Engineering Community Research Articles

Dependence of critical heat flux in vertical flow systems on dimensional and dimensionless parameters using machine learning

The critical heat flux (CHF) associated with the departure from nucleate boiling (DNB) determines the design and safety aspects of two-phase flow boiling systems. Despite the availability of several predictive tools, within the thermal engineering community, the pursuit of an accurate and robust CHF model remains a significant challenge. In this unique study, we extracted a substantial database from literature to develop machine-learning (ML) models to predict CHF for vertical flows commonly employed in the process industry. The extensive database encompasses 15,006 experimental data points gathered from diverse sources covering wide range of geometric and operational ranges of D, L, P, G, h, and x. This database is then employed to develop five ML – based models, namely Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Adaptive Boosting (AdaBoost), Extreme Gradient Boosting (XGBoost), and Random Forests (RF). The selection of optimal input features is conducted by exploring various combinations of both dimensional and dimensionless parameters to identify the most influencing inputs for CHF prediction. The models incorporating features D, L, P, G, h, x, L/D, ρr, We, and BO achieve CHF predictions with Mean Absolute Errors (MAEs) of 8.85 % for the ANN model and 10.39 % for the XGBoost model. The optimized ML models outperformed even the highly reliable CHF correlations and lookup tables. The feature importance analysis of input parameters highlights strong dependence of CHF on dimensionless numbers such as Weber number and Boiling number.

Large eddy simulation of aerodynamic wind pressure on a tall rectangular building by modified synthetic volume forcing method

To accurately predict wind pressures on a tall building by numerical Computational Fluid Dynamics (CFD) using the Large-Eddy Simulation (LES) turbulent model, it is essential to generate inflow with realistic turbulence characteristics. The Discretizing and Synthesizing Random Flow Generation (DSRFG) method, as one of the synthetic Fourier methods, has received significant attention in the Computational Wind Engineering (CWE) community because of its ability to strictly satisfy the continuity condition and generate turbulent wind with the desired power spectra. In traditional LES, the desired turbulent wind is normally generated and specified at the inlet. However, this treatment often leads to significant attenuation in turbulence energy in the high-frequency band of the fluctuating wind speed spectrum along the flow direction and unrealistic large-amplitude wind pressure fluctuations, resulting in unsatisfactory prediction performance. The Synthetic Volume Forcing (SVF) method effectively overcomes these limitations by introducing turbulence as volume force into the moment Navier-Stokes (N-S) equations. In this study, the DSRFG method is applied to generate a fluctuating wind field in combination with the SVF method to simulate dynamic wind pressures on a tall rectangular building through open-source software OpenFOAM. The turbulence intensity amplification factor (TIAF) is introduced in the SVF method to further improve its simulation accuracy. Comparison of results with wind tunnel test results verifies that the proposed TIAF-SVF numerical method developed in this study achieved sufficient accuracy in predicting wind pressures on tall buildings.

The Lost World: Characterizing and Detecting Undiscovered Test Smells

Test smell refers to poor programming and design practices in testing and widely spreads throughout software projects. Considering test smells have negative impacts on the comprehension and maintenance of test code and even make code-under-test more defect-prone, it thus has great importance in mining, detecting, and refactoring them. Since Deursen et al. introduced the definition of “test smell”, several studies worked on discovering new test smells from test specifications and software practitioners’ experience. Indeed, many bad testing practices are “observed” by software developers during creating test scripts rather than through academic research and are widely discussed in the software engineering community (e.g., Stack Overflow) [ 70 , 94 ]. However, no prior studies explored new bad testing practices from software practitioners’ discussions, formally defined them as new test smell types, and analyzed their characteristics, which plays a bad role for developers in knowing these bad practices and avoiding using them during test code development. Therefore, we pick up those challenges and act by working on systematic methods to explore new test smell types from one of the most mainstream developers’ Q&A platforms, i.e., Stack Overflow. We further investigate the harmfulness of new test smells and analyze possible solutions for eliminating them. We find that some test smells make it hard for developers to fix failed test cases and trace their failing reasons. To exacerbate matters, we have identified two types of test smells that pose a risk to the accuracy of test cases. Next, we develop a detector to detect test smells from software. The detector is composed of six detection methods for different smell types. These detection methods are both wrapped with a set of syntactic rules based on the code patterns extracted from different test smells and developers’ code styles. We manually construct a test smell dataset from seven popular Java projects and evaluate the effectiveness of our detector on it. The experimental results show that our detector achieves high performance in precision, recall, and F1 score. Then, we utilize our detector to detect smells from 919 real-world Java projects to explore whether the six test smells are prevalent in practice. We observe that these test smells are widely spread in 722 out of 919 Java projects, which demonstrates that they are prevalent in real-world projects. Finally, to validate the usefulness of test smells in practice, we submit 56 issue reports to 53 real-world projects with different smells. Our issue reports achieve 76.4% acceptance by conducting sentiment analysis on developers’ replies. These evaluations confirm the effectiveness of our detector and the prevalence and practicality of new test smell types on real-world projects.

