Xinzheng Lu

• PhD
• Professor (Full) at Tsinghua University

Collapse resistance of high-rise buildings has become a research focus because of the frequent occurrence of strong earthquakes and terrorist attacks in recent years. Research development has demonstrated that numerical simulation is becoming one of the most powerful tools for collapse analysis in addition to the conventional laboratory model tests...

When a reinforced concrete (RC) frame subjected to an edge-column-removal scenario, its floor system exhibits a complicated mechanism against progressive collapse due to the interaction between beams and slabs and the two-way load transfer characteristics. In this study, laboratory tests of five 1/3-scaled RC frame substructure specimens, including...

The first edition of this monograph, presenting accurate and efficient simulations of seismic damage to buildings and cities, has received significant attention from the research community. To keep abreast of the rapid development in recent years, our latest breakthrough achievements have been added to this new edition, including novel resilient st...

Every year, earthquakes result in severe economic losses and a significant number of casualties worldwide. In limiting the losses that occur after these extreme events, timely and accurate assessment of seismic damages and mobilizing proportionate post‐event relief efforts play crucial roles. Traditional on‐site investigation generally results in p...

Performance-based fire safety design requires thoroughly evaluating building fire scenarios to ensure comprehensive fire safety. However, conventional Computational Fluid Dynamics (CFD) fire simulations are computationally intensive and time-consuming, limiting the number of scenarios that can be practically analyzed. This study addresses these cha...

The development of intelligent design methods for buckling-restrained brace (BRB) retrofit schemes can effectively enhance the seismic performance of reinforced concrete (RC) frame structures to address their insufficient seismic capacity. This study further explores the two-stage intelligent design framework for BRB retrofitting by combining gener...

Artificial intelligent design technology for shear wall structures holds promise in enhancing design efficiency and addressing the tedious and repetitive nature of conventional design work. This technology has experienced rapid development in recent years. However, based on deep learning, the existing design methods for shear wall structures face c...

Traditional reinforced concrete (RC) frame design depends on extensive engineering experience and iterative verification processes, often resulting in significant inefficiencies. The diversity in the topologies and behaviors of structural components further presents considerable obstacles to effective machine learning applications in design. This p...

Generative artificial intelligence-driven design of shear wall structures is crucial for the intelligent design of buildings, but current methods arrange shear walls and then beams successively, overlooking their interdependence. This paper constructed a graph representation of the coupled potential positions for shear walls and beams and proposed...

When solving expensive optimization problems (EOPs), e.g., optimization design of shear-wall structures, conventional evolutionary algorithms (EAs) face a challenge of elevated costs related to fitness evaluation. On the other hand, surrogate-assisted evolutionary algorithms (SAEAs) can effectively reduce evaluation costs and are therefore widely u...

Abstract: The regulatory clauses of building and construction standards or codes usually include diverse engineering concepts, implicit common knowledge, and complex combination of rules , which pose great challenges to the automatic learning and reasoning of standards. Therefore, the authors established a systematic framework for intelligent inter...

The intelligent design of shear wall structures is a critical aspect of smart construction, with a high demand for research and applications. Accurately predicting the shear wall ratio (i.e., the shear wall area-to-floor area ratio) during cost estimation and rapidly generating shear wall layouts during early design is essential. However, the uncle...

This study explores artificial intelligence (AI) for shear wall layout design, aiming to overcome challenges in data feature sparsity and the complexity of drawing representations in existing AI-based methods. We pioneer an innovative method leveraging the potential of diffusion models, establishing a suitable drawing representation, and examining...

Ground motion prediction (GMP) models are critical for hazard reduction before, during and after destructive earthquakes. In these three stages, intensity forecasting, early warning and interpolation models are corresponding employed to assess the risk. Considering the high cost in numerical methods and the oversimplification in statistical methods...

As buildings and structures age, the challenges of reinforcement and retrofitting become more significant, especially as their service life extends and the demand for seismic fortification increases. Integrating buckling-restrained braces (BRBs) is an effective retrofit technique; however, this approach requires multiple iterations of layout adjust...

Rapid progress in intelligent design technology for shear wall structures has significantly advanced the field. However, efficient evaluation and decision-making of various intelligent design outcomes remain challenging, particularly in the automated modeling and analysis of artificial intelligence (AI)-generated designs and the rational selection...

Vision-based digital shadowing is a highly efficient way to monitor the health of buildings in use. However, previous studies on digital shadowing have been limited to laboratory experiments. This paper proposes a novel computer-vision-based digital shadow workflow and presents its successful application in a real engineering case. In this case, a...

The generation and editing of floor plans are critical in architectural planning, requiring a high degree of flexibility and efficiency. Existing methods demand extensive input information and lack the capability for interactive adaptation to user modifications. This paper introduces ChatHouseDiffusion, which leverages large language models (LLMs)...

