• Title/Summary/Keyword: Techno-uncertainty

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Robust stability analysis of real-time hybrid simulation considering system uncertainty and delay compensation

  • Chen, Pei-Ching;Chen, Po-Chang
    • Smart Structures and Systems
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    • v.25 no.6
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    • pp.719-732
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    • 2020
  • Real-time hybrid simulation (RTHS) which combines physical experiment with numerical simulation is an advanced method to investigate dynamic responses of structures subjected to earthquake excitation. The desired displacement computed from the numerical substructure is applied to the experimental substructure by a servo-hydraulic actuator in real time. However, the magnitude decay and phase delay resulted from the dynamics of the servo-hydraulic system affect the accuracy and stability of a RTHS. In this study, a robust stability analysis procedure for a general single-degree-of-freedom structure is proposed which considers the uncertainty of servo-hydraulic system dynamics. For discussion purposes, the experimental substructure is a portion of the entire structure in terms of a ratio of stiffness, mass, and damping, respectively. The dynamics of the servo-hydraulic system is represented by a multiplicative uncertainty model which is based on a nominal system and a weight function. The nominal system can be obtained by conducting system identification prior to the RTHS. A first-order weight function formulation is proposed which needs to cover the worst possible uncertainty envelope over the frequency range of interest. Then, the Nyquist plot of the perturbed system is adopted to determine the robust stability margin of the RTHS. In addition, three common delay compensation methods are applied to the RTHS loop to investigate the effect of delay compensation on the robust stability. Numerical simulation and experimental validation results indicate that the proposed procedure is able to obtain a robust stability margin in terms of mass, damping, and stiffness ratio which provides a simple and conservative approach to assess the stability of a RTHS before it is conducted.

An efficient robust cost optimization procedure for rice husk ash concrete mix

  • Moulick, Kalyan K.;Bhattacharjya, Soumya;Ghosh, Saibal K.;Shiuly, Amit
    • Computers and Concrete
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    • v.23 no.6
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    • pp.433-444
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    • 2019
  • As rice husk ash (RHA) is not produced in controlled manufacturing process like cement, its properties vary significantly even within the same lot. In fact, properties of Rice Husk Ash Based Concrete (RHABC) are largely dictated by uncertainty leading to huge deviations from their expected values. This paper proposes a Robust Cost Optimization (RCO) procedure for RHABC, which minimizes such unwanted deviation due to uncertainty and provides guarantee of achieving desired strength and workability with least possible cost. The RCO simultaneously minimizes cost of RHABC production and its deviation considering feasibility of attaining desired strength and workability in presence of uncertainty. RHA related properties have been modeled as uncertain-but-bounded type as associated probability density function is not available. Metamodeling technique is adopted in this work for generating explicit expressions of constraint functions required for formulation of RCO. In doing so, the Moving Least Squares Method is explored in place of conventional Least Square Method (LSM) to ensure accuracy of the RCO. The efficiency by the proposed MLSM based RCO is validated by experimental studies. The error by the LSM and accuracy by the MLSM predictions are clearly envisaged from the test results. The experimental results show good agreement with the proposed MLSM based RCO predicted mix properties. The present RCO procedure yields RHABC mixes which is almost insensitive to uncertainty (i.e., robust solution) with nominal deviation from experimental mean values. At the same time, desired reliability of satisfying the constraints is achieved with marginal increment in cost.

The Impact of Technostress on Telemedicine App Usage Intentions in the Post-COVID19 Era (포스트 코로나 시대의 원격진료 앱 사용 의도에 대한 연구: 테크노 스트레스의 영향을 중심으로)

  • Dong-eon Lee;Se-Youn Jung
    • Journal of the Korea Safety Management & Science
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    • v.26 no.1
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    • pp.1-8
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    • 2024
  • This study explores the impact of technostress on the intention to use telemedicine applications (apps) in the post-COVID19 era, a period marked by the rapid popularization of such apps to mitigate COVID19 infection risks. Utilizing the Technology Acceptance Model (TAM), the study identifies variables and proposes a research model. A questionnaire survey involving 364 adults is analyzed through Partial Least Squares-Structural Equation Modeling. Results indicate positive significance for variables linked to the TAM (perceived usefulness, perceived ease of use, attitude, and intention to use). Notably, techno-complexity negatively affects perceived ease of use, while techno-unreliability negatively impacts perceived usefulness and ease of use. Surprisingly, techno-uncertainty has a positive effect on both perceived usefulness and ease of use. Techno-overload, although negatively impacting perceived usefulness and ease of use, does not reach statistical significance. The study underscores the need to consider both positive and negative aspects, including technostress, when evaluating telemedicine app usage. Additionally, recognizing the varying impact of technostress based on users' ICT(Information and Communication Technology) confidence levels is crucial. Overall, these findings contribute academically to telemedicine app adoption literature and hold industrial significance by providing a user perspective on these apps.