Pengelolaan Lingkungan dengan Pemanfaatan Air Hujan Menggunakan Teknik SODIS untuk Pemberdayaan Karang Taruna Gebangsari

Gebangsari Village is one of the villages in Genuk District, Semarang City, where when heavy rainfall often experiences floods. When there is rain, there is minimal access to clean water in Gebangsari Village, and people rely only on well water. Therefore, it is necessary to empower Karang Taruna Gebangsari to utilize rainwater with SODIS (Solar Water Disinfection) Technique to meet clean water needs during floods. The method used was interviews and observations with Gebangsari Village, the Community, and Gebangsari Village Taruna Corals. The program's implementation includes Socialization and Focus Group Discussion, Training, Mentoring, and Evaluation activities. This Community Service Program provides new knowledge and skills for the Gebangsari Village Community so that the community gets solutions to flood problems. The village also appreciated the impact of the SODIS Engineering community service program for helping the adequacy of clean water.

Poison Attack and Poison Detection on Deep Source Code Processing Models

In the software engineering (SE) community, deep learning (DL) has recently been applied to many source code processing tasks, achieving state-of-the-art results. Due to the poor interpretability of DL models, their security vulnerabilities require scrutiny. Recently, researchers have identified an emergent security threat to DL models, namely, poison attacks . The attackers aim to inject insidious backdoors into DL models by poisoning the training data with poison samples. The backdoors mean that poisoned models work normally with clean inputs but produce targeted erroneous results with inputs embedded with specific triggers. By using triggers to activate backdoors, attackers can manipulate poisoned models in security-related scenarios (e.g., defect detection) and lead to severe consequences. To verify the vulnerability of deep source code processing models to poison attacks, we present a poison attack approach for source code named CodePoisoner as a strong imaginary enemy. CodePoisoner can produce compilable and functionality-preserving poison samples and effectively attack deep source code processing models by poisoning the training data with poison samples. To defend against poison attacks, we further propose an effective poison detection approach named CodeDetector . CodeDetector can automatically identify poison samples in the training data. We apply CodePoisoner and CodeDetector to six deep source code processing models, including defect detection, clone detection, and code repair models. The results show that ❶ CodePoisoner conducts successful poison attacks with a high attack success rate (average: 98.3%, maximum: 100%). It validates that existing deep source code processing models have a strong vulnerability to poison attacks. ❷ CodeDetector effectively defends against multiple poison attack approaches by detecting (maximum: 100%) poison samples in the training data. We hope this work can help SE researchers and practitioners notice poison attacks and inspire the design of more advanced defense techniques.

