Civil Engineering Applications Research Articles

Full waveform inversion of cross-hole radio frequency electromagnetic data

Summary We consider application of full waveform inversion (FWI) to radio-frequency electromagnetic (EM) data. Radio-frequency imaging (RIM) is a cross-borehole technique to image electromagnetic subsurface properties from measurements of transmitted radio-frequency waves. It is used in coal seam imaging, ore exploration and various engineering and civil engineering applications. RIM operates at frequencies from 50 kHz to several tens of MHz. It differs from other geophysical EM methods, because the frequency band includes the transition between the wave propagation and diffusion regimes. RIM data are acquired in two-dimensional cross-hole sections in a reciprocal manner. Traditionally, radio-frequency data are inverted by straight ray tomography because it is inexpensive and easy to implement. It is argued that due to attenuation, the sensitivity of the transmitted electric field is the strongest within the first Fresnel zone of the ray connecting the transmitter and receiver. While straight ray tomography is a simple to implement and fast method, the non-linearity in the relationship between model parameters and data is often strong enough to warrant non-linear inversion techniques. FWI is an iterative high resolution technique, in which the physical properties are updated to minimize the misfit between the measured and modelled wavefields. Full waveform techniques have been used and extensively studied for the inversion of seismic data, and more recently, they have been applied to the inversion of GPR data. Non-linear inversion methods for RIM data are less advanced. Their use has been hindered by the high cost of full wave modelling and the high conductivity contrasts of many RIM targets, and, to some extent, by the limitations of the measuring instruments. We present the first application of this methodology to simultaneous conductivity and permittivity inversion of RIM data. We implement the inversion in the frequency domain in two dimensions using L-BFGS optimization. We analyze the sensitivity of the data to the model parameters and the parameter trade-off and validate the proposed methodology on a synthetic example with moderate conductivity variations and localized highly conductive targets. We then apply the FWI methodology to a field data set from Sudbury, Canada. For the field data set, we determine the most appropriate preprocessing steps that take into account specific peculiarities of RIM: the insufficient prior information about the subsurface and the limitations of the measuring equipment. We show that FWI is applicable under the conditions of RIM and is robust to imperfect prior knowledge: we obtain satisfactory model recoveries starting from homogeneous initial models in all of our examples. Just as other methods, FWI underestimates large conductivity contrasts due to the loss of sensitivity of the transmitted electric field to the conductivity variations as the conductivity increases above a certain level. The permittivity inside high conductors can not be recovered, however, recovering permittivity variations in the resistive zones helps obtain better focused conductivity images with fewer artifacts. Overall, FWI produces cleaner, less noisy and higher resolution reconstructions than the methods currently used in practice.

Optimisation of mechanical properties and pore structure of lightweight geopolymer concrete

Lightweight geopolymer has good physical and mechanical properties, thermal and chemical stability and low carbon dioxide emissions. The development of high-strength lightweight geopolymer concrete (LGC) for load-bearing structures can expand geopolymer applications. The use of ground granulated blast-furnace slag (GGBFS) to improve the mechanical properties and pore structure of LGC was investigated. The ultimate compressive stress of LGC containing GGBFS were analysed, as well as the variation in microscopic pore structure. Specimens of LGCs with different strengths (LC20, LC30 and LC40) were investigated. As the GGBFS content increases, the ultimate compressive stress and specific strength of LGC increases, while the strain corresponding to the peak stress decreases, indicating that the mechanical properties and deformation resistance of LGC are improved. The carbon dioxide emissions of LGC are less than those of cement-based lightweight concrete, indicating that LGC has good sustainability. Moreover, the addition of GGBFS can produce more gel and reduce the volume proportion of capillary pores and air pores, resulting in LGC densification. Recommended GGBFS contents for strength grades LC20, LC30 and LC40 are 0–12.7%, 12.7–24.6% and 24.6–30%, respectively. The LGC is lightweight and has high strength, and has potential for application in civil engineering.

