to determine the element condition index (CI). The methodology is reinforced with an artificial neural network (ANN) model to predict the element deterioration. The performance of this model was evaluated by comparing the obtained predicted CIs with ordinary least squares (OLS) regression model results to choose the most accurate prediction technique. A case study was applied to a group of wooden doors. The ANN model showed reliable results with R2 values of 0.99, 0.98, and 0.99 for training, cross-validation, and testing sets, respectively. In contrast, the OLS model R2 value was 1.00. These results show the high prediction capability of both models with an advantage to the OLS model. Applying this approach to different elements can help decision-makers develop a preventive maintenance schedule and provide the necessary funds. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive review of moving force identification on simply supported bridges. When a vehicle moves on a bridge deck, there is a dynamic interaction force between the vehicle and the bridge deck. This dynamic interaction force is crucial for the design and condition assessment of bridges. However, this interaction force cannot be directly measured. Therefore, the indirect measurement method based on the bridge response, namely, the moving force identification method, has become an important issue in evaluating bridge condition. This paper provides a comprehensive review of current research and development activities in bridge moving force identification. First, the development and application of moving force identification are introduced. Next, the theoretical methods of bridge moving force identification are presented. Then, the robustness and accuracy of moving time-varying force identification methods are numerically simulated and compared. Finally, the characteristics of these methods are summarized, which provides a basis for selecting the suitable identification methods under different conditions and prospects of the further development of moving force identification. [ABSTRACT FROM AUTHOR]

In Near and Middle Eastern archaeology, satellite-derived digital elevation models (DEM) of medium spatial resolution (≥30 m) are mostly used to locate and map archaeological mounds (namely 'tells'), whereas high resolution DEMs (≤10 m) are still poorly exploited. To fill this gap, the 5 m resolution CartoSat-1 Euro-Maps 3D Digital Surface Model (DSM) is assessed vs. the 30 m Shuttle Radar Topography Mission (SRTM) global DEM, the Advanced Land Observing Satellite (ALOS) World 3D–30 m (AW3D30) and a 10 m COSMO-SkyMed DEM, on a test area in Wasit, southern Iraq, where the high density of tells is yet to be exhaustively documented. A total of 344 sites was mapped, with one order of magnitude improvement compared to previous mapping exercises, existing databases and historical maps. The morphometric analysis not only highlights the reliability of CartoSat-1 DSM height and volume estimates, but also suggests that, in the test area, the volume of a tell can robustly be calculated based on the simple knowledge of its basal area, following a quadratic function. Morphology and elevation of at least 53% irregularly shaped tells were impacted by anthropogenic disturbances. Morphometric indices (e.g., Topographic Position Index, DEViation from mean elevation) are a viable automated method to ease tells detection. When integrated with other satellite datasets (e.g., CORONA, Google Earth, Sentinel-2 imagery), the CartoSat-1 DSM can unveil morphological changes and support condition assessment. In Wasit, agriculture and modern development are among the major threats for tells preservation, alongside looting. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study provides the largest sediment quality assessment of lakes in the conterminous United States (U.S.). A variety of lakes (n = 1005) were selected based on the randomized, probabilistic sampling design of the broader 2017 National Lakes Assessment study. Surficial sediment samples (0-5 cm) were collected at one representative site (generally the deepest point) for each lake (n = 969). The samples were analyzed for 16 metal(loid)s, 25 polycyclic aromatic hydrocarbons (PAHs), 53 polychlorinated biphenyl (PCB) congeners, 27 legacy pesticides and metabolites, total organic carbon, and grain size. Metal(loid)s and PAHs were widely distributed due to natural and potential anthropogenic sources, with regional variations observed for lakes in the nine ecoregions encompassing the U.S. Most sites did not have detectable PCB congeners or legacy pesticides. An integrative chemical index of mean probable effect concentration quotients, composed of seven metal(loid)s and ƩPAH 13 , was used to assess sediment quality for the estimated population of 224,916 lakes in the conterminous U.S. Nationally, 26.5 % (CI of 20-33 %) of lakes were in good condition (corresponding to predicted low incidences of toxicity to benthic organisms), 69.3 % (CI of 63-76 %) of lakes were in fair condition, and 1.8 % (CI of 0.6-3 %) of lakes were in poor condition (corresponding to predicted high incidences of sediment toxicity). Unweighted metal(loid) and ƩPAH 13 concentrations were compared to lake, watershed, and land use data. Deeper lakes were significantly more contaminated (or naturally enriched) with As, Cd, Cu, Pb, Hg, Zn, and ƩPAH 13 than shallow lakes. Lakes at lower elevation were also associated with more contamination (or natural enrichment) of As, Cr, Pb, Hg, Ni, Zn, and ƩPAH 13 than higher elevation lakes. Greater contamination was associated with watersheds containing larger percentages of developed land. This study demonstrates an approach which can be used by others to assess sediment quality in their jurisdictions., (Copyright © 2024. Published by Elsevier B.V.)