Multi-objective SHM sensor path optimisation for damage detection in large composite stiffened panels

This work proposes a novel methodology for the automatic multi-objective optimisation of sensor paths in structural health monitoring (SHM) sensor networks using archived multi-objective simulated annealing. Using all of the sensor paths within a sensor network may not always be beneficial during damage detection. Many sensor paths may experience significant signal noise, attenuation, and wave mode conversion due to the presence of features, such as stiffeners, and hence impair the detection accuracy of the overall system. Many paths will also contribute little to the overall coverage level or damage detection accuracy of the network and can be ignored, reducing complexity. Knowing which paths to include, and which to exclude, can require significant prior expert knowledge, which may not always be available. Furthermore, even when expert knowledge is considered, the optimum path selection might not be achieved. Therefore, this work proposes a novel automatic procedure for optimising the sensor paths of an SHM sensor network to maximise coverage level, maximise damage detection accuracy and minimise the overall signal noise in the network due to geometric features. This procedure was tested on a real-world large composite stiffened panel with many geometric features in the form of frames and stiffeners. Compared to using all of the available sensor pairs, the optimised network exhibits superior performance in terms of detection accuracy and overall noise. It was also found to provide very similar performance, in terms of coverage level and overall signal noise, to a sensor path network designed based on prior expert knowledge but provided up to 35% higher damage detection accuracy. As a result, the novel procedure proposed in this work has the capability to design high-performing SHM sensor path networks for structures with complex geometries but without the need for prior expert knowledge, making SHM more accessible to the engineering community.

Bridges damaged during the 2019 Poldokhtar flood: towards flood-resilient bridges

Bridges are among the most vital parts of infrastructure networks in every country, and have been seriously damaged by natural hazards such as floods and earthquakes in the past. Engineering communities have always faced challenges protecting these structures from flood hazards. Today, the world is facing climate change, with incidences of severe floods increasing globally. Flooding brings the possibility of significant bridge damage and therefore studying bridge performance under flood hazards is of vital importance. The flood in Poldokhtar, Iran, in 2019 was one of the most destructive floods in the last decade. In this research, the performance of 14 bridges during the Poldokhtar flood was reviewed and the damage incurred was assessed through field investigations. The aim of this paper is to demonstrate, based on visual inspections and engineering judgement, the different reasons and scenarios that lead to the destruction of different types of bridges during floods. The results of this study emphasise the need to estimate bridge vulnerability and develop procedures to prevent bridge destruction. The technical and statistical information on bridge destruction due to flooding obtained in this work is vital for the management and inspection systems of bridges, the retrofit of existing bridges and the design of new flood-resilient bridges.

Expotecnología 2022

Expotecnología 2022 was an event that took place in the city of Cartagena de Indias, from November 2 to 6, 2022, with the slogan “The future of engineering in the face of technological disruption” This eighteenth version was a meeting that brought together the scientific and academic community in spaces for the dissemination and transfer of knowledge, where innovation was the essence and a fundamental part of the event. Expotecnología was created in the Faculty of Engineering Sciences - FACI, of the Antonio de Arévalo University Foundation - UNITECNAR and in this version it maintained as mission, the development of the interaction between science, technology and society, through establishing of knowledge networks and academic and professional cooperation. The main objective was to address the challenges that emerge from the everyday life of the engineering community, the problems immersed in the development of projects and programs of Higher Education Institutions (IES), organizations and research centers at the national and international level. In the development of the day of presentations in a virtual way, it was possible to promote the dissemination of the research work of professionals, teachers and students from all areas of engineering, framed in four (4) thematic axes, as follows:• New technologies: Big data, Artificial Intelligence, Business Intelligence, Software Engineering, Education and new technologies and Mobile Applications.• Petrochemicals and process control: Materials Science, Instrumentation and Control Systems, Robotics and Automation and Industrial Maintenance.• Electricity, electronics and telecommunications: IoT, Fiber optics, Digital Signal Processing, Wireless Networks, Mobile Communications, Power Systems, Energy Storage, Smart Grids, Renewable Energies, Operation and Distribution, Energy Dispatch, Energy Markets• Construction Summit: Modern Building Systems and Computational Modeling.On this occasion, the event was attended by 512 people, representatives from 25 national and 6 international universities. 32 presentations were made, of which 32 articles were selected for this volume of the IOP Conference Cycle: Materials Science and Engineering and 13 articles for the book Engineering, Innovation and the fourth industrial revolution., After a process of Peer Review. The plenary conferences were in charge of 2 national and 8 international speakers .List of Invited speakers, Organizing Committee, Special thanks are available in this pdf.

