Kincho H. Law's research while affiliated with Stanford University and other places

Publications (419)

Article
Satellite and street view images are widely used in various disciplines as a source of information for understanding the built environment. In natural hazard engineering, high-quality building inventory data sets are crucial for the simulation of hazard impacts and for supporting decision-making. Screening the building stocks to gather the informat...
Article
Load rating is a widely used approach for evaluating the load-carrying capacity of bridges in an effort to ensure safe bridge operation under expected traffic loads. Load rating often relies on simplified analytical models including empirically derived model parameters that do not reflect bridge-specific information resulting in conservative rating...
Chapter
While the increasing deployment of sensors for structural health monitoring has significantly enhanced the monitoring and management of structures, the volume and the variety of data collected have raised the importance of data management. This chapter describes a cloud-based cyber infrastructure platform that builds upon information modeling, NoSQ...
Article
Additive manufacturing (AM) provides design flexibility and allows rapid fabrications of parts with complex geometries. The presence of internal defects, however, can lead to deficit performance of the fabricated part. X-ray Computed Tomography (XCT) is a non-destructive inspection technique often used for AM parts. Although defects within AM speci...
Conference Paper
Additive manufacturing (AM) provides design flexibility and allows rapid fabrications of parts with complex geometries. The presence of internal defects, however, can lead to deficit performance of the fabricated part. X-ray Computed Tomography (XCT) is a non-destructive inspection technique often used for AM parts. Although defects within AM speci...
Technical Report
Full-text available
This report is a product of the NHERI SimCenter under the auspices of the U.S. National Science Foundation (NSF). It provides an overview and review of simulation requirements and software tools for natural hazards engineering (NHE) of the built environment. The simulations discussed in this report are an essential component of research to address...
Article
Full-text available
The intensity of many natural hazards, such as hurricanes, floods, tornadoes, etc., are increasing as a consequence of climate change. This increase in intensity coupled with the increase in population density, particularly along the coasts, is only magnifying the impact of such events. In order to quantify and mitigate the risk due to the hazards...
Preprint
Full-text available
Segmentation of additive manufacturing (AM) defects in X-ray Computed Tomography (XCT) images is challenging, due to the poor contrast, small sizes and variation in appearance of defects. Automatic segmentation can, however, provide quality control for additive manufacturing. Over recent years, three-dimensional convolutional neural networks (3D CN...
Article
Full-text available
Rapid and accurate identification of potential structural deficiencies is a crucial task in evaluating seismic vulnerability of large building inventories in a region. In the case of multi-story structures, abrupt vertical variations of story stiffness are known to significantly increase the likelihood of collapse during moderate or severe earthqua...
Chapter
This chapter provides an overview of a Cyber Physical System (CPS) for civil infrastructural monitoring. Specifically, a prototype design and implementation of a cyber infrastructure framework for the monitoring of bridges along a highway corridor is described. The cyber infrastructure framework includes two basic components, namely a sensing and m...
Conference Paper
Segmentation of additive manufacturing (AM) defects in X-ray Computed Tomography (XCT) images is challenging, due to the poor contrast, small sizes and variation in appearance of defects. Automatic segmentation can, however, provide quality control for additive manufacturing. Over recent years, three-dimensional convolutional neural networks (3D CN...
Article
Bridges are critical components of highways ensuring traffic can efficiently travel over obstructions such as bodies of water, valleys, and other roads. Ensuring bridges are in sound structural condition is essential for safe and efficient highway operations. Structural health monitoring (SHM) systems designed to measure bridge responses have been...
Article
Full-text available
Convolutional neural networks are becoming a popular tool for image processing in the engineering and manufacturing sectors. However, managing the storage and distribution of trained models is still a difficult task, partially due to the lack of standardized methods for deep neural network representation. Additionally, the interoperability between...
Article
To address the grand challenges brought about by urbanization, “smart city” has become a ubiquitous concept for sustaining urban and economic growthwhile addressing the environmental and social issues created by that growth. While numerous articles and reports have been written about smart cities, a universal definition of what constitutes a smart...
Preprint
Full-text available
In this paper, we provide two case studies to demonstrate how artificial intelligence can empower civil engineering. In the first case, a machine learning-assisted framework, BRAILS, is proposed for city-scale building information modeling. Building information modeling (BIM) is an efficient way of describing buildings, which is essential to archit...
Conference Paper
The use of deep convolutional neural networks is becoming increasingly popular in the engineering and manufacturing sectors. However, managing the distribution of trained models is still a difficult task, partially due to the limitations of standardized methods for neural network representation. This paper seeks to address this issue by proposing a...
Conference Paper
Full-text available
Automated data capture systems could significantly improve the efficiency and productivity of the architecture, engineering, construction and facility management (AEC/FM) industry. However, automatically collecting spatiotemporal information in an unstructured environment such as a construction site or a work place remains a time consuming and chal...
