Study on Model Parameters of Focal Cooling Device Using a Peltier Element for a Living Body

2016 ◽  
Author(s):  
Kenyu Uehara ◽  
Kentaro Miyago ◽  
Koji Mori ◽  
Takashi Saito
Keyword(s):  
Control Function ◽  
Internal Resistance ◽  
Model Parameters ◽  
Cooling Device ◽  
Peltier Element ◽  
Cooling Performance ◽  
Living Body ◽  
Dependent Relation ◽  
Focal Cooling ◽  
Parameter Values

Cooling treatment is known as one of the effective treatment for injury. It has an optimum cooling temperature level depending on a symptom or an injury. Hence a highly precise temperature control function is required for a cooling device for this kind of treatment. A mathematical model of cooling device using a Peltier element is necessary to realize its functions. In this paper, we examined the characteristics of model parameters by identification experimentally and comparison of its values. Three cooling devices (A, B and C) were used. A Peltier element of device A and device B were the same size with different cooling performance respectively. Whereas a Peltier element of device C was bigger than the two devices. Effects of devices size and cooling performance on the model parameters were investigated. It is shown that most of the parameter values were increased in the device C. The Seebeck coefficient and the internal resistance had little dependent relation with the device size while the other heat conductances were strongly dependence upon the size. From these results, the characteristics of each parameters became mostly evident by comparison of three devices of different sizes and cooling performances. However, it is required to analyze more and utilize different devices to carry out the development of cooling device by using this model.

1003 Study on Parameter Identification of the Focal Cooling Device for a Living Body

2016 ◽  
Vol 2016.54 (0) ◽  
pp. _1003-1_-_1003-2_
Author(s):  
Kenyu UEHARA ◽  
Kentaro MIYAGO ◽  
Koji MORI ◽  
Takashi SAITO
Keyword(s):  
Parameter Identification ◽  
Cooling Device ◽  
Living Body ◽  
Focal Cooling

Investigation on Temperature Control Model of the Focal Cooling Human Physiological System

2015 ◽  
Author(s):  
Kenyu Uehara ◽  
Yasumi Ukida ◽  
Takahiro Murakami ◽  
Koji Mori ◽  
Takashi Saito
Keyword(s):  
Temperature Control ◽  
Cooling System ◽  
Temperature Response ◽  
Input Voltage ◽  
Parameters Identification ◽  
Control Surface ◽  
Model Parameters ◽  
Cooling Device ◽  
Unknown Parameters ◽  
Focal Cooling

For efficient temperature control of the cooling device for medical purposes, accurate modeling of the focal cooling system taking into account the human physiological reaction and nonlinearity of the thermoerectric device, is required. In this paper, we examined about model parameters identification in order to establish a mathematical model for a focal cooling device for a living body using a Peltier device. Cooling experiments applied input constant voltage were performed to identify the model parameters. The temperature response data are obtained for every 0.1V, from 0.1V to 1.8V. As a result of the parameters identification, it was shown that some unknown parameters vary with a certain tendency to the input voltage. As a result of comparison between simulation value using identified parameters and experimental value, it was shown that one can simulate results in the error range of the parameter identification in the control surface.

scholarly journals Assimilation of Dynamic Combined Finite Discrete Element Methods Using the Ensemble Kalman Filter

2021 ◽  
Vol 11 (7) ◽  
pp. 2898
Author(s):  
Humberto C. Godinez ◽  
Esteban Rougier
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Failure Modes ◽  
Split Hopkinson Pressure Bar ◽  
Peak Stress ◽  
Discrete Element ◽  
Material Behavior ◽  
Model Parameters ◽  
Hopkinson Pressure Bar ◽  
Parameter Values

