Service Load Research Articles

The spectral analysis of the state parameters of technical systems in the regular and damaged states

It is noted that reaction of bearing elements of structures and engineering components to service loadings, impacts of physical fields and corrosive environments is initiation not only fields of stresses and strains, but also fields of damages. At the same time depending on conditions of a loading and environment various mechanisms of accumulation of damages and fracture which indicators are essential changes in spectra of a response of technical systems to different impacts are realized. The analysis of parameters of a state of such systems by registration of spectral characteristics of service processes allows to carry out estimations of levels of their damage in rather full degree. On the basis of results of research of service states of technical systems on spectral diagnostic parameters approaches to the analysis of amplitude-frequency characteristicses of their actual states both in the regular allowed states, and upon transition to dangerous states owing to accumulation in them of dangerous service damages are offered. At the same time criteria of transition of technical systems from regular in emergency and catastrophic states at accumulation of critical limits of damage are formulated. Examples of the dispersed initiation of microcracks in material of structures parts at a cyclic deformation with their propagation in the main fractures, and also examples of the analysis of dynamic states on vibration spectra of a response of simple and compound technical systems with the crack which arose in them and with existence of defects are given. At the same time the possibility of obtaining initial computation and experimental information on parameters of a stress-strain state and damage of installation with use of methods of the spectral analysis of a response of a compound structure to vibration impact as a result of initiation of damage of its separate parts is shown. Results of such spectral analysis can be used for diagnostics and monitoring of conditions of regular service of high-loaded installations of a technosphere and transition of their states to limit emergency and catastrophic in relation to objects of power engineerings, space-rocket and aircraft equipment.

Global strategies against COVID-19: The role of public health measures, vaccination, and technology

This essay describes the global response to the COVID-19 pandemic, focusing on its virus characteristic, public health strategies employed, and the role of vaccination and technology in the management of the crisis. Back in March 2020, the COVID-19 virus was declared a pandemic by the World Health Organization, which required the international community's collaboration to reduce the health impact of the virus. This essay exposes how SARS-CoV-2 spreads, the complications of asymptomatic transmission, and its mutations, which further complicate the efforts to contain it. The very basic early detection through testing, protection by social distancing and wearing masks, and wide vaccination were the fundamental strategies that had kept the pandemic in control. It was vaccination, with an emphasis on vaccines based on mRNA, that proved to be key in the fight against severe diseases and in lightening the load of health services. The essay identifies that the vaccines represent a big scientific milestone and show promise for the future treatments beyond infectious diseases. Besides, big data, tracking technology, international cooperation were all important technologies to help manage the crisis.

Vibration-Based Damage Prediction in Composite Concrete–Steel Structures Using Finite Elements

The prediction of structural damage through vibrational analysis is a critical task in the field of composite structures. Structural defects and damage can negatively influence the load-carrying capacity of the beam. Therefore, detecting structural damage early is essential to preventing catastrophic failures. This study addresses the challenge of predicting damage in composite concrete–steel beams using a vibration-based finite element approach. To tackle this complex task, a finite element model to a quasi-static analysis emulating a four-point pure bending experimental test was performed. Notably, the numerical model equations were carefully modified using the Newton–Raphson method to account for the stiffness degradation resulting from material strains. These modified equations were subsequently employed in a modal analysis to compute modal shapes and natural frequencies corresponding to the stressed state. The difference between initial and damaged modal shape curvatures served as the foundation for predicting a damage index. The approach effectively captured stiffness degradation in the model, leading to observable changes in modal responses, including a reduction in natural frequencies and variations in modal shapes. This enabled the accurate prediction of damage instances during construction, service, or accidental load scenarios, thereby enhancing the structural and operational safety of composite system designs. This research contributes to the advancement of vibration-based methods for damage detection, emphasizing the complexities in characterizing damage in composite structural geometries. Further exploration and refinement of this approach are essential for the precise classification of damage types.