The extreme weather events highlight the need to develop action concepts to maintain agricultural production security in the future. Hydrological extremes can occur within a year in the form of surplus water (i.e. inland excess water), water scarcity or even drought. These adverse effects are influenced, inhibited and also facilitated by human activity. Previously, complex amelioration interventions, including subsurface drainage, aimed to improve the productivity of agricultural areas with unfavourable water management properties. The current efficiency of the subsurface drain networks in the regulation of groundwater level or soil moisture content can be questioned from several aspects. After the end of the socialist era (after 1990s), lack of maintenance and operation tasks have become typical, and are still a problem today in Hungary. Unfortunately, there is no exact national cadastre on the tile drained areas, and data is only available to a limited extent in the original amelioration plan documentations. In the present study, we aimed to reveal the possibilities of delineating the subsurface drained areas, and to develop a new method of condition assessment. Three tile drained study sites were selected on the Great Hungarian Plain in Central Europe. Our field investigations revealed the typical problems of the drained areas: (1) excessive vegetation of the receiving channels; (2) inadequate condition of the receiving main channel bed; (3) soil compaction in multiple layers above the drainage network; and (4) poor condition of outlets of the drain pipes. The developed methodology enabled us to evaluate the soil and the surface/subsurface water of the tile drained areas, and the technical condition of the drains. The necessary action plans or treatments were also outlined to replace the unused drain networks into use. Based on the scientific literature, we also sketched the target conditions and technological solutions that are required for the installation of new drains. The organization of the derived data into a GIS database could serve as a basis for the development of a cadastre of the tile drained areas based on a regional approach.

Due to the lack of documentation on local poplar farms, 50 sample plots in Kurdistan province were random-systematically- selected and their habitat and vegetative characteristics were recorded in 2018. For quantitative vegetative traits such as tree diameter and height, 30 trees within sample plot were randomly measured and data were analyzed based on nested design (including the factors of city, poplar plot within the city and trees within the plot in the city) and for qualitative traits, their frequencies werecalculated. The results showed that 92% of the poplars in the province belonged to the Populus nigra and 8% of them belonged to P. alba. About 80% of the poplars in the province were closed crown with right trunk and 20% had a wide crown with wavy trunk and multi-stemmed. About 90% of the sproutswere directly planted with 50- 150 cm (Khalf) cuttings in groups, cultivated at the margins of the river, agriculture and garden, and were more than 6 years old. The average age of poplar stands was 17.2 years old and about 65% of them were second or third stage sprout farms. The average of ​​poplar areas was 1628 m2 with average of 1481 trees per hectare, average survival rate of trees 35.8%. The mean of tree DBH and height were 0.17 and 14.2 m, respectively and mean of tree volume and wood volume per hectare equal to 0.21 and 308.43 m3, respectively. Also, the mean of the average annual volume growth was 17.73 (range: 7.3-27.5) m3/ha and there were significant differences (p≤0.01) among the cities of the province as well as the stands in the cities for the mentioned quantitative characteristics. The results showed that the time of exploitation of the native poplar stands was 2.5 times more than modified and industrial farms, the planting density of trees was 8-10 times higher but the diameter, height and volume of wood of the native stands were 40%, 54% and 45% respectively of them. In addition, based on the results, most of poplar farms of Kurdistan province were as a complementary cultivation with traditional planting methods and low wood yield and non-competitive with conventional cultures, thus, should be improved in the wood cultivation and production programs.

