On-site Inspection Research Articles

Monasteries in the vicinity of Armenian capitals (7th–13th centuries ad): Archaeology of architectural and urban context

The article analyzes the spread of monasteries in the immediate vicinity or on distant approaches to two cities of Armenia of the late classical and medieval periods, considering information in the sources, the results of archaeological excavations and on-site inspections of the sites. The author reconstructs the sequence of the topography of churches and monasteries near the capitals of the country – Vagharshapat and Ani, identifying the similarities and differences between them. It is noted that the development of the system of shrines in the vicinity of Vagharshapat was determined by the very history of the establishment of Christianity. The main patrons of the church construction from the 4th to the 7th centuries AD were Catholicoses. In the vicinity of Ani, where a surge in the construction of monasteries occurred in the first half of the 11th century AD, there was no given programme, and the originators included the Bagratuni kings and influential princes. While the development of churches near Vagharshapat started under the Arsacid dynasty, continued after the abolition of their royal power, and reached its peak in the first half of the 7th century AD, the monasteries in the vicinity of Ani, founded under the Bagratids, were subsequently developed less actively. In addition, the paper also reveals the specific location of monastic complexes in the vicinity of Ani in connection with the terrain crossed strongly by gorges and the traditional concentration of towns and monasteries along the right, and less often the left, banks of the Akhuryan River. Both on the Ararat Plain and on the Shirak Plateau, the churches and complexes accompanying the capital cities transformed the landscape, so ecclesiastic architectural images marked the visual boundaries of a special, elite culture.

Application of remote sensing/GIS in the appraisal of geotechnical stability of civil engineering structures in cretaceous sedimentary units in Gombe, Northeastern, Nigeria

The increasing urbanization in Gombe township has necessitated the need for a city-wide assessment of the area to ascertain its spatial geotechnical stability. In this study, the geotechnical stability of Gombe township and environs, Northeastern, Nigeria, was appraised using the geospatial approach. Four different thematic maps (lithology, lineament, elevation, and slope) were generated in a GIS environment. Weights were allocated to the subclasses of the thematic maps based on their contribution to the stability of engineering structures. The thematic maps were integrated using ArcGIS 10.3 software to generate a geotechnical stability model of the study area, which was validated through an on-site inspection of the structures in the area. The study area was delineated into three zones: unstable (17.24%), moderate (77.2%), and stable (4.74%). The moderate zones characterised by medium elevation and slope, average lineament density, and underlain by sandstones were the predominant zones in the area. However, the stable and the unstable zones predominate in the western and eastern parts of the study area respectively. The stable zones that occur in the northwestern and southwestern zones of the study area are underlain by the Kerri-Kerri Formation while the poor and unstable areasare underlain by argillaceous materials of the Pindiga Formation. The validation of the model revealed numerous cracked buildings and bridges and a failed bridge in the unstable zones. The moderate stability zones suffer a mixed fortune, having some stable structures in some parts and failing structures in other parts. The buildings in the stable zones, however, are generally devoid of structural cracks.

Virtual reality visualisation of automatic crack detection for bridge inspection from 3D digital twin generated by UAV photogrammetry

This research develops a UAV photogrammetry methodology to generate 3D digital twins (DT) of the Elvanlı Bridge in Mersin, Turkey. These DTs are then analyzed using advanced image processing algorithms for automatic crack detection. The identified cracks were incorporated into the 3D model, creating a DT to damage-augmented digital twins (DADT). Subsequently, the DADT was rendered in virtual reality, offering an interactive alternative solution with remote access to on-site structural visual inspections in a digital environment. This approach has increased the objectivity and efficiency of inspections in the digital environment. The results demonstrate the potential of this integrated approach to enhance the accuracy and reliability of bridge inspections, reduce operational costs, and provide a comprehensive platform for structural health monitoring through non-invasive methods. The study transformative impact of combining emerging technologies such as UAV photogrammetry and VR in civil engineering, paving the way for more systematic and precise infrastructure assessments.

