The Experts below are selected from a list of 161574 Experts worldwide ranked by ideXlab platform
Necati F Catbas - One of the best experts on this subject based on the ideXlab platform.
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Structural Identification st id using finite element models for optimum sensor configuration and uncertainty quantification
Finite Elements in Analysis and Design, 2014Co-Authors: Yildirim Serhat Erdogan, Necati F Catbas, Pelin Gundes BakirAbstract:Developments and advances in experimental technologies providing useful data make it possible to identify civil engineering structures and to obtain a more reliable model characterizing the existing condition for decision making. Analytical models such as Finite Element (FE) models, which are calibrated using Structural health monitoring (SHM) data, better represent the existing structures' behavior under different loading conditions. However, the SHM data should include sufficient information about the Structural parameters to be identified. In this study, a novel methodology is proposed in order to determine the optimum sensor configuration which provides adequate data for Structural Identification (St-Id). The success of the St-Id is investigated in a comparative fashion by comparing the model parameters calibrated using different sensor configurations. Uncertainties both in the mathematical model and the experimental data are taken into account using the fuzzy number concept. A so-called inverse fuzzy arithmetic technique is used to quantify the uncertainties in the updated parameters. The proximity of linkage values, which are the product of cluster analysis, is used to determine the optimal sensor configuration. The optimal sensor configuration is then verified by using the relative amount of uncertainty in the updating parameters resulting from the inverse propagation of the uncertainties. A hybrid evolutionary optimization algorithm is also proposed in order to efficiently minimize an objective function that consists of differences between the fuzzy experimental measurements and the analytical data. Genetic Algorithms (GA) and Harmony Search (HS) algorithm are combined to enhance the efficiency and the robustness of the optimization process. An analytical benchmark bridge structure developed for bridge health monitoring studies is used as the test structure to verify the proposed methodologies. Three different cases including the undamaged and the damage cases are considered. It has been shown that there is no significant difference between the St-Id results obtained by using a dense sensor configuration and the optimum configuration obtained by the proposed method in terms of accuracy.
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Structural Identification of constructed systems collective effort toward an integrated approach that reduces barriers to adoption
Journal of Structural Engineering-asce, 2013Co-Authors: Necati F Catbas, Tracy KijewskicorreaAbstract:Structural Identification (St-Id) is a powerful tool that bridges the gap between constructed systems and themodels used in their design and assessment. Although St-Id has attracted the attention of numerous researchers worldwide over the last several decades, it unfortunately has not experienced widespread adoption in practice. The ASCE Structural Engineering Institute Structural Identification of Constructed Systems Committee is seeking to reverse this trend by enhancing advocacy toward and promoting implementation of St-Id within the public and private sectors. The committee’s first action on this front was the development of a comprehensive report that benchmarks the current state of the art in St-Id, with special attention to case studies of its successful implementation. To organize the diverse paradigm of St-Id, the committee adopted a six-step cycle that spansmodeling through experimentation and ultimately to decision support. This forum paper overviews the report with the first six chapters dedicated to this cycle, as well as the report’s closing two chapters dedicated to case studies that exemplify the implementation of St-Id to various buildings and bridges around the world.
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Structural Identification of constructed systems approaches methods and technologies for effective practice of st id
2013Co-Authors: Necati F Catbas, Tracy Kijewskicorrea, Emin A. AktanAbstract:Structural Identification of Constructed Systems: Approaches, Methods, and Technologies for Effective Practice of St-Id offers an overview of nearly 20 years of research directed at bridging the gap in Structural engineering between models and real Structural systems. Structural Identification, known as St-Id, can be defined as the process of creating and updating a model of a structure (for instance, a finite element model) using experimental observations and data. By developing reliable estimates of the performance and vulnerability of Structural systems, St-Id produces improved simulations that, in turn, assist in decision making and the transition to performance-based civil engineering. Drawing upon contributions from experts in the field, this report focuses on defining the most critical considerations of St-Id, which include: modelling, both analytical and numerical experimentation, including observations, sensing, and monitoring data processing, including error screening and feature extraction model calibration, including comparisons of models and experimental data, model updating, and model selection decision support, such as scenario analyses and risk assessment Two appendixes present case studies demonstrating the St-Id of buildings and of bridges. Structural engineers, educators, and researchers working in the areas of Structural modelling, health monitoring, assessment, forensics, performance evaluation, predictive analysis, and decision making will find this book useful in covering critical and practical aspects of these concepts.
