The evolving temperature field in a 1-m methanol pool fire

2021 ◽  
pp. 073490412110196
Author(s):  
Jian Chen ◽  
Kunhyuk Sung ◽  
Zhigang Wang ◽  
Wai Cheong Tam ◽  
Ki Yong Lee ◽  
...  
Keyword(s):  
Time Series ◽  
Temperature Field ◽  
Digital Camera ◽  
Thermal Inertia ◽  
Dynamic Structure ◽  
Optical Filters ◽  
Pool Fire ◽  
Pixel Intensity ◽  
Inertia Effects ◽  
Local Probability

Thin filament pyrometry is used to measure the time-varying temperature field in a 1-m methanol pool fire. A digital camera with optical filters and zoom lens recorded the emission intensity of an array of 12-µm silicon–carbide filaments oriented horizontally at various heights across the steadily burning pool fire. A 50-µm-diameter thermocouple measured the temperature at locations corresponding to the filament positions. A correlation was developed between the local probability density functions of the thermocouple time-series measurements corrected for radiation and thermal inertia effects and the camera grayscale pixel intensity of the filaments. A regression analysis yields the local mean temperature and its variance. The time series of the temperature field is transformed into average values during consecutive phases of the fire’s puffing cycle, providing quantitative insight into the complex and dynamic structure of a turbulent fire.

scholarly journals Slow Cortical Waves via Cyclicity

2021 ◽  
Author(s):  
Ivan Abraham ◽  
Bahar Shahsavarani ◽  
Ben Zimmerman ◽  
Fatima Husain ◽  
yuliy baryshnikov
Keyword(s):  
Time Series ◽  
Dynamic Structure ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Fine Grained ◽  
Human Connectome Project ◽  
Fmri Time Series ◽  
The Brain ◽  
Cortical Waves ◽  
Temporal Ordering

Fine-grained information about dynamic structure of cortical networks is crucial in unpacking brain function. Here,we introduced a novel analytical method to characterize the dynamic interaction between distant brain regions,based on cyclicity analysis, and applied it to data from the Human Connectome Project. Resting-state fMRI time series are aperiodic and, hence, lack a base frequency. Cyclicity analysis, which is time-reparametrization invariant, is effective in recovering dynamic temporal ordering of such time series along a circular trajectory without assuming any time scale. Our analysis detected the propagation of slow cortical waves across thebrain with consistent shifts in lead-lag relationships between specific brain regions. We also observed short bursts of strong temporal ordering that dominated overall lead-lag relationships between pairs of regions in the brain, which were modulated by tasks. Our results suggest the possible role played by slow waves of ordered information between brain regions that underlie emergent cognitive function.

scholarly journals Modes of Operation of Thermo-Mechanically Coupled Ice Sheets

1989 ◽  
Vol 12 ◽  
pp. 57-69 ◽  
Author(s):  
Richard C.A. Hindmarsh ◽  
Geoffrey S. Boulton ◽  
Kolumban Hutter
Keyword(s):  
Temperature Field ◽  
Time Scale ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Thermal Inertia ◽  
Coupled System ◽  
Thermal Processes ◽  
Temperature Dependent ◽  
Geothermal Heat ◽  
Diffusive Time

A dimensionless model of thermo-mechanically coupled ice sheets is used to analyse the operation of the system. Three thermal processes are identified: (i) dissipation, having a maximum time-scale of thousands of years; (ii) advection, having a time-scale of tens of thousands of years; and (iii) conduction, having a time-scale of 100000 years. Kinematical processes occur on two time-scales: (i) a marginal advective time-scale of thousands of years; and (ii) a diffusive time-scale of tens of thousands of years dominant in the divide area.The coupling with the temperature field in the bed produces fluctuations to the depth of a few kilometres, which means that horizontal conduction in the bed can be ignored except perhaps in the marginal area. The thermal inertia of the bed could produce significant fluctuations in the geothermal heat gradient.The operation of the thermo-mechanically coupled system is explored with a time-dependent thermo-mechanically coupled numerical algorithm. Dependence of the basal friction on temperature is introduced heuristically, and an enthalpy method is used to represent the effect of latent heat. The marginal area is shown to be dissipation-driven, and always reaches melting point. The divide area can show two modes of behaviour: a warm-based mode where the ice sheet is thin, and a cold-based mode where the ice sheet is thick. Which mode operates depends upon the applied temperature field and the amount of heat conducted from the bed.Calculations where sliding is limited were not found to be possible owing to problems with the reduced model which resulted in a violation of the approximation conditions at the margin. Cases which did work required a substantial sliding component; as a result, a significant coupling between geometry and temperature can only be demonstrated when sliding is made temperature-dependent.

