scholarly journals INTRINSIC PARAMETERS OF DRY CHOPPED MISCANTHUS FOR COLD PARTICLE DYNAMIC MODELING

2020 ◽  
Vol 82 (5) ◽  
Author(s):  
Pasymi ◽  
Yogi Wibisono Budhi ◽  
Yazid Bindar
Keyword(s):  
Dynamic Modeling ◽  
Average Energy ◽  
Particle Dynamics ◽  
Particle Dynamic ◽  
Cylinder Wall ◽  
Intrinsic Parameter ◽  
Furnace Design ◽  
Intrinsic Parameters ◽  
Parameter Values ◽  
Tangential Inlet

Miscanthus is a bioenergy crop that is very easy to cultivate. It has high volatile content with an average energy value of about 18.8 MJ/kg on a dry basis. With the benefits mentioned above, Miscanthus is potential as a fuel for the suspended furnace. Therefore, the furnace design for the Miscanthus particle needs to be developed immediately. A relatively fast and low-cost technique to develop a burner furnace design is the modeling. This study aims to determine the intrinsic parameter values of dry Miscanthus particles needed in cold particle dynamic modeling. The various reasonable experimental techniques were used to obtain these parameter’s values. Then, a series of simulations and experiments of dry chopped Miscanthus dynamic in a special burner was conducted to assess the conformity of these values. The intrinsic parameters values of dry chopped Miscanthus obtained are as follows; shape factor (fs) 0.52, true particle density (ρp) 245 kg m-3, minimum, maximum, and mean particle diameters (dp) 106, 9520, and 1384 µm respectively, and spread parameter (n) 1.22. Qualitatively, the particle dynamic simulation results, using RSM and k-e models, showed similar particle pathlines to the experiment results, in terms of the frequency and intersection of the helical structure formed in the burner cylinder. It indicates that the intrinsic parameter values obtained in this study are reliable results and can be used for further simulation works. In addition, particle dynamics experiments and simulations also revealed that the particle pathline in the burner cylinder tend to move near the cylinder wall in a helical pattern; a single helix pattern in a single tangential inlet burner and a double helix pattern in a double tangential inlets burner. Regardless of the effect of the tangential inlet number, the helical pattern in the burner cylinder was also influenced by the initial swirl number (ISN) of the flow. The lower the ISN, the lower the helical frequency formed and vice versa. This study also proved that at low to moderate swirl intensities, the k-e turbulent model can be relied upon to model particle dynamics in a cyclone burner.

Optimization of fast imaging protocols over a domain of intrinsic parameter values

1987 ◽  
Vol 5 (6) ◽  
pp. 527-528
Author(s):  
Elliot R. McVeigh ◽  
Michael J. Bronskill ◽  
R.Mark Henkelman
Keyword(s):  
Fast Imaging ◽  
Intrinsic Parameter ◽  
Imaging Protocols ◽  
Parameter Values

TURBULENT DIFFUSION OF TEST PARTICLES IN STRONGLY MAGNETIZED PLASMAS

1991 ◽  
Vol 05 (08) ◽  
pp. 1243-1262 ◽  
Author(s):  
MAURIZIO OTTAVIANI ◽  
MARCO PETTINI
Keyword(s):  
Electric Field ◽  
Equations Of Motion ◽  
Charged Particles ◽  
Mean Square Displacement ◽  
Wave Model ◽  
Particle Dynamics ◽  
Suitable Parameter ◽  
Test Particles ◽  
The Mean ◽  
Parameter Values

