Assessment Of Dynamic Properties Of A Crowd Model For Human-Structure Interaction Modeling

As lightweight and slender structural elements are more frequently used in the design, large scale structures become more flexible and susceptible to excessive vibrations. To ensure the functionality of the structure, dynamic properties of the occupied structure need to be estimated during the design phase. Traditional analysis method models occupants simply as an additional mass; however, research has shown that human occupants could be better modeled as an additional degree-of- freedom. In the United Kingdom, active and passive crowd models are proposed by the Joint Working Group as a result of a series of analytical and experimental research. It is expected that the crowd models would yield a more accurate estimation to the dynamic response of the occupied structure. However, experimental testing recently conducted through a graduate student project at Bucknell University indicated that the proposed passive crowd model might be inaccurate in representing the impact on the structure from the occupants. The objective of this study is to provide an assessment of the validity of the crowd models proposed by JWG through comparing the dynamic properties obtained from experimental testing data and analytical modeling results. The experimental data used in this study was collected by Firman in 2010. The analytical results were obtained by performing a time-history analysis on a finite element model of the occupied structure. The crowd models were created based on the recommendations from the JWG combined with the physical properties of the occupants during the experimental study. During this study, SAP2000 was used to create the finite element models and to implement the analysis; Matlab and ME¿scope were used to obtain the dynamic properties of the structure through processing the time-history analysis results from SAP2000. The result of this study indicates that the active crowd model could quite accurately represent the impact on the structure from occupants standing with bent knees while the passive crowd model could not properly simulate the dynamic response of the structure when occupants were standing straight or sitting on the structure. Future work related to this study involves improving the passive crowd model and evaluating the crowd models with full-scale structure models and operating data.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

Experimental Evaluation of the Influence of Human-Structure Interaction for Vibration Serviceability

The effects of human-structure interaction on the dynamic performance of occupied structures have long been observed. The inclusion of the effects of human-structure interaction is important to ensure that the dynamic response of a structure is not overestimated. Previous observations, both in service and in the laboratory, have yielded results indicating that the effects are dependent on the natural frequency of the structure, the posture of the occupants, and the mass ratio of the occupants to the structure. These results are noteworthy, but are limited in their application,because the data are sparse and are only pertinent to a specific set of characteristics identified in a given study. To examine these characteristics simultaneously and consistently, an experimental test structure was designed with variable properties to replicate a variety of configurations within a controlled setting focusing on the effects of passive occupants. Experimental modal analysis techniques were employed to both the empty and occupied conditions of the structure and the dynamic properties associated with each condition were compared. Results similar to previous investigations were observed, including both an increase and a decrease in natural frequency of the occupied structure with respect to the empty structure, as well as the identification of a second mode of vibration. The damping of the combined system was higher for all configurations. Overall, this study provides a broad data set representing a wide array of configurations. The experimental results of this study were used to assess current recommendations for the dynamic properties of a crowd to analytically predict the effects of human-structure interaction. The experimental results were used to select a set of properties for passive, standing occupants and develop a new model that can more accurately represent the behavior of the human-structure system as experimentally measured in this study.