scholarly journals Preliminary Study: Learning the Impact of Simulation Time on Reentry Location and Morphology Induced by Personalized Cardiac Modeling

2021 ◽  
Vol 12 ◽  
Author(s):  
Lv Tong ◽  
Caiming Zhao ◽  
Zhenyin Fu ◽  
Ruiqing Dong ◽  
Zhenghong Wu ◽  
...  
Keyword(s):  
Gaussian Mixture ◽  
Cardiac Modeling ◽  
Simulation Accuracy ◽  
Cardiac Arrythmias ◽  
Simulation Efficiency ◽  
Simulation Group ◽  
Simulation Results ◽  
Clinical Measurements ◽  
The Impact ◽  
Simulation Time

Personalized cardiac modeling is widely used for studying the mechanisms of cardiac arrythmias. Due to the high demanding of computational resource of modeling, the arrhythmias induced in the models are usually simulated for just a few seconds. In clinic, it is common that arrhythmias last for more than several minutes and the morphologies of reentries are not always stable, so it is not clear that whether the simulation of arrythmias for just a few seconds is long enough to match the arrhythmias detected in patients. This study aimed to observe how long simulation of the induced arrhythmias in the personalized cardiac models is sufficient to match the arrhythmias detected in patients. A total of 5 contrast enhanced MRI datasets of patient hearts with myocardial infarction were used in this study. Then, a classification method based on Gaussian mixture model was used to detect the infarct tissue. For each reentry, 3 s and 10 s were simulated. The characteristics of each reentry simulated for different duration were studied. Reentries were induced in all 5 ventricular models and sustained reentries were induced at 39 stimulation sites in the model. By analyzing the simulation results, we found that 41% of the sustained reentries in the 3 s simulation group terminated in the longer simulation groups (10 s). The second finding in our simulation was that only 23.1% of the sustained reentries in the 3 s simulation did not change location and morphology in the extended 10 s simulation. The third finding was that 35.9% reentries were stable in the 3 s simulation and should be extended for the simulation time. The fourth finding was that the simulation results in 10 s simulation matched better with the clinical measurements than the 3 s simulation. It was shown that 10 s simulation was sufficient to make simulation results stable. The findings of this study not only improve the simulation accuracy, but also reduce the unnecessary simulation time to achieve the optimal use of computer resources to improve the simulation efficiency and shorten the simulation time to meet the time node requirements of clinical operation on patients.

Nano-Indentation Simulation Study Based on Parallel Computing

2012 ◽  
Vol 500 ◽  
pp. 696-701
Author(s):  
Ying Zhu ◽  
Sen Song ◽  
Ling Ling Xie ◽  
Shun He Qi ◽  
Qian Qian Liu
Keyword(s):  
Molecular Dynamics ◽  
Parallel Computing ◽  
Molecular Dynamics Simulation ◽  
Large Scale ◽  
Dynamics Simulation ◽  
Parallel Computer ◽  
Nano Indentation ◽  
Simulation Results ◽  
The Impact ◽  
Simulation Time

This method of parallel computing into nanoindentation molecular dynamics simulation (MDS), the author uses a nine-node parallel computer and takes the single crystal aluminum as the experimental example, to implement the large-scale process simulation of nanoindentation. Compared the simulation results with experimental results is to verify the reliability of the simulation. The method improves the computational efficiency and shortens the simulation time and the expansion of scale simulation can significantly reduce the impact of boundary conditions, effectively improve the accuracy of the molecular dynamics simulation of nanoindentation.

Studying the Impact of Return Current Path on the EM Simulation of High-speed Package Designs

2011 ◽  
Vol 2011 (1) ◽  
pp. 000061-000068
Author(s):  
Darryl Kostka ◽  
Antonio Ciccomancini Scogna
Keyword(s):  
High Speed ◽  
Ground Plane ◽  
Three Dimensional ◽  
Simulation Models ◽  
Current Path ◽  
Cavity Resonances ◽  
Simulation Results ◽  
The Impact ◽  
Simulation Time

