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Seismic effects on reinforcement load and lateral deformation of geosynthetic-reinforced soil walls

《结构与土木工程前沿（英文）》 2021年 第15卷 第4期   页码 1001-1015 doi: 10.1007/s11709-021-0734-8

摘要： Current design methods for the internal stability of geosynthetic-reinforced soil (GRS) walls postulate seismic forces as inertial forces, leading to pseudo-static analyses based on active earth pressure theory, which yields unconservative reinforcement loads required for seismic stability. Most seismic analyses are limited to the determination of maximum reinforcement strength. This study aimed to calculate the distribution of the reinforcement load and connection strength required for each layer of the seismic GRS wall. Using the top-down procedure involves all of the possible failure surfaces for the seismic analyses of the GRS wall and then obtains the reinforcement load distribution for the limit state. The distributions are used to determine the required connection strength and to approximately assess the facing lateral deformation. For sufficient pullout resistance to be provided by each reinforcement, the maximum required tensile resistance is identical to the results based on the Mononobe–Okabe method. However, short reinforcement results in greater tensile resistances in the mid and lower layers as evinced by compound failure frequently occurring in GRS walls during an earthquake. Parametric studies involving backfill friction angle, reinforcement length, vertical seismic acceleration, and secondary reinforcement are conducted to investigate seismic impacts on the stability and lateral deformation of GRS walls.

关键词： geosynthetics     reinforced soil     retaining walls     seismic performance    

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Three-dimensional numerical modeling of single geocell-reinforced sand

Xiaoming YANG, Jie HAN, Robert L. PARSONS, Dov LESHCHINSKY,

《结构与土木工程前沿（英文）》 2010年 第4卷 第2期   页码 233-240 doi: 10.1007/s11709-010-0020-7

摘要： This paper summarizes the development of a three-dimensional numerical model for analyzing single geocell-reinforced soil. In this model, the infill soil was modeled using the Duncan-Chang model, which can simulate non-linearity and stress-dependency of soil. Geocell was modeled using linearly elastic plate elements, which can carry both bending and membrane stresses. A linear interface stress-strain relationship with a Mohr-Coulomb yield criterion was adopted to model the interface friction between the geocell wall and the soil. By modeling the geocell and the soil separately, the interaction between the soil and the geocell can be accurately simulated. To verify this model, a plate load test was conducted in the laboratory, in which a 12-cm-thick sand layer reinforced by a single geocell was subjected to a vertical load from a circular steel plate. The load-displacement curves and the horizontal tensile strain of the geocell were recorded during the test. A numerical model was created according to the setup of the load test. The numerical results compared reasonably well with the test data.

关键词： geosynthetic reinforcement     geocell     numerical model     FLAC3D    

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Recent advances in geosynthetic-reinforced retaining walls for highway applications

Jie HAN, Yan JIANG, Chao XU

《结构与土木工程前沿（英文）》 2018年 第12卷 第2期   页码 239-247 doi: 10.1007/s11709-017-0424-8

摘要： Geosynthetic-reinforced retaining (GRR) walls have been increasingly used to support roadways and bridge abutments in highway projects. In recent years, advances have been made in construction and design of GRR walls for highway applications. For example, piles have been installed inside GRR walls to support bridge abutments and sound barrier walls. Geosynthetic layers at closer spacing are used in GRR walls to form a composite mass to support an integrated bridge system. This system is referred to as a geosynthetic-reinforced soil (GRS)-integrated bridge systems (IBS) or GRS-IBS. In addition, short geosynthetic layers have been used as secondary reinforcement in a GRR wall to form a hybrid GRR wall (HGRR wall) and reduce tension in primary reinforcement and facing deflections. These new technologies have improved performance of GRR walls and created more economic solutions; however, they have also created more complicated problems for analysis and design. This paper reviews recent studies on these new GRR wall systems, summarizes key results and findings including but not limited to vertical and lateral earth pressures, wall facing deflections, and strains in geosynthetic layers, discusses design aspects, and presents field applications for these new GRR wall systems.