Proposed formulas for pillar stress estimation in a regular room-and-pillar pattern

Room-and-pillar mining is one of the oldest and most widely employed underground mining methods worldwide, while in recent years it has also been used for civil engineering projects and applications. The pillar design process is quite straightforward, requiring the assessment of two key elements, namely the pillar's strength and the anticipated loading imposed on it. Lots of research work has been elaborated for the estimation of pillars' strength and the main parameters associated with it, while, on the other hand, in terms of the loading the Tributary Area Theory (TAT) has been traditionally and successfully used as the dominant methodology to assess the post-mining pillar induced stresses. This paper focuses primarily on decoding the pillar loading regime by analyzing the identifying the stresses imposed to them through the use of modern computational tools offered by 2D and 3D numerical analyses, over a series of pillars' type (square, ribs), configurations and initial virgin stress fields. This allows for the development of a benchmarking framework that showcase the differences in the stress conditions and reveal the over-conservative behavior of TAT. More importantly though, it allowed for the expression of two (2) general analytical formulae for the direct estimation of the average vertical elastic stresses on pillars, both for the case of rib & square pillars layout; the most typical patterns applied in this method. They aim at providing an easy to use and more accurate estimation of the pillar stress - as compared to TAT - in alignment with the results obtained from numerical analyses. Thus, with the proposed formulas, the time-consuming numerical process needed for preliminary pillars' dimensioning is tackled in a swift and effective manner.

Analytical Evaluation of Natural Frequencies in Hollow-Core Slabs: A Practical Methodology for Civil Engineering Applications

Analytical Evaluation of Natural Frequencies in Hollow-Core Slabs: A Practical Methodology for Civil Engineering Applications

Application of Generalized S-Transform in the Measurement of Dynamic Elastic Modulus

Resonance is commonly used for in situ measurement of the dynamic elastic modulus to evaluate the strength of concrete samples. Many researchers are also exploring the application of this convenient measurement technology for safety monitoring. Nevertheless, the presence of cracks and variations in curing conditions within samples can impact the resonance frequency range, potentially leading to potential inaccuracies in measurements. In order to improve the measurement accuracy of resonance frequency, this study introduces the Generalized S-Transform (GST) algorithm for measuring the dynamic elastic modulus, which utilizes its high time-frequency resolution to scan the power peak-point in non-stationary and transient excitation signals to determine the resonance frequency. For concrete materials with lower consistency, the experimental results verify the high accuracy of this algorithm in measuring resonance frequency compared with Fast Fourier Transform (FFT). This provides a reference for using the algorithm to measure the dynamic elastic modulus in civil engineering applications, such as buildings and bridges.

Performance of Iron Ore Tailings/Cement Composite at High Temperatures: Inconbustibility

Objective: This study aims to evaluate the performance of an iron ore tailings/cement composite at high temperatures, used in brick manufacturing. Specifically, it investigates the non-combustibility of the material and its structural integrity after exposure to intense heat, with an emphasis on compressive strength and the economic and sustainable viability of this composite. Theoretical Framework: The research is based on concepts of sustainability in civil construction and the reuse of industrial waste. The literature highlights the synergy between iron ore tailings and Portland cement, resulting in materials with good durability and non-combustibility. Previous studies indicate a reduction in environmental impact and the economic feasibility of using these composites as substitutes for traditional materials, in addition to the importance of maintaining structural strength under extreme conditions. Method: The adopted methodology involves the manufacture of test specimens using CP V-ARI cement and iron ore tailings, molded and cured according to Brazilian standards. Non-combustibility tests are conducted in a muffle furnace at 750°C, measuring temperature variation, smoke emission, and mass loss. Additionally, compressive strength tests are conducted before and after heat exposure to assess material degradation. Results and Discussion: The results indicate that the composite exhibits satisfactory non-combustibility properties, with an average mass loss of 3.1%, well below the permissible limit of 50%. However, a significant loss of 67.5% in compressive strength was observed after exposure to high temperatures. The discussion contextualizes these results, highlighting the need to optimize the composition to minimize strength loss, although non-combustibility remains a positive aspect. Research Implications: Practical implications include the potential use of the composite in environments subject to high temperatures, as a passive fire protection measure. Theoretically, the research contributes to the understanding of the behavior of cementitious composites with industrial waste under extreme conditions, suggesting directions for future studies and applications in civil engineering and sustainable construction. Originality/Value: This study makes an original contribution by exploring the specific combination of iron ore tailings with cement at high temperatures, providing new insights into its applicability and limitations. The relevance of the research lies in the potential reduction of environmental impact and the promotion of sustainable practices in civil construction, as well as enhancing fire safety in buildings.

