149 resultados para STRAIN RELAXATION
Resumo:
Battery powered bed movers are becoming increasingly common within the hospital setting. The use of powered bed movers is believed to result in reduced physical efforts required by health care workers, which may be associated with a decreased risk of occupation related injuries. However, little work has been conducted assessing how powered bed movers impact on levels of physiological strain and muscle activation for the user. The muscular efforts associated with moving hospital beds using three different methods; manual pushing, StaminaLift Bed Mover (SBM) and Gzunda Bed Mover (GBM)were measured on six male subjects. Fourteen muscles were assessed moving a weighted hospital bed along a standardized route in an Australian hospital environment. Trunk inclination and upper spine acceleration were also quantified. Powered bed movers exhibited significantly lower muscle activation levels than manual pushing for the majority of muscles. When using the SBM, users adopted a more upright posture which was maintained while performing different tasks (e.g. turning a corner, entering a lift), while trunk inclination varied considerably for manual pushing and the GBM. The reduction in lower back muscular activation levels and the load reducing effect of a more upright posture may result in lower incidence of lower back injury.
Resumo:
The search for new multipoint, multidirectional strain sensing devices has received a new impetus since the discovery of carbon nanotubes. The excellent electrical, mechanical, and electromechanical properties of carbon nanotubes make them ideal candidates as primary materials in the design of this new generation of sensing devices. Carbon nanotube based strain sensors proposed so far include those based on individual carbon nanotubes for integration in nano or micro elecromechanical systems (NEMS/MEMS) [1], or carbon nanotube films consisting of spatially connected carbon nanotubes [2], carbon nanotube - polymer composites [3,4] for macroscale strain sensing. Carbon nanotube films have good strain sensing response and offer the possibility of multidirectional and multipoint strain sensing, but have poor performance due to weak interaction between carbon nanotubes. In addition, the carbon nanotube film sensor is extremely fragile and difficult to handle and install. We report here the static and dynamic strain sensing characteristics as well as temperature effects of a sandwich carbon nanotube - polymer sensor fabricated by infiltrating carbon nanotube films with polymer.
Resumo:
Two types of carbon nanotube nanocomposite strain sensors were prepared by mixing carbon nanotubes with epoxy (nanocomposite sensor) and sandwiching a carbon nanotube film between two epoxy layers (sandwich sensor). The conductivity, response and sensitivity to static and dynamic mechanical strains in these sensors were investigated. The nanocomposite sensor with 2-3 wt.% carbon nanotube demonstrated high sensitivity to mechanical strain and environmental temperature, with gauge factors of 5-8. On the other hand, a linear relationship between conductivity and dynamic mechanical strain was observed in the sandwich sensor. The sandwich sensor was also not sensitive to temperature although its strain sensitivity (gauge factor of about 3) was lower as compared with the nanocomposite sensor. Both sensors have excellent response to static and dynamic strains, thereby having great potential for strain sensing applications.
Resumo:
A high sensitive fiber Bragg grating (FBG) strain sensor with automatic temperature compensation is demonstrated. FBG is axially linked with a stick and their free ends are fixed to the measured object. When the measured strain changes, the stick does not change in length, but the FBG does. When the temperature changes, the stick changes in length to pull the FBG to realize temperature compensation. In experiments, 1.45 times strain sensitivity of bare FBG with temperature compensation of less than 0.1 nm Bragg wavelength drift over 100 ◦C shift is achieved.
Resumo:
133Cs relaxation-time studies of tissues from rats into which cesium has been incorporated by dietary loading have been carried out in vivo and in vitro. Whereas tissue T1 values are on the order of seconds, T2 values are as low as a few tens of milliseconds, 133Cs tissue relaxation times are analogous to those of 39K in the same tissues, but are more readily measured because of the greater sensitivity of 133Cs compared with 39K, T1 and T2 data of excised tissue at two resonance frequencies (65.60 and 39.37 MHz) and temperatures (302 and 278 K) have been analyzed in terms of a general description of spin- relaxation. The results are consistent with most of the cesium ions being in a free state, undergoing fast exchange with bound ions having long correlation times located in one or more intracellular compartments,
Resumo:
Differences in the NMR detectability of 39K in various excised rat tissues (liver, brain, kidney, muscle, and testes) have been observed. The lowest NMR detectability occurs for liver (61 ± 3% of potassium as measured by flame photometry) and highest for erythrocytes (100 ± 7%). These differences in detectability correlate with differences in the measured 39K NMR relaxation constants in the same tissues. 39K detectabilities were also found to correlate inversely with the mitochondrial content of the tissues. Mitochondria prepared from liver showed greatly reduced 39K NMR detectability when compared with the tissue from which it was derived, 31.6 ± 9% of potassium measured by flame photometry compared to 61 ± 3%. The detectability of potassium in mitochondria was too low to enable the measurement of relaxation constants. This study indicates that differences in tissue structure, particularly mitochondrial content are important in determining 39K detectability and measured relaxation rates.