The relevance. Soil-ecological potential of technogenic landscape among other components is determined by properties of lithogenic resource, which for mining areas are, primarily, heavy tonnage wastes – overburden rocks and mineral processing wastes. The purpose of this work is to assess the soil-ecological state of the natural-technical system of the tailings dump of the Kachkanarsky Ore Mining and Processing Plant and to identify prospects of ecosystems development and potential for their self-restoration. The research objectives included identification of soil formation features and determination of basic agrochemical and environmental characteristics of technogenic surface formations, assessment of their phytotoxicity, assessment of the vegetation cover condition, and identification of the need for reclamation. The object of the study is technogenic soils, which are part of the lithogenic basis of the natural and technical system of the tailings dump of the Kachkanarsky Ore Mining and Processing Plant. Methods. The study of technogenic surface formations was carried out in the areas of their removal outside the tailings dump. The field studies included general acquaintance with the area, field study of soils and technogenic surface formations, soil sampling, and study of vegetation cover of the area. Laboratory investigations were carried out in specialized laboratories using unified methods. The content of microelements was determined by ICP-MS method. Results. According to obtained results, natural and technogenic deposits represented by tailings of wet magnetic separation of sand fraction are identified as technogenic surface formations of artifact group, artiindustrates subgroup. Compared with the background soils, they are characterized by lower content of organic matter, total nitrogen, and less acidic reaction of the soil solution. They are non-saline in the content of water-soluble ions and are characterized by the admissible level of pollution by elements of hazard classes 1-2 and the absence of acute toxic effect on the studied biological test systems. Active reforestation processes on technogenic surface formations and satisfactory state of vegetation demonstrate the absence of negative effect of the mentioned deposits on the vegetation. Following revegetation of technogenic surface formations, signs of initial soil formation appear. These processes are identified by formation of forest floor, accumulation of organic matter in the upper layers, and initial differentiation of soil horizons. The soil-ecological state of the studied natural-technical system can be recognized as satisfactory. Currently, no special environmental protection measures are required to restore the soil and vegetation layer at the waste disposal sites outside the tailings management facility.

Highway agencies monitor the condition of thousands of bridge decks every year. Even though Ground Penetrating Radar (GPR) has been used in bridge-deck evaluation, Step-Frequency GPR (SF-GPR) provides advanced condition assessment yet requires extensive and complex post-processing analysis. An SF-GPR analysis system was recently developed and used for monitoring the condition of all the bridge decks in the state of Maryland. The objective of this study was to develop a bridge deck condition rating approach using fuzzy sets modeling on the SF-GPR data and analysis. The fuzzy sets membership functions needed to reflect rating score categories similar to those considered in the National Bridge Inventory (NBI) database for uniformity. Thus, the fuzzy sets modeling was built considering nine condition membership functions. The overall bridge deck condition score leading to each of the nine condition states was based on both physical and condition-related bridge deck parameters as obtained from the SF-GPR analysis. The modeling approach is presented herein, along with two bridge deck examples. The proposed novel fuzzy sets modeling can be considered for possible adoption elsewhere where similar GPR systems are used.

Mineral oil (MO) is the most popular insulating liquid that is used as an insulating and cooling medium in electrical power transformers. Indeed, for green energy and environmental protection requirements, many researchers introduced other oil types to study the various characteristics of alternative insulating oils using advanced diagnostic tools. In this regard, natural ester oil (NEO) can be considered an attractive substitute for MO. Although NEO has a high viscosity and high dielectric loss, it presents fire safety and environmental advantages over mineral oil. Therefore, the retrofilling of aged MO with fresh NEO is highly recommended for power transformers from an environmental viewpoint. In this study, two accelerated aging processes were applied to MO for 6 and 12 days to simulate MO in service for 6 and 12 years. Moreover, these aged oils were mixed with 80% and 90% fresh NEO. The dielectric strength, relative permittivity, and dissipation factor were sensed using a LCR meter and oil tester devices for all prepared samples to support the condition assessment performance of the oil mixtures. In addition, the electric field distribution was analyzed for a power transformer using the oil mixtures. Furthermore, the dynamic viscosity was measured for all insulating oil samples at different temperatures. From the obtained results, the sample obtained by mixing 90% natural ester oil with 10% mineral oil aged for 6 days is considered superior and achieves an improvement in dielectric strength and relative permittivity by approximately 43% and 48%, respectively, compared to fresh mineral oil. However, the dissipation factor was increased by approximately 20% but was at an acceptable limit. On the other hand, for the same oil sample, due to the higher molecular weight of the NEO, the viscosities of all mixtures were at a higher level than the mineral oil.

