Analysis of model tests of rainfall-induced soil deposit landslide

A large number of deposit landslides are induced by rainfall, and those with different weak layers may be subject to catastrophic failure. +is research investigates the rainfall infiltration effect on the stability of deposit landslides with a weak layer at different slope angles. Four rainfall physical model tests were conducted with fixed double penetration artificial rainfall technique and dynamic sensor technologies by using the rainfall test methods as modified in the paper. Deformation and mechanics parameters, as well as water content parameters in the key position in the deposit landslide, were monitored by means of various displacement monitoring sensors, dynamic soil pressure sensors, pore water pressure (PWP) monitoring sensors, and water content sensors. +e results show that, under the same rainfall conditions, the rule of displacement and mechanical changes of deposit slope with different angles are similar, that the displacement, soil pressure, and PWP are characterized by two stages of rising and falling, and that the displacement of deposit slope with weak layer remains creep after rainfall. In addition, the displacement at the rear edge of the slope with a small angle is larger than that at the front of the steep slope, but the displacement in the front of the slope is opposite. Furthermore, the slope with a smaller angle is prone to form a tensile crack in the back of the slope, and its deformation and failure have the characteristics of a progressive and thrust-type landslide. While the failure in front of a steep slope (slope angle more than 60°) occurred first, the slope failure was characterized by sudden and retrogressive modes. +e mathematical analysis of the model is also conducted which shows that deformation and failure can be divided into three stages, i.e., creep inoculation, accumulation uplift, and speed-up sliding. +e test results can provide a reference for the investigation, design, and assessment of similar deposit slopes

Numerical simulation of debris flow runout using Ramms : a case study of Luzhuang Gully in China

This study proposes a comprehensive method, which consists of field investigation, flume test and numerical simulation, to predict the velocity and sediment thickness of debris flow. The velocity and sediment thickness of the debris flow in mountainous areas can provide critical data to evaluate the geohazard, which will in turn help to understand the debris runout. The flume test of this debris prototype can provide friction coefficient and viscosity coefficient which are important for numerical simulation of debris flow. The relation between the key parameters in the numerical modelling using the Voellmy model and debris-flow rheology is discussed. Through simulation of a debris flow that occurred in Luzhuang gully, it is observed that the debris flow runout determined by the Voellmy model was well consistent with that obtained from field investigation and flume test, demonstrating the effectiveness of this study. The relationship between the Voellmy model and debris flow runout is also proposed

Flexural strengthening of reinforced concrete beams using hybrid fibre reinforced engineered cementitious composite

In this study, flexural strengthening of reinforced concrete (RC) beams using steel and polyvinyl-alcohol hybrid fibre reinforced engineered cementitious composite (SPH-ECC) with embedded steel reinforcement bars is proposed. The effectiveness of the strengthening was investigated by experimental and numerical studies. The flexural behaviours of one unstrengthened 3500 mm long, 200 mm wide, and 325 mm deep RC beam and three RC beams strengthened with different configurations of 50 mm thick SPH-ECC layer(s) were studied by conducting four-point bending tests. Detailed flexural behaviours in terms of peak load, failure mode, load-deflection curve, cracking patterns, interfacial bond-slip, strain distribution and ductility of the tested beams were studied and compared. Experimental results showed that both the flexural strength of strengthened beams, which were in the range of 125% to 210% of the unstrengthened control beam, and the interfacial bond-slip behaviours between concrete and SPH-ECC was highly depended to the strengthening configuration used. Crack width control ability of the beams was also improved by using SPH-ECC. A finite element (FE) procedure using surface-to-surface cohesive model was also developed to model the flexural behaviours of the strengthened beams. Comparison with experimental results demonstrated that the proposed FE model could accurately predict the flexural behaviours including interfacial bond-slip between the SPH-ECC layers and the RC beam part of the strengthened beams

A particle-based cohesive crack model for brittle fracture problems

Numerical simulations of the fracture process are challenging, and the discrete element (DE) method is an effective means to model fracture problems. The DE model comprises the DE connective model and DE contact model, where the former is used for the representation of isotropic solids before cracks initiate, while the latter is employed to represent particulate materials after cracks propagate. In this paper, a DE particle-based cohesive crack model is developed to model the mixed-mode fracture process of brittle materials, aiming to simulate the material transition from a solid phase to a particulate phase. Because of the particle characteristics of the DE connective model, the cohesive crack model is constructed at inter-particle bonds in the connective stage of the model at a microscale. A potential formulation is adopted by the cohesive zone method, and a linear softening relation is employed by the traction-separation law upon fracture initiation. This particle-based cohesive crack model bridges the microscopic gap between the connective model and the contact model and, thus, is suitable to describe the material separation process from solids to particulates. The proposed model is validated by a number of standard fracture tests, and numerical results are found to be in good agreement with the analytical solutions. A notched concrete beam subjected to an impact loading is modeled, and the impact force obtained from the numerical modeling agrees better with the experimental result than that obtained from the finite element method

Numerical modelling of additive manufacturing process for stainless steel tension testing samples

