Effect of Box Microspring Size on Spring Constant

2008 ◽  
Vol 33-37 ◽  
pp. 975-980
Author(s):  
Cho Chun Wu ◽  
Rong Shun Chen ◽  
Meng Ju Lin
Keyword(s):  
Exponential Decay ◽  
Rate Of Change ◽  
Spring Constant ◽  
Limit Value ◽  
Symmetric Structure ◽  
Constant Rate ◽  
Spring Constants

There are two kinds of microsprings often used: box microsprings and zig-zag (serpentine) microsprings. Box microsprings are considered with larger spring constant k and more symmetric structure keeping balance than zig-zag microspring. Density of spring number, N, is defined as the numbers of turns within a constant total spring length to investigate performance of box microspring. With applying the same force, the relation between spring constants and microspring sizes are discussed. Under different size parameters of box microsprings: B, W, T, and L, the spring constants decrease like exponential decay and approach a limit value as density of spring number increasing. The results show density of spring number has significant effect on spring constant. Rate of change on spring constant, Kt, is defined as the ratio of spring constant between N=1 and N=10. It means normalization of spring constant that increase density of spring number from minimum to maximum. The results show Kt decreases when B and W increase and increase as T and L increasing. Therefore, the spring constant is coupled affected by different size parameters due to different tendency as results shown. Such that the results can apply in microspring design by adjusting these size parameters to obtain the spring constant.

The Appropriate Lumped Constants of Vibrating Shaft Systems

1943 ◽  
Vol 10 (4) ◽  
pp. A220-A224
Author(s):  
G. Horvay ◽  
J. Ormondroyd
Keyword(s):  
Total Mass ◽  
Spring Constant ◽  
New Method ◽  
Concentrated Mass ◽  
Shaft System ◽  
Spring Constants

Abstract The present paper is a theoretical supplement to the descriptive article, “Static and Dynamic Spring Constants.” It is concerned with the derivation of the constants (1a)Ki=ki+16miω2=ki(1+16ϵi2)(ϵi2=ω2mi/ki)(1b)Mi=μi+12(mleft+mright) of the appropriately lumped shaft system (Section 1), and with an estimate of the range of the new method (Sections 2, 3, 4). Term ki denotes the distributed static spring constant, mi the total mass of the ith (uniform) shaft section of the system; μi is the ith concentrated mass, ω the frequency of vibration.

Fast-phase transvascular fluid flux and the Fahraeus effect

1987 ◽  
Vol 62 (4) ◽  
pp. 1513-1520 ◽  
Author(s):  
W. N. Richardson ◽  
D. Bilan ◽  
M. Hoppensack ◽  
L. Oppenheimer
Keyword(s):  
Mechanical Properties ◽  
Slow Rate ◽  
Time Course ◽  
Rate Of Change ◽  
Distributed Model ◽  
Slow Phase ◽  
Fluid Flux ◽  
Fast Phase ◽  
Constant Rate ◽  
Fahraeus Effect

Transvascular fluid flux was induced in six isolated blood-perfused canine lobes by increasing and decreasing hydrostatic inflow pressure (Pi). Fluid flux was followed against the change in concentration of an impermeable tracer (Blue Dextran) measured directly with a colorimetric device. The time course of fluid flux was biphasic with an initial fast transient followed by a slow phase. Hematocrit changes unrelated to fluid flux occurred due to the Fahraeus effect, and their contribution to the total color signal was subtracted to determine the rate of fast fluid flux (Qf). Qf was related to Pi to derive fast-phase conductance (Kf). Slow-phase Kf was calculated from the constant rate of change of lobe weight. For a mean change in Pi of 7 cmH2O, 40% of the color signal was due to fluid flux. Fast- and slow-phase Kf's were 0.86 +/- 0.15 and 0.27 +/- 0.05 ml X min-1. cmH2O–1 X 100 g dry wt-1. The fast-phase Kf is smaller than that reported for plasma-perfused lobes. Possible explanations discussed are the nature of the perfusate, the mechanical properties of the interstitium, and the slow rate of rise of the driving pressure at the filtration site on the basis of a distributed model of pulmonary vascular compliance.