The current use of health index algorithms is mainly limited to single assessments of the unit's condition or the device comparison. The paper focuses on the changes in the health index values between the consecutive analyses. The algorithm used for this purpose was previously developed by the authors. The test group included 359 complete oil evaluation results from 86 power transformers monitored over several years. For each outcome, the influence of the sub-components of the main score was calculated. Additional health index increase simulations were performed based on the IEC 60599 standard guidelines. The highest increases and decreases in the total score were listed and analyzed to determine the main factors behind the changes. The study has shown that the changes in dissolved gases concentrations have a much more significant influence on the health index values than the changes in physicochemical properties of the oil and furfural content. Based on the magnitude of the observed changes and the simulation outcomes, the authors have proposed two assessment thresholds—the 50th percentile health index increase within a population as an alarm zone, and the 90th or 95th percentile increase as a pre-failure zone. [ABSTRACT FROM AUTHOR]

The purpose of the present study is to analyse the distribution of arsenic in the soils of the Verkhnekamskoe potassium salt deposit (Perm Krai, Russia). The danger of arsenic pollution is determined by its high toxicity and carcinogenic hazard. Being a technophilic element, arsenic enters the environment primarily as a result of mining activities. Mining and processing sites for arsenic-containing ores are the most prone to technophilic arsenic accumulation. Solid wastes from potash production also contain elevated concentrations of arsenic. The content of arsenic in soils was determined by inductively coupled plasma mass spectrometry (ICP-MS). Statistical methods were used to analyse the features of arsenic distribution in soils of background areas and potash mining areas near production facilities. Three types of landscapes were studied within each territory, which were each distinguished by the leading processes of substance migration. Arsenic concentrations in both the background areas and the potash mining territories vary considerably, ranging from n × 10−1 to n × 10. The study found no statistically significant differences in arsenic concentrations in soils of potash mining areas and background areas. Arsenic concentrations in soils from various types of landscapes also do not differ statistically. Arsenic concentrations in soils of saline areas were found to be higher than in the rest of the territories. Outside of saline areas, the identified patterns of arsenic distribution in the soils of the Verkhnekamskoe potassium salt deposit indicate that potash operations are not a determinant in the technophilic accumulation of arsenic. [ABSTRACT FROM AUTHOR]

Riparian invertebrate communities are species rich, but variability in sampling methods hampers assessment of their distributions and inference of the quality of their habitats. To reduce this variability, a standardized, multi‐method survey protocol was recently developed. Here, riparian beetle community surveys conducted before and after the protocol's introduction were used to evaluate its effectiveness in characterizing communities and in limiting variability among surveys. Use of the standardized protocol reduced variability in sampling effort, and this had a limited effect on estimates of taxonomic richness. Surveys using the protocol captured significantly more species than surveys done before its introduction, evidencing the benefits of standardized multi‐method survey protocols. Our study highlights that standardized multi‐method survey protocols may enable identification and prioritization of sites requiring management to improve habitat quality. As such, we recommend the integration of such protocols into monitoring programmes, to enhance protection of biodiverse invertebrate communities in vulnerable riparian habitats. [ABSTRACT FROM AUTHOR]