Unveiling the Subterranean Heritage: A Case Study of the Underground City of Kukës, Albania

Abstract This paper investigates the viability of conserving and repurposing Kukës’ underground city, which was built as a system of civil defence tunnels during the communist era in Albania. Beneath contemporary Kukës, the underground complex, which houses administrative offices and hospitals, is an important but underutilized historical and architectural asset. This study assesses the architectural elements, historical value, and present state of the tunnels using an extensive methodology that includes expert interviews, public consultations, on-site inspections, and archival research. Results highlight the site’s dual significance as a historical landmark and a possible center for innovation and tourism. The research offers strategic proposals for reviving the tunnels to strengthen the local economy, maintain cultural identity, and increase tourist attraction, drawing on foreign case studies. By promoting the inclusion of Kukës’ underground city in larger regional development projects and considering both community goals and pragmatic concerns, the article adds to the current conversations in urban planning and cultural preservation. Sustaining and repurposing Kukës’ underground city has various benefits, including enhanced cultural tourism and economic resurgence that encourage sustainable growth, the paper points out. Still, challenges like deteriorating infrastructure, security concerns, and accessibility issues must be overcome. Urban planners and politicians can apply the research’s practical implications by using it to develop a model for cultural preservation that aligns with modern social and economic goals. A sense of shared identity and legacy among the local community’s members is fostered by the initiative, which has significant social implications as well. The study has some drawbacks, including the need for significant funding and the potential for opposition from groups who do not recognize the advantages of these kinds of initiatives. To summarise, this research highlights the potential of adaptive reuse to bolster the sustainability and resilience of urban ecosystems by offering useful guidance and strategies that may be used to comparable initiatives worldwide.

A combination of XGBoost and neural network in LIBS spectrum processing for precise determination of critical elements in 620 iron ore samples of various origins

China is the worldwide largest importer of iron ores for supplying its iron and steel industries. The necessary inspections of iron ores not only concern total iron content but also involve minor elements, such as silicium, aluminum, magnesium, and calcium. Laser-induced breakdown spectroscopy (LIBS) promises in situ and on-site detection and analysis capabilities, which is required for efficient, reliable, and large-scale impartation inspections. Such opportunity represents at the same time, a challenge for the technique in terms of the quantitative analysis ability. A fundamental issue corresponds to the matrix effect in LIBS analysis due to a large diversity of iron ores in terms of mineralogical and chemical compositions. Demonstrated as effective to deal with the matrix effect in LIBS analyses of geological materials, the machine learning approach needs to be implemented within an optimized data processing pipeline, combining algorithms carefully chosen and tested. In this work, we developed a sequentially connected combination of an extreme gradient boosting (XGBoost) model and a back propagation neural network (BPNN) model, to effectively fit the functional relation between the concentrations and the spectra. The specificity of the approach consists in fitting the linear, low-order nonlinear, and high-order nonlinear terms in a sequential way to substantially improve the model prediction performances. The method has been developed and tested with a significant set of 620 collected iron ore samples of eight production countries and 35 different commercial brands, with a wide range of matrices in terms of mineralogical and chemical compositions. The samples underwent prior characterization using conventional laboratory analysis methods to establish the reference elemental concentrations. The results from this necessary step of laboratory investigation, with root mean square error for prediction (RMSEP) of 0.407 wt%, 0.372 wt%, 0.085 wt%, 0.131 wt%, and 0.114 wt%, respectively for total iron (TFe), SiO2, Al2O3, MgO, and CaO, show the potential for on-site inspections.

Consideration of the Impact of COVID-19 Crises on Radiation Safety: Focus on Regulatory Systems and Related Activities

Background: The radiation safety regulation system, characterized by its critical and domestically tailored features, encountered unexpected challenges due to coronavirus disease 2019 (COVID-19). Accordingly, each country implemented diverse measures to ensure the continuous efficacy of its regulatory system. This study investigates the responses of five institutions concerning radiation safety, collecting data aiming to enhance preparedness through systematic procedure.Materials and Methods: The data were extracted from official documents or websites of respective regulatory bodies (RBs) that discussed their responses to the radiation safety regulation system from COVID-19. From this data, it was observed that each country responded uniquely based on its specific conditions.Results and Discussion: Due to the repercussions of COVID-19, the regulatory system faced challenges, particularly regarding on-site inspections. In response, many countries published COVID-19 annual reports, with a few set up dedicated websites addressing its impact on the radiation regulatory frameworks. This data observed the distinct and situation-specific approaches adopted by each country in response to the pandemic. Notably, several nations introduced digital technologies into their regulations, including remote systems and online methods, while also customizing their regulatory systems according to respective circumstances.Conclusion: A variety of responses from the national RB regarding the radiation safety regulation system after the outbreak of COVID-19 highlight the importance of crisis preparedness and indicate that the current regulatory system could be enhanced.