Shear strengthening of damaged reinforced concrete beams with iron-based shape memory alloy (Fe-SMA) strips: numerical and parametric analysis

Shape memory alloys (SMAs) are metallic materials that are characterized by their ability to restore their original shape after large deformation when activated by heating. This unique property renders SMAs appealing for various civil engineering applications. Iron-based SMAs (Fe-SMAs), including alloys like Fe–Mn–Si, stand out due to their cost-effectiveness and high strength. The primary focus of this research lies in the computational modeling of Fe-SMA strips utilized to reinforce damaged concrete structures. To achieve this, details from an experimental test are leveraged for the computational simulation of real-scale reinforced concrete beams that were first loaded to some level of damage, then released and strengthened, and subsequently retested. The strengthening approach involves the application of external Fe-SMA strips wrapping around the beams. This paper presents an original computational modeling setup that incorporates a switch option for the Fe-SMA material. This feature enables one to use a single simulation platform for the whole process. The significance of this method originates from its capacity to ensure a robust analysis that includes all simulation steps-testing unstrengthened beams, installing and heating Fe-SMA strips, and testing both damaged and strengthened beams—in a single, multi-step analysis. The computational simulation results were compared with the outcomes of the experimental test, revealing an acceptable level of agreement. The findings indicate a substantial increase in both shear strength and ductility as a result of the application of Fe-SMA strips. Additionally, parametric and mesh sensitivity studies were conducted. These aimed to investigate the mesh dependency of the model and to identify the optimal mesh size. Furthermore, variations in the details of the Fe-SMA strips, including thickness, width, quantity, and effect of applied temperature were explored to compare the outcomes of different applications of these strips.

Feasibility of Repairing Concrete with Ultra-High Molecular Weight Polyethylene Fiber Cloth: A Comprehensive Literature Review

This review explores the use of Ultra-High Molecular Weight Polyethylene (UHMWPE) fiber cloth as an innovative solution for the repair and reinforcement of concrete structures. UHMWPE is a polymer formed from a very large number of repeated ethylene (C2H4) units with higher molecular weight and long-chain crystallization than normal high-density polyethylene. With its superior tensile strength, elongation, and energy absorption capabilities, UHMWPE emerges as a promising alternative to traditional reinforcement materials like glass and carbon fibers. The paper reviews existing literature on fiber-reinforced polymer (FRP) applications in concrete repair in general, highlighting the unique benefits and potential of UHMWPE fiber cloth compared to other commonly used methods of strengthening concrete structures, such as enlarging concrete sections, near-surface embedded reinforcement, and externally bonded steel plate or other FRPs. Despite the scarcity of experimental data on UHMWPE for concrete repair, this review underscores its feasibility and calls for further research to fully harness its capabilities in civil engineering applications.

Two-scale finite element simulations for UT inspection of micro-structured materials in CIVA

Ultrasonic testing (UT) of highly heterogeneous structures is an important issue for many industrial applications in civil engineering for concrete inspection as well as in nuclear and oil & gas, where it applies to cast steels and weld joints. In these materials, performance is limited by the phenomenon of multiple wave scattering at the microstructure scale. In this context, the use of effective simulation tools is particularly useful both for improving interpretation of UT and for optimizing or demonstrating the performance of inspections. However, the scales of heterogeneity to be taken into account are often smaller than fractions of a tenth of a wavelength. In 3D simulations, it is therefore difficult, if not impossible, to combine computational performances with the refinement of the modelled interactions. To meet this challenge, CEA is developing an original approach based on two applications of the finite element (FE) method implemented in CIVA. The first application uses micro-scale heterogeneous material data on small representative elemental volumes (REVs) to feed a second code dedicated to macro-scale with effective medium characteristic. This second code relies on a high-order finite element model that is very efficient at the scale of the inspected industrial component. In this communication we present the main features of these FE tools and illustrate their performances on different application cases for welded parts and concrete