Three-dimensional electromagnetic simulation models are often simplified in order to reduce the simulation time and memory requirements without sacrificing the accuracy of the results. A commonly adopted methodology in the simulation of electronic package designs is to truncate the size of the package model leaving only a few important features surrounding the nets of interest. In this paper we demonstrate that this simplification can have a significant impact of the simulation results if it is not performed carefully and it can introduce spurious/non physical resonances. The interaction between cavities and signals is first studied using a simple coupled differential via test structure. It is demonstrated that the return currents generated by these vias excite cavity resonances in power-ground plane pairs causing them to behave as parallel-plate waveguides. The role of interplane shorting vias in suppressing cavity resonances is then investigated and the impact of boundary conditions on the simulation results of package models is also shown and discussed. Finally, a realistic complex multilayer package model is analyzed and it is demonstrate that through proper truncation of the geometry, accurate results can be obtained.

scholarly journals Measuring Hydrometeors Using a Precipitation Microphysical Characteristics Sensor: Sampling Effect of Different Bin Sizes on Drop Size Distribution Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xichuan Liu ◽  
Taichang Gao ◽  
Yuntao Hu ◽  
Xiaojian Shu
Keyword(s):  
Drop Size ◽  
Rain Rate ◽  
Monte Carlo Model ◽  
Rain Gauge ◽  
Sampling Schemes ◽  
Distribution Parameters ◽  
Optimum Sampling ◽  
Simulation Results ◽  
The Impact ◽  
Good Agreement

In order to improve the measurement of precipitation microphysical characteristics sensor (PMCS), the sampling process of raindrops by PMCS based on a particle-by-particle Monte-Carlo model was simulated to discuss the effect of different bin sizes on DSD measurement, and the optimum sampling bin sizes for PMCS were proposed based on the simulation results. The simulation results of five sampling schemes of bin sizes in four rain-rate categories show that the raw capture DSD has a significant fluctuation variation influenced by the capture probability, whereas the appropriate sampling bin size and width can reduce the impact of variation of raindrop number on DSD shape. A field measurement of a PMCS, an OTT PARSIVEL disdrometer, and a tipping bucket rain Gauge shows that the rain-rate and rainfall accumulations have good consistencies between PMCS, OTT, and Gauge; the DSD obtained by PMCS and OTT has a good agreement; the probability of N0, μ, and Λ shows that there is a good agreement between the Gamma parameters of PMCS and OTT; the fitted μ-Λ and Z-R relationship measured by PMCS is close to that measured by OTT, which validates the performance of PMCS on rain-rate, rainfall accumulation, and DSD related parameters.

scholarly journals A New Method to Determine the Impact of Individual Field Quantities on Cycle-to-Cycle Variations in a Spark-Ignited Gas Engine

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4136
Author(s):  
Clemens Gößnitzer ◽  
Shawn Givler
Keyword(s):  
Kinetic Energy ◽  
Flow Field ◽  
Turbulent Kinetic Energy ◽  
Negative Impact ◽  
Operating Conditions ◽  
Engine Operation ◽  
Gas Engine ◽  
Cycle Simulation ◽  
Simulation Results ◽  
The Impact

Cycle-to-cycle variations (CCV) in spark-ignited (SI) engines impose performance limitations and in the extreme limit can lead to very strong, potentially damaging cycles. Thus, CCV force sub-optimal engine operating conditions. A deeper understanding of CCV is key to enabling control strategies, improving engine design and reducing the negative impact of CCV on engine operation. This paper presents a new simulation strategy which allows investigation of the impact of individual physical quantities (e.g., flow field or turbulence quantities) on CCV separately. As a first step, multi-cycle unsteady Reynolds-averaged Navier–Stokes (uRANS) computational fluid dynamics (CFD) simulations of a spark-ignited natural gas engine are performed. For each cycle, simulation results just prior to each spark timing are taken. Next, simulation results from different cycles are combined: one quantity, e.g., the flow field, is extracted from a snapshot of one given cycle, and all other quantities are taken from a snapshot from a different cycle. Such a combination yields a new snapshot. With the combined snapshot, the simulation is continued until the end of combustion. The results obtained with combined snapshots show that the velocity field seems to have the highest impact on CCV. Turbulence intensity, quantified by the turbulent kinetic energy and turbulent kinetic energy dissipation rate, has a similar value for all snapshots. Thus, their impact on CCV is small compared to the flow field. This novel methodology is very flexible and allows investigation of the sources of CCV which have been difficult to investigate in the past.

scholarly journals Detection of Unknown DDoS Attacks with Deep Learning and Gaussian Mixture Model