Conference Paper
Bridge information modeling (BrIM) techniques have been developed to integrate information from architecture, engineering, construction, and operation. The models developed by these different stakeholders, however, are oftentimes not interoperable. To address the challenge, this paper proposes a BrIM framework to ensure consistent data exchange. De...
Conference Paper
Automated data capture systems could significantly improve the efficiency and productivity of the architecture, engineering, construction, and facility management (AEC/FM) industry. However, automatically collecting spatiotemporal information in an unstructured environment such as a construction site or a work place remains a time consuming and cha...
Conference Paper
Full-text available
The supplementary material contains: (1) a video that shows detailed and comprehensive results, as well as a PDF file which includes (2) more experimental results and examples, (3) additional implementation details and a description of the 3D convolutional neural network (4), additional information about the worksite object dataset that was collect...
Conference Paper
Full-text available
Automation in facility management and construction could significantly improve efficiency and productivity of the building industry. However, for robots and autonomous systems to operate effectively in dynamic and unstructured environments such as construction sites, they must be able to infer or obtain a semantic model of the environment. We propo...
Article
Full-text available
Cloud computing is a computing paradigm wherein computing resources, such as servers, storage and applications, can be provisioned and accessed in real time via advanced communication networks. In the era of Internet of Things (IoT) and big data, cloud computing has been widely developed in many industrial applications involving large volume of dat...
Article
Full-text available
With recent advances in sensor and computing technology, it is now possible to use real-time machine learning techniques to monitor the state of manufacturing machines. However, making accurate predictions from raw sensor data is still a difficult challenge. In this paper, we describe how a data processing pipeline is developed to predict the condi...
Article
Full-text available
Quality control is a fundamental component of many manufacturing processes, especially those involving casting or welding. However, manual quality control procedures are often time-consuming and error-prone. In order to meet the growing demand for high-quality products, the use of intelligent visual inspection systems is becoming essential in produ...
Preprint
Full-text available
Automatic detection of defects in metal castings is a challenging task, owing to the rare occurrence and variation in appearance of defects. However, automatic defect detection systems can lead to significant increases in final product quality. Convolutional neural networks (CNNs) have shown outstanding performance in both image classification and...
Article
Emergency evacuation (egress) is an important issue in safety design of facilities and buildings. Studies of past emergency events have highlighted the need to consider occupants’ behaviors for better understanding of evacuation patterns. Occupants’ background and knowledge (such as the level of familiarity with the space and previous experience of...
Conference Paper
Full-text available
IoT technology can have a huge impact in engineering by leveraging state-of-the-art information and communication technologies (ICT). In practice, however, it is challenging for IoT platforms to handle domain-specific engineering information (e.g., geometric model, engineering simulation model, etc.) along with sensor data of different types. Engin...
Article
We use model-free reinforcement learning, extensive simulation, and transfer learning to develop a continuous control algorithm that has good zero-shot performance in a real physical environment. We train a simulated agent to act optimally across a set of similar environments, each with dynamics drawn from a prior distribution. We propose that the...
Chapter
Full-text available
This presentation discusses the potential use of machine learning techniques to build data-driven models to characterize an engineering system for performance assessment, diagnostic analysis and control optimization. Focusing on the Gaussian Process modeling approach, engineering applications on constructing predictive models for energy consumption...
Chapter
Persistent and emerging social and environmental issues require new approaches and tools to help develop policies that address the complexities inherent in these problems. Here a policy informatics tool, developed iteratively with the feedback of ocean and coastal domain experts, is presented. The tool relies on two user inputs: a conceptually mode...
Conference Paper
Full-text available
Automatic localization of defects in metal castings is a challenging task, owing to the rare occurrence and variation in appearance of defects. Convolutional neural networks (CNN) have recently shown outstanding performance in both image classification and localization tasks. We examine how several different CNN architectures can be used to localiz...
Conference Paper
Full-text available
The purpose of this paper is to discuss the potential use of machine learning techniques to build data-driven models for diagnostic analysis of civil infrastructures. The discussion will focus on the reconstruction of sensor data collected from a bridge monitoring system using Support Vector Regression (SVR). The reconstructed data can be used not...
Conference Paper
Full-text available
This paper describes a hybrid cloud-based distributed data management infrastructure platform for bridge monitoring applications. As the deployment of sensors and the collection of monitoring data continue to grow, proper management of the data becomes a paramount issue. Cloud computing is one viable approach that is popular among IoT and big data...
Conference Paper
The application of machine learning techniques in the manufacturing sector provides opportunities for increased production efficiency and product quality. In this paper, we describe how audio and vibration data from a sensor unit can be combined with machine controller data to predict the condition of a milling tool. Emphasis is placed on the gener...
