scholarly journals Coupled Delft3D-Object Model to Predict Mobility of Munition on Sandy Seafloor

Fluids ◽  
2021 ◽  
Vol 6 (9) ◽  
pp. 330
Author(s):  
Peter C. Chu ◽  
Vinicius S. Pessanha ◽  
Chenwu Fan ◽  
Joseph Calantoni
Keyword(s):  
Experimental Data ◽  
Sediment Transport ◽  
Time Series Data ◽  
Major Axis ◽  
Series Data ◽  
Physical Parameters ◽  
Object Model ◽  
Wave Direction ◽  
Rolling Moment ◽  
Object Mobility

The coupled Delft3D-object model has been developed to predict the mobility and burial of objects on sandy seafloors. The Delft3D model is used to predict seabed environmental factors such as currents, waves (peak wave period, significant wave height, wave direction), water level, sediment transport, and seabed change, which are taken as the forcing term to the object model consisting of three components: (a) physical parameters such as diameter, length, mass, and rolling moment; (b) dynamics of the rolling cylinder around its major axis; (c) an empirical sediment scour model with re-exposure parameterization. The model is compared with the observational data collected from a field experiment from 21 April to 13 May 2013 off the coast of Panama City, Florida. The experimental data contain both object mobility using sector scanning sonars and maintenance divers as well as simultaneous environmental time series data of the boundary layer hydrodynamics and sediment transport conditions. Comparison between modeled and observed data clearly shows the model’s capabilities and limitations.

scholarly journals Coupled Delft3D-Object Model to Predict Mobility and Burial of Munition on Sandy Floor

2021 ◽  
Author(s):  
Peter C. Chu ◽  
Vinicius S. Pessanha ◽  
Chenwu Fan
Keyword(s):  
Sediment Transport ◽  
Time Series Data ◽  
Development Program ◽  
Environmental Research ◽  
Series Data ◽  
Physical Parameters ◽  
Object Model ◽  
Wave Direction ◽  
Peak Period ◽  
Rolling Moment

Coupled Delft3D-object model has been developed to predict object’s mobility and burial on sandy seafloor. The Delft3D model is used to predict seabed environment such as currents, waves (peak period, significant wave height, wave direction), water level, sediment transport, and seabed change, which are taken as the forcing term to the object model consisting of three components: (a) object‘s physical parameters such as diameter, length, mass, and rolling moment, (b) dynamics of rolling cylinder around its major axis, and (c) empirical sediment scour model with re-exposure parameterization. The model is compared with the observational data collected from a field experiment from 21 April to 23 May 2013 off the coast of Panama City, Florida funded by the Department of Defense Strategic Environmental Research and Development Program. The experimental data contain both objects’ mobility using sector scanning and pencil beam sonars and simultaneous environmental time series data of the boundary layer hydrodynamics and sediment transport conditions. Comparison between modeled and observed data clearly show the model capability.

scholarly journals Modeling cell proliferation in human acute myeloid leukemia xenografts

2019 ◽  
Vol 35 (18) ◽  
pp. 3378-3386 ◽  
Author(s):  
Marco S Nobile ◽  
Thalia Vlachou ◽  
Simone Spolaor ◽  
Daniela Bossi ◽  
Paolo Cazzaniga ◽  
...  
Keyword(s):  
Experimental Data ◽  
Cell Proliferation ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Time Series Data ◽  
Supplementary Information ◽  
Series Data ◽  
Proliferative Potential ◽  
Proliferating Cells ◽  
Acute Myeloid