Simulation of fracture initiation, propagation, and arrest is a problem of interest for many applications in the scientific community. There are a number of numerical methods used for this purpose, and among the most widely accepted is the combined finite-discrete element method (FDEM). To model fracture with FDEM, material behavior is described by specifying a combination of elastic properties, strengths (in the normal and tangential directions), and energy dissipated in failure modes I and II, which are modeled by incorporating a parameterized softening curve defining a post-peak stress-displacement relationship unique to each material. In this work, we implement a data assimilation method to estimate key model parameter values with the objective of improving the calibration processes for FDEM fracture simulations. Specifically, we implement the ensemble Kalman filter assimilation method to the Hybrid Optimization Software Suite (HOSS), a FDEM-based code which was developed for the simulation of fracture and fragmentation behavior. We present a set of assimilation experiments to match the numerical results obtained for a Split Hopkinson Pressure Bar (SHPB) model with experimental observations for granite. We achieved this by calibrating a subset of model parameters. The results show a steady convergence of the assimilated parameter values towards observed time/stress curves from the SHPB observations. In particular, both tensile and shear strengths seem to be converging faster than the other parameters considered.

scholarly journals An enhanced set of displacement parameter restraints in CRYSTALS

2018 ◽  
Vol 51 (4) ◽  
pp. 1059-1068 ◽  
Author(s):  
Pascal Parois ◽  
James Arnold ◽  
Richard Cooper
Keyword(s):  
Structural Model ◽  
Rigid Bodies ◽  
Model Parameters ◽  
Coordinate Systems ◽  
Principal Axes ◽  
Anisotropic Displacement Parameters ◽  
Set Up ◽  
Meaningful Relationships ◽  
Parameter Values ◽  
Total Model

Crystallographic restraints are widely used during refinement of small-molecule and macromolecular crystal structures. They can be especially useful for introducing additional observations and information into structure refinements against low-quality or low-resolution data (e.g. data obtained at high pressure) or to retain physically meaningful parameter values in disordered or unstable refinements. However, despite the fact that the anisotropic displacement parameters (ADPs) often constitute more than half of the total model parameters determined in a structure analysis, there are relatively few useful restraints for them, examples being Hirshfeld rigid-bond restraints, direct equivalence of parameters and SHELXL RIGU-type restraints. Conversely, geometric parameters can be subject to a multitude of restraints (e.g. absolute or relative distance, angle, planarity, chiral volume, and geometric similarity). This article presents a series of new ADP restraints implemented in CRYSTALS [Parois, Cooper & Thompson (2015), Chem. Cent. J. 9, 30] to give more control over ADPs by restraining, in a variety of ways, the directions and magnitudes of the principal axes of the ellipsoids in locally defined coordinate systems. The use of these new ADPs results in more realistic models, as well as a better user experience, through restraints that are more efficient and faster to set up. The use of these restraints is recommended to preserve physically meaningful relationships between displacement parameters in a structural model for rigid bodies, rotationally disordered groups and low-completeness data.

scholarly journals The identification of a device based on a Peltier element by the least squares method

2020 ◽  
pp. 17-27
Author(s):  
Vladimir Grinkevich ◽  
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Control Object ◽  
Object Identification ◽  
Model Parameters ◽  
Peltier Element ◽  
Transport Delay ◽  
Non Linear ◽  
The Mathematical Model

The evaluation of the mathematical model parameters of a non-linear object with a transport delay is considered in this paper. A temperature controlled stage based on a Peltier element is an identification object in the paper. Several input signal implementations are applied to the input of the identification object. The least squares method is applied for the calculation of the non-linear differential equitation parameters which describe the identification object. The least squares method is used due to its simplicity and the possibility of identification non-linear objects. The parameters values obtained in the process of identification are provided. The plots of temperature changes in the temperature control system with a controller designed based on the mathematical model of the control object obtained as a result of identification are shown. It is found that the mathematical model obtained in the process of identification may be applied to design controllers for non-linear systems, in particular for a temperature stage based on a Peltier element, and for self-tuning controllers. However, the least square method proposed in the paper cannot estimate the transport delay time. Therefore it is required to evaluate the time delay by temperature transient processes. Dynamic object identification is applied when it is required to obtain a mathematical model structure and evaluate the parameters by an input and output control object signal. Also, identification is applied for auto tuning of controllers. A mathematical model of a control object is required to design the controller which is used to provide the required accuracy and stability of control systems. Peltier elements are applied to design low-power and small- size temperature stage . Hot benches based on a Peltier element can provide the desired temperature above and below ambient temperature.