Origin and Geomorphology

2006 ◽  
Author(s):  
Thomas S. Bianchi
Keyword(s):  
Sea Level ◽  
Rate Of Change ◽  
Interglacial Period ◽  
Continental Margins ◽  
Before Present ◽  
Sea Level Changes ◽  
The Past ◽  
Constant Rate ◽  
Geologic Record ◽  
The U.S

Geologically speaking, estuaries are ephemeral features of the coasts. Upon formation, most begin to fill in with sediments and, in the absence of sea level changes, would have life spans of only a few thousand to tens of thousands of years (Emery and Uchupi, 1972; Schubel, 1972; Schubel and Hirschberg, 1978). Estuaries have been part of the geologic record for at least the past 200 million years (My) BP (before present; Williams, 1960; Clauzon, 1973). However, modern estuaries are recent features that only formed over the past 5000 to 6000 years during the stable interglacial period of the middle to late Holocene epoch (0–10,000 y BP), which followed an extensive rise in sea level at the end of the Pleistocene epoch (1.8 My to 10,000 y BP; Nichols and Biggs, 1985). There is general agreement that four major glaciation to interglacial periods occurred during the Pleistocene. It has been suggested that sea level was reduced from a maximum of about 80 m above sea level during the Aftoninan interglacial to 100 m below sea level during the Wisconsin, some 15,000 to 18,000 y BP (figure 2.1; Fairbridge, 1961). This lowest sea level phase is referred to as low stand and is usually determined by uncovering the oldest drowned shorelines along continental margins (Davis, 1985, 1996); conversely, the highest sea level phase is referred to as high stand. It is generally accepted that low-stand depth is between 130 and 150 m below present sea level and that sea level rose at a fairly constant rate until about 6000 to 7000 y BP (Belknap and Kraft, 1977). A sea level rise of approximately 10 mm y−1 during this period resulted in many coastal plains being inundated with water and a displacement of the shoreline. The phenomenon of rising (transgression) and falling (regression) sea level over time is referred to as eustacy (Suess, 1906). When examining a simplified sea level curve, we find that the rate of change during the Holocene is fairly representative of the Gulf of Mexico and much of the U.S. Atlantic coastline (Curray, 1965).

Evaluation of bridge support condition using bridge responses

2018 ◽  
Vol 18 (3) ◽  
pp. 767-777 ◽  
Author(s):  
Young-Soo Park ◽  
Sehoon Kim ◽  
Namgyu Kim ◽  
Jong-Jae Lee
Keyword(s):  
Sensitivity Analysis ◽  
Numerical Analysis ◽  
Field Test ◽  
Laboratory Tests ◽  
Spring Constant ◽  
Scale Model ◽  
Support Condition ◽  
Bridge Responses ◽  
Spring Constants

This article presents a method for evaluating the support condition of bridges. This is done by representing the aging and deteriorated supports as rotation springs with equivalent spring constants. Sensitivity analysis was performed to obtain a relationship between the spring constant and the bridge responses (deflections/slopes). From this relationship, measured bridge responses can be used to estimate the equivalent spring constants through interpolation. Numerical analysis was performed to check whether the method can be used to calculate equivalent spring constants. Then, the method was verified by performing laboratory tests on a scale model bridge and field test on an actual bridge. In both tests, spring constants were estimated using the proposed method and then verified by calculating the displacements and frequencies and comparing them to the measured values.

Factors Influencing the Rate-of-Pickling Test on Tin-Plate Steel★

CORROSION ◽  
1959 ◽  
Vol 15 (3) ◽  
pp. 51-56 ◽  
Author(s):  
R. M. HUDSON ◽  
G. L. STRAGAND
Keyword(s):  
Weight Loss ◽  
Corrosion Resistance ◽  
Steel Surface ◽  
Lag Time ◽  
Rate Of Change ◽  
Surface Layers ◽  
Experimental Conditions ◽  
Constant Rate ◽  
High Concentrations ◽  
Future Work

Abstract “Lag time” is a measure of the time of pickling necessary to produce a constant rate of weight loss from steel immersed in acid. This measurement has been used as a guide for improving the corrosion resistance of commercial electrolytic tin plate. It is determined by measuring either the rate of change of weight loss, hydrogen evolution, or corroding potential of a specimen in 6N hydrochloric acid at 90 C (194 F.) The lag time depends on surface effects inasmuch as removing the surface layers of steel by abrasion or by pickling destroys the lag. The influence of box-annealing atmospheres, cleanliness of steel, and time-temperature cycles on lag time have been investigated, and the complexity of these effects has been demonstrated. Explanations in terms of oxidation or decarburization of the steel surface during annealing are not feasible for the development of lag time under all the experimental conditions studied. Preliminary data demonstrating the high concentrations of certain elements on the steel surface before annealing, and the enrichment of the surface layer by some of these elements during annealing, are suggested as particularly promising areas for future work. In this way lag time phenomena in tin-plate steels may be better understood and further improvement in tin-plate corrosion resistance can be made. 2.3.4

Experimental Study for Identifying Stiffness of Bridge Slab by Using Wavelet Transform

2006 ◽  
Author(s):  
Naoto Imanishi ◽  
Akira Sone ◽  
Arata Masuda
Keyword(s):  
Experimental Study ◽  
Wavelet Transform ◽  
Reinforced Concrete ◽  
Health Monitoring ◽  
Spring Constant ◽  
Acceleration Response ◽  
Graphic Form ◽  
Noisy Conditions ◽  
Excitation Force ◽  
Spring Constants

