Quintuple Friction Pendulum Isolator: Behavior, Modeling, and Validation

2016 ◽  
Vol 32 (3) ◽  
pp. 1607-1626 ◽  
Author(s):  
Donghun Lee ◽  
Michael C. Constantinou
Keyword(s):  
Computational Model ◽  
Analytical Model ◽  
Adaptive Behavior ◽  
Computational Models ◽  
Behavior Modeling ◽  
Analysis And Design ◽  
Frictional Properties ◽  
Sliding Surfaces ◽  
Multi Stage ◽  
Friction Pendulum

This paper describes the behavior of the quintuple friction pendulum isolator, a spherical sliding isolator with six sliding surfaces, five effective pendula, and nine regimes of operation that allow for complex multi-stage adaptive behavior depending on the amplitude of displacement. An analytical model is presented that is capable of tracing the behavior of the isolator in two general configurations of geometric and frictional properties. This analytical model is useful for verifying computational models and in performing simplified calculations for analysis and design. A computational model that can be implemented in the program SAP2000 is also presented and verified by comparison to the analytical model. A model quintuple friction pendulum isolator has been tested and the results have been used to validate the analytical and computational models.

Behavior of Quintuple Friction Pendulum System Under Near-Fault Earthquakes

2017 ◽  
Vol 11 (05) ◽  
pp. 1750017
Author(s):  
A. H. Sodha ◽  
D. P. Soni ◽  
M. K. Desai ◽  
S. Kumar
Keyword(s):  
Adaptive Behavior ◽  
Service Level ◽  
Base Shear ◽  
Pendulum System ◽  
Directivity Effect ◽  
Sliding Surfaces ◽  
Near Fault ◽  
Effective Period ◽  
Fling Step ◽  
Friction Pendulum

The Quintuple Friction Pendulum (QTFP) system is a new generation sliding isolation having six spherical sliding surfaces with five effective pendula. Due to multiple sliding surfaces, QTFP system shows highly adaptive behavior under different hazard level of earthquakes, despite being a passive system. The paper describes mathematical model and seismic response of QTFP system under 60 earthquake records consisting of service level, design basis and maximum considered earthquakes. To study the effect of directivity focusing and fling step, additional 15 records consist of far-field, near-fault with forward directivity and fling step effect are also considered. Three types of effective period and effective damping in combination with two different displacement capacities of QTFP bearing resulting in six isolator designs are considered. The seismic demand parameters like base shear, top floor absolute acceleration and isolator displacement have been studied. It is found that the QTFP bearing stiffens at low input, softens with increasing input, and then stiffens again at higher levels of input. Thus, it shows highly adaptive behavior under different hazard levels of earthquake. Further, due to forward and backward momentum conveyed by the directivity pulse, near-fault directivity effect imposes higher demand compared to fling step containing only forward momentum.

CSBPI_Site：Multi-Information Sources of Features to RNA Binding Sites Prediction

2021 ◽  
Vol 15 ◽  
Author(s):  
Lichao Zhang ◽  
Zihong Huang ◽  
Liang Kong
Keyword(s):  
Computational Model ◽  
Binding Sites ◽  
Noncoding Rna ◽  
Computational Models ◽  
Information Sources ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Gradient Boosting ◽  
Position Information ◽  
Rna Binding Sites

Background: RNA-binding proteins establish posttranscriptional gene regulation by coordinating the maturation, editing, transport, stability, and translation of cellular RNAs. The immunoprecipitation experiments could identify interaction between RNA and proteins, but they are limited due to the experimental environment and material. Therefore, it is essential to construct computational models to identify the function sites. Objective: Although some computational methods have been proposed to predict RNA binding sites, the accuracy could be further improved. Moreover, it is necessary to construct a dataset with more samples to design a reliable model. Here we present a computational model based on multi-information sources to identify RNA binding sites. Method: We construct an accurate computational model named CSBPI_Site, based on xtreme gradient boosting. The specifically designed 15-dimensional feature vector captures four types of information (chemical shift, chemical bond, chemical properties and position information). Results: The satisfied accuracy of 0.86 and AUC of 0.89 were obtained by leave-one-out cross validation. Meanwhile, the accuracies were slightly different (range from 0.83 to 0.85) among three classifiers algorithm, which showed the novel features are stable and fit to multiple classifiers. These results showed that the proposed method is effective and robust for noncoding RNA binding sites identification. Conclusion: Our method based on multi-information sources is effective to represent the binding sites information among ncRNAs. The satisfied prediction results of Diels-Alder riboz-yme based on CSBPI_Site indicates that our model is valuable to identify the function site.

scholarly journals Numerical and Experimental Investigations on Vocal Fold Approximation in Healthy and Simulated Unilateral Vocal Fold Paralysis

2021 ◽  
Vol 11 (4) ◽  
pp. 1817
Author(s):  
Zheng Li ◽  
Azure Wilson ◽  
Lea Sayce ◽  
Amit Avhad ◽  
Bernard Rousseau ◽  
...  
Keyword(s):  
Computational Model ◽  
Vocal Fold ◽  
High Speed ◽  
Computational Models ◽  
Ex Vivo ◽  
Vocal Fold Paralysis ◽  
Future Application ◽  
Experimental Investigations ◽  
Type I ◽  
Mri Scans