The motion of charged particles is described in the presence of a strong magnetic field and of an electric field made of three spatial Fourier modes whose amplitudes vary in time. The dynamics of the wave amplitudes is governed by a model of three interacting drift waves. For suitable parameter values of the three-wave model, chaotic solutions are found so that the Eulerian electric field is made of three turbulent modes. The E × B motion is described for charged particles in the guiding center approximation, which brings to nonlinear Hamiltonian equations of motion. The Hamiltonian (that coincides with the electric potential) is explicitly time-dependent through the temporal variation of the mode-amplitudes of the electric field, this fact is at the origin of the intrinsic chaoticity of particle dynamics (lagrangian chaos). Diffusive behaviour of particle trajectories is due to their intrinsic chaoticity and thus it is of non-collisional origin. Some results are reported concerning the particle dynamics when the Eulerian electric field is either quasi-periodically or chaotically varying in time. In particular, one finds different diffusion laws in the two cases (anomalous and classical respectively). The scaling behaviour of the diffusion coefficients (when the mean square displacement grows linearly in time) is reported. A simple stochastic model is also used to account for some of the observed features of particle diffusion.

scholarly journals An Intrinsic Parameter Calibration Method for R-LAT System Based on CMM

2021 ◽  
Author(s):  
Wenjun Su ◽  
Junkang Guo ◽  
Zhigang Liu ◽  
Kang Jia
Keyword(s):  
Large Scale ◽  
Mathematic Model ◽  
Calibration Method ◽  
Initial Guess ◽  
Least Square ◽  
Target Point ◽  
Parameter Calibration ◽  
Intrinsic Parameter ◽  
Intrinsic Parameters ◽  
Equation Group

Abstract Rotary-laser automatic theodolite (R-LAT) system is a distributed large-scale metrology system, which provides parallel measurement in scalable measurement room without obvious precision losing. Each of R-LAT emits two nonparallel laser planes to scan the measurement space via evenly rotation, while the photoelectric sensors receive these laser planes signals and performs the coordinate calculation based on triangulation. The accurate geometric parameters of the two laser planes plays a crucial role in maintaining the measurement precision of R-LAT system. Practically, the geometry of the two laser plane, which is termed as intrinsic parameters, is unknown after assembled. Therefore, how to figure out the accurate intrinsic parameters of each R-LAT is a fundamental question for the application of R-LAT system. This paper proposed an easily operated intrinsic parameter calibration method for R-LAT system with adopting coordinate measurement machine. The mathematic model of laser planes and the observing equation group of R-LAT are established. Then, the intrinsic calibration is formulated as a nonlinear least square problem that minimize the sum of deviations of target points and laser planes, and the ascertain of its initial guess is introduced. At last, experience is performed to verify the effectiveness of this method, and simulations are carried out to investigate the influence of the target point configuration on the accuracy of intrinsic parameters.

Experimental modelling of single-particle dynamic processes in crystallization by controlled colloidal assembly

2014 ◽  
Vol 43 (7) ◽  
pp. 2324-2347 ◽  
Author(s):  
Tian Hui Zhang ◽  
Xiang Yang Liu
Keyword(s):  
Single Particle ◽  
Particle Dynamics ◽  
Experimental Modeling ◽  
Dynamic Processes ◽  
Particle Dynamic ◽  
Comprehensive Review ◽  
Experimental Modelling ◽  
Colloidal Assembly

A comprehensive review of the experimental modeling of single particle dynamics in crystallization is presented.

scholarly journals Dynamic Modeling, Parameter Estimation and Uncertainty Analysis in 𝗥

2016 ◽  
Author(s):  
Daniel Kaschek ◽  
Wolfgang Mader ◽  
Mirjam Fehling-Kaschek ◽  
Marcus Rosenblatt ◽  
Jens Timmer
Keyword(s):  
Inverse Problem ◽  
Parameter Estimation ◽  
Uncertainty Analysis ◽  
Dynamic Modeling ◽  
Dynamic Models ◽  
R Package ◽  
Automatic Generation ◽  
Point Of View ◽  
Set Up ◽  
Parameter Values