In December 2023, a 6.2 magnitude earthquake struck Jishishan, Gansu Province. This study utilized the Real-time Earthquake Damage Assessment using City-scale Time-history analysis (RED-ACT) system to analyze the seismic damage caused by the event. The analysis included assessments of strong ground motion records, building damage, and human acceler...

Fire following earthquakes remains a significant and threatening hazard to communities in urban regions. Addressing this critical issue requires an effective simulation method that is suitable for widespread adoption. This paper presents a systematic end-to-end framework for simulating fire following earthquakes at a regional scale by integrating m...

The assessment of the post-earthquake functionality of medical buildings (PEFMB) is critical for the post-earthquake emergency response, recovery, and resilience-based seismic design of medical buildings. Hospitals are complex functional systems that exhibit multilevel functional coupling from components to departments to floors. Existing methods h...

The generative intelligent design of building structures has been a rapidly evolving field in recent years, with shear wall structures efficiently designed using generative adversarial networks (GANs). Nevertheless, using RGB images to represent structural design drawings may not accurately capture the correlations and distinctions between building...

Intelligent design technology for shear wall structures has great potential for enhancing design efficiency and addressing the challenges of tedious and repetitive design tasks. Recently, there has been a surge in the development of this technology. However, existing deep learning-based design methods for shear wall structures suffer from poor qual...

As society places higher demands on the quality of building designs, design software has become more professional and complicated. Current design software not only incurs high learning costs but also features complex interaction modes. The recent breakthroughs in large language models (LLM) have enabled computers to clearly comprehend instructions...

Construction of disaster-resilient cities has attracted considerable attention. However, traditional methods of studying urban disaster resilience through experimental approaches are often constrained by various limitations, such as testing sites, costs and ethical considerations. To address these constraints, this paper proposes incorporating digi...

Dynamic displacement response is an essential indicator for assessing structural state and performance. Vision-based structural displacement monitoring is considered as a promising approach. However, the current vision-based methods usually only focus on certain application scenarios. This study introduces a Sparse Bayesian Learning-based (SBL) alg...

To enable secondary energy-dissipation components to actively attract and dissipate seismic energy, a new type of sacrificial-energy dissipation beam-column joint (SEDJ) was proposed. This study validates the performance of the proposed SEDJ through full-scale quasi-static loading tests. The rotation angle of the proposed SEDJ at the beam end, corr...

To address the issue of costly computational expenditure related to high-fidelity numerical models, surrogate models have been widely used in various engineering tasks, including design optimization. Despite the successful application of the existing surrogate models, physics-based models depend largely on simplifications and assumptions, which ren...

Progressive structural collapse is a typical low-probability high-consequence event. Progressive collapse design can effectively improve the robustness of structures against accidental local damage and reduce the probability of collapse. However, progressive collapse design also increases the construction cost of buildings. Hence, it is necessary t...

Social media aids disaster response but suffers from noise, hindering accurate impact assessment and decision making for resilient cities, which few studies considered. To address the problem, this study proposes the first domain-specific LLM model and an integrated method for rapid earthquake impact assessment. First, a few categories are introduc...

In the safety design of supertall buildings, the collapse resistance analysis account for one significantly important part, and ensuing sufficient collapse resistance of supertall buildings is of great significance to protect the safety of people's lives and property. To the authors’ knowledge, the design cases that comprehensively consider earthqu...

Long-term structural health monitoring (SHM) using vision-based methods may encounter challenges of data storage, low-sampling resolution, and data loss. Compressive sensing (CS) offers the possibility for alleviating these problems, by using less than half of the complete signal to recover the signal based on the sparsity. This paper proposed a mo...

Vision-based structural motion estimation methods show great potential in structural health monitoring (SHM). However, available methods cannot automatically estimate and eliminate three-dimensional (3D) camera motion effects caused by environmental factors from the video containing structural motions. This limits further applications of vision-bas...

After a city-scale natural hazard, policymakers should plan sound decisions on the repair sequence to ensure the resilient recovery of the community, which consists of interdependent infrastructures. Stochastic scheduling for repairing interdependent infrastructure systems is a difficult control problem with huge decision spaces. This study propose...

Beam placement in shear wall systems is crucial in transferring vertical loads from floors to shear walls, ensuring structural integrity and optimal performance. Existing solutions using deep generative algorithms rely on pixel images and involve many model parameters, resulting in high computational costs. To address this issue, this paper present...

Interpreting regulatory documents or building codes into computer-processable formats is essential for the intelligent design and construction of buildings and infrastructures. Although automated rule interpretation (ARI) methods have been investigated for years, most of them are highly dependent on the early and manual filtering of interpretable c...