New fuzzy method in choosing Ground Motion Prediction Equation (GMPE) in probabilistic seismic hazard analysis

  • Mahmoudi, Mostafa;Shayanfar, MohsenAli;Barkhordari, Mohammad Ali;Jahani, Ehsan
    • Earthquakes and Structures
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    • v.10 no.2
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    • pp.389-408
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    • 2016
  • Recently, seismic hazard analysis has become a very significant issue. New systems and available data have been also developed that could help scientists to explain the earthquakes phenomena and its physics. Scientists have begun to accept the role of uncertainty in earthquake issues and seismic hazard analysis. However, handling the existing uncertainty is still an important problem and lack of data causes difficulties in precisely quantifying uncertainty. Ground Motion Prediction Equation (GMPE) values are usually obtained in a statistical method: regression analysis. Each of these GMPEs uses the preliminary data of the selected earthquake. In this paper, a new fuzzy method was proposed to select suitable GMPE at every intensity (earthquake magnitude) and distance (site distance to fault) according to preliminary data aggregation in their area using ${\alpha}$ cut. The results showed that the use of this method as a GMPE could make a significant difference in probabilistic seismic hazard analysis (PSHA) results instead of selecting one equation or using logic tree. Also, a practical example of this new method was described in Iran as one of the world's earthquake-prone areas.

Mode shape expansion with consideration of analytical modelling errors and modal measurement uncertainty

  • Chen, Hua-Peng;Tee, Kong Fah;Ni, Yi-Qing
    • Smart Structures and Systems
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    • v.10 no.4_5
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    • pp.485-499
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    • 2012
  • Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring; however most existing expansion methods can not consider the modelling errors in the finite element model and the measurement uncertainty in the modal properties identified from vibration data. This paper presents a reliable approach for expanding mode shapes with consideration of both the errors in analytical model and noise in measured modal data. The proposed approach takes the perturbed force as an unknown vector that contains the discrepancies in structural parameters between the analytical model and tested structure. A regularisation algorithm based on the Tikhonov solution incorporating the L-curve criterion is adopted to reduce the influence of measurement uncertainties and to produce smooth and optimised expansion estimates in the least squares sense. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is then utilised to demonstrate the applicability of the proposed expansion approach to the actual structure. The results from the benchmark problem studies show that the proposed approach can provide reliable predictions of mode shape expansion using only limited information on the operational modal data identified from the recorded ambient vibration measurements.

Topological optimized design considering dynamic problem with non-stochastic structural uncertainty

  • Lee, Dong-Kyu;Starossek, Uwe;Shin, Soo-Mi
    • Structural Engineering and Mechanics
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    • v.36 no.1
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    • pp.79-94
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    • 2010
  • This study shows how uncertainties of data like material properties quantitatively have an influence on structural topology optimization results for dynamic problems, here such as both optimal topology and shape. In general, the data uncertainties may result in uncertainties of structural behaviors like deflection or stress in structural analyses. Therefore optimization solutions naturally depend on the uncertainties in structural behaviors, since structural behaviors estimated by the structural analysis method like FEM need to execute optimization procedures. In order to quantitatively estimate the effect of data uncertainties on topology optimization solutions of dynamic problems, a so-called interval analysis is utilized in this study, and it is a well-known non-stochastic approach for uncertainty estimate. Topology optimization is realized by using a typical SIMP method, and for dynamic problems the optimization seeks to maximize the first-order eigenfrequency subject to a given material limit like a volume. Numerical applications topologically optimizing dynamic wall structures with varied supports are studied to verify the non-stochastic interval analysis is also suitable to estimate topology optimization results with dynamic problems.