AbstractIn a wide variety of research elds, dynamic modeling is employed as an instrument to learn and understand complex systems. The differential equations involved in this process are usually non-linear and depend on many parameters whose values decide upon the characteristics of the emergent system. The inverse problem, i.e. the inference or estimation of parameter values from observed data, is of interest from two points of view. First, the existence point of view, dealing with the question whether the system is able to reproduce the observed dynamics for any parameter values. Second, the identi ability point of view, investigating invariance of the prediction under change of parameter values, as well as the quanti cation of parameter uncertainty.In this paper, we present the R packagedModproviding a framework for dealing with the inverse problem in dynamic systems. The particularity of the approach taken bydModis to provide and propagate accurate derivatives computed from symbolic expres-sions wherever possible. This derivative information highly supports the convergence of optimization routines and enhances their numerical stability, a requirement for the appli-cability of so sticated uncertainty analysis methods. Computational efficiency is achieved by automatic generation and execution of C code. The framework is object oriented (S3) and provides a variety of functions to set up dynamic models, observation functions and parameter transformations for multi-conditional parameter estimation.The key elements of the framework and the methodology implemented indModare highlighted by an application on a three-compartment transporter model.

Kinematic-Dynamic Modeling and Test Control of Tracked Drive Vehicle for Indoor Mapping

2011 ◽  
Vol 148-149 ◽  
pp. 1510-1513
Author(s):  
Hasnan Bin Khalid ◽  
Budi Saesar Luhur
Keyword(s):  
Dynamic Modeling ◽  
Control Architecture ◽  
Unmanned Ground Vehicle ◽  
Telemetry Data ◽  
Ground Vehicle ◽  
Sensor Actuator ◽  
Time Simulation ◽  
Real Performance ◽  
Parameter Values ◽  
Test Control

This paper presents one approach in designing and testing an unmanned ground vehicle (UGV) for indoor mapping. The approach makes use of computer real-time simulation and animation direct with the testing in real environment. Novel control architecture was proposed, by exploit the communication between two laptop installed Matlab/Simulink and telemetry data collected from it. The parameter values between real performance and model can be easily evaluated and also from its ladar scanning result, then researcher can explore more variation of modeling aspect, parameter and sensor-actuator configuration to enhance performance of their indoor unmanned vehicle

Optimal algorithm for distinguishing radio navigation signals by a set of “spaced” correlators

2021 ◽  
Vol 8 ◽  
pp. 11-23
Author(s):  
V.N. Kharisov ◽  
D.A. Eremeev
Keyword(s):  
Parameter Estimation ◽  
Noise Immunity ◽  
Optimal Algorithm ◽  
Average Energy ◽  
Large Signal ◽  
Energy Potential ◽  
True Parameter ◽  
Discrete Parameter ◽  
Classical Algorithm ◽  
Parameter Values

The classical algorithm for signal distinction, signal detecting and estimating signal parameters consists in analyzing discrete parameter values using a correlator. The value of the parameter with the maximum absolute value of the correlator is taken as an estimate. Obviously, this is accompanied by losses in sensitivity and noise immunity, since the specified discrete parameter values do not accurately correspond to the true parameter values of the real signal. In this case, the accuracy of the parameter estimation, even at large signal-to-noise ratios, is limited by the value of the correlators placement interval. Therefore, it is of interest to optimally use the entire set of correlators for parameter estimation and signal detection. The article presents the derivation of algorithm for distinguishing signals by a given parameter by a set of "spaced" correlators. Unlike the classical algorithm, it uses decisive statistics not by one, but by a pair of neighboring correlators, detuned by the correlation interval. In this case, at first, the number of the interval between correlators is estimated according to the maximum of the decisive statistics, and then the value of the parameter is refined within this interval. Additionally, the algorithm allows you to estimate the signal amplitude. The proposed algorithm is compared with the classical one. By means of simulation, the dependences on the energy potential of the average probability of signal distinction for both algorithms are plotted. It is shown that the proposed algorithm has a higher probability of correct distinction than the classical algorithm. It is also shown that the maximum and average energy losses of the distinction algorithm based on a set of "spaced" correlators are less than the losses of the classical algorithm. Thus, the proposed algorithm for distinction signals by a set of "spaced" correlators has greater noise immunity and accuracy of estimating the desired parameter than the classical distinction algorithm.