Number of tall buildings in metropolitan areas such as Istanbul increased dramatically in recent years. On the other hand, it is crucial to conduct condition assessment of such structures after an earthquake due to public safety and owner-need reasons. Structural health monitoring (SHM) enables condition assessment of structures before, during and after earthquake rapidly, remotely and objectively. SHM systems are mandatory to be installed on tall buildings in Turkey since 2019 because of their significant contribution to our understanding of dynamic behavior of tall buildings and our capability of condition monitoring. With the motivations and reasons mentioned above, three tall buildings in Istanbul have been monitored continuously by the research team led by the second author. In the first part of this paper, results from long-term monitoring of Building-3 are presented and also, identification of modal parameters before, during and after Mw 5.7 earthquake by different methods are discussed. Afterwards, a unique methodology on the development and updating of Timoshenko beam model of the building based on identification results is given. This methodology is able to estimate the accelerations of non-instrumented floors from instrumented floors; therefore, condition assessment of the building during an earthquake can be precisely performed by computing inter-story drift ratios. In addition to tracking modal values and calculating inter-story drifts, determination of wave propagation is explained as an alternative condition assessment tool. Lastly, in-house developed software platform for real-time monitoring of tall buildings is presented. [ABSTRACT FROM AUTHOR]

Crossarms are widely used in power distribution and telecommunication sectors to support overhead cables. These structures are horizontally attached to the top of vertically erected utility poles and are essential elements in connecting overhead cables to the poles. Timber is the dominantly used material type for crossarms in the existing distribution networks. Nevertheless, there are alternative crossarms made from steel, composites, polymers, and even from concrete. This paper reviews the studies on the condition assessment of timber crossarms considering the aspects of decay identification and flexural strength assessment. The limitations and shortcomings of the conventional inspection techniques for crossarms are presented. Then, the studies on the developments of non-destructive test methods to address these issues are reviewed. Further, the results from the experimental work conducted to assess the structural capacity of in-service crossarms are presented and analysed. In addition, the possible future advancements of alternative crossarm types are also discussed, considering the mechanical strength, durability performance, and sustainability aspects. This paper aims to highlight the advantages and disadvantages of different condition assessment techniques for crossarms, indicating the importance of an integrated approach combining both the conventional and non-destructive testing techniques. [ABSTRACT FROM AUTHOR]

On the territory of the Republic of Bulgaria, a total of 233 protected areas for protection of natural habitats under „Natura 2000" have been declared, which cover 30.3% of the country's area. There are 32 forest habitats, 11 of which are a priority for the European Union. In the period 2005-2006, the first stage of habitat and species mapping, including forest habitats, was carried out. Standard data forms have been prepared for each protected area. During the second stage of mapping in the period 2011-2013, a detailed determination of the boundaries of the habitats in the polygons was made. After 2020, a number of projects funded and controlled by the MoEW were launched to set specific and detailed nature protection objectives in protected areas. These objectives, in turn, must create the basis for improving the conservation status of habitats. One of the areas where field research was carried out to determine the objectives is Protected Area BG0000518 „Vartopski dol" in Vidin district. Its choice is conditioned by the fact that after the mapping of the habitats in 2012 a number of discrepancies were found - polygons are not included and unreported forest habitats in the Standard Form of the area. The zone is located in Northwestern Bulgaria, Vidin district, between the town of Dimovo and the village of Archar. The conservation status of the following forest habitats was studied in the area: *91E0 (Alluvial forests with Alnus glutinosa and Fraxinus excelsior (Alno-Pandion, Alnion incanae, Salicion albae), *91G0 (Pannonic woods with Quercus petraea and Carpinus betulus), *91H0 (Pannonian woods with Quercus pubescens), 91M0 (Pannonian-Balkanic turkey oak - sessile oak forests). The conservation status of forest habitats, which were established for the first time and are not indicated in the standard form of the area, were also studied: 9150 (Medio-European limestone beech forests of the Cephalanthero-Fagion), * 9180 (Tilio-Acerion forests of slopes, screes and ravines), 91Z0 (Moesian silver lime woods). New main threats to the habitats have been confirmed or identified and recommendations have been given for improving the conservation status of the forest habitats in the „Vartopski Dol" Protected Area. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Architecture & Civil Engineering is the property of Chang'an Daxue Zazhishe and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: Bayesian inference methods usually require numerous forward model simulations to generate converged samples. When the forward model is expensive to evaluate, it becomes a challenging problem to estimate the posterior distribution function from Bayesian inference. We propose a computationally efficient Bayesian inference method with a combination of polynomial chaos and Gibbs sampling for structural damage detection and condition assessment. The likelihood function is approximated with the polynomial chaos expansion, and the Gibbs sampling method is performed to generate the samples for the posterior distribution. In the Gibbs sampling, the forward model is not required, which reduces the computation time for Bayesian inference. The proposed Bayesian inference method is conducted to update the probability distributions of unknown structural parameters for structural condition assessment, and the observer data comprise the correlation function of the acceleration responses. The analytical formula for the correlation function of the acceleration response is also derived in this study. Both numerical studies and experimental studies were conducted to verify the accuracy and efficiency of the proposed method. The results show that the posterior distribution of unknown parameters can be successfully estimated by using the proposed method. In addition, the proposed improved Bayesian inference is robust to measurement noise. Comparison studies with the original Gibbs sampling method are presented. The results indicate that the proposed improved Bayesian inference method is about 100 times faster than the original Gibbs sampling method. [ABSTRACT FROM AUTHOR]