Nowadays additive manufacturing (AM) technologies including 3D printing grow rapidly and they are expected to replace conventional subtractive manufacturing technologies to some extents. During a selective laser melting (SLM) process as one of popular AM technologies for metals, large amount of heats is required to melt metal powders, and this leads to distortions and/or shrinkages of additively manufactured parts. It is useful to predict the 3D printed parts to control unwanted distortions and shrinkages before their 3D printing. This study develops a two-phase numerical modelling and simulation process of AM process for 17-4PH stainless steel and it considers the importance of post-processing and the need for calibration to achieve a high-quality printing at the end. By using this proposed AM modelling and simulation process, optimal process parameters, material properties, and topology can be obtained to ensure a part 3D printed successfully

Applications of two neuro-based metaheuristic techniques in evaluating ground vibration resulting from tunnel blasting

Peak particle velocity (PPV) caused by blasting is an unfavorable environmental issue that can damage neighboring structures or equipment. Hence, a reliable prediction and minimization of PPV are essential for a blasting site. To estimate PPV caused by tunnel blasting, this paper proposes two neuro-based metaheuristic models: neuro-imperialism and neuro-swarm. The prediction was made based on extensive observation and data collecting from a tunnelling project that was concerned about the presence of a temple near the blasting operations and tunnel site. A detailed modeling procedure was conducted to estimate PPV values using both empirical methods and intelligence techniques. As a fair comparison, a base model considered a benchmark in intelligent modeling, artificial neural network (ANN), was also built to predict the same output. The developed models were evaluated using several calculated statistical indices, such as variance account for (VAF) and a-20 index. The empirical equation findings revealed that there is still room for improvement by implementing other techniques. This paper demonstrated this improvement by proposing the neuro-swarm, neuro-imperialism, and ANN models. The neuro-swarm model outperforms the others in terms of accuracy. VAF values of 90.318% and 90.606% and a-20 index values of 0.374 and 0.355 for training and testing sets, respectively, were obtained for the neuro-swarm model to predict PPV induced by blasting. The proposed neuro-based metaheuristic models in this investigation can be utilized to predict PPV values with an acceptable level of accuracy within the site conditions and input ranges used in this study

A review on conducting polymers and nanopolymer composite coatings for steel corrosion protection

Corrosion is the principal reason for causing degradation of steel material properties, and coating is one of the most popular and effective ways to protect steel from corrosion. There are many kinds of coatings with different constituents, mechanisms and effectiveness. This paper presents a comprehensive review on the development of coating technology including traditional coatings, hydrophobic coatings, conducting polymer coatings and nanopolymer composite coatings. In particular, conducting polymers and nanopolymer composite coatings are reviewed in detail, which are the most popular and promising coatings. The advantages and limitations of each coating method as well as the influencing factors on corrosion protection are elaborated. Finally, the future research and applications are proposed

Toughening mechanisms for fiber-reinforced polymer-reinforced concrete beams

The bond between reinforcing bars and the surrounding concrete is one of the dominant mechanisms affecting the structural behaviour of fiber-reinforced polymer (FRP)-reinforced concrete structures. In this chapter, the experimental and numerical studies on the bond mechanism between FRP rebars and concrete in FRP-reinforced concrete beams are presented. Concrete beams reinforced with three types of FRP rebars with different rebar surfaces were tested under four-point bending loads to investigate the effects of types and surface conditions of FRP rebars on the bond-slip behaviour of reinforced concrete beams. A new finite element model recently developed and validated by the authors was employed to numerically investigate the bond-slip behaviour of FRP-reinforced concrete beams and the effects of different rebar surfaces and different rebar types on the bond-slip behaviour. The results are presented and the toughening mechanism between FRP rebars and concrete is analyzed

Multiscale finite element modeling of failure process of composite laminates

A multiscale nonlinear finite element modeling technique is developed in this paper to predict the progressive failure process for composite laminates. A micromechanical elastic–plastic bridging constitutive model, which considers the nonlinear material properties of the constituent fiber and matrix materials and their interaction and the damage and failure in fibrous composites at the fiber and matrix level, is proposed to represent the material behavior of fiber-reinforced composite laminates. The micromechanics constitutive model is employed in the macroscale finite element analysis of structural behavior especially progressive failure process of the fiber-reinforced composites based on a 4-node 24-DOF shear-locking free rectangular composite plate element

Advances in Engineered Cementitious Composites: Materials, Structures, and Numerical Modeling

Advances in Engineered Cementitious Composite: Materials, Structures and Numerical Modelling focuses on recent research developments in high-performance fiber-reinforced cementitious composites, covering three key aspects, i.e., materials, structures and numerical modeling. Sections discuss the development of materials to achieve high-performance by using different type of fibers, including polyvinyl alcohol (PVA), polyethylene (PE) polypropylene (PP) and hybrid fibers. Other chapters look at experimental studies on the application of high-performance fiber-reinforced cementitious composites on structures and the performance of structural components, including beams, slabs and columns, and recent development of numerical methods and modeling techniques for modeling material properties and structural behavior. This book will be an essential reference resource for materials scientists, civil and structural engineers and all those working in the field of high-performance fiber-reinforced cementitious composites and structures