关键词： bridge     geosynthetic     highway     reinforced     wall    

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Field testing of geosynthetic-reinforced and column-supported earth platforms constructed on soft soil

Qiangong CHENG,Jiujiang WU,Dongxue ZHANG,Fengping MA

《结构与土木工程前沿（英文）》 2014年 第8卷 第2期   页码 124-139 doi: 10.1007/s11709-014-0255-9

摘要： This paper is focused on the behavior of geosynthetic-reinforced and column-supported (GRCS) earth platforms in soft soil. By analyzing the data of a 15-month long field monitoring project, the bearing behavior and effectiveness of GRCS earth platforms are discussed in detail. It can be found that the soil arching is generated when the filling reaches a certain height. The measured pressure acting on the soil in the center of four piles was smaller than that acting on the soil between two piles. The elongation and the tension of the geogrid located in the soil between piles are both larger than the corresponding values on the pile top. The skin friction of piles is relatively small in the soil layer with low strength and the load transfer of the axial force in those layers is significant; meanwhile, the opposite situation occurs in the soil layer with high strength. The pore water pressure at shallow locations increases slightly with the filling height and is greatly affected by the increasing filling load. The layered settlement is directly proportional to the filling height, and the corresponding amount is relevant to the locations and the properties of specific soil layers. Additionally, the lateral displacement of the embankment increases with greater loading and decreases with increased depth. These suggest that the use of GRCS system can reduce lateral displacements and enhance the stability of an embankment significantly.

关键词： geosynthetic-reinforced and column-supported (GRCS) earth platforms     soft soil     bearing behavior     settlement and deformation     field testing    

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

《机械工程前沿（英文）》 2022年 第17卷 第2期 doi: 10.1007/s11465-022-0673-7

摘要： Convolutional neural network (CNN) has achieved remarkable applications in fault diagnosis. However, the tuning aiming at obtaining the well-trained CNN model is mainly manual search. Tuning requires considerable experiences on the knowledge on CNN training and fault diagnosis, and is always time consuming and labor intensive, making the automatic hyper parameter optimization (HPO) of CNN models essential. To solve this problem, this paper proposes a novel automatic CNN (ACNN) for fault diagnosis, which can automatically tune its three key hyper parameters, namely, learning rate, batch size, and L2-regulation. First, a new deep reinforcement learning (DRL) is developed, and it constructs an agent aiming at controlling these three hyper parameters along with the training of CNN models online. Second, a new structure of DRL is designed by combining deep deterministic policy gradient and long short-term memory, which takes the training loss of CNN models as its input and can output the adjustment on these three hyper parameters. Third, a new training method for ACNN is designed to enhance its stability. Two famous bearing datasets are selected to evaluate the performance of ACNN. It is compared with four commonly used HPO methods, namely, random search, Bayesian optimization, tree Parzen estimator, and sequential model-based algorithm configuration. ACNN is also compared with other published machine learning (ML) and deep learning (DL) methods. The results show that ACNN outperforms these HPO and ML/DL methods, validating its potential in fault diagnosis.

关键词： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

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Punching of reinforced concrete slab without shear reinforcement: Standard models and new proposal

Luisa PANI, Flavio STOCHINO

《结构与土木工程前沿（英文）》 2020年 第14卷 第5期   页码 1196-1214 doi: 10.1007/s11709-020-0662-z

摘要： Reinforced concrete (RC) slabs are characterized by reduced construction time, versatility, and easier space partitioning. Their structural behavior is not straightforward and, specifically, punching shear strength is a current research topic. In this study an experimental database of 113 RC slabs without shear reinforcement under punching loads was compiled using data available in the literature. A sensitivity analysis of the parameters involved in the punching shear strength assessment was conducted, which highlighted the importance of the flexural reinforcement that are not typically considered for punching shear strength. After a discussion of the current international standards, a new proposed model for punching shear strength and rotation of RC slabs without shear reinforcement was discussed. It was based on a simplified load-rotation curve and new failure criteria that takes into account the flexural reinforcement effects. This experimental database was used to validate the approaches of the current international standards as well as the new proposed model. The latter proved to be a potentially useful design tool.

