Ultrasound application in civil engineering – Future steps

Engineering and environmental properties of foamed recycled glass as a lightweight engineering material

Hydrothermal aging of carbon fiber reinforced polymer rods intended for cable applications in civil engineering

Biostabilization techniques and applications in Civil Engineering: State-of-the-Art

This article focuses on the search for efficient solutions to enhance the mechanical strength of geomaterials, especially soils, with crucial applications in civil engineering. Four promising materials are explored as soil improvement agents: natural latex (rubber trees), lignosulfonate (paper industry byproduct), xanthan gum (bacterial fermentation), and eggshell lime. While other sustainable options exist, these four were chosen for their distinct characteristics and potential for further study. Natural latex, derived from rubber trees, demonstrates exceptional potential for strengthening the mechanical resistance of soils, offering a path to effective stabilization without compromising environmental sustainability. Lignosulfonate, a paper industry byproduct, emerges as an alternative that can significantly enhance the load-bearing capacity of soils, boosting its applicability in civil engineering projects. Xanthan gum, produced through bacterial fermentation, possesses unique properties that increase soil cohesion and strength, making it a valuable option for geotechnical applications. Finally, despite potential challenges, eggshell lime shows promising potential in enhancing the mechanical resistance of soils. This study highlights the importance of evaluating and comparing these agents in terms of their effectiveness in improving the mechanical strength of soils in civil engineering applications. In the literature review, the impact of stabilizer addition (%) was examined for the four cementing agents studied, along with its influence on key soil properties like optimum moisture content (OMC, %), maximum dry density (MDD, gm/cc), California bearing ratio (CBR, %), uniaxial compressive strength (UCS) at 28 days (MPa), and the change in UCS (ΔUCS, %) among other physicochemical parameters. Appropriate selection of these materials can lead to developing more robust and sustainable geomaterials, promoting significant advancements in geotechnical engineering and civil construction practices. To evaluate their effectiveness, the efficiency of one of them was assessed experimentally. Xanthan gum (XG) was selected to biopolymerize clay soil. Specimens were prepared for strength and stiffness tests, including unconfined compression, scanning electron microscopy (SEM), and ultrasonic wave analysis. The impact of stabilizer concentration was examined (e.g., 1%, 3%, 5% xanthan gum) to assess how dosage affects the soil–stabilizer mixture. The results showed that the rubber increases the unconfined compression and stiffness of the soil, controlled by the XG’s porosity/volumetric quantity ratio. The research demonstrates the potential of XG, but a broader analysis of all four materials with the outlined testing methods paves the way for future advancements in geotechnical engineering.

Fiber reinforced concrete (FRC) is a material with increasing application in civil engineering. Here it is assumed that material consists of a great number of rather small fibers embedded the concrete matrix. It would be advantageous to predict mechanical properties of FRC using nondestructive testing ; unfortunately, many testing methods for concrete are not applicable to FRC. In addition, design methods for FRC are either inaccurate or complicated. In three-point bending tests of FRC prisms, it has been observed that fiber reinforcement does not break but simply pulls out during specimen failure. Following that observation, this work is based on an assumption that the main components of a simple and rather accurate FRC model are mechanical properties of the concrete matrix and fiber pullout force. Properties of a concrete matrix could be determined from measurements on samples taken during concrete production and fiber pullout force could be measured on samples with individual fibers embedded into concrete. However, there is no clear relationship between measurements on individual samples of concrete matrix with a single fiber and properties of the produced FRC. This work presents an inverse model for FRC that establishes a relation between parameters measured on individual material samples and properties of a structure made of the composite material. However, deterministic relationship is clearly not possible since only a single beam specimen of 60 cm could easily contain over 100000 fibers. Our inverse model assumes that probability density function of individual fiber properties is known and that global sample load – displacement curve is obtained from the experiment. Thus, each fiber is stochastically characterized and accordingly parameterized. A relationship between fiber parameters and global load – displacement response, the so-called forward model, is established. From the forward model, based on Levenberg – Marquardt procedure, the inverse model is formulated and successfully applied.

Compressive sampling (CS) is a novel signal processing paradigm whereby the data compression is performed simultaneously with the sampling, by measuring some linear functionals of original signals in the analog domain. Once the signal is sparse sufficiently under some bases, it is strictly guaranteed to stably decompress/reconstruct the original one from significantly fewer measurements than that required by the sampling theorem, bringing considerable practical convenience. In the field of civil engineering, there are massive application scenarios for CS, as many civil engineering problems can be formulated as sparse inverse problems with linear measurements. In recent years, CS has gained extensive theoretical developments and many practical applications in civil engineering. Inevitable modelling and measurement uncertainties have motivated the Bayesian probabilistic perspective into the inverse problem of CS reconstruction. Furthermore, the advancement of deep learning techniques for efficient representation has also contributed to the elimination of the strict assumption of sparsity in CS. This paper reviews the advancements and applications of CS in civil engineering, focusing on challenges arising from data acquisition and analysis. The reviewed theories also have applicability to inverse problems in broader scientific fields.