Abstract Motivation Acute myeloid leukemia (AML) is one of the most common hematological malignancies, characterized by high relapse and mortality rates. The inherent intra-tumor heterogeneity in AML is thought to play an important role in disease recurrence and resistance to chemotherapy. Although experimental protocols for cell proliferation studies are well established and widespread, they are not easily applicable to in vivo contexts, and the analysis of related time-series data is often complex to achieve. To overcome these limitations, model-driven approaches can be exploited to investigate different aspects of cell population dynamics. Results In this work, we present ProCell, a novel modeling and simulation framework to investigate cell proliferation dynamics that, differently from other approaches, takes into account the inherent stochasticity of cell division events. We apply ProCell to compare different models of cell proliferation in AML, notably leveraging experimental data derived from human xenografts in mice. ProCell is coupled with Fuzzy Self-Tuning Particle Swarm Optimization, a swarm-intelligence settings-free algorithm used to automatically infer the models parameterizations. Our results provide new insights on the intricate organization of AML cells with highly heterogeneous proliferative potential, highlighting the important role played by quiescent cells and proliferating cells characterized by different rates of division in the progression and evolution of the disease, thus hinting at the necessity to further characterize tumor cell subpopulations. Availability and implementation The source code of ProCell and the experimental data used in this work are available under the GPL 2.0 license on GITHUB at the following URL: https://github.com/aresio/ProCell. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals X-ray Flux and Spectral Variability of the TeV Blazars Mrk 421 and PKS 2155-304

Galaxies ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 64
Author(s):  
Alok C. Gupta
Keyword(s):  
Black Hole ◽  
Time Series Data ◽  
Series Data ◽  
Physical Parameters ◽  
Electromagnetic Spectrum ◽  
Black Hole Mass ◽  
Spectral Variability ◽  
Massive Black Hole ◽  
X Ray ◽  
Northern And Southern Hemispheres

We reviewed X-ray flux and spectral variability properties studied to date by various X-ray satellites for Mrk 421 and PKS 2155-304, which are TeV emitting blazars. Mrk 421 and PKS 2155-304 are the most X-ray luminous blazars in the northern and southern hemispheres, respectively. Blazars show flux and spectral variabilities in the complete electromagnetic spectrum on diverse timescales ranging from a few minutes to hours, days, weeks, months and even several years. The flux and spectral variability on different timescales can be used to constrain the size of the emitting region, estimate the super massive black hole mass, find the dominant emission mechanism in the close vicinity of the super massive black hole, search for quasi-periodic oscillations in time series data and several other physical parameters of blazars. Flux and spectral variability is also a dominant tool to explain jet as well as disk emission from blazars at different epochs of observations.

scholarly journals Evaluating the Within-Host Dynamics of Ranavirus Infection with Mechanistic Disease Models and Experimental Data

Viruses ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 396 ◽  
Author(s):  
Joseph R. Mihaljevic ◽  
Amy L. Greer ◽  
Jesse L. Brunner
Keyword(s):  
Experimental Data ◽  
Time Series ◽  
Immune System ◽  
Viral Replication ◽  
Time Series Data ◽  
Immune Defense ◽  
Series Data ◽  
System Response ◽  
Mechanistic Models ◽  
Viral Titer

Mechanistic models are critical for our understanding of both within-host dynamics (i.e., pathogen replication and immune system processes) and among-host dynamics (i.e., transmission). Within-host models, however, are not often fit to experimental data, which can serve as a robust method of hypothesis testing and hypothesis generation. In this study, we use mechanistic models and empirical, time-series data of viral titer to better understand the replication of ranaviruses within their amphibian hosts and the immune dynamics that limit viral replication. Specifically, we fit a suite of potential models to our data, where each model represents a hypothesis about the interactions between viral replication and immune defense. Through formal model comparison, we find a parsimonious model that captures key features of our time-series data: The viral titer rises and falls through time, likely due to an immune system response, and that the initial viral dosage affects both the peak viral titer and the timing of the peak. Importantly, our model makes several predictions, including the existence of long-term viral infections, which can be validated in future studies.