Resumo:
The quadrupole coupling constants (qcc) for39K and23Na ions in glycerol have been calculated from linewidths measured as a function of temperature (which in turn results in changes in solution viscosity). The qcc of39K in glycerol is found to be 1.7 MHz, and that of23Na is 1.6 MHz. The relaxation behavior of39K and23Na ions in glycerol shows magnetic field and temperature dependence consistent with the equations for transverse relaxation more commonly used to describe the reorientation of nuclei in a molecular framework with intramolecular field gradients. It is shown, however, that τc is not simply proportional to the ratio of viscosity/temperature (ηT). The 39K qcc in glycerol and the value of 1.3 MHz estimated for this nucleus in aqueous solution are much greater than values of 0.075 to 0.12 MHz calculated from T2 measurements of39K in freshly excised rat tissues. This indicates that, in biological samples, processes such as exchange of potassium between intracellular compartments or diffusion of ions through locally ordered regions play a significant role in determining the effective quadrupole coupling constant and correlation time governing39K relaxation. T1 and T2 measurements of rat muscle at two magnetic fields also indicate that a more complex correlation function may be required to describe the relaxation of39K in tissue. Similar results and conclusions are found for23Na.
Resumo:
This paper presents two novel concepts to enhance the accuracy of damage detection using the Modal Strain Energy based Damage Index (MSEDI) with the presence of noise in the mode shape data. Firstly, the paper presents a sequential curve fitting technique that reduces the effect of noise on the calculation process of the MSEDI, more effectively than the two commonly used curve fitting techniques; namely, polynomial and Fourier’s series. Secondly, a probability based Generalized Damage Localization Index (GDLI) is proposed as a viable improvement to the damage detection process. The study uses a validated ABAQUS finite-element model of a reinforced concrete beam to obtain mode shape data in the undamaged and damaged states. Noise is simulated by adding three levels of random noise (1%, 3%, and 5%) to the mode shape data. Results show that damage detection is enhanced with increased number of modes and samples used with the GDLI.
Resumo:
As a part of vital infrastructure and transportation network, bridge structures must function safely at all times. Bridges are designed to have a long life span. At any point in time, however, some bridges are aged. The ageing of bridge structures, given the rapidly growing demand of heavy and fast inter-city passages and continuous increase of freight transportation, would require diligence on bridge owners to ensure that the infrastructure is healthy at reasonable cost. In recent decades, a new technique, structural health monitoring (SHM), has emerged to meet this challenge. In this new engineering discipline, structural modal identification and damage detection have formed a vital component. Witnessed by an increasing number of publications is that the change in vibration characteristics is widely and deeply investigated to assess structural damage. Although a number of publications have addressed the feasibility of various methods through experimental verifications, few of them have focused on steel truss bridges. Finding a feasible vibration-based damage indicator for steel truss bridges and solving the difficulties in practical modal identification to support damage detection motivated this research project. This research was to derive an innovative method to assess structural damage in steel truss bridges. First, it proposed a new damage indicator that relies on optimising the correlation between theoretical and measured modal strain energy. The optimisation is powered by a newly proposed multilayer genetic algorithm. In addition, a selection criterion for damage-sensitive modes has been studied to achieve more efficient and accurate damage detection results. Second, in order to support the proposed damage indicator, the research studied the applications of two state-of-the-art modal identification techniques by considering some practical difficulties: the limited instrumentation, the influence of environmental noise, the difficulties in finite element model updating, and the data selection problem in the output-only modal identification methods. The numerical (by a planer truss model) and experimental (by a laboratory through truss bridge) verifications have proved the effectiveness and feasibility of the proposed damage detection scheme. The modal strain energy-based indicator was found to be sensitive to the damage in steel truss bridges with incomplete measurement. It has shown the damage indicator's potential in practical applications of steel truss bridges. Lastly, the achievement and limitation of this study, and lessons learnt from the modal analysis have been summarised.
Resumo:
The present research examined the effects of occupational stress in psychiatric nursing on employee well!being using the full Job Strain Model.The Job Strain Model was assessed for its ability to predict employee well!being in terms of job satisfaction and mental health. The original Job Strain Model was expanded to include social support based on previous research concerning the impact of social support on well!being[ In the present study\ both work support and non-work were assessed for their contribution to wellbeing.The results of this study indicate that the full Job Strain Model can be used to significantly predict job satisfaction and mental health in this sample of Australian psychiatric nurses. Furthermore social support was shown to be an important component of the Job Strain Model.
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This paper investigates the effects of lane-changing in driver behavior by measuring (i) the induced transient behavior and (ii) the change in driver characteristics, i.e., changes in driver response time and minimum spacing. We find that the transition largely consists of a pre-insertion transition and a relaxation process. These two processes are different but can be reasonably captured with a single model. The findings also suggest that lane-changing induces a regressive effect on driver characteristics: a timid driver (characterized by larger response time and minimum spacing) tends to become less timid and an aggressive driver less aggressive. We offer an extension to Newell’s car-following model to describe this regressive effect and verify it using vehicle trajectory data.