Multivariate Time Series Link Prediction for Evolving Heterogeneous Network

2019 ◽  
Vol 18 (01) ◽  
pp. 241-286 ◽  
Author(s):  
Alper Ozcan ◽  
Sule Gunduz Oguducu
Keyword(s):  
Time Series ◽  
Real World ◽  
Link Prediction ◽  
Multivariate Time Series ◽  
Similarity Measures ◽  
Dynamic Structure ◽  
Social Bookmarking ◽  
Node Connectivity ◽  
Worldwide Web ◽  
Heterogeneous Social Networks

Link prediction is considered as one of the key tasks in various data mining applications for recommendation systems, bioinformatics, security and worldwide web. The majority of previous works in link prediction mainly focus on the homogeneous networks which only consider one type of node and link. However, real-world networks have heterogeneous interactions and complicated dynamic structure, which make link prediction a more challenging task. In this paper, we have studied the problem of link prediction in the dynamic, undirected, weighted/unweighted, heterogeneous social networks which are composed of multiple types of nodes and links that change over time. We propose a novel method, called Multivariate Time Series Link Prediction for evolving heterogeneous networks that incorporate (1) temporal evolution of the network; (2) correlations between link evolution and multi-typed relationships; (3) local and global similarity measures; and (4) node connectivity information. Our proposed method and the previously proposed time series methods are evaluated experimentally on a real-world bibliographic network (DBLP) and a social bookmarking network (Delicious). Experimental results show that the proposed method outperforms the previous methods in terms of AUC measures in different test cases.

An Investigation of Droplet Diffusion in Isotropic Turbulence With Digital Holographic PIV

Volume 3 ◽  
2004 ◽  
Author(s):  
Edwin Malkiel ◽  
Jian Sheng ◽  
David Garber ◽  
Joseph Katz
Keyword(s):  
Time Series ◽  
Isotropic Turbulence ◽  
Diffusion Rate ◽  
Density Ratio ◽  
Digital Camera ◽  
Stokes Number ◽  
Sample Volume ◽  
Tracer Particles ◽  
Fluid Velocities ◽  
Digital Holograms

In-line digital holography is utilized to measure the Lagrangian trajectory of droplets in locally isotropic turbulence. The objective of these measurements is to determine the diffusion rate of these droplets as a function of density ratio between the continuous and dispersed phases, Stokes number and turbulence level relative to the quiescent settling/rise velocity of the droplets. The present experiments are conducted using diesel fuel with diameters of 0.5–2 mm, specific gravity of 0.85 and Stokes number in the 0.2 to 5 range. The droplets are injected into a 50 × 50 × 50 mm sample volume located in the center of a 160 1 tank. The turbulence is generated by four spinning grids, located symmetrically in the corners of the tank. Planar PIV has been used to characterize the turbulence prior to the experiments. A time series of in-line digital holograms is recorded at 2000 frames per second using a 1000×1000 pixel digital camera by back illuminating the sample volume with a collimated laser beam. Numerical reconstruction generates a time series of high-resolution images of the droplets and tracer particles throughout the sample volume. Subsequent analysis is used to obtain the velocity along the droplet trajectory. Lagrangian correlations can then be used for calculating the diffusion rate of these droplets. In a smaller sample volume, with a 15×15 mm cross section, and by using localized seeding, we can also simultaneously measure the droplet velocity along with the velocity of the fluid in the vicinity of this droplet. The results provide statistics on the correlations between the droplet and fluid velocities.

An innovative model to quantify corneal transparency in donor corneal buttons

2017 ◽  
Vol 6 (6) ◽  
pp. 202-205
Author(s):  
Jeyanth Rose ◽  
Syrpailyne Wankhar ◽  
Aarwin Joshua ◽  
Sanita Korah ◽  
Thomas Kuriakose
Keyword(s):  
Anterior Chamber ◽  
Digital Camera ◽  
Laser Source ◽  
Corneal Transplant ◽  
Human Cornea ◽  
Proof Of Concept ◽  
Pixel Intensity ◽  
Corneal Transparency ◽  
Average Pixel Intensity ◽  
Corneal Button