In this paper, an artificial intelligence (AI) system is created in order to overcome difficulties in extracting information about electrical generator stator condition from data generated during offline electrical testing. The proposed AI system will enable classification of generators and that way expose urgency for any service activity. The logic used in expert decision-making is implemented in a fuzzy expert system and tested on a database of 82 generators in Serbia's power plants. This way an objective tool is made to overcome deficiency in sharp, discrete criteria or lack of criteria in international standards. Analysis and fuzzy system rule base will be based on conclusions from official reports about each generator condition and valid international standards and recommendations. The presented methodology is used for condition-based management (CBM) and risk-based management (RBM) of generators. [ABSTRACT FROM AUTHOR]

Corrosion of reinforcement is the most significant cause of premature deterioration of reinforced concrete structures. Many of the concrete structures have been exposed to aggressive environments, suffer from durability problems, and fail to fulfil their design service life requirements. Chlorideinduced corrosion is one of the deterioration mechanisms that may reduce the service life of reinforced concrete structures. The condition assessment of a reinforced concrete structure over a period of time is useful with routine monitoring. The majority of water supply systems have some form of water storage tanks, most often constructed from reinforced concrete. These tanks are an integral part of the potable water distribution network. To ensure durability and sustainability, they should be adequately inspected and maintained. For effective and durable repairing or retrofitting of reinforced concrete tanks, the use of a suitable condition assessment system may give more sustainable results. This study aimed to propose a system to perform a condition assessment of existing reinforced concrete water retaining structures. The reinforced concrete tanks were selected in Galle, Matara, and Hambanthota districts in Sri Lanka, to perform visual inspections and non-destructive tests. The service life of reinforced concrete structures in marine environments depends on chloride-induced corrosion. Therefore, the development of the chloride penetration model is essential for its assessment. Fick's Second Law of diffusion provides a simple way to predict the chloride penetration in such situations. Therefore, an analytical method is introduced to predict the service life of reinforced concrete water retaining structures taking into account well-known corrosion models such as Fick's Second Law and the Bazant model. Both the predicted service life and the tank soundness score can be used to develop a tank remediation plan more effectively. Therefore, the repair / retrofitting methods proposed based on such assessment will be cost-effective as well as more reliable in enhancing the service life of the water retaining structures. However, modelling the service life of reinforced concrete structures is a complex process as it includes many uncertainties. [ABSTRACT FROM AUTHOR]

Health state estimation can quantitatively evaluate the current degradation state of equipment, and remaining life prediction can quantitatively predict the remaining service time of equipment. These two technologies can provide a basis for condition-based maintenance and predictive maintenance of equipment, respectively. In recent years, a large amount of research has been implemented in these two technologies. However, there is not any systematic review that covers these two technologies, and their engineering applications, comprehensively. To fill the gap, this paper makes a comparative analysis of existing health state estimation and remaining life prediction methods, and details the characteristics and limitations of various methods. The engineering applications of these two methods are summarized, and their applicable objects are briefly given. Finally, these two methods are summarized, and their feasibility for engineering application is discussed. This work provides guidance for the selection of industrial equipment health assessment and remaining life prediction methods. [ABSTRACT FROM AUTHOR]

Procedures for estimating damage and remaining bearing capacity of RC structures after fire are presented in the paper. The damage to structural RC elements of a column, beam, slab, wall, and connection details, is presented in the paper. Although RC elements are generally considered to be fire resistant, their physical and mechanical characteristics are greatly influenced by temperature, while the bearing capacity before and after fire can be determined through a number of different methods that are presented in the paper. An overview of condition assessment for RC structures after fire is proposed, and methodology for taking further action is presented.