We have developed a novel surgical/computational model for the investigation of unilat-eral vocal fold paralysis (UVFP) which will be used to inform future in silico approaches to improve surgical outcomes in type I thyroplasty. Healthy phonation (HP) was achieved using cricothyroid suture approximation on both sides of the larynx to generate symmetrical vocal fold closure. Following high-speed videoendoscopy (HSV) capture, sutures on the right side of the larynx were removed, partially releasing tension unilaterally and generating asymmetric vocal fold closure characteristic of UVFP (sUVFP condition). HSV revealed symmetric vibration in HP, while in sUVFP the sutured side demonstrated a higher frequency (10–11%). For the computational model, ex vivo magnetic resonance imaging (MRI) scans were captured at three configurations: non-approximated (NA), HP, and sUVFP. A finite-element method (FEM) model was built, in which cartilage displacements from the MRI images were used to prescribe the adduction, and the vocal fold deformation was simulated before the eigenmode calculation. The results showed that the frequency comparison between the two sides was consistent with observations from HSV. This alignment between the surgical and computational models supports the future application of these methods for the investigation of treatment for UVFP.

scholarly journals Computational models of adaptive behavior and prefrontal cortex

2021 ◽  
Author(s):  
Alireza Soltani ◽  
Etienne Koechlin
Keyword(s):  
Prefrontal Cortex ◽  
Adaptive Behavior ◽  
Computational Models ◽  
Cognitive Architecture ◽  
Behavioral Outcomes ◽  
Internal Models ◽  
Multiple Systems ◽  
Statistical Inferences ◽  
Neural Computations ◽  
Task Sets

AbstractThe real world is uncertain, and while ever changing, it constantly presents itself in terms of new sets of behavioral options. To attain the flexibility required to tackle these challenges successfully, most mammalian brains are equipped with certain computational abilities that rely on the prefrontal cortex (PFC). By examining learning in terms of internal models associating stimuli, actions, and outcomes, we argue here that adaptive behavior relies on specific interactions between multiple systems including: (1) selective models learning stimulus–action associations through rewards; (2) predictive models learning stimulus- and/or action–outcome associations through statistical inferences anticipating behavioral outcomes; and (3) contextual models learning external cues associated with latent states of the environment. Critically, the PFC combines these internal models by forming task sets to drive behavior and, moreover, constantly evaluates the reliability of actor task sets in predicting external contingencies to switch between task sets or create new ones. We review different models of adaptive behavior to demonstrate how their components map onto this unifying framework and specific PFC regions. Finally, we discuss how our framework may help to better understand the neural computations and the cognitive architecture of PFC regions guiding adaptive behavior.

scholarly journals Using Dissipative Particle Dynamics to Model Effects of Chemical Reactions Occurring within Hydrogels

Nanomaterials ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 2764
Author(s):  
Ya Liu ◽  
Joanna Aizenberg ◽  
Anna C. Balazs
Keyword(s):  
Computational Models ◽  
Structural Changes ◽  
Dissipative Particle Dynamics ◽  
Chemical Species ◽  
Structural Response ◽  
Particle Dynamics ◽  
Multi Stage ◽  
Chemical Stimuli ◽  
Chemical Events ◽  
Collapsed States

Computational models that reveal the structural response of polymer gels to changing, dissolved reactive chemical species would provide useful information about dynamically evolving environments. However, it remains challenging to devise one computational approach that can capture all the interconnected chemical events and responsive structural changes involved in this multi-stage, multi-component process. Here, we augment the dissipative particle dynamics (DPD) method to simulate the reaction of a gel with diffusing, dissolved chemicals to form kinetically stable complexes, which in turn cause concentration-dependent deformation of the gel. Using this model, we also examine how the addition of new chemical stimuli and subsequent reactions cause the gel to exhibit additional concentration-dependent structural changes. Through these DPD simulations, we show that the gel forms multiple latent states (not just the “on/off”) that indicate changes in the chemical composition of the fluidic environment. Hence, the gel can actuate a range of motion within the system, not just movements corresponding to the equilibrated swollen or collapsed states. Moreover, the system can be used as a sensor, since the structure of the layer effectively indicates the presence of chemical stimuli.

scholarly journals The Exponential-Weight Mean-Variance Model: A novel computational model for the Balloon Analogue Risk Task

2019 ◽  
Author(s):  
Harhim Park ◽  
Jaeyeong Yang ◽  
Jasmin Vassileva ◽  
Woo-Young Ahn
Keyword(s):  
Computational Model ◽  
Computational Models ◽  
Model Comparison ◽  
Exponential Weight ◽  
Multiple Model ◽  
Variance Model ◽  
Balloon Analogue Risk Task ◽  
Parameter Recovery ◽  
Post Hoc ◽  
Mean Variance

The Balloon Analogue Risk Task (BART) is a popular task used to measure risk-taking behavior. To identify cognitive processes associated with choice behavior on the BART, a few computational models have been proposed. However, the extant models are either too simplistic or fail to show good parameter recovery performance. Here, we propose a novel computational model, the exponential-weight mean-variance (EWMV) model, which addresses the limitations of existing models. By using multiple model comparison methods, including post hoc model fits criterion and parameter recovery, we showed that the EWMV model outperforms the existing models. In addition, we applied the EWMV model to BART data from healthy controls and substance-using populations (patients with past opiate and stimulant dependence). The results suggest that (1) the EWMV model addresses the limitations of existing models and (2) heroin-dependent individuals show reduced risk preference than other groups in the BART.

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