Assessment of corneal transparency in donor corneal buttons has only been performed qualitatively. The quantification of corneal transparency has implications with respect to clinical suitability of the donor cornea and research involving corneal transparency as an outcome measure. In this study an artificial anterior chamber was modified to create a central transparent passage. This was made possible by replacing the base of the chamber with Perspex and a water  tight seal. An inlet and outlet tube was a ached to the sides of chamber. This was done to maintain a standardized pressure within the chamber when connected to an IV bo le. A corneal button rejected for corneal transplant was placed on the artificial anterior chamber and the chamber was  filled with normal saline. A digital camera and a laser source were placed on either side of the chamber at predetermined intervals. Alignment was achieved so that the laser light passed through the center of the cornea. The image of the laser spot was acquired and subjected to image analysis. To test this proof of concept, a human cornea rejected for human transplant was injected with intrastromal saline to create corneal haze. Pre and Post injection images were analyzed. The average pixel intensity that was calculated was found to be 111 pre-saline injury and 17.2 post-saline injection. Pre and Post-saline measurement showed a marked difference in average pixel intensity. This simple inexpensive setup and ease of analysis are advantages of this method of quantification.

Effect of Accelerating Convergence in Adjoining 1D Domains Having Large Difference in Thermal Time Scales

2021 ◽  
Author(s):  
Tanvi Kaushik ◽  
Liangyu Wang ◽  
Jaydeep Basani ◽  
Fang Xu
Keyword(s):  
Temperature Field ◽  
Time Scales ◽  
Spatial Scales ◽  
Thermal Inertia ◽  
Navier Stokes ◽  
Time Step ◽  
Eddy Simulation ◽  
Acceleration Techniques ◽  
Implementation Methodology ◽  
Combustor Liner

Abstract Combustor liners are subjected to high operating temperatures and high temperature gradients, which have an adverse effect on the durability of liners. Accurate prediction of liner wall temperature distribution can provide better insight into the design of effective cooling systems that have the potential to improve liner structure life. When compared to RANS (Reynolds averaged Navier Stokes), LES (Large eddy simulation) framework provides better accuracy in resolving the large range of temporal and spatial scales of turbulent flow inside combustors. In simulations in which an unsteady LES fluid solver is interacting with an unsteady solid thermal solver, it would be impractical to advance and synchronize fluid and solid domains in physical time, due to a large difference between small fluid time scales set by turbulence and large solid time scales set by the thermal inertia of the solid. By advancing the fluid and solid solvers with different time step sizes, or by loosely coupling fluid and solid solvers such that they communicate at a defined frequency, convergence can be artificially accelerated. The convergence of the predicted temperature field solution is dependent on the implementation methodology of the acceleration techniques. A combustor liner is subjected to hot turbulent gases on one side of its boundary and relatively colder air on the other side. This scenario is analyzed to understand the effect of accelerating convergence on the temperature field in a simplified 1D linear framework. A representative polychromatic temperature wave that a combustor liner is subjected to, is used in defining the boundary condition of a 1D implicit unsteady heat conduction solver.

Dynamic Simulation of Road Vehicle Performance Under Transient Accelerating Conditions

1996 ◽  
Vol 210 (1) ◽  
pp. 11-21 ◽  
Author(s):  
C-W Hong
Keyword(s):  
Steady State ◽  
Dynamic Simulation ◽  
Thermal Inertia ◽  
Engine Performance ◽  
Reconstruction Method ◽  
Passenger Cars ◽  
Road Vehicle ◽  
Vehicle Performance ◽  
Inertia Effects ◽  
Engine Model

A personal computer-based simulation package has been developed to design the powertrain system of passenger cars aiming to operate at optimal performance. This package is capable of dynamic simulation of road vehicle performance under transient accelerating conditions. Two methods are included: one is the traditional transient-reconstruction method using steady-state engine performance maps; the other is a dynamic simulation technique newly developed by the author. The latter is described in this paper. It is based on cyclic analysis of the engine thermofluid-combustion phenomena with additional considerations of flow inertia, thermal inertia and mechanical inertia effects. This transient engine model plus a dynamic powertrain model and a transient road-load simulation make it possible to predict the automobile performance under road-driving conditions. Two examples of transient performance prediction, including a sudden full-throttle acceleration at a fixed gear and a changing-gear starting acceleration from standstill, are demonstrated in this paper. These examples show that the relation between the engine speed and the road speed under accelerating conditions is very different to the steady-state relationships normally assumed.

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