Obtaining real time quantitative condition assessment results is a focus in the field of nuclear power system PHM. The existing researches on the nuclear power system condition assessment based on the Multi-Criteria Decision-Making framework do not consider the faults perniciousness differences. This leads to the assessment results relying on the system status deviation degrees(severity), and the weighting and aggregation processes cannot effectively reflect the differences in the consequences and risks of different faults, which represent the faults harmfulness. A quantitative assessment method based on fault severity and fault harmfulness is proposed to address this issue. The novel method quantifies the fault severity based on the similarity principle while diagnosing system faults, and then analyzes the devices mainly affected by various faults to quantifies the harmfulness. Combining the system status deviation degrees(severity), the devices and parameters importance, and the differences in faults harmfulness, the novel method aggregates comprehensive system condition assessment results. Based on a widely recognized nuclear power system faults dataset, the novel method was compared with other methods. The conclusion is that the novel method considers the differences in the faults harmfulness, resulting in more reasonable assessment results and avoiding insufficient or excessive warnings. • An novel nuclear power system quantitative condition assessment method. • The weighting and aggregation consider the faults perniciousness differences. • Avoid insufficient or excessive warnings and support efficient maintenance. [ABSTRACT FROM AUTHOR]

Water utilities stand a better chance of a smoothly run project to replace or rehabilitate pipes if they choose an approach that's the best fit for their specific circumstances. [ABSTRACT FROM AUTHOR]

Steel-concrete (SC) is a structural typology and construction method in which continuous steel plates are used on the surfaces of concrete walls or slabs, having dual role of formwork and longitudinal reinforcement. The continuous steel-plates on both sides of the concrete element improve economy by prefabrication, but hinder the use of traditional non-destructive evaluation (NDE) to assess the condition of the concrete. In this research, conventional NDE techniques were investigated with regards to their suitability for SC elements, with focus on detection of mechanical damage. Tests were performed on large-scale, mechanically damaged, SC elements. The deployed NDE methods were based on ultrasonic measurements using: the pulse echo technique; radiographic inspection; ultrasound 3D tomographer; impact-echo (IE); impulse-response (IR) and ground penetrating radar (GPR). It was assessed whether cracks of different sizes in the SC beams could be detected through the steel-plated surface. Perpendicular and oblique cracks of 0.1–2.5 mm width were studied. Results: show that ultrasonic testing and GPR were not suitable for testing through the steel surface, due to loss of the transmitted energy in the steel plates. Mechanical impact-based testing systems revealed promising results to detect cracks and de-bonding. Radiographic testing was successful in detecting the presence of cracks in cases when these had sufficient opening and length.

Decision-making in bridge management has changed considerably in the past two decades and owners are additionally considering what types of interventions to implement, but correct decisions still need certain input. In Estonia, like in many countries, bridge management is based on inventory records and condition information. The main emphasis of this investigation is on improving the regular condition assessment. More accurate non-destructive testing methods and optimised inspection scheduling are proposed, to reduce condition assessment uncertainties. A conversion matrix for translating additional assessment results to the rating scale of the current Estonian Transport Administration management system is introduced and uncertainties in the condition state are analysed probabilistically. In addition, stochastic degradation models based on existing information are investigated to help considering uncertainties as a part of the overall management process. What impact the adopting of quantitative assessment, rather than qualitative visual inspection, may have on the suggested interventions schedule is also analysed. The probabilistic characteristics of the condition profiles of the most common bridge elements are computed using Markov Chain Monte Carlo stochastic simulation. The optimisation of inspection scheduling is performed considering the uncertainty of the initial deterioration model. When a threshold value, defined by the owner, is reached, the model is updated with assessment data to maintain the level of uncertainty below that threshold. The results confirm that deviations in the degradation model and assessment results influence the bridge condition uncertainty. Likewise, times of both inspection and intervention are influenced, which will ultimately impact the overall management reliability and costs.