Sustainable End-of-Life Tyre Management: A Comprehensive Analysis of Environmental Impacts and Crumb Rubber Integration in Composite Concretes

The research explores pollution prevention strategies associated with end-of-life tyres (ELTs) through sustainable practices, focusing on repurposing ELTs into crumb rubber (CR) for use in composite concretes for civil engineering applications. Three disposal approaches are considered: recycling into crumb rubber for use in cement composites to enhance acoustic properties, incineration for cement production, and landfill disposal. The study aims to assess the environmental impact of each method, particularly in terms of carbon dioxide (CO2) emissions during the recycling phase, utilizing the OpenLCA program for a comprehensive life cycle analysis. The primary objective is to provide insights into the sustainability of incorporating recycled rubber in concrete mixes as fine aggregate to improve concrete acoustic and shock absorbance properties. The research also gathers data on CO2 emissions from ELT incineration for cement production and the environmental implications of ELT’s landfill disposal. By comparing these three strategies, the study offers a holistic perspective on the environmental ramifications of ELT management. Notably, a recent study highlights the energy recovery and CO2 emissions from ELT incineration, demonstrating the potential benefits of recycling. The research identifies a gap in existing studies, emphasizing the need to consider the entire life cycle, including the transportation and use stages. Notably, the use stage significantly contributes to environmental impacts, with carbon emissions ranging from 550 to 840 kg CO2 eq., per car tyre. Additionally, a proposed inventory analysis method evaluates greenhouse gas emissions from Portland cement concrete pavement construction, revealing that raw material production accounts for most emissions. The findings of this research are providing valuable insights for policymakers, industry professionals, and environmentalists aiming for sustainable practices in the construction sector. By allocating a fraction of tyre production CO2 emissions to obtain raw material for concrete composites, the study suggests a potential avenue for reducing environmental impact. Further calculations using the OpenLCA program may refine these recommendations.

Enhancing Load-Bearing Capacity of Calcareous Sands through Gel Stabilization: A Mechanical and Material Characterization Study.

Calcareous sands often display wide ring grain configurations, high intragranular porosity, a complex structure, and low grain hardness. These attributes typically do not meet the strength criteria necessary to sustain overlying infrastructure in civil engineering applications. This study investigates gel stabilization techniques, blending gel material with calcareous sand at concentrations ranging from 5% to 22%, followed by curing periods of 3 to 28 days to evaluate the load-bearing capacity. Subsequently, an unconfined compressive test is performed to determine the gel material content in stabilized specimens and investigate the influence of gel material types. The gel material-to-sand ratios employed are set at 5%, 10%, and 16% for Portland cement and 13%, 16%, and 22% for gypsum. After that, a triaxial consolidated undrained test is conducted to assess mechanical behavior, pore water pressure, and mechanical properties. The findings reveal increased dilation, stress-strain hardening, and softening post-yield, regardless of gel material type. Principal stress ratios, secant modulus, and cohesion show a positive correlation with maintenance duration and binder content, with implications for improved load-bearing capacity. The study also elucidates the qualitative relationship between secant modulus E50 and confining pressure.