Load Testing Application for Truss Bridge Design Verification: Live Load Testing

This is the second of two companion papers discussing application of load testing techniques for verification of bridge design. The bridge was a six-spans continuous steel truss structure, about 338-m long and 14.45-m wide, in the State of New York. Design of the bridge was completed using an unconventional approach where the top chords of the main trusses, floor beams, and stringers were designed to act composite with the concrete deck. In addition to axial forces, such a design also gives rise to secondary moments in the truss main members under design loads. This aroused interest in verification of the design through an instrumentation, monitoring, and load testing program. Comparing the members’ actual service load axial forces and moments with those used in the design, it was concluded that axial forces were overestimated in the design by about 20 percent for service dead load and by about 25 percent for service live load. Similar comparison for moments, indicated that service dead load moments were within 20 percent of those used in the design and service live load moments were underestimated by about 55 percent. The above differences for service dead load can be attributed to the way the deck pours were accounted for in the design and the possibility of construction loads being on the structure during the deck pour monitoring. For service live load, these differences can be explained by possible discrepancies in estimating service live load from the test results and the fact that the analysis for service live load in the design was performed ignoring the contribution of the composite concrete deck. Adequacy of the structural design under actual axial forces and moments was confirmed by checking the AASHTO interaction equations for steel members under combined axial and bending loading conditions. The major contribution of this and the companion paper is that, they introduced a new approach for estimating total dead load effects by only monitoring strains in a limited number of truss members during staged deck construction and load testing of a very large truss bridge structure, it validated the unconventional design under both dead load and live load as a viable method for design of truss bridge structures, and it supplemented the very limited literature on dead load monitoring of bridges.

Pultruded GFRP beams subjected to 10 years of natural aging under service loads

Pultruded GFRP beams subjected to 10 years of natural aging under service loads

Cybersecurity Defence Mechanism Against DDoS Attack with Explainability

Application-layer attacks (Layer 7 attacks), a form of distributed denial-of-service (DDoS) aimed at web servers, have become a significant concern in cybersecurity because of their ability to disrupt services by overwhelming server resources. This study focuses on addressing the challenges of detecting and mitigating the impact of such attacks, which are difficult to counter due to their sophisticated nature. The primary objective of this study is to develop an effective monitoring and defence model to detect, defend, and respond to these attacks efficiently. To achieve this, SHapley Additive exPlanations (SHAP) technology was used to understand the behaviour of the model and to increase the efficiency of the detection classifiers. The defence model is designed with three states: normal, observing, and suspicious. The observing mode, which represents the detection part, is triggered when the server load exceeds a predefined threshold. The detection system incorporates five machine learning (ML) algorithms: decision trees (DTs), support vector machines (SVMs), logistic regression (LR), naive Bayes (NB), and K-nearest neighbours (KNNs). A stacked classifier (SC) was then employed to combine these models to achieve optimal performance. The algorithms were evaluated in terms of accuracy (ACC), precision (PRC), recall (REC), F1 score (F1), and time (T). The SC demonstrates superior accuracy in distinguishing between legitimate traffic and malicious traffic. If the server continues to suffer from overload, the suspicious part of the defence model will be activated, and the mitigation algorithm will be called, which, in turn, bans users responsible for the attack and prevents illegitimate users from connecting to the server. The effects of the mitigation algorithm were noticeable in the server traffic rate, transmission rate, memory utilization, and CPU utilization, confirming its ability to defend against application-layer attacks.

An effective method for strengthening steel beams and purlins using an elastic support in the span

The article is devoted to the development of theoretical approaches to strengthening bending elements, such as beams and girders, through the installation of an elastic support at the midpoint of the span where the maximum bendingmoment occurs, as well as the development of a practical calculation method for such reinforcement. The need for strengthening may arise under various conditions, including prolonged operation beyond the design lifespan, increased service loads on existing structures, wear and tear of structures, or damage caused by episodic additional loads (e.g.,earthquakes, explosions). The purpose of the study is to provide a practical method for reinforcing girders and beams using an elastic support at the span to increase the load-bearing capacity of structures under increased loads (e.g., installation of solar power stations or other additional equipment on roofs) or in cases of damage caused by explosions or other episodic loads that reduce the cross-sectional geometric characteristics and require rapid strengthening. The article proposes a calculation methodology for this type of reinforcement that addresses shortcomings in existing scientific and technical literature and facilitates the broader implementation of the method to enhance the reliability of structures.The article presents an effective method for reinforcing girders and beams in response to increased loading. Using an elastic support (brace) at the span enhances the load-bearing capacity of structures.The method involves installing a brace under the element to be strengthened, secured with additional bolts to create an elastic support that reduces the applied load. This solution eliminates the need for welding or disrupting the structural integrity. Atechnological gap is provided to create pre-stressing, which is closed during bolt tightening. The main advantages include minimal intervention, pre-stressing creation, and increased structural reliability. The article contains a calculation methodology for this reinforcement method, promoting its practical application to improve the efficiency and reliability of structures.The proposed reinforcement method is demonstrated on steel structures but can be extended, if necessary, to structures made of other materials, such as wood or reinforced concrete.