Quantum metrology and its applications in civil engineering

A discussion of four applications of virtual reality in civil engineering is presented. These applications simulate traffic accidents responses, the prevention of construction falls from a building during construction, form scaffolding fall protection, and bridge girder erection. The models developed can be used for training students and civil engineers in a virtual civil engineering environment without exposing them to the danger of real operations.

New materials are continuously made available to meet the modern need for various applications in civil engineering. This book consists of eight chapters describing the advanced materials in civil engineering. The various chapters includes the use of construction and demolition waste material for soil stabilization;review on application and performance of RAP in highway construction; static load response of laminated composite stiffened cylindrical shell using finite element analysis; review on the importance of coarse recycled concrete aggregates as alternative construction materials; performance evaluation of light transmitting concrete made with plastic optical fibers; effect of water to geopolymer solids ratio on properties of fly ash and slag-based one-part geopolymer binders; impact response of laminated composite simply- supported stiffened conoidal shell with cut-out and finally statistical review of bamboo's mechanical properties for building applications.

Application of nanomaterials in civil engineering

Experimental study on flexural performance of prestressed concrete beams strengthened by Fe-SMA plates

A variety of fuzzy multiple criteria decision making (MCDM) models have been proposed to solve complicated decision-making problems. Many applications have been achieved, especially in the field of civil engineering. To analyze the developments about the fuzzy MCDM methods and their applications in civil engineering in recent years and further explore the future research directions, this study conducts a state of the art survey in which 52 journal papers focusing on the applications of fuzzy MCDM models in civil engineering from 2016 to 2020 are reviewed. We respectively classify these articles according to research problems and research methods. Through the literature review, we get findings in terms of the most concerned decision-making problem, the most widely-used evaluation criterion and the most popular fuzzy MCDM model. Furthermore, we present four aspects of research challenges and corresponding future research directions in the field of civil engineering, which may be helpful for researchers and practitioners to further investigate.

We implemented a field check for calibrating surveying equipment. It was geo-referenced with a Total Station Theodolite and by implementing procedures concerning repeatability and reproducibility. We carried out GNSS (Global Navigation Satellite System) static positioning with double frequency equipment, sensitizing occupation times, day times, uncorrected coordinates subjected to a differential correction procedure and type of coordinates obtained. This facilitated an evaluation of precision and accuracy for the GNSS system with the static method, which gave a global RMS (root mean square) error of 1 cm for conditions with no multi-path effect and 4cm for field calibration points close to buildings. Additionally, we found optimal results for occupation times of 30 minutes, and the need to use planar Cartesian coordinates to ensure compatibility with the surveys using electronic measurement of distances, which allows for the use of the static GNSS system in precise surveys for different applications in Civil Engineering.

This research delves into utilizing Artificial Intelligence (AI) in civil engineering, specifically construction simulations. The primary objective is to reconcile the discrepancies between conventional structural analysis techniques and the actual performance of structures. By integrating AI technologies—neural networks, cellular automata, and support vector machines— with data mining, this research proposes a novel approach for simulating civil building constructions. Traditional methods, often constrained by underlying assumptions, fail to capture the complex behaviors of engineering structures accurately. The developed AI simulation framework utilizes experimental and on-site data to construct digital models, enabling precise prediction of structural behaviors without the limitations of traditional assumptions. Results indicate that AI-enhanced simulations can significantly improve the accuracy of structural analysis, demonstrating potential for wider application in civil engineering. This advancement promises to enhance the predictability, efficiency, and safety of civil constructions, marking a significant step forward in the field.

In the United Kingdom engineering geomorphology occupies a niche within engineering geology concentrating on mapping surface form. The main aims of the mapping have been to identify natural hazards and to provide a framework within which an engineering geological model of the ground conditions can be developed through traditional site investigation procedures. However, the natural landscape contains a wealth of information relevant to civil engineering construction works. Significantly over the past 30 years, geomorphologists have moved away from the qualitative description of the landscape into detailed analyses of the geomorphological processes that have created them. These analyses provide data that have direct application in civil engineering. For example, studies of natural sub-surface piping provide data relevant to soft ground tunnelling. Evaluations of hillslope form and landslide investigations are applicable to earthworks design. Geomorphological studies of fluvial systems involve analyses of flood recurrence intervals and scour potential, that can be used for the design of bridges. As this geomorphological research has predominantly been carried out in university geography departments, the subject has largely been discounted as qualitative and descriptive by civil engineers. However, with reference to on-going research in Southeast Spain, this paper illustrates how geomorphological studies can provide quantitative data of direct relevance to civil engineering in three distinct subjects areas, landscape history, hillslopes, and ephemeral river systems.