Aging behaviour assessment of cellulosic fibres in alkaline media: A green technology approach in construction materials

With the increasing demand for buildings, the utilisation of green materials represents a novel approach toward achieving sustainable development goals. Cellulose-based materials, such as jute, exemplify eco-friendly substances for civil engineering applications. The present study aims at studying the aging behavior of jute fibers in an alkaline environment. For this purpose, three alkali environments (NaOH, KOH, Ca(OH)2) with three different concentrations were selected. Samples were treated at three different periods (7 d, 14 d, and 28 d) to assess the impact of treatment on the fiber properties. This study introduces a pioneering concept of the alkali treatment of jute-based fibres to evaluate tensile strength and weight loss, marking the first of its kind. This approach incorporates various characterisation techniques, including Differential Scanning Calorimetry (DSC), Thermo-Gravimetric Analysis (TGA), and Scanning Electron Microscopy (SEM) to assess the treatment process. In our experimental procedures, we evaluated key parameters such as the type of alkali, alkali concentration, and curing time for their influence on tensile strength. Subsequently, we applied Response Surface Methodology (RSM) in conjunction with bagging techniques to develop mathematical models based on the acquired data. Results demonstrated varied tensile strengths based on alkali type, concentration, and treatment duration. Fibres treated with 15 g/L concentration of NaOH exhibited an increase in tensile strength from 7 days (79.66 MPa) to 28 days (225.05 MPa). The highest tensile strength of jute fibres treated with KOH was observed with 15 g/L concentration at 14 days (237.58 MPa). For Ca(OH)₂ treatments, the highest tensile strength was observed with 30 g/L concentration at 14 days (111.28 MPa). It was also observed that prolonged exposure to very high alkali concentrations could adversely affect the tensile strength, as observed in the case of 30 g/L concentration of NaOH at 28 days (84.73 MPa). Among the various alkali materials tested, NaOH and KOH demonstrated greater effectiveness compared to Ca(OH)2. According to RSM analysis, the time of sample curing was found to be the most significant factor in tensile strength, with a P-value of 0.009. On average, the tensile strength changes by 54 %, 52 %, and 35 % for NaOH, KOH, and Ca(OH)₂, respectively, when the curing time shifts from 7 days to 28 days.

Experimental study of self-tightening high-strength single-side bolted joints under low cyclic loading

Single-side bolts can be installed on one operating surface and are very suitable for closed cross-section connections. Based on the forming mechanism of materials, a new type of self-tightening high-strength single-side bolt, named SHSB-PRO (Progressed version), was developed herein. The SHSB-PRO was successfully applied to the assembled steel structure joints, with a range of low cyclic loading tests executed. In this test, three assembled steel structure joints were designed. Two of them were connected using SHSB-PRO, while the third was connected using traditional torsional shear high-strength bolt. Different bolt types and axial compression ratios of the steel column were examined to explore their impact on the seismic behavior of the joints. Through the low cyclic loading test, data such as hysteresis curves, skeleton curves, and strain in key parts of the joints were obtained. The mechanical properties, energy dissipation characteristics, failure mechanisms, and seismic performance of these assembled joints were elucidated. The test results indicate that the forming quality of the SHSB-PRO is stable within the joint, and a fine stress condition is maintained. The joints connected by the SHSB-PRO exhibit seismic performance comparable to those with torshear high-strength bolted connection. All joints failed due to the formation of the plastic hinge of the steel beam above the stiffener, and the joints connected by SHSB-PRO belong to the rigid joint. The influence of the axial compression ratio on the load-bearing capacity, ductility, and stiffness of the joints connected using SHSB-PRO is virtually minimal when the ratio is no more than 0.2. The finite element model was rigorously validated against the experimental results, demonstrating its accuracy and reliability in capturing the behavior of SHSB-PRO joints. The research herein lays a foundation for the design and improvement of SHSB-PRO, and promotes its wide application in civil engineering.