In health monitoring of bridge slabs, it is suitable to identify the change in their stiffness. The authors have been proposing the method to identify the spring constant of slab by wavelet transform of an excitation force and acceleration response. In previous paper, the method to identify the spring constants of slabs is theoretically investigated under the noisy conditions. The method to find the specific values of constant α in an analyzing wavelet by which the most reliable value of the spring constant is given according to the graphic form showing the relation between identified mass and constant α. In this paper, the effectiveness of the method is proven from the experiment results using the reinforced concrete panel specimen.

How does the magnetosphere go to sleep?

2020 ◽  
Author(s):  
Therese Moretto Jorgensen ◽  
Michael Hesse ◽  
Lutz Rastaetter ◽  
Susanne Vennerstrom ◽  
Paul Tenfjord
Keyword(s):  
Magnetic Field ◽  
Solar Wind ◽  
Interplanetary Magnetic Field ◽  
Exponential Decay ◽  
Rate Of Change ◽  
Total Field ◽  
Summer Hemisphere ◽  
Field Aligned Current ◽  
Field Lines ◽  
Line Tying

<p>Energy and circulation in the Earth’s magnetosphere and ionosphere are largely determined by conditions in the solar wind and interplanetary magnetic field. When the driving from the solar wind is turned off (to a minimum), we expect the activity to die down but exactly how this happens is not known.  Utilizing global MHD modelling, we have addressed the questions of what constitutes the quietest state for the magnetosphere and how it is approached following a northward turning in the IMF that minimizes the driving. We observed an exponential decay with a decay time of about 1 hr in several integrated parameters related to different aspects of magnetospheric activity, including the total field-aligned current into and out of the ionosphere.  The time rate of change for the cessation of activity was also measured in total field aligned current estimates from the AMPERE project, adding observational support to this finding.  Events of distinct northward turnings of the interplanetary magnetic field were identified, with prolonged periods of stable southward driving conditions followed by northward interplanetary magnetic field conditions. A well-defined exponential decay could be identified in the total hemispheric field-aligned current following the northward turning with a generic decay constant of 0.9, corresponding to an e-folding time of 1.1 hr. A possible physical explanation for the exponential decay follows from considering what needs to happen for the convection in the magnetosphere to slow down, or stop, namely the unwinding of the field-aligned current carrying flux tubes in the coupled magnetosphere-ionosphere system. A statistical analysis of the ensemble of events also reveals both a seasonal and a day/night variation in the decay parameter, with faster decay observed in the winter than in the summer hemisphere and on the nightside than on the dayside. These results can be understood in terms of stronger/weaker line tying of the ionospheric foot points of magnetospheric field lines for higher/lower conductivity.  Additional global modeling results with varying conductance scenarios for the ionosphere confirm this interpretation.   </p>

Constant rate of change of magnetization hysteresis loop tracer

1991 ◽  
Vol 69 (8) ◽  
pp. 5100-5102 ◽  
Author(s):  
R. Cammarano ◽  
R. Street ◽  
P. G. McCormick ◽  
M. E. Evans
Keyword(s):  
Hysteresis Loop ◽  
Rate Of Change ◽  
Magnetization Hysteresis ◽  
Constant Rate ◽  
Magnetization Hysteresis Loop

Statistical Response of a Simplified Nonlinear Fluid Model Under Random Parameters

2007 ◽  
Author(s):  
T-P. Chang
Keyword(s):  
Fluid Model ◽  
Closed Form Solution ◽  
Mean Value ◽  
Form Solution ◽  
Viscoelastic Materials ◽  
Nonlinear Springs ◽  
Constant Rate ◽  
Viscoelastic Modeling ◽  
Spring Constants ◽  
Nonlinear Fluid

In this paper, a simplified spring-dashpot model is proposed to represent the complicated nonlinear response of some viscoelastic materials. Recently, the viscoelastic modeling has been adopted by many researchers to characterize some parts of human body in bioengineering. Among others, the following researchers have already contributed to the development of this field (Weiss et al., [1]; Guedes et al., [2]). Sometimes it is impossible to estimate the constant parameters in the model deterministically, therefore, the damping coefficient of the dashpot and the spring constants of the linear and nonlinear springs are considered as stochastic to characterize the random properties of the viscoelastic materials. The mean value of the displacement of the nonlinear model, subjected to constant rate displacement, can be solved analytically. Based on the closed-form solution, the proposed method produces the statistical responses of the simplified nonlinear fluid model, which is fairly useful in estimating the reliability of the nonlinear system.

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