关键词： punching shear strength     reinforced concrete     slabs     reinforcement ratio    

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Spatial embedded reinforcement of 20-node block element for analysis PC bridges

LONG Peiheng, DU Xianting, CHEN Weizhen

《结构与土木工程前沿（英文）》 2008年 第2卷 第3期   页码 274-280 doi: 10.1007/s11709-008-0039-1

摘要： The formula for the contribution of prestressed reinforcement on embedded reinforcement element is derived according to the mechanical behavior of PC bridges and the foundational principle of finite element method. Mechanical concept is definite and examples validate the calculation results. Reinforcement element model allows generating a finite element mesh without taking into consideration the layout of reinforcements. Furthermore, the prestressing tendon may pass through the concrete elements in an arbitrary manner. It is an effective approach that the no-node loads are diverted from the tendons to the adjacent concrete elements. A useful arithmetic analysis of the spatial curved tendon PC Bridges is provided.

关键词： arithmetic analysis     calculation     prestressed reinforcement     mechanical     arbitrary    

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Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse Reinforcement

Jian Wu,Yang Yan,Yulong Liu,Yahui Liu,

《工程（英文）》 doi: 10.1016/j.eng.2023.07.018

摘要： The forward design of trajectory planning strategies requires preset trajectory optimization functions, resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits. In addition, owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios, it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters. Therefore, an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed. First, numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset. Subsequently, a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory. Furthermore, a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function, and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed. Finally, the proposed strategy is verified based on real driving scenarios. The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the “emergency degree” of obstacle avoidance and the state of the vehicle. Moreover, this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories, effectively improving the adaptability and acceptability of trajectories in driving scenarios.

关键词： Obstacle avoidance trajectory planning     Inverse reinforcement theory     Anthropomorphic     Adaptive driving scenarios    

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Automated synthesis of steady-state continuous processes using reinforcement learning

《化学科学与工程前沿（英文）》 2022年 第16卷 第2期   页码 288-302 doi: 10.1007/s11705-021-2055-9

摘要： Automated flowsheet synthesis is an important field in computer-aided process engineering. The present work demonstrates how reinforcement learning can be used for automated flowsheet synthesis without any heuristics or prior knowledge of conceptual design. The environment consists of a steady-state flowsheet simulator that contains all physical knowledge. An agent is trained to take discrete actions and sequentially build up flowsheets that solve a given process problem. A novel method named SynGameZero is developed to ensure good exploration schemes in the complex problem. Therein, flowsheet synthesis is modelled as a game of two competing players. The agent plays this game against itself during training and consists of an artificial neural network and a tree search for forward planning. The method is applied successfully to a reaction-distillation process in a quaternary system.

关键词： automated process synthesis     flowsheet synthesis     artificial intelligence     machine learning     reinforcement learning    

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Deep reinforcement learning-based critical element identification and demolition planning of frame structures

Shaojun ZHU; Makoto OHSAKI; Kazuki HAYASHI; Shaohan ZONG; Xiaonong GUO

《结构与土木工程前沿（英文）》 2022年 第16卷 第11期   页码 1397-1414 doi: 10.1007/s11709-022-0860-y

摘要： This paper proposes a framework for critical element identification and demolition planning of frame structures. Innovative quantitative indices considering the severity of the ultimate collapse scenario are proposed using reinforcement learning and graph embedding. The action is defined as removing an element, and the state is described by integrating the joint and element features into a comprehensive feature vector for each element. By establishing the policy network, the agent outputs the Q value for each action after observing the state. Through numerical examples, it is confirmed that the trained agent can provide an accurate estimation of the Q values, and handle problems with different action spaces owing to utilization of graph embedding. Besides, different behaviors can be learned by varying hyperparameters in the reward function. By comparing the proposed method and the conventional sensitivity index-based methods, it is demonstrated that the computational cost is considerably reduced because the reinforcement learning model is trained offline. Besides, it is proved that the Q values produced by the reinforcement learning agent can make up for the deficiencies of existing indices, and can be directly used as the quantitative index for the decision-making for determining the most expected collapse scenario, i.e., the sequence of element removals.