Combining Non-Parametric and Parametric Models for Stable and Computationally Efficient Battery Health Estimation

2020 ◽  
Author(s):  
Antti Aitio ◽  
David Howey
Keyword(s):  
Latent Variables ◽  
Linear Time ◽  
Full Range ◽  
Real Life ◽  
Internal Resistance ◽  
State Of Charge ◽  
Parametric Models ◽  
Model Parameters ◽  
Battery Management ◽  
Resistance Change

Abstract Equivalent circuit models for batteries are commonly used in electric vehicle battery management systems to estimate state of charge and other important latent variables. They are computationally inexpensive, but suffer from a loss of accuracy over the full range of conditions that may be experienced in real-life. One reason for this is that the model parameters, such as internal resistance, change over the lifetime of the battery due to degradation. However, estimating long term changes is challenging, because parameters also change with state of charge and other variables. To address this, we modelled the internal resistance parameter as a function of state of charge and degradation using a Gaussian process (GP). This was performed computationally efficiently using an algorithm [1] that interprets a GP to be the solution of a linear time-invariant stochastic differential equation. As a result, inference of the posterior distribution of the GP scales as 𝒪(n) and can be implemented recursively using a Kalman filter.

scholarly journals Modelling temperature variations in polar snow using DAISY

1997 ◽  
Vol 43 (143) ◽  
pp. 180-191 ◽  
Author(s):  
Ε. M. Morris ◽  
H. -P. Bader ◽  
P. Weilenmann
Keyword(s):  
Field Experiments ◽  
A Priori ◽  
Model Parameters ◽  
Data Set ◽  
International Geophysical Year ◽  
Snow Model ◽  
Using Data ◽  
Polar Snow ◽  
Parameter Values ◽  
The Antarctic

AbstractA physics-based snow model has been calibrated using data collected at Halley Bay, Antarctica, during the International Geophysical Year. Variations in snow temperature and density are well-simulated using values for the model parameters within the range reported from other polar field experiments. The effect of uncertainty in the parameter values on the accuracy of the predictions is no greater than the effect of instrumental error in the input data. Thus, this model can be used with parameters determined a priori rather than by optimization. The model has been validated using an independent data set from Halley Bay and then used to estimate 10 m temperatures on the Antarctic Peninsula plateau over the last half-century.

Torsional damping of a back-to-back gearbox rig: Experimental measurements and frequency domain modelling

2002 ◽  
Vol 216 (2) ◽  
pp. 157-168 ◽  
Author(s):  
S J Drew ◽  
B J Stone
Keyword(s):  
Frequency Domain ◽  
Natural Frequencies ◽  
Model Parameters ◽  
Modal Damping ◽  
Torsional Damping ◽  
Analysis Of Results ◽  
Torsional Frequency ◽  
Signal Processing Methods ◽  
Parameter Values ◽  
Future Work

This paper is concerned with the experimental measurement and modelling of the torsional damping levels of a back-to-back gearbox rig. The aims of the investigation were to experimentally measure and analyse modal damping levels for the first nine torsional natural frequencies; to optimize damping parameters for modelling and to assess any limitations of the models for future work. Standard signal processing methods were used to determine modal damping levels from measured torsional frequency responses, with good confidence in the results. A damping sensitivity analysis for the two frequency domain receptance (FDR) models was used to determine optimum damping parameter values. Damping levels for six of nine natural frequencies were well matched with the experimental data. Discrepancies at other frequencies were attributed mainly to torsional-transverse coupling, present in the rig but not the model. Analysis of results for the ninth natural frequency determined a very low level of damping for the gearbox. It was also concluded that the model parameters may be used with confidence in a time domain receptance model for future investigations related to the test gearbox damping.

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