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Charles R. Farrar

Other affiliations: Analysis Group
Bio: Charles R. Farrar is an academic researcher from Los Alamos National Laboratory. The author has contributed to research in topics: Structural health monitoring & Sensor node. The author has an hindex of 70, co-authored 357 publications receiving 26338 citations. Previous affiliations of Charles R. Farrar include Analysis Group.


Papers
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Book ChapterDOI
24 Jun 2013
TL;DR: This research attacked the mode confusion problem by developing a modeling framework to describe the role of language and language-based interactions in the construction of systems.
Abstract: Note: Chapter 5, Structural Identification of Constructed Systems Reference EPFL-CHAPTER-191194 Record created on 2013-12-10, modified on 2016-08-09

1 citations

01 Jan 1989
TL;DR: In this article, a new configuration of a reinforced concrete shear wall structure was designed and tested to investigate the analytical-experimental differences observed during the previous model testing, and the test structures are shown in Fig. 1.
Abstract: The Seismic Category I Structures Program is being carried out at the Los Alamos National Laboratory under sponsorship of the US Nuclear Regulatory Commission (NRC), Office of Nuclear Regulatory Research. In the class of structure being investigated, the primary lateral load-resisting structural element is the reinforced concrete shear wall. Previous results from microconcrete models indicated that these structures responded to seismic excitations with initial frequencies that were reduced by factors of 2 or more over those calculated based on an uncracked cross-section strength-of-materials approach. Furthermore, though the structures themselves were shown to have sufficient reserve margins, the equipment and piping are designed to response spectra that are based on uncracked cross-sectional member properties, and these spectra may not be inappropriate for actual building responses. The current phase of the program is aimed at verification of these conclusions using conventional concrete structures to demonstrate that previous microconcrete results can be scaled to prototype structures. A new configuration of a shear wall structure was designed and tested to investigate the analytical-experimental differences observed during the previous model testing. Shear wall height-to-length aspect ratios were to vary from 1 to 0.25. Percentage steel ratios were to vary from 0.25% to 0.6% by area,more » in both horizontal and vertical directions. The test structures are shown in Fig. 1. TRG-1 and -2 were constructed with microconcrete. TRG-3, -4, -5, and -6 were constructed with conventional (19-mm aggregate) concrete. 11 refs., 4 figs.« less

1 citations

Proceedings ArticleDOI
02 Jun 2014
TL;DR: The goal of this work is to develop a new autonomous capability for remotely deploying precisely located sensor nodes without damaging the sensor nodes in the process.
Abstract: The goal of this work is to develop a new autonomous capability for remotely deploying precisely located sensor nodes without damaging the sensor nodes in the process. Over the course of the last decade there has been significant interest in research to deploy sensor networks. This research is driven by the fact that the costs associated with installing sensor networks can be very high. In order to rapidly deploy sensor networks consisting of large numbers of sensor nodes, alternative techniques must be developed to place the sensor nodes in the field.To date much of the research on sensor network deployment has focused on strategies that involve the random dispersion of sensor nodes [1]. In addition other researchers have investigated deployment strategies utilizing small unmanned aerial helicopters for dropping sensor networks from the air. [2]. The problem with these strategies is that often sensor nodes need to be very precisely located for their measurements to be of any use. The reason for this could be that the sensor being used only have limited range, or need to be properly coupled to the environment which they are sensing. The problem with simply dropping sensor nodes is that for many applications it is necessary to deploy sensor nodes horizontally. In addition, to properly install many types of sensors, the sensor must assume a specific pose relative to the object being measured.In order to address these challenges we are currently developing a technology to remotely and rapidly deploy precisely located sensor nodes. The remote sensor placement device being developed can be described as an intelligent gas gun (Figure 1). A laser rangefinder is used to measure the distance to a specified target sensor location. This distance is then used to estimate the amount of energy required to propel the sensor node to the target location with just enough additional energy left over to ensure the sensor node is able to attach itself to the target of interest. We are currently in the process of developing attachment mechanisms for steel, wood, fiberglass (Figure 2).In this demonstration we will perform a contained, live demo of our prototype pneumatic remote sensor placement device along with some prototype sensor attachment mechanisms we are developing.

