Gregory L. Fenves
Other affiliations: University of California, Berkeley, Lehigh University, University of California ...read more
Bio: Gregory L. Fenves is an academic researcher from University of Texas at Austin. The author has contributed to research in topics: Earthquake engineering & Finite element method. The author has an hindex of 36, co-authored 106 publications receiving 7986 citations. Previous affiliations of Gregory L. Fenves include University of California, Berkeley & Lehigh University.
Papers published on a yearly basis
TL;DR: In this paper, a new plastic-damage model for concrete subjected to cyclic loading is developed using the concepts of fracture-energy-based damage and stiffness degradation in continuum damage mechanics.
Abstract: A new plastic-damage model for concrete subjected to cyclic loading is developed using the concepts of fracture-energy-based damage and stiffness degradation in continuum damage mechanics. Two damage variables, one for tensile damage and the other for compressive damage, and a yield function with multiple-hardening variables are introduced to account for different damage states. The uniaxial strength functions are factored into two parts, corresponding to the effective stress and the degradation of elastic stiffness. The constitutive relations for elastoplastic responses are decoupled from the degradation damage response, which provides advantages in the numerical implementation. In the present model, the strength function for the effective stress is used to control the evolution of the yield surface, so that calibration with experimental results is convenient. A simple and thermodynamically consistent scalar degradation model is introduced to simulate the effect of damage on elastic stiffness and its recovery during crack opening and closing. The performance of the plastic-damage model is demonstrated with several numerical examples of simulating monotonically and cyclically loaded concrete specimens.
••25 Apr 2007
TL;DR: A Wireless Sensor Network for Structural Health Monitoring is designed, implemented, deployed and tested on the 4200 ft long main span and the south tower of the Golden Gate Bridge and the collected data agrees with theoretical models and previous studies of the bridge.
Abstract: A Wireless Sensor Network (WSN) for Structural Health Monitoring (SHM) is designed, implemented, deployed and tested on the 4200 ft long main span and the south tower of the Golden Gate Bridge (GGB). Ambient structural vibrations are reliably measured at a low cost and without interfering with the operation of the bridge. Requirements that SHM imposes on WSN are identified and new solutions to meet these requirements are proposed and implemented. In the GGB deployment, 64 nodes are distributed over the main span and the tower, collecting ambient vibrations synchronously at 1 kHz rate, with less than 10 mus jitter, and with an accuracy of 30 muG. The sampled data is collected reliably over a 46-hop network, with a bandwidth of 441 B/s at the 46th hop. The collected data agrees with theoretical models and previous studies of the bridge. The deployment is the largest WSN for SHM.
TL;DR: Sequence diagrams document the interoperability of the analysis classes for solving nonlinear finite-element equations, demonstrating that object composition with design patterns provides a general approach to developing and refactoring nonlinear infinite-element software.
Abstract: Object composition offers significant advantages over class inheritance to develop a flexible software architecture for finite-element analysis. Using this approach, separate classes encapsulate fu...
TL;DR: A new plastic hinge integration method overcomes the problems with nonobjective response caused by strain-softening behavior in force-based beam-column finite elements by using the common concept of a plastic hinge length in a numerically consistent manner.
Abstract: A new plastic hinge integration method overcomes the problems with nonobjective response caused by strain-softening behavior in force-based beam-column finite elements. The integration method uses the common concept of a plastic hinge length in a numerically consistent manner. The method, derived from the Gauss-Radau quadrature rule, integrates deformations over specified plastic hinge lengths at the ends of the beam-column element, and it has the desirable property that it reduces to the exact solution for linear problems. Numerical examples show the effect of plastic hinge integration on the response of force-based beam-column elements for both strain-hardening and strain-softening section behavior in the plastic hinge regions. The incorporation of a plastic hinge length in the element integration method ensures objective element and section response, which is important for strain-softening behavior in reinforced concrete structures. Plastic rotations are defined in a consistent manner and clearly related to deformations in the plastic hinges.
TL;DR: In this paper, a new plastic-damage constitutive model for cyclic loading of concrete has been developed for the earthquake analysis of concrete dams, which consistently includes the effects of strain softening, represented by separate damage variables for tension and compression.