Applied Data Analytics to Buoy Records for Weather Window Evaluation

2021 ◽  
Author(s):  
Tirtharaj Bhaumik ◽  
Shiladitya Basu
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Data Analytics ◽  
Time Series Data ◽  
Weather Data ◽  
Series Data ◽  
Wave Direction ◽  
Significant Wave ◽  
Using Data ◽  
Future Work

This paper analyzes weather data recorded by typical oceanographic buoys using data analytics and regression techniques. Time series data over a period of more than four decades (1976 – 2020) are reviewed and profiled. A set of key variables including seasonality, wind speed, wind direction, wave period, wave direction, etc., are screened from the buoy measurements to build a predictive model based on multiple linear regression for significant wave height prediction. A sensitivity analysis is then conducted for the available weather window corresponding to specified threshold operational limits of the significant wave height. Key insights are presented along with suggestions for future work to assist marine operators in planning and derisking offshore operations. Utilizing the algorithms and workflows presented in this paper, a user can increase confidence in weather window prediction, and develop safer, efficient offshore operation plans.

Extremely peculiar spectrum of the primary component of the eclipsing binary HD 66051

2019 ◽  
Vol 15 (S350) ◽  
pp. 412-414
Author(s):  
E. Niemczura ◽  
P. A. Kołaczek-Szymański ◽  
F. Castelli ◽  
S. Hubrig ◽  
S. P. Järvinen ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Primary Component ◽  
Series Data ◽  
Physical Parameters ◽  
Orbital Parameters ◽  
Chemically Peculiar ◽  
Peculiar Stars ◽  
Chemically Peculiar Stars ◽  
Chemical Peculiarity

AbstractHD 66051 is an eclipsing and spectroscopic double-lined binary (SB2), hosting two chemically peculiar stars: a highly peculiar B star as primary and an Am star as secondary. The investigation of the new high-resolution UVES spectrum of HD 66051 allowed us to decide on the chemical peculiarity type of both components with more reliability. An analysis of TESS photometric time series data will further specify the physical parameters of the stars and the orbital parameters of the system.

A SIMPLE TEST FOR HIDDEN PERIODICITY IN TIME SERIES DATA

1995 ◽  
Vol 05 (01) ◽  
pp. 265-269 ◽  
Author(s):  
MICHAEL ROSENBLUM ◽  
JÜRGEN KURTHS
Keyword(s):  
Experimental Data ◽  
Time Series ◽  
Spectral Analysis ◽  
Additive Noise ◽  
Time Series Data ◽  
Series Data ◽  
Simple Test ◽  
Data Set ◽  
Dynamical Characteristics

We would like to draw the attention of specialists in time series analysis to a simple but efficient algorithm for the determination of hidden periodic regimes in complex time series. The algorithm is stable towards additive noise and allows one to detect periodicity even if the examined data set contains only a few periods. In such cases it is more suitable than other techniques, such as spectral analysis or recurrence map. We recommend the use of this test prior to the evaluation of attractor dimensions and other dynamical characteristics from experimental data.

scholarly journals Experimental Analysis of Dynamic Interaction Between a Centrifugal Compressor and its Casing

2014 ◽  
Author(s):  
P. Almeida ◽  
C. Gibert ◽  
F. Thouverez ◽  
X. Leblanc ◽  
J.-P. Ousty
Keyword(s):  
Centrifugal Compressor ◽  
Time Series Data ◽  
Laser Doppler Vibrometer ◽  
Series Data ◽  
Physical Parameters ◽  
Full Spectrum ◽  
Scanning Laser Doppler Vibrometer ◽  
Recorded Data ◽  
Interaction Experiment ◽  
Run Up

In turbomachinery, one way to improve aerodynamic performance and reduce fuel consumption consists of minimizing the clearance between rotor and casing. Yet the probability of contact is increased and this may lead in some specific conditions to a large and even unstable excitation on the impeller and stator. To achieve better understanding of the dynamic behavior occurring during the blade-to-casing contact, many numerical studies have been conducted but only a few experiments have been reported in the literature thus far. The interaction experiment reported in this paper involves a low-pressure, rotating centrifugal compressor and its casing tested in a vacuum chamber. Contact is initiated by introducing a gap near zero, and certain events with significant dynamic levels are observed during the run-up. Measurements are performed using strain gauges on both the rotating and stationary parts and a Scanning Laser Doppler Vibrometer on the stator. This research focuses on an analysis of the recorded data. Time series data are also analyzed by means of standard signal processing and a full spectrum analysis in order to identify the direction of traveling wave propagation on the two structures as well as nodal diameters and frequencies. The dynamic response of structures is accompanied by variations in other physical parameters such as temperature, static deformed shapes, speed and torque. A wearing pattern is evaluated following the contact experiments. The spectral content of response is dominated by frequency modes excited by engine orders as well as by sidebands due to inherent system non-linearity.

