Over-Temperature Forecasts on Electronic Packages Through a Transient R–C Model

1999 ◽  
Vol 122 (1) ◽  
pp. 42-47
Author(s):  
Ben-Je Lwo ◽  
Kun-Fu Tseng ◽  
Ching-Hsing Kao ◽  
Luke Su Lu
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Real Time ◽  
Electronic Packaging ◽  
Input Power ◽  
Electronic Packages ◽  
Temperature Prediction ◽  
Steady State Temperature ◽  
New Methodologies ◽  
Capacitance Model

Based on experimental data, a simple R–C (thermal resistance–heat capacitance) model with software precaution strategies are proposed in this paper to predict the steady-state temperature of the circuit in an electronic packaging in real time. Further developments on the new methodology lead to real time monitoring if input power and/or the environment are changing during operations. It is concluded that the new methodologies, which make the over-temperature prediction much more reliable, efficient, sensible, and faster, can be easily employed for over-temperature protection designs on electronic packaging. [S1043-7398(00)00301-7]

scholarly journals Numerical prediction of steady state temperature based on transient measurements

2018 ◽  
Vol 240 ◽  
pp. 05024
Author(s):  
Ewa Pelińska-Olko ◽  
Marek Lewkowicz
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Heat Exchange ◽  
Time Range ◽  
Radiative Heat Exchange ◽  
Steady State Temperature ◽  
Long Time ◽  
Experimental Values ◽  
Short Time ◽  
Transient Measurements

We show how to use numerical analysis of short-time range experimental data for predicting the limit steady-state value of the investigated parameter. In this article the approach has been applied to a specific, although typical, thermal problem: determining the average steady-state temperature of a heater in the convective and radiative heat exchange with the environment. First, we describe a heat exchange experiment aimed at obtaining temperature experimental data in both short and long time range. Then we present a methodology for applying two methods, i.e., neural networks and least squares approximations, for obtaining predictions about the steady-state temperature values based on short time experimental data. The aim of the study is to compare the predictions to each other and to the long time experimental values, with the aim of determining the applicability range of the two methods.

Combination of a Nonlinear Static and a Linear Dynamic Model of the NETL HyPer System

2010 ◽  
Author(s):  
Bernardo Restrepo ◽  
Larry E. Banta ◽  
Alex J. Tsai ◽  
David Tucker
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Fuel Cell ◽  
Control Systems ◽  
Real Time ◽  
Gas Turbine ◽  
Transfer Functions ◽  
State Variables ◽  
Linear Dynamic ◽  
Wide Range

A nonlinear steady-state thermodynamic model was coupled with linearized dynamic transfer functions to achieve a dynamic description of the NETL HyPer Fuel Cell Gas Turbine (FC/GT) power plant. Nonlinear dynamic models insure accuracy in modeling steady-state behavior over a wide range of operation, but such models are often complex and difficult to implement in real-time using conventional control systems equipment. Conversely, the linearized models provide the ability to predict transient behavior upon which dynamic control systems can be constructed, but are valid only about a narrow operating point. In systems with one or two state variables, it is relatively straightforward to construct controllers that use gain scheduling schemes. But the HyPer system contains many coupled state variables and high degrees of nonlinearity. A method called Real-Time Piecewise Linear Dynamic Modeling (RPLDM) has been implemented to provide both modeling accuracy and real-time performance for the HyPer system over a multi-dimensional hypersurface. Both the nonlinear and the linear constituent models were constructed based on experimental data collected in tests performed on the HyPer system. The models presently consider only the cathode circuit of the fuel cell and contain a recuperated gas turbine system equipped with an electric generator, a simulated fuel cell cathode and various bypass valves for thermal management and system control. The key variables of air temperature, air pressure and mass flow to the cathode of the fuel cell and the turbomachinery have been predicted to within 2% of measured values. This paper presents the modeling technique and comparisons of the model output with experimental data.

Steady-State Tilting-Pad Bearing Performance Under Reduced Oil Supply Flow Rates

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Bradley R. Nichols ◽  
Roger L. Fittro ◽  
Christopher P. Goyne
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Flow Rate ◽  
Flow Model ◽  
Leading Edge ◽  
Input Power ◽  
Flow Rates ◽  
Flow Models ◽  
Oil Supply ◽  
Tilting Pad

Reduced oil supply flow rates in fluid film bearings can cause cavitation, or lack of a fully developed hydrodynamic film layer, at the leading edge of the bearing pads. Reduced oil flow has the well-documented effects of higher bearing operating temperatures and decreased power losses and is commonly referred to as starvation. This study looks at the effects of oil supply flow rate on steady-state bearing performance and provides increased experimental data for comparison to computational predictions. Tests are conducted on a five-pad tilting-pad bearing positioned in a vintage, flooded housing with oil supply nozzles. Pad temperatures, sump temperature, journal operating position, and motor input power are measured at various operating speeds ranging from 2000 to 12,000 rpm and various oil supply flow rates. Predicted results are obtained from bearing modeling software based on thermoelastohydrodynamic (TEHD) lubrication theory. A starved flow model was previously developed as an improvement over the original flooded flow model to more accurately capture bearing behavior under reduced flow conditions. Experimental results are compared to both flow models. The starved bearing model predicts significantly higher journal operating positions than the flooded model and shows good correlation with the experimental data. Predicted pressure profiles from the starved bearing model show cavitation of the upper unloaded pads that increase in severity with increasing speed and decreasing oil supply flow rate. The progressive unloading of these top pads explains the rise in shaft centerline position and helps further validate the starvation model.