Cement kiln dust and polypropylene fiber in expansive clay improvement

For civil engineers, expansive soils pose a great deal of difficulty because of their sensitivity to volume changes with different moisture levels. These difficulties are compounded by the widespread occurrence of swelling clay, which can seriously harm infrastructure, especially in arid or semi-arid areas. The geotechnical qualities of these soils have been improved through the use of various additives and techniques, resolving this problem and making the soils suitable for building. Numerous stabilization techniques, nevertheless, may have negative environmental effects. Therefore, it is imperative to investigate the use of local waste or by-products to stabilize soil in order to preserve the environment and lower stabilization costs, especially in road construction projects.To address these issues, an experiment was conducted to determine how locally obtained cement kiln dust (CKD), both alone and combined with polypropylene fibers, affected the properties of plastic clay soil, also referred to as expansive clay from Cheffia.The main objective of this study is to assess how well different CKD percentages (from 5% to 25%) stabilize soil while improving its mechanical and physical properties. The study also aims to explain how the addition of polypropylene fiber affects the unconfined compressive strength and compaction behavior of the soil in the optimal CKD-soil mixture. The results of the analysis show that the addition of cement kiln dust (CKD) significantly improved the studied soil's workability, compaction, and strength. Additionally, adding polypropylene fibers strengthens the clay's resistance to compression, which presents encouraging opportunities for reducing the difficulties brought on by expansive soils in civil engineering applications.

Optimizing compressive strength of quaternary-blended cement concrete through ensemble-instance-based machine learning

Optimizing the composition of concrete, particularly when incorporating ordinary Portland cement (OPC) along with supplementary materials such as ground granulated blast furnace slag (BF), fly ash (FA), and silica fume (SF), poses challenges due to the intricate nonlinearity inherent in concrete properties. Addressing this challenge has urged growing interest in employing Machine Learning (ML) techniques for precise property assessment. In this investigation, various predictive models, encompassing eXtra Gradient Boosting (XGB), random forests (RF), and K-Nearest Neighbor (KNN) algorithms were formulated to predict the compressive strength (CS) of ternary-blended concrete incorporating OPC, BF, FA, and SF. Through comprehensive analysis of an extensive dataset comprising 810 distinct records, the study identifies optimal concrete blends, providing invaluable insights for practical applications. Evaluation of ML models underscores the superior performance of XGB, with a coefficient of multiple determination (R2) values of 0.923 and 0.997 for training and testing datasets, respectively, indicative of exceptional predictive accuracy. Additionally, SHAP values underscore the importance of input age, water–binder ratio, and OPC content. This research enhances understanding of ternary-blended concrete characteristics, offering practical implications for construction practices and laying a foundation for future research endeavors to refine ML models, explore attribute interactions, and optimize concrete constituent proportions for broader civil engineering applications.

Application of Waste Tire in Construction: A Road towards Sustainability and Circular Economy

The global demand for rubber is on a steady rise, which is driven by the increasing production of automobiles and the growing need for industrial, medical, and household products. This surge in demand has led to a significant increase in rubber waste, posing a major global environmental challenge. End-of-life tire (ELT) is a primary source of rubber waste, having significant environmental hazards due to its massive stockpiles. While landfilling is a low-cost and easy-to-implement solution, it is now largely prohibited due to environmental concerns. Recently, ELT rubber waste has received considerable attention for its potential applications in civil engineering and construction. These applications not only enhance sustainability but also foster a circular economy between ELT rubber waste with the civil engineering and construction sectors. This review article presents a general overview of the recent research progress and challenges in the civil engineering applications of ELT rubber waste. It also discusses commercially available recycled rubber-based construction materials, their properties, testing standards, and certification. To the best of the authors’ knowledge, this is the first time such a discussion on commercial products has been presented, especially for civil engineering applications.

Determining the number of soil layers using the surface wave method based on decision tree and random forest

The surface wave method is an efficient non-invasive technique to infer shear wave velocity profiles and has wide applications in civil engineering, earthquake engineering, and geophysics. Inversion analysis is a key step in this method. However, inferring the soil layer number is a challenging problem in inversion analysis and needs improvement. Machine-learning algorithms, including decision tree and random forest, are used in this study to infer the number of soil layers based on the dispersion curve of the surface wave. This process includes two steps for obtaining the model. In Step 1, a large set of synthetic dispersion curves is produced, and in Step 2, a model using machine-learning algorithms is trained based on the synthetic data. The analysis results showed that the obtained model could gain more than 75% accuracy in the test data. Comparing the results from the two machine learning models indicated that the random forest method produced a more favorable prediction. Furthermore, investigating the importance of features implied that the longest and shortest wavelengths were more important than other features.