Spatial variability analysis of soil strength to slope stability assessment

  • Lombardi, Mara;Cardarilli, Monica;Raspa, Giuseppe
    • Geomechanics and Engineering
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    • v.12 no.3
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    • pp.483-503
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    • 2017
  • Uncertainty is a fact belonging to engineering practice. An important uncertainty that sets geotechnical engineering is the variability associated with the properties of soils or, more precisely, the characterization of soil profiles. The reason is due largely to the complex and varied natural processes associated with the formation of soil. Spatial variability analysis for the study of the stability of natural slopes, complementing conventional analyses, is able to incorporate these uncertainties. In this paper the characterization is performed in back-analysis for a case of landslide occurred to verify afterwards the presence of the conditions of shear strength at failure. This approach may support designers to make more accurate estimates regarding slope failure responding, more consciously, to the legislation dispositions about slope stability evaluation and future design. By applying different kriging techniques used for spatial analysis it has been possible to perform a 3D-slope reconstruction. The predictive analysis and the areal mapping of the soil mechanical characteristics would support the definition of priority interventions in the zones characterized by more critical values as well as slope potential instability. This tool of analysis aims to support decision-making by directing project planning through the efficient allocation of available resources.

Health Monitoring System (HMS) for structural assessment

  • e Matos, Jose Campos;Garcia, Oscar;Henriques, Antonio Abel;Casas, Joan Ramon;Vehi, Josep
    • Smart Structures and Systems
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    • v.5 no.3
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    • pp.223-240
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    • 2009
  • As in any engineering application, the problem of structural assessment should face the different uncertainties present in real world. The main source of uncertainty in Health Monitoring System (HMS) applications are those related to the sensor accuracy, the theoretical models and the variability in structural parameters and applied loads. In present work, two methodologies have been developed to deal with these uncertainties in order to adopt reliable decisions related to the presence of damage. A simple example, a steel beam analysis, is considered in order to establish a liable comparison between them. Also, such methodologies are used with a developed structural assessment algorithm that consists in a direct and consistent comparison between sensor data and numerical model results, both affected by uncertainty. Such algorithm is applied to a simple concrete laboratory beam, tested till rupture, to show it feasibility and operational process. From these applications several conclusions are derived with a high value, regarding the final objective of the work, which is the implementation of this algorithm within a HMS, developed and applied into a prototype structure.

New GPU computing algorithm for wind load uncertainty analysis on high-rise systems

  • Wei, Cui;Luca, Caracoglia
    • Wind and Structures
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    • v.21 no.5
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    • pp.461-487
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    • 2015
  • In recent years, the Graphics Processing Unit (GPU) has become a competitive computing technology in comparison with the standard Central Processing Unit (CPU) technology due to reduced unit cost, energy and computing time. This paper describes the derivation and implementation of GPU-based algorithms for the analysis of wind loading uncertainty on high-rise systems, in line with the research field of probability-based wind engineering. The study begins by presenting an application of the GPU technology to basic linear algebra problems to demonstrate advantages and limitations. Subsequently, Monte-Carlo integration and synthetic generation of wind turbulence are examined. Finally, the GPU architecture is used for the dynamic analysis of three high-rise structural systems under uncertain wind loads. In the first example the fragility analysis of a single degree-of-freedom structure is illustrated. Since fragility analysis employs sampling-based Monte Carlo simulation, it is feasible to distribute the evaluation of different random parameters among different GPU threads and to compute the results in parallel. In the second case the fragility analysis is carried out on a continuum structure, i.e., a tall building, in which double integration is required to evaluate the generalized turbulent wind load and the dynamic response in the frequency domain. The third example examines the computation of the generalized coupled wind load and response on a tall building in both along-wind and cross-wind directions. It is concluded that the GPU can perform computational tasks on average 10 times faster than the CPU.

Probabilistic sensitivity of base-isolated buildings to uncertainties

  • Gazi, Hatice;Alhan, Cenk
    • Smart Structures and Systems
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    • v.22 no.4
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    • pp.441-457
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    • 2018
  • Characteristic parameter values of seismic isolators deviate from their nominal design values due to uncertainties and/or errors in their material properties and element dimensions, etc. Deviations may increase over service life due to environmental effects and service conditions. For accurate evaluation of the seismic safety level, all such effects, which would result in deviations in the structural response, need to be taken into account. In this study, the sensitivity of the probability of failure of the structures equipped with nonlinear base isolation systems to the uncertainties in various isolation system characteristic parameters is investigated in terms of various isolation system and superstructure response parameters in the context of a realistic three-dimensional base-isolated building model via Monte Carlo Simulations. The inherent record-to-record variability nature of the earthquake ground motions is also taken into account by carrying out analyses for a large number of ground motion records which are classified as those with and without forward-directivity effects. Two levels of nominal isolation periods each with three different levels of uncertainty are considered. Comparative plots of cumulative distribution functions and related statistical evaluation presented here portray the potential extent of the deviation of the structural response parameters resulting from the uncertainties and the uncertainty levels considered, which is expected to be useful for practicing engineers in evaluating isolator test results for their projects.