Randomised, multicentre, placebo-controlled trial of fenofibrate for treatment of diabetic macular oedema with economic evaluation (FORTE study): study protocol for a randomised control trial

IntroductionDiabetic macular oedema (DMO), a serious ocular complication of diabetic retinopathy (DR), is a leading cause of vision impairment worldwide. If left untreated or inadequately treated, DMO can lead to...

A Study on the Feasibility of Natural Frequency-Based Crack Detection

Owing to the long-standing statement that natural frequency-based crack detection is not sensitive enough to localised damage to identify small cracks, many natural frequency-based crack detection methods are validated by detecting cracks of moderate size. However, a direct comparison between the crack severity causing a measurable natural frequency change and the crack severity reaching the initiation of crack propagation or leading to brittle fracture is constantly ignored. Without this understanding, it is debatable whether the presented crack detection methods are feasible in practical situations. Through natural frequency calculation and linear elastic fracture mechanics, this study is dedicated to filling the above gap in knowledge. To directly utilize the solution of stress intensity factor, common fracture toughness test specimens featuring a single-edge crack are used. These specimens are essentially cracked rectangular plates under uniform uniaxial tension. Considering the stress resultants obtained via the extended finite element method, the natural frequency of the loaded cracked plates is calculated using the Rayleigh–Ritz method incorporating corner functions. In addition, assuming the specimens as structural components under remote uniform tension, the development of critical load versus crack length is derived based on the solution of the stress intensity factor. Thus, critical crack lengths corresponding to a series of safety factors are obtained by equating service load with critical load. After obtaining natural frequencies of the cracked plates with critical crack lengths, the natural frequency drop caused by a critical crack can be computed. Hence, the critical crack length can be compared with the crack length when the frequency drop is measurable. It is found that the brittleness of the employed metals plays a vital role in the feasibility of natural frequency-based crack detection.

FedLSTM: A Federated Learning Framework for Sensor Fault Detection in Wireless Sensor Networks

The rapid growth of Internet of Things (IoT) devices has significantly increased reliance on sensor-generated data, which are essential to a wide range of systems and services. Wireless sensor networks (WSNs), crucial to this ecosystem, are often deployed in diverse and challenging environments, making them susceptible to faults such as software bugs, communication breakdowns, and hardware malfunctions. These issues can compromise data accuracy, stability, and reliability, ultimately jeopardizing system security. While advanced sensor fault detection methods in WSNs leverage a machine learning approach to achieve high accuracy, they typically rely on centralized learning, and face scalability and privacy challenges, especially when transferring large volumes of data. In our experimental setup, we employ a decentralized approach using federated learning with long short-term memory (FedLSTM) for sensor fault detection in WSNs, thereby preserving client privacy. This study utilizes temperature data enhanced with synthetic sensor data to simulate various common sensor faults: bias, drift, spike, erratic, stuck, and data-loss. We evaluate the performance of FedLSTM against the centralized approach based on accuracy, precision, sensitivity, and F1-score. Additionally, we analyze the impacts of varying the client participation rates and the number of local training epochs. In federated learning environments, comparative analysis with established models like the one-dimensional convolutional neural network and multilayer perceptron demonstrate the promising results of FedLSTM in maintaining client privacy while reducing communication overheads and the server load.