This paper considered integrity management (IM) based on the convergence of inspection technologies with those for defect assessment, as occurred circa 2000. A reformulation of the assessment criterion PCORRC, termed R-PCORRC, was presented, which now embeds a function of the steel’s strain-hardening response. Relative to full-scale tests for Grades from B up through and beyond X100 (L690) this criterion was shown accurate within 1%, with a low coefficient of variation of just 0.077. In contrast, B31G and Modified B31G showed significant bias, and scatter. The highly selective sometimes significant effect of width was shown to depend on the structural stiffness within the metal loss as compared to the stiffness of the pipe surrounding it. Defect assessment based on ILI of real corrosion was considered next, to identify technology gaps in the practical applications of this technology. It was apparent that improvements in MFL signal interpretation will help to resolve the issues with boxing criteria. While such concerns currently can be managed using the concept of plausible paths, as feature size and interaction are better characterized this concern will diminish. In such cases the predictive outcome of the plausible paths concept will in the limit tend toward that of B31G.The need for and benefits of accurate precise predictive schemes for metal-loss severity were illustrated. It was shown that a conservative prediction of failure pressure gives rise to a non-conservative prediction of defect size, leading to a non-conservative re-inspection interval for a pipeline. Finally, it was also shown that using an accurate scheme can result in significantly reduced maintenance, with a related benefit in a reduced scope of field digs to demonstrate the viability of inspection-based IM.

The condition of stay cables greatly affects the safety of bridges. Cable force is an important health indicator of cables, but it is difficult to directly assess the condition of a stay cable by the cable force because the cable force is affected by the operating environment including temperature and vehicles. In this paper, the condition of the stay cable is assessed by constructing a normalized sequence of the vehicle-induced cable force peaks (VICFPs) of the stay cables on the same side. The normalized sequence of the VICFPs of the same side cables is only related to the structure itself, and the damage to the cable can cause an abnormal reduction in the sequence. First, the normalized sequence of the VICFPs of the same side cables is derived and defined, and the change in the normalized sequence of the VICFPs with damage is qualitatively analyzed by a simplified mechanical model. An indicator of the change in the normalized sequences is constructed, and the condition assessment of the stay cables is realized by building the control chart of the indicator. Second, via a finite element model of a cable-stayed bridge, the sequences of different vehicle weights, different lanes, and different damage degrees are verified and analyzed. Last, the proposed method is applied to an actual bridge, and the results indicate that the proposed method has sufficient feasibility and accuracy. • The vehicle-induced cable force peak (VICFP) is derived through mechanical analysis using influence coefficients. • The effects of various damages on VICFP are distinguished by a simplified model, and a condition indicator is established. • A new method for condition assessment of stay cables is proposed by combining indicators with mean value control charts. • A vehicle-induced cable force extraction method based on local largest distribution density fitting is presented. • The numerical simulations and an engineering application are carried out to verify the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

At present, the condition assessment of transformer winding based on frequency response analysis (FRA) measurements demands skilled personnel. Despite many research efforts in the last decade, there is still no definitive methodology for the interpretation and condition assessment of transformer winding based on FRA results, and this is a major challenge for the industrial application of the FRA method. To overcome this challenge, this paper proposes a transformer condition assessment (TCA) algorithm, which is based on numerical indices, and a supervised machine learning technique to develop a method for the automatic interpretation of FRA results. For this purpose, random forest (RF) classifiers were developed for the first time to identify the condition of transformer winding and classify different faults in the transformer windings. Mainly, six common states of the transformer were classified in this research, i.e., healthy transformer, healthy transformer with saturated core, mechanically damaged winding, short-circuited winding, open-circuited winding, and repeatability issues. In this research, the data from 139 FRA measurements performed in more than 80 power transformers were used. The database belongs to the transformers having different ratings, sizes, designs, and manufacturers. The results reveal that the proposed TCA algorithm can effectively assess the transformer winding condition with up to 93% accuracy without much human intervention.