关键词： progressive collapse     alternate load path     demolition planning     reinforcement learning     graph embedding    

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Geosynthetics used to stabilize vegetated surfaces for environmental sustainability in civil engineering

Jie HAN,Jun GUO

《结构与土木工程前沿（英文）》 2017年 第11卷 第1期   页码 56-65 doi: 10.1007/s11709-016-0380-8

摘要： Geosynthetics, factory-manufactured polymer materials, have been successfully used to solve many geotechnical problems in civil engineering. Two common applications are earth stabilization and erosion control. Geosynthetics used for earth stabilization include but are not limited to stabilized slopes, walls, embankments, and roads. Geosynthetics used for erosion control are mostly related to slopes, river channels and banks, and pond spillways. To enhance environmental sustainability, vegetation has been increasingly planted on the facing or surfaces of these earth structures. Under such a condition, geosynthetics mainly function as surficial soil stabilization while vegetation provides green appearance and erosion protection of earth surfaces. Recently, geosynthetic or geosynthetic-like material has been used to form green walls outside or inside buildings to enhance sustainability. Geosynthetics and vegetation are often integrated to provide combined benefits. The interaction between geosynthetics and vegetation is important for the sustainability of the earth and building wall surfaces. This paper provides a review of the current practice and research in the geosynthetic stabilization of vegetated earth and building surfaces for environmental sustainability in civil engineering with the emphases on geosynthetic used for erosion protection, geosynthetic-stabilized slopes, geosynthetic-stabilized unpaved shoulders and parking lots, and geosynthetic-stabilized vegetated building surfaces.

关键词： erosion     geosynthetic     stabilization     sustainability     vegetation    

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Effect of earth reinforcement, soil properties and wall properties on bridge MSE walls

《结构与土木工程前沿（英文）》 2021年 第15卷 第5期   页码 1209-1221 doi: 10.1007/s11709-021-0764-2

摘要： Mechanically stabilized earth (MSE) retaining walls are popular for highway bridge structures. They have precast concrete panels attached to earth reinforcement. The panels are designed to have some lateral movement. However, in some cases, excessive movement and even complete dislocation of the panels have been observed. In this study, 3-D numerical modeling involving an existing MSE wall was undertaken to investigate various wall parameters. The effects of pore pressure, soil cohesion, earth reinforcement type and length, breakage/slippage of reinforcement and concrete strength, were examined. Results showed that the wall movement is affected by soil pore pressure and reinforcement integrity and length, and unaffected by concrete strength. Soil cohesion has a minor effect, while the movement increased by 13–20 mm for flexible geogrid reinforced walls compared with the steel grid walls. The steel grid stresses were below yielding, while the geogrid experienced significant stresses without rupture. Geogrid reinforcement may be used taking account of slippage resistance and wall movement. If steel grid is used, non-cohesive soil is recommended to minimize corrosion. Proper soil drainage is important for control of pore pressure.

关键词： mechanically stabilized earth walls     precast concrete panels     backfill soil     finite element modeling     earth reinforcement    

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Layout optimization of steel reinforcement in concrete structure using a truss-continuum model