Microstructural mechanism underlying the stress recovery behavior of a Fe–Mn–Si shape memory alloy

Recovery stress governs the prestress strengthening effect of Fe–Mn–Si-based shape memory alloys in civil engineering applications. Although the effects of grain size, texture, and precipitates on recovery stresses have been extensively studied, the generation of recovery stress has not been thoroughly discussed regarding martensite growth behavior, especially considering the interaction of martensite variants. This study investigates the stress recovery and ε martensite growth behavior of a Fe–30Mn–6Si–5Cr (wt.%) alloy subjected to varying levels of deformation. The Fe–30Mn–6Si–5Cr (wt.%) alloy exhibits a yield strength of approximately 450 MPa, with an ultimate elongation of 44 % and a tensile strength of 950 MPa observed in uniaxial incremental cyclic tensile tests. Additionally, the results reveal an initial increase in recovery stress with pre-strain, peaking at 7 %, followed by a subsequent decrease with further deformation. With increasing pre-strain, the primary ε martensites initially grow parallelly, followed by the appearance of secondary martensites with a different orientation, intersecting multiple parallel primary martensites along with the increasing density of dislocations and stacking faults. A microstructural mechanism is proposed to elucidate the stress recovery behavior, encompassing the impact of primary martensites and secondary martensites interaction, and the influence of dislocations and stacking faults. This work offers microstructural scenarios that help to understand the generation of recovery stress and provides guidance for regulating recovery stress in Fe–Mn–Si-based shape memory alloys for civil engineering applications requiring prestress strengthening.

INTERACTION BETWEEN GEOGRID REINFORCEMENT AND STONE AGGREGATES MIXED WITH TIRE-DERIVED AGGREGATES

The disposal of discarded tires creates a major problem, as they are non-biodegradable and occupy huge landfill space. The scrap tires can be utilized in civil engineering applications as an alternative material by partial or complete substitution of conventional materials. In many of these applications, scrap tires are not utilized directly; instead, they are shredded to produce a material known as tire-derived aggregate (TDA). In this study, an attempt is made to understand the interaction between geogrid reinforcement and stone aggregates mixed with TDA using a large-scale triaxial test with a specimen diameter of 150 mm and height (Hs) of 300. The geogrid reinforcement is placed at a spacing of Hs/2, Hs/3, Hs/4, and Hs/5 along the length of the sample. The results are analyzed to understand the effect of geogrid reinforcement on stone aggregate mixed with TDA, and it is noticed that the deviatoric stress increases with the inclusion of geogrid reinforcement in the mix proportion.

Reliability and sensitivity analysis of delamination growth of composite laminate structures using two efficient sampling methods

In recent years, composite structures have been used in a large number of applications in aerospace, machinery, marine, and civil engineering. However, there are inevitably many uncertainties in the whole life cycle of composite structures, which can easily lead to structural damage and failure. Therefore, it is important to analyze the reliability and sensitivity of composite structures. At present, most of the contributions use the first-order reliability method (FORM) and the second-order reliability method (SORM) to study the reliability of composite structures and compare them with the results of the Monte Carlo simulation. However, both methods have their limitations. FORM cannot guarantee the calculation accuracy for the highly nonlinear limit state equation, and the calculation efficiency of SORM is too low. Therefore, this paper proposes to use importance sampling (IS) and backpropagation neural network-based Monte Carlo (MC-BPNN) to study the reliability, sensitivity, and dispersion of delamination growth of composite laminates. The results show that compared with FORM and SORM, IS and MC-BPNN have higher calculation accuracy and efficiency and can more accurately evaluate the failure degree of composite structures and ensure their safe operation in the field of aerospace equipment. The universality of this method can make it being widely used in the reliability and sensitivity analysis of different composite materials as well as dispersion analysis.