2021 ◽  
Vol 11 (11) ◽  
pp. 5213
Author(s):  
Chin-Shiuh Shieh ◽  
Wan-Wei Lin ◽  
Thanh-Tuan Nguyen ◽  
Chi-Hong Chen ◽  
Mong-Fong Horng ◽  
...  
Keyword(s):  
Deep Learning ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Denial Of Service ◽  
Gaussian Mixture ◽  
Mitigation Measures ◽  
Distribution Model ◽  
Ddos Attacks ◽  
Open Set ◽  
The Impact

DDoS (Distributed Denial of Service) attacks have become a pressing threat to the security and integrity of computer networks and information systems, which are indispensable infrastructures of modern times. The detection of DDoS attacks is a challenging issue before any mitigation measures can be taken. ML/DL (Machine Learning/Deep Learning) has been applied to the detection of DDoS attacks with satisfactory achievement. However, full-scale success is still beyond reach due to an inherent problem with ML/DL-based systems—the so-called Open Set Recognition (OSR) problem. This is a problem where an ML/DL-based system fails to deal with new instances not drawn from the distribution model of the training data. This problem is particularly profound in detecting DDoS attacks since DDoS attacks’ technology keeps evolving and has changing traffic characteristics. This study investigates the impact of the OSR problem on the detection of DDoS attacks. In response to this problem, we propose a new DDoS detection framework featuring Bi-Directional Long Short-Term Memory (BI-LSTM), a Gaussian Mixture Model (GMM), and incremental learning. Unknown traffic captured by the GMM are subject to discrimination and labeling by traffic engineers, and then fed back to the framework as additional training samples. Using the data sets CIC-IDS2017 and CIC-DDoS2019 for training, testing, and evaluation, experiment results show that the proposed BI-LSTM-GMM can achieve recall, precision, and accuracy up to 94%. Experiments reveal that the proposed framework can be a promising solution to the detection of unknown DDoS attacks.

A Dicode Signaling Scheme for Capacitively Coupled Interface

2011 ◽  
Vol 497 ◽  
pp. 296-305
Author(s):  
Yasushi Yuminaka ◽  
Kyohei Kawano
Keyword(s):  
Partial Response ◽  
Data Transmission ◽  
High Speed ◽  
Circuit Simulation ◽  
Frequency Bandwidth ◽  
Capacitively Coupled ◽  
Limited Frequency ◽  
Simulation Results ◽  
Response Coding ◽  
The Impact

In this paper, we present a bandwidth-efficient partial-response signaling scheme for capacitivelycoupled chip-to-chip data transmission to increase data rate. Partial-response coding is knownas a technique that allows high-speed transmission while using a limited frequency bandwidth, by allowingcontrolled intersymbol interference (ISI). Analysis and circuit simulation results are presentedto show the impact of duobinary (1+D) and dicode (1-D) partial-response signaling for capacitivelycoupled interface.

An Improved Initial Alignment Method of Strap-Down Inertial Navigation System on a Swaying Base

2013 ◽  
Vol 415 ◽  
pp. 143-148
Author(s):  
Li Hua Zhu ◽  
Xiang Hong Cheng
Keyword(s):  
Navigation System ◽  
Inertial Navigation System ◽  
Alignment Algorithm ◽  
Alignment Method ◽  
Initial Alignment ◽  
Vehicle Simulation ◽  
Robust Property ◽  
Simulation Results ◽  
Lever Arm Effect ◽  
The Impact

The design of an improved alignment method of SINS on a swaying base is presented in this paper. FIR filter is taken to decrease the impact caused by the lever arm effect. And the system also encompasses the online estimation of gyroscopes’ drift with Kalman filter in order to do the compensation, and the inertial freezing alignment algorithm which helps to resolve the attitude matrix with respect to its fast and robust property to provide the mathematical platform for the vehicle. Simulation results show that the proposed method is efficient for the initial alignment of the swaying base navigation system.