Reliability Assessment of Cracked Reinforced Concrete Slab and Verification using a Full-Scale in-Situ Load Test

This paper presents a case study focused on the deterministic and probabilistic structural assessments of a cracked reinforced concrete (RC) slab and evaluation using in-situ load testing. The case study explores the practical application of in-situ load testing as a diagnostic tool for evaluating the condition of the slab and determining its ultimate load-carrying capacity in the presence of cracks, and service loads are used to verify its serviceability. Through comprehensive analysis and interpretation of test results, this study aims to provide valuable insights into the structural performance of cracked reinforced concrete slabs and inform effective repair and rehabilitation strategies. The building under examination is a G+4 reinforced concrete structure constructed using ready mix concrete transported to the construction site. Upon inspecting the slab, which had a total thickness of 170 mm, numerous deeply mapped cracks were evident, visible from the slab's surface and extending through its entire depth. Structural analysis indicated that the design included sufficient reinforcement and that the loads acting upon the slab were not expected to induce the cracking. Factors such as poor construction practices, potential issues with the cement used, and excessive evaporation may have contributed to the occurrence of these cracks, necessitating repairs. A full-scale in-situ load test was performed following ACI 318-08 testing procedures and results show that the slab under investigation is reasonably safe against serviceability and strength requirements with “no evidence” of failure.

ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ В СИСТЕМАХ КЛІЄНТ-СЕРВЕР ЧЕРЕЗ ВИКОРИСТАННЯ МЕРЕЖ CDN

In modern information systems, the client-server architecture is one of the most common models of interaction between users and servers. It ensures a clear distribution of responsibilities between the client, which makes requests for information or operations, and the server, which processes them and provides responses. With the development of technology and the increase in the load on servers, there is a need to improve the interaction mechanisms to ensure greater efficiency and performance of the system. One of the key aspects affecting the efficiency of client-server systems is the use of CDN networks. Using CDN reduces response time and improves overall system performance. This technology is becoming increasingly popular due to its ability to increase the efficiency and scalability of modern web resources and services. The relevance of this topic is that CDN networks can solve a number of problems associated with high server loads and decreased system response speed, which is especially important in conditions of a large number of users simultaneously using network resources. The purpose of this study is to analyze the efficiency of client-server interaction using CDN, as well as to study technologies that improve the efficiency of this interaction. The study will examine the theoretical foundations of client-server systems using CDN and analyze the efficiency of their use. Keywords: client-server, CDN network, response time, work optimization, performance.

ПІДВИЩЕННЯ ЕФЕКТИВНОСТІ В СИСТЕМАХ КЛІЄНТ-СЕРВЕР ЧЕРЕЗ ВИКОРИСТАННЯ МЕРЕЖ CDN

In modern information systems, the client-server architecture is one of the most common models of interaction between users and servers. It ensures a clear distribution of responsibilities between the client, which makes requests for information or operations, and the server, which processes them and provides responses. With the development of technology and the increase in the load on servers, there is a need to improve the interaction mechanisms to ensure greater efficiency and performance of the system. One of the key aspects affecting the efficiency of client-server systems is the use of CDN networks. Using CDN reduces response time and improves overall system performance. This technology is becoming increasingly popular due to its ability to increase the efficiency and scalability of modern web resources and services. The relevance of this topic is that CDN networks can solve a number of problems associated with high server loads and decreased system response speed, which is especially important in conditions of a large number of users simultaneously using network resources. The purpose of this study is to analyze the efficiency of client-server interaction using CDN, as well as to study technologies that improve the efficiency of this interaction. The study will examine the theoretical foundations of client-server systems using CDN and analyze the efficiency of their use. Keywords: client-server, CDN network, response time, work optimization, performance.