Edukasi Bahaya Gempa Bumi di Sdn 51 Maluku Tengah, Dusun Wainuru, Desa Liang

Liang Village in Central Maluku district, Maluku province, was the village that was most affected by successive earthquakes in 2019. The location of the point of the earthquake which was near caused the Liang village to suffer a lot of damage to buildings. Damage to this building can cause the ceiling and walls of the building to collapse, so it is very dangerous for the community. The purpose of this service is that after carrying out this service, activity participants can understand the dangers of earthquakes, the causes of earthquakes, the disasters that follow earthquakes and rescue actions. This educational activity is one of a series of civil engineering community service activities at Pattimura University. This education is carried out by conducting live presentations and showing video material that will be delivered to teachers and students of SDN 51 Central Maluku. The results of this education can be seen from the enthusiasm of students who can answer the speaker's questions from the material that has been provided. After this educational activity, students and teachers at SDN 51 Central Maluku, Dusun Wainuru, are expected to be able to understand how to take preventive and rescue measures when an earthquake occurs in the future.

Autonomous Robotic Capabilities in Space Exploration: From Mars to Beyond

The historical timeline of automated systems functioning in space settings spans around 75 years, whereas the existence of practical automated equipment to facilitate astronomical observation dates back over 200 years. Over time, physical servomechanisms have seen advancements in both hardware and software capabilities, enabling their successful operation on the Martian surface and even during journeys to the heliopause, which marks the outer boundary of interstellar space. Contemporary spaceflight operations exemplify a growing capacity to provide decentralized coordination across several automated systems, intricate communication networks, and diverse communities of scientists and engineers. This article examines the impact of autonomous robotic functionalities on space explorations, specifically emphasizing the investigation of Mars' surface. The article examines the use of robotic systems in past missions, specifically focusing on their application in activities like as the identification and analysis of water ice deposits, study of geological features, and the deployment of sensor devices. The article further emphasizes the achievements of autonomous operations in missions conducted in Earth's orbit, as well as the progress made in developing autonomy for operations in close vicinity to minor celestial bodies. This research explores the Chang'e 4 lunar mission and the OSIRIS-REx mission as instances of autonomous exploration and sample gathering on minor celestial bodies. The research also encompasses the exploration of prospective autonomy in forthcoming expeditions to oceanic realms and distant locales.

RENEWABLE ENERGY TECHNOLOGIES IN ENGINEERING: A REVIEW OF CURRENT DEVELOPMENTS AND FUTURE PROSPECTS

This comprehensive review examines the current state of renewable energy technologies within the field of engineering, analyzing recent developments and outlining future prospects. As the global demand for sustainable energy solutions continues to rise, understanding the advancements in renewable technologies becomes crucial for the engineering community. The review encompasses a diverse range of renewable sources, including solar, wind, hydropower, biomass, and geothermal energy. The solar energy sector has witnessed remarkable progress, with innovations in photovoltaic materials, energy storage, and efficiency enhancements. Advancements in wind energy technologies focus on improving turbine designs, optimizing energy conversion, and exploring offshore wind farms. Hydropower developments emphasize sustainable and eco-friendly dam designs, while biomass technologies explore novel methods for efficient biofuel production. Geothermal energy, often overlooked, is gaining momentum with advancements in enhanced geothermal systems and innovative drilling techniques. The review also delves into the integration of renewable energy sources into smart grids, promoting efficient energy distribution and storage. Additionally, it addresses the role of artificial intelligence and machine learning in optimizing renewable energy systems, enhancing predictability, and maximizing energy output. Furthermore, the review emphasizes the importance of policy frameworks and financial incentives in driving renewable energy adoption. The ongoing transition towards decentralized energy systems and the exploration of novel materials for energy capture and storage are highlighted as key areas for future research. The potential of emerging technologies such as perovskite solar cells and floating offshore wind farms is also discussed. This review provides a holistic overview of the current landscape of renewable energy technologies in engineering, offering valuable insights into the advancements made thus far and outlining the promising prospects for a sustainable energy future. Engineers and researchers will find this review instrumental in navigating the evolving field of renewable energy and contributing to the ongoing global efforts towards a greener and more sustainable energy landscape.
 Keywords: Renewable Energy, Energy, Climate Change, Development, Engineering, Review.

