419 research outputs found

    System identification & damage assessment of structures using optical tracker array data

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    Damage assessment of a steel structure involves acquiring and identifying dynamic characteristics of the structure and using these characteristics to evaluate behavior and performance. To ensure the objective assessment three major issues need to be developed: sensing system, system identification and feature extraction. In this study, a unsymmetrical 3-story steel structure (fabricated with one week column in the first floor) subjected to a series of earthquake excitations with increasing level of excitation back to back. In between the earthquake excitation white noise excitation was also applied. Both the traditional sensing system (accelerometer and LVDT) and the optical tracker system were implemented in the structure to collect the vibration-based responses. First, the traditional system identification using global response data is used (subspace identification) to extract system natural frequencies and mode shapes from different set of seismic responses. Besides, to evaluate whether optical tracker array data from local measurement could be used to identify deterioration or damaged-induced changes in damage assessment, principal component analysis was applied to extract the curvature ad the earthquake–induce local stress of the structural member. From which the local stress distribution from different seismic event can be estimated. The relationship among the local displacement profiles, stress distributions and the global dynamic characteristics of the structure are investigated. The results reveal that the local flexibility was an excellent objective for both local and global condition assessment. Finally, discussion on the identified global dynamic characteristics from global measurement in relating to the calculated structural integrity index using optical sensing array data and local element strain on the identification of damage severity are presented

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    Hsu Chih-mo, a literary biography.

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    This paper attempts to give a relatively accurate picture of Hsu Chih-mo's life with emphasis on the literary side as the title suggests. A generally chronological order is observed throughout the discussion. Chapter one covers the first period of Hsu's life, stressing his Cambridge days. Chapter two gives an account of Hsu's love life, literary works and activities in the first two to three years after he returned to Peking from abroad in 1922. Chapter three is a continuation of the previous one, up to the year 1926. Chapter four deals with Hsu's last years in Shanghai, with a special note on his disillusionment with love and life, and the final "revival" shortly before his death. Hsu is treated primarily as a poet rather than an essayist in this paper and his poetical works are examined separately in the relevant sections, i.e., chapters two, three and four. Some incidents and activities in Hsu's life are investigated in greater detail than others with a view to either (1): correcting erroneous or inaccurate impressions which have almost been perpetuated in both journalistic writings and even scholarly works concerning Hsu, or (2): demonstrating facts hitherto little known to the world so as to illustrate some important points which would otherwise remain unclear. Quite a number of Hsu's poems and articles, long forgotten or practically unknown because they have not been included in any of his collections, have been exhumed, and dozens of unpublished letters by him have been used in this biography

    Using Monte Carlo Simulation for Vehicle Emission Estimation-A Case Study in Hong Kong

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    Background and Objectives: Air pollution caused by vehicular emission has been a public concern and is more seriously in Hong Kong which is a highly urbanized and congested city. Therefore, a study was conducted to observe the vehicular pollutant emission and concentration. This study intends to update the driving behavior in terms of vehicle speed and vehicle acceleration for heavy diesel vehicles in Hong Kong residential area. Materials and Methods: A total of over 900 min of data were collected by the car chasing technique for 93 heavy diesel vehicles in Shatin, one of the most crowd residential area in Hong Kong during the period November and December, 2019. A three dimensions speed-acceleration matrix and plot were developed by the sampled result. Project team further applied the Hong Kong based speed-acceleration probability distribution to the tunnel mass balance emission model for CO and NO vehicle emission estimation. Results: A Hong Kong based three-dimension speed-acceleration-frequency matrix was successfully developed. Monte Carlo simulation were further carried out for 1000 times within obtained driving cycle and then further calculating the CO and NO emission factor. It was observed that in average one heavy diesel vehicles has emitted 6.5 g CO and 7.1 g NO for one trip in residential area (around 10 km). Conclusion: This research project focuses on the interaction effect between vehicle speed and acceleration and showed there was interaction effect. This method is simple and extremely good under limited budgets. Statistical Monte Carlo simulation further improved the accuracy of the driving cycle modeling

    Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries

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    Deep ensembles (DE) have been successful in improving model performance by learning diverse members via the stochasticity of random initialization. While recent works have attempted to promote further diversity in DE via hyperparameters or regularizing loss functions, these methods primarily still rely on a stochastic approach to explore the hypothesis space. In this work, we present Multi-Symmetry Ensembles (MSE), a framework for constructing diverse ensembles by capturing the multiplicity of hypotheses along symmetry axes, which explore the hypothesis space beyond stochastic perturbations of model weights and hyperparameters. We leverage recent advances in contrastive representation learning to create models that separately capture opposing hypotheses of invariant and equivariant functional classes and present a simple ensembling approach to efficiently combine appropriate hypotheses for a given task. We show that MSE effectively captures the multiplicity of conflicting hypotheses that is often required in large, diverse datasets like ImageNet. As a result of their inherent diversity, MSE improves classification performance, uncertainty quantification, and generalization across a series of transfer tasks.Comment: Camera Ready Revision. ICML 202

    Pintura Ă  base de cal como alternativa de revestimento frio

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    Os centros urbanos vêm sofrendo alterações climáticas oriundas do fenômeno das ilhas de calor. Como consequência, há o aumento na demanda de energia para condicionamento térmico, além de causar desconforto em habitações que não fazem uso de ar-condicionado. Revestimento frio é uma alternativa que pode minimizar os efeitos da ilha de calor, pois possui capacidade de refletir a luz solar incidente, bem como reemitir parte do calor absorvido pela superfície para o ambiente. Tradicionalmente, superfícies brancas são responsáveis por alto poder de reflexão. Partindo desse conceito, o presente trabalho mediu as propriedades de refletância e emissividade térmica de superfícies pintadas com tinta à base de cal, em diferentes números de demãos, sobre substratos distintos. Além dessas propriedades, foi feita uma análise da capacidade de cobertura das amostras nas condições úmida e seca. Os resultados de refletância variaram de 0,56 a 0,83, dependendo do número de demãos e do tipo de substrato. A emissividade térmica manteve-se com índice de, em média, 0,97, independentemente do tipo de substrato e demãos de pintura. Por fim, percebeu-se um contraste expressivo entre as superfícies sob as condições úmida e seca. Os resultados demonstram que a pintura de cal atende aos requisitos de refletância e emissividade térmica para um revestimento frio
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