Optical performance maintenance of solar dish collector system under service loads based on tracking compensation and receiver translational compensation methods

Optical performance maintenance of solar dish collector system under service loads based on tracking compensation and receiver translational compensation methods

Flexural behavior of GFRP and steel bars reinforced lightweight ultra-high performance fiber-reinforced concrete beams with various reinforcement ratios

The synergistic operating mode of the concrete matrix and the reinforcing bar determines the dependability of a structure in complicated environments. The objective of this research has been to provide a comprehensive analysis of the flexural behavior exhibited by lightweight ultra-high performance fiber-reinforced concrete (LUHPC) beams that have been reinforced with high-strength steel bars (HRB500) and glass fiber-reinforced plastic (GFRP) bars. LUHPC was used as the matrix material with a compressive strength of 120 MPa and a density of 2050 kg/m3. This study focused on examining the impact of different reinforcement ratios (0.59 %, 1.27 %, and 1.94 %) and reinforcement types (GFRP and HRB500 bars) about the flexural performance of LUHPC beams under four-point bend loading. As demonstrated by the results of experiments, GFRP-reinforced LUHPC (G-LUHPC) beams with higher reinforcement ratios have higher peak loads, flexural stiffness, and cracking loads but lower ductility. Compared with steel-reinforced LUHPC (S-LUHPC) beams, the bending strength of G-LUHPC beams was reduced by 18.2 %, 24.2 %, and 6.7 %, the peak deflection was increased by 166.5 %, 24.8 %, and 56.9 %, and stiffness degradation and crack development were rapid. After comparing the test results with the current commonly used specifications, it was seen that the codes could better predict the cracking moments and the deflections under service loads of G-LUHPC beams. However, it was noted that both the ultimate moments and the corresponding mid-span deflections were greatly underestimated.

Assessing Seismic Vulnerability Methods for RC-Frame Buildings Pre- and Post-Earthquake

The seismic vulnerability of reinforced concrete (RC) buildings has been an important issue, especially in earthquake-prone regions with limited seismic design codes such as South Sudan. Improving the seismic performance of reinforced concrete buildings is critical for maintaining structural functionality under normal service loads and for rapid recovery after natural disasters such as earthquakes. This research aims to thoroughly assess the methods used to evaluate the seismic vulnerability of RC frame structures in pre- and post-earthquake scenarios. The primary objective is to provide a comprehensive framework that integrates empirical, analytical, and experimental methods, categorizing existing assessment methods and proposing improvements for resource-constrained environments. However, empirical methods have always used historical earthquake data to estimate potential damage. In contrast, analytical methods have used computational tools such as fragility curves to assess the probability of damage at different seismic intensities. Additionally, experimental methods, such as shaking table tests and pseudo-dynamic analyses, have validated theoretical predictions and provided insights into structural behavior under simulated conditions. Furthermore, key findings highlight critical vulnerabilities in RC buildings, quantify damage probabilities, and compare the strengths and limitations of different assessment methods. However, challenges such as limited data availability, computational limitations, and difficulties replicating actual conditions in test setups highlight areas for improvement. By addressing these challenges, the review provides recommendations for future studies, including integrating advanced computational and regional hazard characterization methods, improving experimental methods to enhance the accuracy of vulnerability assessments, and ultimately supporting the design of more resilient RC structures and increasing disaster preparedness.

Damage-Sensitive Feature for Long-Span Steel Box-Girder Suspension Bridges Under Service Loads Based on Long-Term Monitoring

To extract valuable data from long-term monitoring and identify structural damage to ensure the serviceability and safety of bridges, a commonly used method in large bridge maintenance. This article developed a time-domain energy-based method for identifying bridge damage based on long-term structural health monitoring noisy output measurements. This method first calculated an energy threshold within the structural frequency bandwidth of natural vibration at measurement points. Then, the structural damage was assessed by computing the time-domain energy accumulation. The improved procedure of this proposed method involved extracting modal frequencies from the signal for each modal order, determining the structural frequency bandwidth of natural vibration, and applying the square root envelope method to smooth vibration data and mitigate the impact of abnormal signals. Later, the applicability of the proposed method for damage identification was verified by comparing it with conventional modal flexibility and modal curvature methods. Finally, a case study on the Runyang bridge, a supported steel-box-girder suspension bridge with a main span of 1490 m in China, was made for demonstration. The results indicated that the area between 1/4-span and 1/2-span of the bridge was more sensitive to damage under service loads. The method performed well in identifying potential damage locations and assessing vulnerability. The calculation results using the method proposed in this article were consistent with those of traditional methods. The research offers methodological backing for utilizing extensive data monitoring in evaluating structural damage.