Assessing Embodied Carbon for Reinforced Concrete Structures in Canada

The global emphasis on reducing greenhouse gas emissions means that engineers and architects are increasingly required to account for embodied carbon in their designs. However, there is a lack of knowledge and tools in the structural engineering community to enable calculation of embodied carbon for reinforced concrete structures. This paper aims to address this concern by providing a review of the most up-to-date approaches for calculating embodied carbon as well as the important factors that engineers should consider during the design phase to reduce embodied carbon. Environmental product declarations for concrete in four Canadian provinces will also be compared to illustrate the variability in the embodied carbon and the factors that influence this variability. Finally, the paper will present a case-study on the design of a reinforced concrete beam to demonstrate how to calculate embodied carbon and to illustrate how changes in design can influence the total embodied carbon.

Secondary-deposited elevated self-assembling nanosphere lithography: A powerful tool to achieve heterostructure metasurface

The heterostructure integration of nanostructures, which can involve higher freedom of degree by applying two or more materials into one integrated photonic or electromagnetic devices, attracted extensively increasing attention among the communities of electrons, photonics, materials science, and engineering. However, it is still a challenging topic to realize heterostructure integration with accurate micro–nano-scale geometry in a large area. Here, we propose the secondary-deposited elevated self-assembling nanosphere lithography for large-area heterostructure integration of plasmonic metasurface. As the proof of concept, an infrared metasurface composed of Au–Ag crescent pairs is realized in the practice. By adjusting the evaporation angle, crescent pairs with different morphologies can be freely machined without changing masks. Optical characterization and numerical results show that the heterostructure crescent-pair metasurface owns uniform and stable geometrical properties and flexible capability on infrared optical field modulation. Our work enriches the degree of freedom of nano-structure-based optical devices and paves the heterostructure integrated metasurface to potential industrial applications with large dimension, low cost, and fast production.

Optimization of Prestressed Anchor Cable Layout for Left Pier of Jinchuan Hydropower Station

With the increase of the flood discharge capacity of the flood discharge structure, the size of the flood discharge orifice is widened, which leads to the increasing thrust of the radial gate. A large tensile stress zone will be formed at the connection between the anchor block and the pier, which may lead to concrete cracking. The optimization design of the prestressed anchor cable of the pier has always been a concern of the engineering community. In this paper, the left pier of Jinchuan Hydropower Station is taken as the research object, and the finite element simulation model is established. The layout position of prestressed anchor cable is optimized, and different layout schemes of prestressed anchor cable on the left pier are designed and calculated. The results show that when the amount of main anchor cable is the same, it should be arranged outside the pier as far as possible; under the condition that the number of main anchor cables on the inner side of the pier is constant, when the direction of the main anchor cable force is consistent with the direction of the radial gate thrust, the main anchor cable prestress plays the greatest role; the arrangement of balance cable has no obvious effect on the tension of concrete at pier neck. It can provide reference for structural design.

Renewable energy technologies in engineering: A review of current developments and future prospects