Article
Multifunctional thin film materials have opened many opportunities for novel sensing strategies for structural health monitoring. While past work has established methods of optimizing multifunctional materials to exhibit sensing properties, comparatively less work has focused on their integration into fully functional sensing systems capable of bei...
Article
Full-text available
This paper discusses a data-driven, cooperative control strategy to maximize wind farm power production. Conventionally, every wind turbine in a wind farm is operated to maximize its own power production without taking into account the interactions between the wind turbines in a wind farm. Because of wake interference, such greedy control strategy...
Article
Bridge management involves a variety of information from different data sources, including geometric model, analysis model, bridge management system (BMS) and structural health monitoring (SHM) system. Current practice of bridge management typically handles these diverse types of data using isolated systems and operates with limited use of the data...
Article
Full-text available
This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilit...
Conference Paper
Full-text available
The use of data-driven predictive models is becoming increasingly popular in engineering and manufacturing sectors. This paper discusses the deployment of Gaussian Process Regression (GPR) predictive models for smart manufacturing. A scoring engine is developed based on the Predictive Model Markup Language (PMML) standard to illustrate the portabil...
Conference Paper
Full-text available
This paper describes a cloud-based cyber infrastructure for the management of information involved in bridge monitoring applications. Recent years have seen an emergence and increasing use of sensor technologies for bridge monitoring. In addition to the measurement data from the sensors, bridge monitoring and management systems require many differe...
Article
Full-text available
Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the op...
Article
Regional seismic damage simulation of buildings can potentially reveal possible consequences that are important for disaster mitigation and decision making. However, such a simulation involving all the buildings in a region can be computationally intensive. In this study, a computational framework using a network of distributed computers, each equi...
Chapter
Cloud computing, where services are delivered over a network, has the potential to transform the practice of engineering. With tools and services residing in the cloud environment, engineering and manufacturing companies can now have access to shared computing resources and advanced application services everywhere and anytime on an as-needed basis....
Conference Paper
Full-text available
This paper describes an information repository to support bridge monitoring applications on a cloud computing platform. Bridge monitoring, with instrumentation of sensors in particular, collects significant amount of data. In addition to sensor data, a wide variety of information such as bridge geometry, analysis model and sensor description need t...
Article
Full-text available
Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describe...
Article
Full-text available
This paper describes a data-driven approach for real-time control of a physical system. Specifically, this paper focuses on the cooperative wind farm control where the objective is to maximize the total wind farm power production by using control actions as an input and measured power as an output. For real time, data-driven wind farm control, it i...
Conference Paper
Full-text available
This paper describes a real-time data collection framework and an adaptive machining learning method for constructing a real-time energy prediction model for a machine tool. To effectively establish the energy consumption pattern of a machine tool over time, the energy prediction model is continuously updated with new measurement data to account fo...
Article
Purpose – The purpose of this paper is to present a framework for integrating construction supply chain in order to resolve the data heterogeneity and data sharing problems in the construction industry. Design/methodology/approach – Standardized web service technology is used in the proposed framework for data specification, transfer, and integrat...
Article
Studies of past emergency events have revealed that occupants’ behaviors, local geometry, and environmental constraints affect crowd movement and evacuation. Design of egress systems should take into consideration the social characteristics of the occupants and the unique layout of the buildings. This paper describes an agent-based egress simulatio...
Article
This paper describes the use of a cooperative wind farm control approach to improve the power production of a wind farm. The power production by a downstream wind turbine can decrease significantly due to reduced wind speed caused by the upstream wind turbines, thereby lowering the overall wind farm power production efficiency. In spite of the inte...
Conference Paper
Full-text available
Using a machine learning approach, this study investigates the effects of machining parameters on the energy consumption of a milling machine tool, which would allow selection of optimal operational strategies to machine a part with minimum energy. Data-driven prediction models, built upon a nonlinear regression approach, can be used to gain an und...
Conference Paper
Full-text available
This paper discusses a data management infrastructure framework for bridge monitoring applications. As sensor technologies mature and become economically affordable, their deployment for bridge monitoring will continue to grow. Data management becomes a critical issue not only for storing the sensor data but also for integrating with the bridge mod...
Article
The objective of this study is to develop a model-free optimization algorithm to improve the total wind farm power production in a cooperative game framework. Conventionally, for a given wind condition, an individual wind turbine maximizes its own power production without taking into consideration the conditions of other wind turbines. Under this g...
Article
The ability to access patents and relevant patent-related information pertaining to a patented technology can fundamentally transform the patent system and its functioning and patent institutions such as the USPTO and the federal courts. This paper describes an ontology-based computational framework that can resolve some of difficult issues in retr...