Enzyme-Mediated Duplex Exponential Amplification: A New Platform for Rapid Screening of <i>Hylurgus ligniperda</i>

As the world's second largest timber importer, wood demand in China has been growing extremely rapidly, leading to an increase of 163% from 2009 to 2018. The plant quarantine pest <i>H. ligniperda Fabricius, 1787</i> is an invasive species frequently intercepted at ports. <i>H. ligniperda</i> causes damage mainly to pine and spruce. To improve the efficiency of on-site inspection and the efficacy of early detection, tight quarantine in ports, time-effective identification, and a national surveillance program for high-risk invasive bark beetles are in urgent need. In this study, a simple, fast and accurate classification method for <i>H. ligniperda </i>is established based on the enzyme-mediated duplex exponential amplification (EmDEA) technique. Partial region from <i>inhibitor of apoptosis 2</i> (<I>IAP2)</I> gene was selected as the target and 6 primer/probe combinations were designed. Through selection, the combination of 3-HY-F3, 3-HY-R2 and 3-HY-RNA5 was chosen as the final primer-probe set, as it showed the lowest Ct with highest final fluorescence signal. Method validation and specificity test using 6 other beetle species living on coniferous wood showed that this method is result reliable and specific. Through parameter analysis with positive plasmid, the detection limit was calculated to be 13.6 copies/μL (9×10<sup>-7</sup> ng DNA/ reaction), much higher than conventional molecular methods such as PCR. The whole process including isothermal amplification, data analysis, and result output can be finished in 30 min, which is highly time-effective. Besides, the operation is simple and little training is needed for non-professionals. The application prospects of this rapid screening system include customs screening in ports, wild survey in non-lab situations and early warning system development. The new analysis platform EmDEA, can also be implemented in rapid detection and identification of other forestry pests.

Analysis of user acceptance of information and communications technology for electrical safety inspection based on a choice experiment and hierarchical Bayesian model

The development of information and communications technology has resulted in changes in electrical safety inspection. Electrical safety inspectors plan to introduce smart devices that detect causes of extensive electrical fires in real time without problems of power disconnections and on-site visits. However, smart inspection is expected to encounter acceptance issues because users are unaccustomed to it and obligated to pay additional costs for device installation and data communications. This study aims to investigate smart inspection acceptance using survey data. A hierarchical Bayesian model is employed to explore the effects of users' characteristics on its acceptance. The respondents prefer attributes of smart inspection to those of the prevailing method of on-site inspection, excluding monthly inspection costs. They prefer more frequent and extensive inspections, and prefer to avoid power disconnections and physical interaction. Accordingly, the government should inform users that smart inspection is convenient and accurate. It is also attractive to users who wish to avoid on-site visits because of privacy issues. The acceptance rate can increase if the government reduces inspection costs using the existing smart devices and communications infrastructure, and offers real-time electrical safety information using smart phones and in-home displays.

On-site inspection as a tool for developing auditing skills in engineering: integrating continuous education contents into higher education programs

On-site inspection as a tool for developing auditing skills in engineering: integrating continuous education contents into higher education programs

Accident or abuse? Differential diagnosis of contact burns from radiators/heaters in children.

Contact burns in children are not uncommon and are often due to accidental contact. Medico-legal assessment is of paramount importance in these contexts to identify cases of abuse. In three cases of burns caused by contact with radiators or a portable heater -two accidental and one deliberate- thorough medico-legal assessment, combined with on-site event reconstruction, enabled accurate diagnoses. Accidental burns displayed a 'pattern' compatible with the incandescent instrument but were more irregular, with different depths and in different parts of the body. In contrast, intentional burns were uniform in depth, distribution and localisation, inconsistent with accidental events. In this context, the on-site inspection and direct evaluation of the objects involved were crucial in the medico-legal assessment. These are indispensable elements for a thorough analysis and abuse recognition.

Enhancing geotechnical damage detection with deep learning: a convolutional neural network approach.