1 citations

01 Jan 2007
TL;DR: The Los Alamos Dynamic Summer School (LADSS) as mentioned in this paper is a joint LANL/UCSD degree program with a unique focus in validated simulations, structural health monitoring, and damage prognosis.
Abstract: Los Alamos National Laboratory (LANL) and the University of California, San Diego (UCSD) have taken the unprecedented step of creating a collaborative, multi-disciplinary graduate education program and associated research agenda called the Engineering Institute. The technology thrust of the Engineering Institute is damage prognosis, a multidisciplinary engineering science concerned with assessing the current condition and predicting the remaining life of a wide variety of structural systems. The mission of the Engineering Institute is to develop a comprehensive approach for conducting LANL mission-driven, multidisciplinary engineering research and to improve recruiting, revitalization and retention of the current and future staff necessary to support LANL’s nuclear weapons stockpile stewardship responsibilities. The components of the Engineering Institute to be discussed in this paper are 1) the Los Alamos Dynamic Summer School (LADSS), 2) a joint LANL/UCSD degree program with a unique focus in validated simulations, structural health monitoring, and damage prognosis, 3) joint LANL/UCSD research projects, and 4) industry short courses. This program is a possible model for future industry/government interactions with university partners.

1 citations

Proceedings ArticleDOI
TL;DR: This research effort was to assess the performance of Structural Health Monitoring techniques to replace the high-cost qualification procedure and to localize faults introduced by improper assembly.
Abstract: The rapid deployment of satellites is hindered by the need to flight-qualify their components and the resulting mechanical assembly. Conventional methods for qualification testing of satellite components are costly and time consuming. Furthermore, full-scale vehicles must be subjected to launch loads during testing. The focus of this research effort was to assess the performance of Structural Health Monitoring (SHM) techniques to replace the high-cost qualification procedure and to localize faults introduced by improper assembly. SHM techniques were applied on a small-scale structure representative of a responsive satellite. The test structure consisted of an extruded aluminum spaceframe covered with aluminum shear plates, which was assembled using bolted joints. Multiple piezoelectric patches were bonded to the test structure and acted as combined actuators and sensors. Piezoelectric Active-sensing based wave propagation and frequency response function techniques were used in conjunction with finite element modeling to capture the dynamic properties of the test structure. Areas improperly assembled were identified and localized. This effort primarily focused on determining whether or not bolted joints on the structure were properly tightened.

1 citations


Cited by
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Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

Journal ArticleDOI
TL;DR: This survey tries to provide a structured and comprehensive overview of the research on anomaly detection by grouping existing techniques into different categories based on the underlying approach adopted by each technique.
Abstract: Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with.

9,627 citations

Journal ArticleDOI
TL;DR: This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making.

3,848 citations

ReportDOI
01 May 1996
TL;DR: A review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response is presented in this article, where the authors categorize the methods according to required measured data and analysis technique.
Abstract: This report contains a review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response. The report first categorizes the methods according to required measured data and analysis technique. The analysis categories include changes in modal frequencies, changes in measured mode shapes (and their derivatives), and changes in measured flexibility coefficients. Methods that use property (stiffness, mass, damping) matrix updating, detection of nonlinear response, and damage detection via neural networks are also summarized. The applications of the various methods to different types of engineering problems are categorized by type of structure and are summarized. The types of structures include beams, trusses, plates, shells, bridges, offshore platforms, other large civil structures, aerospace structures, and composite structures. The report describes the development of the damage-identification methods and applications and summarizes the current state-of-the-art of the technology. The critical issues for future research in the area of damage identification are also discussed.

2,916 citations