《结构与土木工程前沿（英文）》 2023年 第17卷 第5期   页码 669-685 doi: 10.1007/s11709-023-0963-0

摘要： Owing to advancement in advanced manufacturing technology, the reinforcement design of concrete structures has become an important topic in structural engineering. Based on bi-directional evolutionary structural optimization (BESO), a new approach is developed in this study to optimize the reinforcement layout in steel-reinforced concrete (SRC) structures. This approach combines a minimum compliance objective function with a hybrid truss-continuum model. Furthermore, a modified bi-directional evolutionary structural optimization (M-BESO) method is proposed to control the level of tensile stress in concrete. To fully utilize the tensile strength of steel and the compressive strength of concrete, the optimization sensitivity of steel in a concrete–steel composite is integrated with the average normal stress of a neighboring concrete. To demonstrate the effectiveness of the proposed procedures, reinforcement layout optimizations of a simply supported beam, a corbel, and a wall with a window are conducted. Clear steel trajectories of SRC structures can be obtained using both methods. The area of ​​critical tensile stress in concrete yielded by the M-BESO is more than 40% lower than that yielded by the uniform design and BESO. Hence, the M-BESO facilitates a fully digital workflow that can be extremely effective for improving the design of steel reinforcements in concrete structures.

关键词： bi-directional evolutionary structural optimization     steel-reinforced concrete     concrete stress     reinforcement method     hybrid model    

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Toward Trustworthy Decision-Making for Autonomous Vehicles: A Robust Reinforcement Learning Approach

Xiangkun He,Wenhui Huang,Chen Lv,

《工程（英文）》 doi: 10.1016/j.eng.2023.10.005

摘要： While autonomous vehicles are vital components of intelligent transportation systems, ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving. Therefore, we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles. The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety. Specifically, an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics. In addition, an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics. Moreover, we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety model. Finally, the proposed approach is evaluated through both simulations and experiments. These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

关键词： Autonomous vehicle     Decision-making     Reinforcement learning     Adversarial attack     Safety guarantee    

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概念加固思想及工程应用

段敬民,钱永久,张方,曾宪桃

《中国工程科学》 2005年 第7卷 第8期   页码 22-25

摘要：

提出了工程结构加固中新的思路——概念加固。概念加固是运用人的思维和判断，从宏观上决定工程加固中的基本问题、基本概念及基本原则，并阐述了基于“概念加固”思想指导下的整体预应力加固技术，介绍了在工程加固中的应用实例。

关键词： 工程结构     概念加固     整体预应力加固技术    

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标题 作者 时间 类型 操作

Seismic effects on reinforcement load and lateral deformation of geosynthetic-reinforced soil walls

期刊论文

Three-dimensional numerical modeling of single geocell-reinforced sand

Xiaoming YANG, Jie HAN, Robert L. PARSONS, Dov LESHCHINSKY,

期刊论文

Recent advances in geosynthetic-reinforced retaining walls for highway applications

Jie HAN, Yan JIANG, Chao XU

期刊论文

Field testing of geosynthetic-reinforced and column-supported earth platforms constructed on soft soil

Qiangong CHENG,Jiujiang WU,Dongxue ZHANG,Fengping MA

期刊论文

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

期刊论文

Punching of reinforced concrete slab without shear reinforcement: Standard models and new proposal

Luisa PANI, Flavio STOCHINO

期刊论文

Spatial embedded reinforcement of 20-node block element for analysis PC bridges

LONG Peiheng, DU Xianting, CHEN Weizhen

期刊论文

Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse Reinforcement

Jian Wu,Yang Yan,Yulong Liu,Yahui Liu,

期刊论文

Automated synthesis of steady-state continuous processes using reinforcement learning

期刊论文

Deep reinforcement learning-based critical element identification and demolition planning of frame structures

Shaojun ZHU; Makoto OHSAKI; Kazuki HAYASHI; Shaohan ZONG; Xiaonong GUO

期刊论文

Geosynthetics used to stabilize vegetated surfaces for environmental sustainability in civil engineering

Jie HAN,Jun GUO

期刊论文

Effect of earth reinforcement, soil properties and wall properties on bridge MSE walls

期刊论文

Layout optimization of steel reinforcement in concrete structure using a truss-continuum model

期刊论文

Toward Trustworthy Decision-Making for Autonomous Vehicles: A Robust Reinforcement Learning Approach

Xiangkun He,Wenhui Huang,Chen Lv,

期刊论文

概念加固思想及工程应用

段敬民,钱永久,张方,曾宪桃

期刊论文