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ambient vibration data analysis for Structural Identification and global condition assessment
Journal of Engineering Mechanics-asce, 2008Co-Authors: Necati F CatbasAbstract:System Identification is an area which deals with developing mathematical models to characterize the input-output behavior of an unknown system by means of experimental data. Structural health monitoring (SHM) provides the tools and technologies to collect and analyze input and output data to track the Structural behavior. One of the most commonly used SHM technologies is dynamic testing. Ambient vibration testing is a practical dynamic testing method especially for large civil structures where input excitation cannot be directly measured. This paper presents a conceptual and reliable methodology for system Identification and Structural condition assessment using ambient vibration data where input data are not available. The system Identification methodology presented in this study is based on the use of complex mode indicator functions (CMIFs) coupled with the random decrement (RD) method to identify the modal parameters from the output only data sets. CMIF is employed for parameter Identification from t...
Junhui Wang - One of the best experts on this subject based on the ideXlab platform.
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Structural Identification and immunostimulating activity of a laminaria japonica polysaccharide
International Journal of Biological Macromolecules, 2015Co-Authors: Xueqiang Zha, Shaohua Cui, Lihua Pan, Hailin Zhang, Junhui Wang, Jianping LuoAbstract:Abstract In the present study, a new water-soluble polysaccharide (LJP-11) was obtained from Laminaria japonica by anion exchange DEAE-cellulose chromatography and Sephacryl S-500 chromatography. The average molecular weight of this polysaccharide was estimated to be about 2.89 × 10 6 Da by high performance liquid chromatography system. Gas chromatography showed that LJP-11 was composed of arabinose, mannose and glucose in a molar ratio of 1.0:1.16:6.33. LJP-11 contains a long backbone consisting of (1→4)-β- d -Glc p Ac, (1→4)-α- d -Glc p , (1→6)-β- d -Glc p and (1→3,6)-α- d -Man p . The 1-linked β- l -Ara f was linked to the C-6 of (1→3)-α- d -Man p and the sulfate group was attached to the C-4 of (1→6)-β- d -Glc p . Pharmacological tests displayed that LJP-11 can stimulate macrophages to release NO, IL-6, TNF-α and IL-10 as well as the up-regulation of their gene expressions, indicating LJP-11 has beneficial effects on immunostimulation. Moreover, LJP-11 exhibited positive effects on the translocation of NF-κB p65 from cytoplasm to nucleus and the phosphorylation of IκBα, ERK1/2, JNK1/2 and P38 in macrophages. These results suggested that the activation of MAPK and NF-κB signaling pathways is one of the mechanisms responsible for the immunostimulating activity of LJP-11.
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Structural Identification and immunostimulating activity of a laminaria japonica polysaccharide
International Journal of Biological Macromolecules, 2015Co-Authors: Chaoqun Lu, Hailin Zhang, Junhui WangAbstract:Abstract In the present study, a new water-soluble polysaccharide (LJP-11) was obtained from Laminaria japonica by anion exchange DEAE-cellulose chromatography and Sephacryl S-500 chromatography. The average molecular weight of this polysaccharide was estimated to be about 2.89 × 10 6 Da by high performance liquid chromatography system. Gas chromatography showed that LJP-11 was composed of arabinose, mannose and glucose in a molar ratio of 1.0:1.16:6.33. LJP-11 contains a long backbone consisting of (1→4)-β- d -Glc p Ac, (1→4)-α- d -Glc p , (1→6)-β- d -Glc p and (1→3,6)-α- d -Man p . The 1-linked β- l -Ara f was linked to the C-6 of (1→3)-α- d -Man p and the sulfate group was attached to the C-4 of (1→6)-β- d -Glc p . Pharmacological tests displayed that LJP-11 can stimulate macrophages to release NO, IL-6, TNF-α and IL-10 as well as the up-regulation of their gene expressions, indicating LJP-11 has beneficial effects on immunostimulation. Moreover, LJP-11 exhibited positive effects on the translocation of NF-κB p65 from cytoplasm to nucleus and the phosphorylation of IκBα, ERK1/2, JNK1/2 and P38 in macrophages. These results suggested that the activation of MAPK and NF-κB signaling pathways is one of the mechanisms responsible for the immunostimulating activity of LJP-11.