Designing building structures presents various challenges, including inefficient design processes, limited data reuse, and the underutilization of previous design experience. Generative artificial intelligence (AI) has emerged as a powerful tool for learning and creatively using existing data to generate new design ideas. Learning from past experie...

The rapid advancement of intelligent design technology in building structures has been primarily implemented in engineering practice through the use of local or cloud-based software to offer intelligent design services. However, local intelligent design services are time-consuming and require high-end hardware, whereas cloud-based designs fail to i...

The construction industry, traditionally labor-intensive, has now been evolving towards automation and the incorporation of intelligence. Notably, the shear wall layout has been a critical component in structural construction, where neural networks have promoted the emergence of sophisticated design methods. These methods integrate graph neural net...

An accurate and efficient simulation of the hysteretic behavior of materials and components is essential for structural analysis. The surrogate model based on neural networks shows significant potential in balancing efficiency and accuracy. However, its serial information flow and prediction based on single-level features adversely affect the netwo...

To improve the seismic resiliency of precast concrete (PC) wall, a type of emulative PC wall with replaceable corner components (RCCs) was developed in this study. The damage of the PC wall was deliberately concentrated in the RCCs, which can be replaced after an earthquake. Four large-aspect-ratio specimens (including three PC walls with different...

To enable secondary energy-dissipating components to actively attract and dissipate seismic energy, a new type of sacrificial-energy dissipation beam-column joint (SEDJ) was proposed for frame structures. During strong earthquakes, the post-yield strength of the SEDJ was actively weakened by the shear failure of the bolts, and the friction between...

Intelligent structural design based on machine learning represents a novel structural design paradigm and has received extensive attention in recent years. However, the performance of the machine learning models is heavily dependent on the quality and quantity of training data, as the underlying approaches are inherently data-driven. Well-recognize...

The construction material quantity (CMQ) is widely concerned in the structural design of reinforced concrete buildings and is often included among the objective functions of computer-aided optimization design techniques. To minimize construction cost and carbon emissions, an accurate and efficient CMQ estimation method is timely required. In this s...

Deep learning-driven intelligent generative design for building structures provides novel insights into intelligent construction. In a structural scheme design, the cross-sectional design of the shear wall components is critical. However, the current manual method is time-consuming and labor-intensive, and a statistical regression-based design is i...

Accurately evaluating derivatives poses a key challenge when numerically implementing complex constitutive models. This work presents an implicit stress update algorithm that utilizes the hyper dual step derivative approximation to address derivative evaluations in elastoplastic problems. Initially, the performance of various numerical differentiat...

Seismic isolation can significantly improve the seismic resilience of buildings, resulting in a growing demand for seismic isolation designs. Meanwhile, the deep generative network-based intelligent design can significantly increase scheme design efficiency. However, the performance of existing intelligent scheme designs is constrained by data qual...

The vibration data are quite important for structural health monitoring (SHM). This paper proposed a novel method, to adaptively estimate video motions of the structure in subpixel accuracy, without attaching any targets. The proposed method includes three steps. In the first step, to remove outliers and simultaneously preserve feature points, the...

Automated rule checking (ARC), which is expected to promote the efficiency of the compliance checking process in the architecture, engineering, and construction (AEC) industry, is gaining increasing attention. Throwing light on the ARC application hotspots and forecasting its trends are useful to the related research and drive innovations. Therefor...

As a vital stage of automated rule checking (ARC), rule interpretation of regulatory texts requires considerable effort. However, interpreting regulatory clauses with implicit properties or complex computational logic is still challenging due to the lack of domain knowledge and limited expressibility of conventional logic representations. Thus, LLM...

A realistic and practical damping model is essential for structural dynamics. In this study, the second-order accurate time discretization of a high-performance uniform damping model for response history analysis is derived. Its stability and accuracy are proven, and its object-oriented implementation is introduced in OpenSees. The proposed time di...

Design review, i.e., design compliance checking, is a key step to ensure the safety, environmental protection, comfort, and compliance of a design. To address the problem of high cost, subjectivity, low efficiency and error-proneness of manual checking of building designs, intelligent design review (e.g., automated compliance checking) has been pro...

Accurate force–deformation hysteretic models for structures, components, and materials are essential for structural analysis. The development of an explicit mathematical model for hysteresis poses challenges in the fields of artificial model selection and precise and efficient calibration of key parameters. In recent years, deep learning-based impl...

There are numerous advantages of deep neural network surrogate modeling for response time-history prediction. However, due to the high cost of refined numerical simulations and actual experiments, the lack of data has become an unavoidable bottleneck in practical applications. An iterative self-transfer learningmethod for training neural networks b...