Optimization of RANS Solver Simulation Setup for Propeller Open Water Performance Prediction

2015 ◽  
Author(s):  
Mohammed Islam ◽  
Fatima Jahra ◽  
Michael Doucet
Keyword(s):  
Domain Size ◽  
Open Water ◽  
Fractional Factorial ◽  
Navier Stokes ◽  
Calm Water ◽  
Simulation Results ◽  
Open Water Performance ◽  
Thrust And Torque ◽  
Simulation Time ◽  
Fixed Pitch

Mesh and domain optimization strategies for a RANS solver to accurately estimate the open water propulsive characteristics of fixed pitch propellers are proposed based on examining the effect of different mesh and computation domain parameters. The optimized mesh and domain size parameters were selected using Design of Experiments (DoE) methods enabling simulations to be carried out in a limited memory environment, and in a timely manner; without compromising the accuracy of results. A Reynolds-Averaged Navier Stokes solver is used to predict the propulsive performance of a fixed pitch propeller. The predicted thrust and torque for the propeller were compared to the corresponding measurements. A total of six meshing parameters were selected that could affect the computational results of propeller open water performance. A two-level fractional factorial design was used to screen out parameters that do not significantly contribute to explaining the dependent parameters: namely simulation time, propeller thrust and propeller torque. A total of 32 simulations were carried out only to find out that the selected six meshing parameters were significant in defining the response parameters. Optimum values of each of the input parameters were obtained for the DOE technique and additional simulations were run with those parameters. The simulation results were validated using open water experimental results of the same propeller. It was found that with the optimized meshing arrangement, the propeller opens simulation time was reduced by at least a factor of 6 as compared to the generally popular meshing arrangement. Also, the accuracy of propulsive characteristics was improved by up to 50% as compared to published simulation results. The methodologies presented in this paper can be similarly applied to other simulations such as calm water ship resistance, ship propulsion to systematically derive the optimized meshing arrangement for simulations with minimal simulation time and maximum accuracy. This investigation was carried out using STAR-CCM+, a commercial CFD package; however the findings can be applied to any RANS solver.

scholarly journals Multigrid Nonlocal Gaussian Mixture Model for Segmentation of Brain Tissues in Magnetic Resonance Images

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Yunjie Chen ◽  
Tianming Zhan ◽  
Ji Zhang ◽  
Hongyuan Wang
Keyword(s):  
Magnetic Resonance ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Magnetic Resonance Images ◽  
Intensity Inhomogeneity ◽  
Mr Images ◽  
Proposed Model ◽  
Brain Mr Images ◽  
The Impact

We propose a novel segmentation method based on regional and nonlocal information to overcome the impact of image intensity inhomogeneities and noise in human brain magnetic resonance images. With the consideration of the spatial distribution of different tissues in brain images, our method does not need preestimation or precorrection procedures for intensity inhomogeneities and noise. A nonlocal information based Gaussian mixture model (NGMM) is proposed to reduce the effect of noise. To reduce the effect of intensity inhomogeneity, the multigrid nonlocal Gaussian mixture model (MNGMM) is proposed to segment brain MR images in each nonoverlapping multigrid generated by using a new multigrid generation method. Therefore the proposed model can simultaneously overcome the impact of noise and intensity inhomogeneity and automatically classify 2D and 3D MR data into tissues of white matter, gray matter, and cerebral spinal fluid. To maintain the statistical reliability and spatial continuity of the segmentation, a fusion strategy is adopted to integrate the clustering results from different grid. The experiments on synthetic and clinical brain MR images demonstrate the superior performance of the proposed model comparing with several state-of-the-art algorithms.

Investigation on penetration model of shaped charge jet in water

2016 ◽  
Vol 30 (02) ◽  
pp. 1550268 ◽  
Author(s):  
Jinwei Shi ◽  
Xingbai Luo ◽  
Jinming Li ◽  
Jianwei Jiang
Keyword(s):  
Numerical Simulation ◽  
Theoretical Model ◽  
Model Simulation ◽  
Theoretical Models ◽  
Theoretical Research ◽  
Water Medium ◽  
Simulation Results ◽  
Jet Penetration ◽  
The Impact ◽  
Penetration Velocity

To analyze the process of jet penetration in water medium quantitatively, the properties of jet penetration spaced target with water interlayer were studied through test and numerical simulation. Two theoretical models of jet penetration in water were proposed. The theoretical model 1 was established considering the impact of the shock wave, combined with the shock equation Rankine–Hugoniot and the virtual origin calculation method. The theoretical model 2 was obtained by fitting theoretical analysis and numerical simulation results. The effectiveness and universality of the two theoretical models were compared through the numerical simulation results. Both the models can reflect the relationship between the penetration velocity and the penetration distance in water well, and both the deviation and stability of theoretical model 1 are better than 2, the lower penetration velocity, and the larger deviation of the theoretical model 2. Therefore, the theoretical model 1 can reflect the properties of jet penetration in water effectively, and provide the reference of model simulation and theoretical research.

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