This comprehensive review examines the current state of renewable energy technologies within the field of engineering, analyzing recent developments and outlining future prospects. As the global demand for sustainable energy solutions continues to rise, understanding the advancements in renewable technologies becomes crucial for the engineering community. The review encompasses a diverse range of renewable sources, including solar, wind, hydropower, biomass, and geothermal energy. The solar energy sector has witnessed remarkable progress, with innovations in photovoltaic materials, energy storage, and efficiency enhancements. Advancements in wind energy technologies focus on improving turbine designs, optimizing energy conversion, and exploring offshore wind farms. Hydropower developments emphasize sustainable and eco-friendly dam designs, while biomass technologies explore novel methods for efficient biofuel production. Geothermal energy, often overlooked, is gaining momentum with advancements in enhanced geothermal systems and innovative drilling techniques. The review also delves into the integration of renewable energy sources into smart grids, promoting efficient energy distribution and storage. Additionally, it addresses the role of artificial intelligence and machine learning in optimizing renewable energy systems, enhancing predictability, and maximizing energy output. Furthermore, the review emphasizes the importance of policy frameworks and financial incentives in driving renewable energy adoption. The ongoing transition towards decentralized energy systems and the exploration of novel materials for energy capture and storage are highlighted as key areas for future research. The potential of emerging technologies such as perovskite solar cells and floating offshore wind farms is also discussed. This review provides a holistic overview of the current landscape of renewable energy technologies in engineering, offering valuable insights into the advancements made thus far and outlining the promising prospects for a sustainable energy future. Engineers and researchers will find this review instrumental in navigating the evolving field of renewable energy and contributing to the ongoing global efforts towards a greener and more sustainable energy landscape.

High-Order Spectral Irregular Wave Generation Procedure in Experimental and Computational Fluid Dynamics Numerical Wave Tanks, with Application in a Physical Wave Tank and in Open-Source Field Operation and Manipulation

The accurate generation of a target sea state in numerical or experimental wave tanks is a fundamental line of research for the ocean engineering community. It guarantees the quality and relevance of wave–structure interaction tests. This study presents a reproducible irregular wave generation and qualification procedure, accounting for the nonlinear aspects of wave propagation. It can be used for both numerical simulation and experiments. The presented numerical and experimental results are obtained from the OpenFOAM solver and the Ecole Centrale Nantes wave tank facilities, respectively. The procedure comprises two steps: First, the wavemaker motion is calibrated numerically to generate the target wave spectrum at the position of interest. This is achieved with a wavemaker-equipped nonlinear potential flow solver. The open-source HOS-NWT solver, based on the high-order spectral method, was employed in this study. Then, the corrected wavemaker motion is used directly in the experimental wave tank. OpenFOAM simulations were performed to generate waves with the relaxation method, using wave elevation and velocity field data from HOS-NWT. The procedure was finally tested for mild and extreme breaking sea states. The waves generated by the HOS-NWT solver, the experiment, and the OpenFOAM simulation were compared from both stochastic and deterministic perspectives.

A Distributed Impact Model for Seismic Analysis of Planar Rocking Body

ABSTRACT The problem of a planar rigid rocking block subject to dynamic loading is of significant interest to the earthquake engineering community due to its wide application. Despite its simple configuration, rocking itself is a highly nonlinear phenomenon which exhibits non-smooth dynamic behavior. The non-smoothness in dynamics comes from the sudden impact of the rocking body with ground when the sign of rotation angle reverses. Therefore the impact model used in the simulation for rocking problem has a profound influence on the dynamic behavior. Most of existing impact models assume that the impulse during impact is concentrated at the pivot point of the block, ignoring the potential distribution of impulses. This study proposes a distributed impact model for dynamic analysis of planar rigid rocking body. The distributed impulses are achieved through the integration of normal forces induced by penetration over a dummy time period during impact. The distributed impact model is subsequently used to evaluate the post-impact quantities of interest. Numerical simulations suggest Housner’s impact model is a special case of the proposed model. The developed impact model is also compared with published experimental result, showing good accuracy. Finally, evaluation of overturning spectra under analytical pulse excitations suggests that using the distributed impact model can give substantially different results compared to the classic concentrated impact model for relatively stocky blocks. Similar observations can also be made when evaluating rocking responses under seismic excitations.

"There's plenty of room at the bottom": deep brain imaging with holographic endo-microscopy.