Most natural disasters result from geodynamic events such as landslides and slope collapse. These failures cause catastrophes that directly impact the environment and cause financial and human losses. Visual inspection is the primary method for detecting failures in geotechnical structures, but on-site visits can be risky due to unstable soil. In addition, the body design and hostile and remote installation conditions make monitoring these structures inviable. When a fast and secure evaluation is required, analysis by computational methods becomes feasible. In this study, a convolutional neural network (CNN) approach to computer vision is applied to identify defects in the surface of geotechnical structures aided by unmanned aerial vehicle (UAV) and mobile devices, aiming to reduce the reliance on human-led on-site inspections. However, studies in computer vision algorithms still need to be explored in this field due to particularities of geotechnical engineering, such as limited public datasets and redundant images. Thus, this study obtained images of surface failure indicators from slopes near a Brazilian national road, assisted by UAV and mobile devices. We then proposed a custom CNN and low complexity model architecture to build a binary classifier image-aided to detect faults in geotechnical surfaces. The model achieved a satisfactory average accuracy rate of 94.26%. An AUC metric score of 0.99 from the receiver operator characteristic (ROC) curve and matrix confusion with a testing dataset show satisfactory results. The results suggest that the capability of the model to distinguish between the classes 'damage' and 'intact' is excellent. It enables the identification of failure indicators. Early failure indicator detection on the surface of slopes can facilitate proper maintenance and alarms and prevent disasters, as the integrity of the soil directly affects the structures built around and above it.

Headspace-SERS assay for early mildewing tobacco leaves

Mildewed tobacco leaves seriously impact on cigarette product quality and pose a health risk to person. However, early moldy tobacco leaves are hardly found by naked eyes in the workshop. In this work, we self-assemble AuAg nanoalloys on silicon wafers to construct Si/AuAg chips. The headspace-surface enhanced Raman scattering (SERS) protocol is developed to monitor volatile 1,2-dichloro-3-methoxybenzene (2,3-DCA) and 2,4,6-trichloroanisole (2,4,6-TCA) released from postharvest tobacco. Consequently, the visualization of the SERS peak at 1592 cm−1 assigned to ν(CC) after headspace collection for 10 min and the SERS intensity ratio of 1054 and 1035 cm−1 from 2,3-DCA and 2,4,6-TCA less than 0.5 could be used as indicators to predict early moldy tobacco. Additionally, with headspace collection time prolonging to 2 h, a SERS band at 682 cm−1 due to ν(CCl) of 2,4,6-TCA occurs, confirming the mildew of leaves. The headspace-SERS protocol paves a path for rapid and on-site inspection of the quality of tobacco leaves and cigarettes during storage with a portable Raman system.

Improving Supervisory Consultant Performance in Construction Projects: Assessments in the LKPP's SIKaP Application for Enhanced Efficiency

This article focuses on enhancing the performance of supervisory consultants in construction projects through assessments conducted in the LKPP's SIKaP application. Supervision plays a crucial role in ensuring the smooth execution of construction activities and addressing potential obstacles. The quality and safety of construction operations have become increasingly important, necessitating effective supervision. The article highlights the importance of conducting assessments to measure the success of supervisory consultants in meeting project objectives and adhering to established standards. It emphasizes the evaluation of various performance criteria, including human resources, equipment, materials, costs, time, and quality. The assessment process enables the identification of strengths and weaknesses, facilitating corrective measures and improving future performance. The article also emphasizes the interconnectedness of construction supervision and project management, with project management playing a pivotal role in achieving project goals. Communication management is highlighted as a crucial aspect for effective project execution. The regulatory framework governing technical supervision activities in construction projects is discussed, along with the roles and responsibilities of construction management and construction supervision service providers. The article emphasizes the importance of on-site inspections, project administration, progress monitoring, and quality management in construction supervision. Lastly, the article discusses the evaluation of providers' performance in goods/services procurement, emphasizing the importance of quality, cost efficiency, and adherence to standards. The implementation of the SIKaP application is seen as a means to enhance transparency, accountability, and project quality in the construction industry, fostering a culture of continuous improvement and industry benchmarking.

Compressive Strength Predictive Analysis using Spectroradiometer.