Coarse-Graining of a Fluid and its Relation with Dissipative Particle Dynamics and Smoothed Particle Dynamic

1997 ◽  
Vol 08 (04) ◽  
pp. 899-908 ◽  
Author(s):  
Pep Español ◽  
Mar Serrano ◽  
Ignacio Zuñiga
Keyword(s):  
Weight Function ◽  
Physical Meaning ◽  
Dissipative Particle Dynamics ◽  
Coarse Graining ◽  
Particle Dynamics ◽  
Point Of View ◽  
Particle Dynamic ◽  
Fluid System ◽  
Close Analogy ◽  
Smoothed Particle

We propose a coarse-graining procedure for a fluid system that allows us to discuss from a conceptual point of view different "mesoscopic" approaches to hydrodynamic problems. Dissipative Particle Dynamics (DPD) and Smoothed Particle Dynamics (SPS) are discussed simultaneously within this framework. In particular, we give physical meaning to the weight function used in SPD. The close analogy between DPD and SPD suggests a synthesis of both approaches that overcomes the conceptual shortcomings of both.

scholarly journals VALIDATION OF LIDAR CALIBRATION USING A LIDAR SIMULATOR

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 39-44
Author(s):  
G. Lee ◽  
J. Cheon ◽  
I. Lee
Keyword(s):  
Lidar Measurement ◽  
Intrinsic Parameter ◽  
Geometric Information ◽  
Simulation Data ◽  
Scanning Method ◽  
Intrinsic Parameters ◽  
Estimated Parameters ◽  
Surrounding Environment ◽  
Extrinsic Parameters ◽  
Lidar Calibration

Abstract. LIDAR is being widely used for mapping and modelling because it accurately scans and acquires 3D geometric information of the surrounding environment. In order to improve the accuracy of the LIDAR measurement, it is necessary to precisely estimate the intrinsic parameters as well as extrinsic parameters and eliminate the systematic errors. Many studies are conducted to eliminate these errors caused by the intrinsic parameters of LIDAR. However, when the result of intrinsic calibration is verified using actual LIDAR data, there is a problem that other error factors cannot be excluded. Therefore, in this study, the LIDAR intrinsic calibration is verified by using a LIDAR simulator that simulates the mechanism of the actual LIDAR. When constructing a LIDAR simulator, the systematic error is inserted according to the intrinsic parameter model of LIDAR. And according to the method of scanning with LIDAR, it is divided into upright scanning and tilted scanning, and the error included LIDAR simulation data is generated. After that, the intrinsic parameters are estimated by applying the plane-based intrinsic calibration. Since values of the intrinsic parameters are known, they are compared with the estimated parameters, and the results of estimate are analyzed according to the scanning method.

Stopping-power determination for compound by EELS

1994 ◽  
Vol 52 ◽  
pp. 948-949 ◽  
Author(s):  
David C. Joy ◽  
Suichu Luo ◽  
John R. Dunlap ◽  
Dick Williams ◽  
Siqi Cao
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Materials Science ◽  
Average Energy ◽  
Stopping Power ◽  
Accurate Information ◽  
Power Calculation ◽  
Coulomb Collisions ◽  
Electron Energy Loss

In Physics, Chemistry, Materials Science, Biology and Medicine, it is very important to have accurate information about the stopping power of various media for electrons, that is the average energy loss per unit pathlength due to inelastic Coulomb collisions with atomic electrons of the specimen along their trajectories. Techniques such as photoemission spectroscopy, Auger electron spectroscopy, and electron energy loss spectroscopy have been used in the measurements of electron-solid interaction. In this paper we present a comprehensive technique which combines experimental and theoretical work to determine the electron stopping power for various materials by electron energy loss spectroscopy (EELS ). As an example, we measured stopping power for Si, C, and their compound SiC. The method, results and discussion are described briefly as below.The stopping power calculation is based on the modified Bethe formula at low energy:where Neff and Ieff are the effective values of the mean ionization potential, and the number of electrons participating in the process respectively. Neff and Ieff can be obtained from the sum rule relations as we discussed before3 using the energy loss function Im(−1/ε).

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