Efficient slicing scheme and cache optimization strategy for structured dependent tasks in intelligent transportation scenarios

The challenges posed by structured large-scale tasks to resource-sensitive intelligent transportation systems have been acknowledged, particularly regarding the need to reduce delay and energy consumption during the caching and offloading processes. To address these challenges and improve the quality of service for vehicular users, a cloud–edge-end collaboration caching strategy (CACCSC) based on structured task content awareness was proposed in this paper. The dependencies among task fragments were modeled through fuzzy judgment criteria. In addition, a system delay model, an energy consumption model, and an edge server load balancing model were developed, along with a multi-objective optimization model that integrates system delay, energy consumption, and edge server load balancing variance. To solve this multi-objective optimization problem, an adaptive multi-objective optimization algorithm (MDE-NSGA-III) was developed, which combines an enhanced version of the Differential Evolution algorithm with improvements to the NSGA-III algorithm. Finally, it has been demonstrated through simulation experiments that when the number of users in the system reaches 35, the system delay, energy consumption, and load balancing variance of the MDE-NSGA-III optimization scheme proposed in this paper are 6.1%, 6.6%, and 25% lower than those of the NSGA-III scheme, 15.8%, 10%, and 41.7% lower than those of the NSGA-II scheme, and 62.7%, 20.7%, and 8.3% lower than those of the PeEA scheme.

Analytical Fragility Surfaces and Global Sensitivity Analysis of Buried Operating Steel Pipeline Under Seismic Loading

The structural integrity of buried pipelines is threatened by the effects of Permanent Ground Deformation (PGD), resulting from seismic-induced landslides and lateral spreading due to liquefaction, requiring accurate analysis of the system performance. Analytical fragility functions allow us to estimate the likelihood of seismic damage along the pipeline, supporting design engineers and network operators in prioritizing resource allocation for mitigative or remedial measures in spatially distributed lifeline systems. To efficiently and accurately evaluate the seismic fragility of a buried operating steel pipeline under longitudinal PGD, this study develops a new analytical model, accounting for the asymmetric pipeline behavior in tension and compression under varying operational loads. This validated model is further implemented within a fragility function calculation framework based on the Monte Carlo Simulation (MCS), allowing us to efficiently assess the probability of the pipeline exceeding the performance limit states, conditioned to the PGD demand. The evaluated fragility surfaces showed that the probability of the pipeline exceeding the performance criteria increases for larger soil displacements and lengths, as well as cover depths, because of the greater mobilized soil reaction counteracting the pipeline deformation. The performed Global Sensitivity Analysis (GSA) highlighted the influence of the PGD and soil–pipeline interaction parameters, as well as the effect of the service loads on structural performance, requiring proper consideration in pipeline system modeling and design. Overall, the proposed analytical fragility function calculation framework provides a useful methodology for effectively assessing the performance of operating pipelines under longitudinal PGD, quantifying the effect of the uncertain parameters impacting system response.

Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave Conditions

A hybrid ship uses integrated generators, an energy storage system (ESS), and photovoltaics (PV) to match its propulsion and service loads, and together with optimal power and voyage scheduling, this can lead to a substantial improvement in ship operation cost, ensuring compliance with the environmental constraints and enhancing ship sustainability. During the operation, significant uncertainties such as waves, wind, and PV result in considerable speed loss, which may lead to voyage delays and operation cost increases. To address this issue, a distributionally robust optimization (DRO) model is proposed to schedule power generation and voyage. The problem is decoupled into a bi-level optimization model, the slave level can be solved directly by commercial solvers, the master level is further formulated as a two-stage DRO model, and linear decision rules and column and constraint generation algorithms are adopted to solve the model. The algorithm aims at minimizing the operation cost, limiting greenhouse gas (GHG) emissions, and satisfying the technical and operational constraints considering the uncertainty. Extensive simulations demonstrate that the expected total cost under the worst-case distribution is minimized, and compared with the conventional robust optimization methods, some distribution information can be incorporated into the ambiguity sets to generate fewer conservative results. This method can fully ensure the on-time arrival of hybrid ships in various uncertain scenarios while achieving expected operation cost minimization and limiting greenhouse gas (GHG) emissions.