Abstract Rapid urbanization in emerging economies has prompted a focus on quality inspections of construction materials, particularly concrete. Standard tests assessing the mechanical strength of concrete involve breaking samples. Remote sensing presents an opportunity to map and monitor these materials, enabling the identification of properties like mechanical strength without causing damage. This non-destructive approach allows on-site inspection, swiftly and inexpensively, which is crucial during ongoing construction phases. Using a Field Spec® 3 spectroradiometer, spectroscopic analysis was performed to observe the spectral behavior of mechanical strengths in cement-based mortar materials based on spectral curves that were obtained from the reflected and absorbed electromagnetic radiation of the samples. This study is groundbreaking as there is no existing literature on utilizing this technique to differentiate compressive strengths of mortar cubes.

Selective detection of MnO4- in non-standard explosives by nitrogen-doped carbon quantum dots-copper complexes (NCQDs@Cu)

Nitrogen-doped carbon quantum dots (NCQDs) with bright yellow fluorescence (quantum yield of 27.3 %) were synthesized via a solvothermal method using 2,3-diaminopyridine as the carbon and nitrogen source and ethanol as the solvent. Subsequently, the NCQDs were reacted with Cu2+ in an aqueous solution, forming nitrogen-doped carbon quantum dots-copper complexes (NCQDs@Cu) with great potential for selective determination of MnO4- ions. The aqueous solution of NCQDs@Cu exhibiting a very weak fluorescence (quantum yield of 2.2 %) demonstrated a significant enhancement (quantum yield of 10.0 %) upon interaction with MnO4-(Turn-on). Furthermore, this enhancement remained unaffected by the interfering conventional or unconventional explosives, inorganic ions, and oxidants. Moreover, a good linear relationship existed between the fluorescence intensity of the NCQDs@Cu and the concentration of the permanganate ions in a range of 0 to 5 μmol/L with a detection limit of 32.4 nmol/L. Additionally, the study investigated the underlying principles of the detection mechanism using advanced technologies such as X-ray photoelectron spectroscopy(XPS), The Fourier-transform infrared (FTIR), ultraviolet visible spectrometer (UV–Vis), fluorescence spectrometer and other methods. Finally, the NCQDs@Cu were successfully applied for detecting MnO4- in simulated and actual unconventional explosives, demonstrating a good correlation with standard methods. Therefore, the developed NCQDs@Cu can be used for rapid on-site inspection in explosive incident scenarios. This new method of using carbon dots-metal complexes as fluorescent probes will also provide new ideas for researchers.

Reconstruction method for a three-demensional discrete element numerical model of landslides using an integrated multi-electrode resistivity tomography method and an unmanned aerial vehicle survey

To analyze the hazard-causing modes of landslides, this paper proposes a three-dimensional discrete element model reconstruction method that employs an unmanned aerial vehicle survey and multi-electrode resistivity tomography method. To convert the resistivity profile into a material profile, we adopt the peak of the probability density method for material classification and utilize the Haar wavelet transform for image denoising. Subsequently, inverse distance weighting interpolation and the curtain-point method are used to transform two-dimensional profiles into a 3D visualization model. Similarly, the triangular mesh boundary can be extracted from the 3D visualization model using the curtain-point method. A mapping function f including the macroscopic parameters, was defined to populate the particles within the boundaries. Using the iterative method and defining the loss function L for parameter calibration, the targeted 3D discrete element model was constructed after setting the velocity threshold. This method was applied to the Changhe landslide (September 14, 2019) in Gansu Province, China, which had a typical damaged soil layer due to earthquake and rainfall factors. The results indicate that the lower part first exhibits significant displacement, followed by the upper and middle parts, which is consistent with the on-site inspections and UAV findings.