scholarly journals Practical steady-state temperature prediction of active embedded chips into high density electronic board

2016 ◽  
Vol 745 ◽  
pp. 032095 ◽  
Author(s):  
Eric Monier-Vinard ◽  
Brice Rogie ◽  
Nhat-Minh Nguyen ◽  
Najib Laraqi ◽  
Valentin Bissuel ◽  
...  
Keyword(s):  
Steady State ◽  
High Density ◽  
Temperature Prediction ◽  
Steady State Temperature ◽  
Electronic Board ◽  
Embedded Chips

Multi-Component Liquid Analyzer During Steady-State and Dynamic CO2 Capture Operations: Near Real-Time Feedback in Industrialized Environment

2019 ◽  
Author(s):  
Chuck Panaccione ◽  
Greg Staab ◽  
Andy Awtry ◽  
Rene Kupfer ◽  
Tyler Silverman ◽  
...  
Keyword(s):  
Steady State ◽  
Real Time ◽  
Co2 Capture

Kinetic analysis of mechanism of intestinal Na+-dependent sugar transport

1985 ◽  
Vol 248 (5) ◽  
pp. C498-C509 ◽  
Author(s):  
D. Restrepo ◽  
G. A. Kimmich
Keyword(s):  
Experimental Data ◽  
Steady State ◽  
Sugar Transport ◽  
Enzyme Kinetic ◽  
Steady State Distribution ◽  
State Distribution ◽  
Least Squares Fit ◽  
Coupling Stoichiometry ◽  
Rate Limiting ◽  
Kinetics Of

Zero-trans kinetics of Na+-sugar cotransport were investigated. Sugar influx was measured at various sodium and sugar concentrations in K+-loaded cells treated with rotenone and valinomycin. Sugar influx follows Michaelis-Menten kinetics as a function of sugar concentration but not as a function of Na+ concentration. Nine models with 1:1 or 2:1 sodium:sugar stoichiometry were considered. The flux equations for these models were solved assuming steady-state distribution of carrier forms and that translocation across the membrane is rate limiting. Classical enzyme kinetic methods and a least-squares fit of flux equations to the experimental data were used to assess the fit of the different models. Four models can be discarded on this basis. Of the remaining models, we discard two on the basis of the trans sodium dependence and the coupling stoichiometry [G. A. Kimmich and J. Randles, Am. J. Physiol. 247 (Cell Physiol. 16): C74-C82, 1984]. The remaining models are terter ordered mechanisms with sodium debinding first at the trans side. If transfer across the membrane is rate limiting, the binding order can be determined to be sodium:sugar:sodium.

scholarly journals A Study of Developing a Prediction Equation of Electricity Energy Output via Photovoltaic Modules

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1503
Author(s):  
Minsu Kim ◽  
Hongmyeong Kim ◽  
Jae Hak Jung
Keyword(s):  
Experimental Data ◽  
Real Time ◽  
Air Temperature ◽  
Temperature Difference ◽  
Prediction Accuracy ◽  
Prediction Equation ◽  
Energy Output ◽  
Photovoltaic Modules ◽  
Mean Error ◽  
Pv Module

Various equations are being developed and applied to predict photovoltaic (PV) module generation. Currently, quite diverse methods for predicting module generation are available, with most equations showing accuracy with ≤5% error. However, the accuracy can be determined only when the module temperature and the value of irradiation that reaches the module surface are precisely known. The prediction accuracy of outdoor generation is actually extremely low, as the method for predicting outdoor module temperature has extremely low accuracy. The change in module temperature cannot be predicted accurately because of the real-time change of irradiation and air temperature outdoors. Calculations using conventional equations from other studies show a mean error of temperature difference of 4.23 °C. In this study, an equation was developed and verified that can predict the precise module temperature up to 1.64 °C, based on the experimental data obtained after installing an actual outdoor module.

scholarly journals Identification of DC Thermal Steady-State Differential Inductance of Ferrite Power Inductors

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3854
Author(s):  
Salvatore Musumeci ◽  
Luigi Solimene ◽  
Carlo Stefano Ragusa
Keyword(s):  
Steady State ◽  
Input Voltage ◽  
Switching Frequency ◽  
Ohmic Losses ◽  
Steady State Temperature ◽  
Wide Range ◽  
Average Current ◽  
Power Inductors ◽  
Saturable Inductor ◽  
Thermal Steady State

In this paper, we propose a method for the identification of the differential inductance of saturable ferrite inductors adopted in DC–DC converters, considering the influence of the operating temperature. The inductor temperature rise is caused mainly by its losses, neglecting the heating contribution by the other components forming the converter layout. When the ohmic losses caused by the average current represent the principal portion of the inductor power losses, the steady-state temperature of the component can be related to the average current value. Under this assumption, usual for saturable inductors in DC–DC converters, the presented experimental setup and characterization method allow identifying a DC thermal steady-state differential inductance profile of a ferrite inductor. The curve is obtained from experimental measurements of the inductor voltage and current waveforms, at different average current values, that lead the component to operate from the linear region of the magnetization curve up to the saturation. The obtained inductance profile can be adopted to simulate the current waveform of a saturable inductor in a DC–DC converter, providing accurate results under a wide range of switching frequency, input voltage, duty cycle, and output current values.

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