Miche Le Basseville - One of the best experts on this subject based on the ideXlab platform.
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Subspace-Based Algorithms for Structural Identification, Damage Detection, and Sensor Data Fusion
EURASIP Journal on Advances in Signal Processing, 2007Co-Authors: Miche Le Basseville, Albert Benveniste, Maurice Goursat, Laurent MevelAbstract:This paper reports on the theory and practice of covariance-driven output-only and input/output subspace-based Identification and detection algorithms. The motivating and investigated application domain is vibration-based Structural analysis and health monitoring of mechanical, civil, and aeronautic structures.
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stochastic subspace based Structural Identification and damage detection and localisation application to the z24 bridge benchmark
Mechanical Systems and Signal Processing, 2003Co-Authors: Laurent Mevel, Maurice Goursat, Miche Le BassevilleAbstract:Numerical results from the application of new stochastic subspace-based Structural Identification and damage detection and localisation methods to the Z24 concrete bridge of EMPA are discussed. For this benchmark, particular emphasis is put on damage detection and localisation.
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output only subspace based Structural Identification from theory to industrial testing practice
Journal of Dynamic Systems Measurement and Control-transactions of The Asme, 2001Co-Authors: Miche Le Basseville, Albert Benveniste, Maurice Goursat, Luc Hermans, Laurent Mevel, Herman Van Der AuweraerAbstract:We address the problem of Structural model Identification during normal operating conditions and thus with uncontrolled, unmeasured, and nonstationary excitation. We advocate the use of output-only and covariance-driven subspace-based stochastic Identification methods. We explain how to handle nonsimultaneously measured data from multiple sensor setups, and how robustness with respect to nonstationary excitation can be achieved. Experimental results obtained for three real application examples are shown.
Shengmin Sang - One of the best experts on this subject based on the ideXlab platform.
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Structural Identification of mouse urinary metabolites of pterostilbene using liquid chromatography tandem mass spectrometry
Rapid Communications in Mass Spectrometry, 2010Co-Authors: Xi Shao, Xiaoxin Chen, Vladimir Badmaev, Shengmin SangAbstract:Pterostilbene, the dimethoxy derivative of resveratrol, has drawn much attention recently due to its potential beneficial health effects. The metabolic fate of pterostilbene, however, is not well understood. In the present study, we identified nine novel mouse urinary pterostilbene metabolites, pterostilbene glucuronide, pterostilbene sulfate, mono-demethylated pterostilbene glucuronide, mono-demethylated pterostilbene sulfate, mono-hydroxylated pterostilbene, mono-hydroxylated pterostilbene glucuronide, mono-hydroxylated pterostilbene sulfate, and mono-hydroxylated pterostilbene glucuronide sulfate, using liquid chromatography/atmospheric pressure chemical ionization and electrospray ionization tandem mass spectrometry. The structures of these metabolites were confirmed by analyzing the MS(n) (n = 1-3) spectra. To our knowledge, this is the first report of the Identification of urinary metabolites of pterostilbene in mice.
Ian F C Smith - One of the best experts on this subject based on the ideXlab platform.
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Population-based Structural Identification for reserve-capacity assessment of existing bridges
Journal of Civil Structural Health Monitoring, 2018Co-Authors: Marco Proverbio, Didier G. Vernay, Ian F C SmithAbstract:Transportation networks provide an essential contribution to addressing the needs of reliable and safe mobility in urban environments. The core of these networks is made up of infrastructure such as roads and bridges that often, have not been designed to meet current needs. Optimal management requires an accurate knowledge of how existing structures behave. This helps avoid unnecessary replacement and expensive interventions when cheaper and more sustainable alternatives are available. Structural-model updating takes advantage of measurements and more qualitative observations to identify suitable behaviour model classes and values for parameters that influence real behaviour. Error domain model falsification (EDMF) has been proposed as a robust population-based methodology to identify sets of models by comparing finite-element model predictions with measurements at sensor locations. This paper introduces a methodology, which is compatible with EDMF, to assess the reserve capacity of bridges for serviceability and ultimate limit states. A case study—the Structural Identification of a reinforced-concrete bridge in Singapore—illustrates the framework developed for the estimation of reserve capacity. Several analyses with increasing levels of model detail using design and updated values of relevant parameters are presented. Traffic-load specifications of design-stage codes (British Code—1978) and current codes (Eurocodes) are compared. Results show that typical conservative practices carried out during design and construction have led to an as-built reserve capacity of 60%. A large proportion of the as-built reserve capacity has been exploited to accommodate dramatically increased values of traffic-load specifications that are provided by current Singapore codes which have caused a reduction in reserve capacity to 20%. Such a reduction may be less significant in countries where code specifications have not changed as much. Finally, it is shown that advanced methods of analysis and assessment are more suitable than design-stage approaches to quantify the reserve capacity.