Tall buildings can affect the seismic safety of shorter buildings in their vicinities. Majority of the studies have investigated such influences by analyzing the structure-soil-structure interactions in the local vicinity. Considering the large mass and long fundamental period of tall buildings, perturbations during earthquakes can affect a very br...

Intelligent construction (IC) has emerged as a new approach to transforming the architecture, engineering, and construction (AEC) industry through the integration of advanced information technologies such as artificial intelligence (AI) and the Internet of Things (IoT). However, due to its interdisciplinary nature, the relevant documents on IC are...

Computer vision-based displacement measurement methods have received increasing attention for the structural health monitoring of buildings and infrastructures owing to their advantages over traditional contact sensors. Meanwhile, surveillance cameras widely equipped in urban areas can record a large number of images and videos of buildings and inf...

Progressive collapse, usually caused by accidental or abnormal loading, is a structural failure disproportionate to its original cause. Reinforced concrete (RC) flat plate structures are vulnerable to brittle punching shear failure in the vicinity of slab-column joints, which may initiate disastrous progressive collapse causing significant economic...

An accurate prediction of the number of passengers trapped in elevators under earthquakes in urban areas is essential for promoting earthquake emergencies. A probability-based city-scale method for assessing the earthquake-induced risk of passenger entrapment in elevators was proposed, in which city-scale time history analysis was performed to simu...

Central business districts are densely built with clusters of high-rise buildings that are exposed to winds, impacting their strength, serviceability, and habitability. A computational framework to perform the city-scale evaluation of wind effects on buildings was proposed in this work, while existing studies have been mostly limited to isolated bu...

Structural progressive collapse design is essential for improving the robustness of structures against accidental local loads. In this study, a design framework was developed for optimizing the nonlinear dynamic progressive collapse design of reinforced concrete (RC) frame structures. An objective function featuring both structural response and mat...

Port based transportations are key elements governing the operation of global maritime logistics. In China, the southeast coastline suffers from typhoons frequently every year and causes many disruptions to port operations and thus economic losses. Quantitative evaluation of coastal ports' economic losses induced by typhoons is quite demanding and...

In the elastic dynamic response analysis of a structure, damping has an important influence and directly determines the energy dissipation and decay behavior of the structure. An accurate understanding of the applicable conditions of different damping models is of great significance for the analysis of practical engineering problems. The main chara...

Structural scheme design of shear wall structures is important because it is the first stage that guides the project along its entire structural design process and significantly impacts the subsequent design stages. Design methods for shear wall layouts based on deep generative algorithms have been proposed and achieved some success. However, curre...

The preliminary layout design of the shear wall is critical for the design of reinforced concrete shear wall structures. Deep learning-based methods can learn design experience from existing design data and generate new designs efficiently. However, existing research is insufficient for the design of the local layout of shear walls in critical zone...

The layout design of the frame structure beams is a critical task in frame structure design. Traditional automatic layout methods often rely on established rules. However, the predefined rules are often incomplete, and the conflicts and priorities between different constraints are often unclear. Consequently, it is difficult for traditional automat...

The phase-based estimation, as one type of target-free methods, can estimate small structural motions from video data. However, in the two-dimensional (2D) domain, this method is prone to noisy errors because of the ill-posed problem, and its measurement range is limited due to the periodicity of the phase variation. Additionally, it cannot estimat...

Like the way engineers designing buildings, competent generative design methods try to understand the prescriptive requirement in text and architectural sketches, apply engineering principles and develop the structural design. However, this requirement may be challenging to existing methods because they are not good at simultaneously taking text an...

In the schematic design phase of framed tube structures, component sizing is a vital task that requires expert experience and domain knowledge. Deep learning-based structural design methods enable machines to acquire expert experiences, but domain knowledge (e.g., empirical laws summarized by engineers from engineering practices) has not been embed...

Automated rule checking (ARC), which is expected to promote the efficiency of the compliance checking process in the architecture, engineering, and construction (AEC) industry, is gaining increasing attention. Throwing light on the ARC application hotspots and forecasting its trends are useful to the related research and drive innovations. Therefor...

Earthquakes have a deep impact on wide areas, and emergency rescue operations may benefit from social media information about the scope and extent of the disaster. Therefore, this work presents a text miningbased approach to collect and analyze social media data for early earthquake impact analysis. First, disasterrelated microblogs are collected f...

Long-span cable-stayed bridges often have a design service life of more than a hundred years, during which they may experience multiple earthquake events and accumulate seismic damage if they are located in seismic-prone regions. Earthquake occurrence is discretely and randomly distributed over the life cycle of a long-span cable-stayed bridge and...

This paper proposed a novel, efficient method to estimate challenging small structural motions from noisy video. To eliminate the phase limitation, ill‐posed problem, and high computational burden, the structural motion function is resampled and recovered. Because video signals have tremendous redundancies in spatial, block, and time domains, the o...