scholarly journals Experimental Analysis of Dynamic Interaction Between a Centrifugal Compressor and Its Casing

2014 ◽  
Vol 137 (3) ◽  
Author(s):  
P. Almeida ◽  
C. Gibert ◽  
F. Thouverez ◽  
X. Leblanc ◽  
J.-P. Ousty
Keyword(s):  
Centrifugal Compressor ◽  
Time Series Data ◽  
Laser Doppler Vibrometer ◽  
Series Data ◽  
Physical Parameters ◽  
Full Spectrum ◽  
Rotating Speed ◽  
Scanning Laser Doppler Vibrometer ◽  
System Nonlinearity ◽  
Run Up

In turbomachinery, one way to improve aerodynamic performance and reduce fuel consumption consists of minimizing the clearance between rotor and casing. Yet, the probability of contact is increased and this may lead in some specific conditions to a large and even unstable excitation on the impeller and stator. To achieve better understanding of the dynamic behavior occurring during the blade-to-casing contact, many numerical studies have been conducted but only a few experiments have been reported in the literature thus far. The interaction experiment reported in this paper involves a low-pressure, rotating centrifugal compressor and its casing tested in a vacuum chamber. Contact is initiated by introducing a gap near zero, and certain events with significant dynamic levels are observed during the run-up. Measurements are performed using strain gauges on both the rotating and stationary parts and a scanning laser Doppler vibrometer on the stator. This research focuses on an analysis of the recorded data. Time series data are also analyzed by means of standard signal processing and a full spectrum analysis in order to identify the direction of traveling wave propagation on the two structures as well as nodal diameters and frequencies. The dynamic response of structures is accompanied by variations in other physical parameters such as temperature, static deformed shapes, speed, and torque. A wearing pattern is evaluated following the contact experiments. The spectral content of response is dominated by frequency modes excited by rotating speed harmonics as well as by sidebands due to inherent system nonlinearity.

Transcriptional processes: Models and inference

2018 ◽  
Vol 16 (05) ◽  
pp. 1850023 ◽  
Author(s):  
Keerthi S. Shetty ◽  
Annappa B
Keyword(s):  
Experimental Data ◽  
Time Series Data ◽  
Stochastic Simulation Algorithm ◽  
Process Models ◽  
Series Data ◽  
Erlang Distribution ◽  
Model Parameters ◽  
Compute Model ◽  
Transcriptional Bursting ◽  
Multistep Reaction

Many biochemical events involve multistep reactions. One of the most important biological processes that involve multistep reaction is the transcriptional process. Models for multistep reaction necessarily need multiple states and it is a challenge to compute model parameters that best agree with experimental data. Therefore, the aim of this work is to design a multistep promoter model which accurately characterizes transcriptional bursting and is consistent with observed data. To address this issue, we develop a model for promoters with several OFF states and a single ON state using Erlang distribution. To explore the combined effects of model and data, we combine Monte Carlo extension of Expectation Maximization (MCEM) and delay Stochastic Simulation Algorithm (DSSA) and call the resultant algorithm as delay Bursty MCEM. We apply this algorithm to time-series data of endogenous mouse glutaminase promoter to validate the model assumptions and infer the kinetic parameters. Our results show that with multiple OFF states, we are able to infer and produce a model which is more consistent with experimental data. Our results also show that delay Bursty MCEM inference is more efficient.

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