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iterative Structural Identification framework for evaluation of existing structures
Engineering Structures, 2016Co-Authors: Romain Pasquier, Ian F C SmithAbstract:Evaluation of aging infrastructure has been a world-wide concern for decades due to its economic, ecological and societal importance. Existing structures usually have large amounts of unknown reserve capacity that may be evaluated though Structural Identification in order to avoid unnecessary expenses related to the repair, retrofit and replacement. However, current Structural Identification techniques that take advantage of measurement data to infer unknown properties of physics-based models fail to provide robust strategies to accommodate systematic errors that are induced by model simplifications and omissions. In addition, behavior diagnosis is an ill-defined task that requires iterative acquisition of knowledge necessary for exploring possible model classes of behaviors. This aspect is also lacking in current Structural Identification frameworks. This paper proposes a new iterative framework for Structural Identification of complex aging structures based on model falsification and knowledge-based reasoning. This approach is suitable for ill-defined tasks such as Structural Identification where information is obtained gradually through data interpretation and in-situ inspection. The study of a full-scale existing bridge in Wayne, New Jersey (USA) confirms that this framework is able to support Structural Identification through combining engineering judgment with on-site measurements and is robust with respect to effects of systematic uncertainties. In addition, it is shown that the iterative Structural-Identification framework is able to explore the compatibility of several model classes by model-class falsification, thereby helping to provide robust diagnosis and prognosis.
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Structural Identification with systematic errors and unknown uncertainty dependencies
Computers & Structures, 2013Co-Authors: Jamesa Goulet, Ian F C SmithAbstract:When system Identification methodologies are used to interpret measurement data taken from structures, uncertainty dependencies are in many cases unknown due to model simplifications and omissions. This paper presents how error-domain model falsification reveals properties of a structure when uncertainty dependencies are unknown and how incorrect assumptions regarding model-class adequacy are detected. An illustrative example is used to compare results with those from a residual minimization technique and Bayesian inference. Error-domain model falsification correctly identifies parameter values in situations where there are systematic errors, and can detect the presence of unrecognized systematic errors.
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hybrid probabilities and error domain Structural Identification using ambient vibration monitoring
Mechanical Systems and Signal Processing, 2013Co-Authors: Jamesa Goulet, Clotaire Michel, Ian F C SmithAbstract:For the assessment of Structural behaviour, many approaches are available to compare model predictions with measurements. However, few approaches include uncertainties along with dependencies associated with models and observations. In this paper, an error-domain Structural Identification approach is proposed using ambient vibration monitoring (AVM) as the input. This approach is based on the principle that in science, data cannot truly validate a hypothesis, it can only be used to falsity it. Error-domain model falsification generates a space of possible model instances (combination of parameters), obtains predictions for each of them and then rejects instances that have unlikely differences (residuals) between predictions and measurements. Models are filtered in a two step process. Firstly a comparison of mode shapes based on MAC criterion ensures that the same modes are compared. Secondly, the frequencies from each model instance are compared with the measurements. The instances for which the difference between the predicted and measured value lie outside threshold bounds are discarded. In order to include “uncertainty of uncertainty” in the Identification process, a hybrid probability scheme is also presented. The approach is used for the Identification of the Langensand Bridge in Switzerland. It is used to falsify the hypothesis that the bridge was behaving as designed when subjected to ambient vibration inputs, before opening to the traffic. Such small amplitudes may be affected by low-level bearing-device friction. This inadvertently increased the apparent stiffness of the structure by 17%. This observation supports the premiss that ambient vibration surveys should be cross-checked with other information sources, such as numerical models, in order to avoid misinterpreting the data.