Over more than 300 years, microscopic imaging keeps providing fundamental insights into the mechanisms of living organisms. Seeing microscopic structures beyond the reach of free-space light-based microscopy, however, requires dissection of the tissue-an intervention seriously disturbing its physiological functions. The hunt for low-invasiveness tools has led a growing community of physicists and engineers into the realm of complex media photonics. One of its activities represents exploiting multimode optical fibers (MMFs) as ultra-thin endoscopic probes. Employing wavefront shaping, these tools only recently facilitated the first peeks at cells and their sub-cellular compartments at the bottom of the mouse brain with the impact of micro-scale tissue damage. Here, we aim to highlight advances in MMF-based holographic endo-microscopy facilitating microscopic imaging throughout the whole depth of the mouse brain. We summarize the important technical and methodological prerequisites for stabile high-resolution imaging in vivo. We showcase images of the microscopic building blocks of brain tissue, including neurons, neuronal processes, vessels, intracellular calcium signaling, and red blood cell velocity in individual vessels. This perspective article helps to understand the complexity behind the technology of holographic endo-microscopy, summarizes its recent advances and challenges, and stimulates the mind of the reader for further exploitation of this tool in the neuroscience research.

A Study on the Mechanical Properties of Glass-Fiber-Reinforced Defective Gypsum Boards

As a waste derivative, glass fiber has drawn a lot of interest from the engineering community. The purpose of this study was to use glass fiber to improve the performance of defective gypsum boards. Single compression experiments, repeated loading experiments, and scanning electron microscopy (SEM) testing were performed on defective gypsum boards. The results showed that the addition of glass fiber can improve the compressive strength of defective gypsum boards. When the fiber concentration is 1.5%, the strength of single-hole gypsum boards increases by 77.1%. Energy evolution and residual strain evaluation after repeated loading showed the significant reinforcement of the dual-hole gypsum board samples with the addition of glass fiber, improving the stress distribution and elasticity, which was confirmed using damage factor analysis. Glass fibers reduce stress concentrations, improve integrity, and prevent brittle failure, especially at high stress levels. The microstructural analysis showed that the addition of glass fiber improves adhesion and prevents microcracking while acting as a stress transfer bridge, enhancing the behavior of the specimen under cyclic loading. Based on the experimental results and cost, 1.5% glass fiber is the optimal concentration. The research results provide new ideas for the application of glass fiber in defective and brittle materials and contribute toward the sustainable development of the construction industry.

Full-Scale/Model Test Comparisons to Validate the Traditional Atmospheric Boundary Layer Wind Tunnel Tests: Literature Review and Personal Perspectives

For this paper, full-scale/model test comparisons to validate the traditional atmospheric boundary layer (ABL) wind-tunnel simulation technique performed until now by the wind engineering community are systematically reviewed. The engineering background includes some benchmark low-rise buildings specifically established for use in wind engineering research (the Aylesbury experimental buildings, the Texas Tech University experimental building, the Silsoe buildings, etc.), several high-rise buildings in North America and East Asia, long-span bridges, large-span structures, and cooling towers. These structures are of different geometries, are located in different wind environments, and are equipped with various transducers and anemometers. By summarizing the different articles in the literature, it is evident that notable discrepancies between the full-scale measurement and the model test results were observed in most full-scale/model test comparisons, which usually took certain forms: the mean and/or the peak negative pressures at the flow separation regions on buildings were underestimated in the wind tunnel; differences in the root-mean-square (rms) values of the acceleration samples between the full-scale measurements and the force balance model tests were non-negligible; the vertical vortex-induced vibration amplitudes of bridges measured using section models and aero-elastic models were much lower than those observed on the prototypes, etc. Most scholars subjectively inferred that inherent technical issues with the ABL wind tunnel simulation technique could be responsible for the observed full-scale/model test discrepancies, including the Reynolds number effects, the turbulent flow characteristics effects, and the non-stationarity effects. However, based on the authors’ years of experience and after discussion with experienced researchers, it was found that some of the full-scale measurements performed in earlier research were inherently less accurate and deterministic than the wind tunnel experiments they were supposed to validate, which could also be a significant cause of the full-scale/model test discrepancies observed. It is suggested herein that future studies in this field should regard full-scale measurements only as benchmarks, and that future works should focus on synthesizing the results from different schools of physical experiments and formulating universal empirical models of high theoretical significance to properly validate future wind tunnel tests.