Analysis of the Long-Term Interaction Between Molten Core and Dry Concrete at Fukushima Daiichi Unit 1

The latest investigations of Fukushima Daiichi Unit 1 have demonstrated that corium attack to the pedestal walls and pedestal floor has occurred in Fukushima Daiichi Unit 1 to a certain extent. The results of past analytical benchmarks, such as the Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) Benchmark Study of the Accident at the Fukushima Daiichi Nuclear Power Plant (BSAF project), have agreed with this finding. However, the latest investigation does not show evidence of unlimited molten core–concrete interaction (MCCI), which is one of the main discrepancies from the BSAF project. More recently a MCCI benchmark has been launched in the context of the OECD/NEA project ARC-F (Analysis of Information from Reactor Building and Containment Vessels of Fukushima Daiichi Nuclear Power Station). In the benchmark, common geometry, boundary, and initial conditions have been selected among all the participants. The results show an improved agreement among different codes for what concerns overall erosion, corium temperature, and hydrogen generation, confirming that to some extent, the earlier scatter found in these variables came from differences in the MCCI scenario modeled by each partner. However, common unlimited erosion, not observed by onsite visual inspections, is still predicted. Understanding the origin of this deviation might provide insights into boundary conditions, model drawbacks, or ill-posed assumptions that might need to be revisited (e.g. interfacial temperature, effective heat transfer coefficients, concrete heat transfer). In this paper, a summary of the overall results and a discussion of modeling and boundary conditions is presented to disclose the results of the activity and the future steps to be taken in the OECD/NEA project FACE (Fukushima Daiichi Nuclear Power Station Accident Information Collection and Evaluation).

Development of Hardware-in-the-Loop Simulation Test Bed to Verify and Validate Power Management System for LNG Carriers

Liquefied natural gas carrier (LNGC) orders are increasing owing to marine environment regulations. The complexity of the integrated system applied to shipbuilding and software errors have increased with the high degree of automation. Direct on-site inspection methods are associated with high costs and safety risks, whereas software-based simulations rely heavily on the accuracy of the models of power system components. Hardware-in-the-loop simulation (HILS) can be utilized for designing and testing intricate real-time embedded systems. Specifically, HILS offers a reliable means of evaluating power management system (PMS) performance for LNGCs, which are high-value vessels commonly used in offshore plants. This study proposes a PMS–HIL test bed comprising a power supply unit, consumer, simulation control console, and main switchboard. The proposed HILS test bed utilizes the real equipment data of the shipbuilding industry to replicate the conditions associated with actual LNGCs. The proposed system is verified and validated through a software acceptance test procedure. Additionally, load-sharing, load-dependent start, blackout prevention, and preferential tests are performed for the PMS function evaluation. Test results indicate that the proposed system has great potential for conventional PMS commissioning. Therefore, it exhibits the potential to replace traditional factory acceptance tests. Additional development of the system will be conducted for ship automation, utilizing PMS control and an energy management system.

Ultrasensitive analyses of zearalenone in grain samples with a catalytic oxidation platform involving gold nanomaterials

Zearalenone (ZEN) contamination in cereals poses a serious threat to human and animal health, yet existing rapid test methods still suffer from poor stability and low sensitivity. The studied sensor reduces inspection time while enabling applications for on-site grain inspection. Specifically, a ZEN detector that can sensitively detect ZEN content in grains was developed. Ion implantation is an effective method for modifying screen-printed electrodes (SPEs). Gold nanoparticles (AuNPs; 5–10 nm) were uniformly implanted using screen-printed electrodes as a catalytic oxidation medium to generate an electrochemical sensor. The surface structure of the modified electrode was characterized using scanning electron microscopy and X-ray photoelectron spectroscopy. The results showed that differential pulse voltammetry had good linear electrochemical response to ZEN at 10 ng/kg to 10 mg/kg, with a detection limit of 1.1 ng/kg. We used AuNP-SPE sensors to detect ZEN in grain samples such as maize and oats.

Engineering an enzyme-like catalytic sensor for on-site dual-mode evaluation of total antioxidant capacity.

Anovel Fe-MoOx nanozyme, engineered with enhanced peroxidase (POD)-like activity through strategic doping and the creation of oxygen vacancies, is introducedto catalyze the oxidation of TMB with high efficiency. Furthermore, Fe-MoOx is responsive to single electron transfer (SET) and hydrogen atom transfer (HAT) mechanisms related to antioxidants and can serve as a desirable nanozyme for total antioxidant capacity (TAC) determination. The TAC colorimetric platform can reach a low LOD of 0.512μM in solution and 24.316μM in the smartphone-mediated RGB hydrogel (AA as the standard). As proof of concept, the practical application in real samples was explored. The work paves a promising avenue to design diverse nanozymes for visual on-site inspection of food quality.