Abstract: A new plastic-damage constitutive model for cyclic loading of concrete has been developed for the earthquake analysis of concrete dams. The rate-independent model consistently includes the effects of strain softening, represented by separate damage variables for tension and compression. A simple scalar degradation model simulates the effects of damage on the elastic stiffness and the recovery of stiffness after cracks close. To simulate large crack opening displacements, the evolution of inelastic strain is stopped beyond a critical value for the tensile damage variable. Subsequent deformation can be recovered upon crack closing. The rate-independent plastic-damage model forms the backbone model for a rate-dependent viscoplastic extension. The rate-dependent regularization is necessary to obtain a unique and mesh objective numerical solution. Damping is represented as a linear viscoelastic behaviour proportional to the elastic stiffness including the degradation damage. The plastic-damage constitutive model is used to evaluate the response of Koyna dam in the 1967 Koyna earthquake. The analysis shows two localized cracks forming and then joining at the change in geometry of the upper part of the dam. The upper portion of the dam vibrates essentially as rigid-body rocking motion after the upper cracks form, but the dam remains stable. The vertical component of ground motion influences the post-cracking response. © 1998 John Wiley & Sons, Ltd.
••01 May 2009
TL;DR: This paper breaks down the energy consumption for the components of a typical sensor node, and discusses the main directions to energy conservation in WSNs, and presents a systematic and comprehensive taxonomy of the energy conservation schemes.
Abstract: In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.
TL;DR: The background and state-of-the-art of big data are reviewed, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid, as well as related technologies.
Abstract: In this paper, we review the background and state-of-the-art of big data. We first introduce the general background of big data and review related technologies, such as could computing, Internet of Things, data centers, and Hadoop. We then focus on the four phases of the value chain of big data, i.e., data generation, data acquisition, data storage, and data analysis. For each phase, we introduce the general background, discuss the technical challenges, and review the latest advances. We finally examine the several representative applications of big data, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid. These discussions aim to provide a comprehensive overview and big-picture to readers of this exciting area. This survey is concluded with a discussion of open problems and future directions.
01 Jan 2011
TL;DR: The Building Code Requirements for Structural Concrete (Code) as mentioned in this paper covers the materials, design, and construction of structural concrete used in buildings and where applicable in nonbuilding structures, including the strength evaluation of existing concrete structures.
Abstract: The “Building Code Requirements for Structural Concrete” (“Code”) covers the materials, design, and construction of structural concrete used in buildings and where applicable in nonbuilding structures. The Code also covers the strength evaluation of existing concrete structures. Among the subjects covered are: contract documents; inspection; materials; durability requirements; concrete quality, mixing, and placing; formwork; embedded pipes; construction joints; reinforcement details; analysis and design; strength and serviceability; flexural and axial loads; shear and torsion; development and splices of reinforcement; slab systems; walls; footings; precast concrete; composite flexural members; prestressed concrete; shells and folded plate members; strength evaluation of existing structures; provisions for seismic design; structural plain concrete; strut-and-tie modeling in Appendix A; alternative design provisions in Appendix B; alternative load and strength reduction factors in Appendix C; and anchoring to concrete in Appendix D. The quality and testing of materials used in construction are covered by reference to the appropriate ASTM standard specifications. Welding of reinforcement is covered by reference to the appropriate American Welding Society (AWS) standard. Uses of the Code include adoption by reference in general building codes, and earlier editions have been widely used in this manner. The Code is written in a format that allows such reference without change to its language. Therefore, background details or suggestions for carrying out the requirements or intent of the Code portion cannot be included. The Commentary is provided for this purpose. Some of the considerations of the committee in developing the Code portion are discussed within the Commentary, with emphasis given to the explanation of new or revised provisions. Much of the research data referenced in preparing the Code is cited for the user desiring to study individual questions in greater detail. Other documents that provide suggestions for carrying out the requirements of the Code are also cited.
TL;DR: This paper presents a systematic framework to decompose big data systems into four sequential modules, namely data generation, data acquisition, data storage, and data analytics, and presents the prevalent Hadoop framework for addressing big data challenges.
Abstract: Recent technological advancements have led to a deluge of data from distinctive domains (e.g., health care and scientific sensors, user-generated data, Internet and financial companies, and supply chain systems) over the past two decades. The term big data was coined to capture the meaning of this emerging trend. In addition to its sheer volume, big data also exhibits other unique characteristics as compared with traditional data. For instance, big data is commonly unstructured and require more real-time analysis. This development calls for new system architectures for data acquisition, transmission, storage, and large-scale data processing mechanisms. In this paper, we present a literature survey and system tutorial for big data analytics platforms, aiming to provide an overall picture for nonexpert readers and instill a do-it-yourself spirit for advanced audiences to customize their own big-data solutions. First, we present the definition of big data and discuss big data challenges. Next, we present a systematic framework to decompose big data systems into four sequential modules, namely data generation, data acquisition, data storage, and data analytics. These four modules form a big data value chain. Following that, we present a detailed survey of numerous approaches and mechanisms from research and industry communities. In addition, we present the prevalent Hadoop framework for addressing big data challenges. Finally, we outline several evaluation benchmarks and potential research directions for big data systems.