303 resultados para nanocomposite strain sensor


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Purpose To observe the incidence rates of hamstring strain injuries (HSIs) across different competition levels and ages during the Penn Relays Carnival. Methods Over a 3-year period all injuries treated by the medical staff were recorded. The type of injury, anatomic location, event in which the injury occurred, competition level and demographic data were documented. Absolute and relative HSI (per 1000 participants) were determined and odds ratios (OR) were calculated between genders, competition levels and events. Results Throughout the study period 48,473 athletes registered to participate in the Penn Relays Carnival, with 118 HSIs treated by the medical team. High school females displayed lesser risk of HSI than high school males (OR = 0.55, p = 0.021), and masters athletes were more likely than high school (OR = 4.26, p < 0.001) and college (OR = 3.55, p = 0.001) level athletes to suffer a HSI. The 4x400m relay displayed a greater likelihood of HSI compared to the 4x100m relay (OR = 1.77, p = 0.008). Conclusions High school males and masters levels athletes are most likely to suffer HSI, and there is higher risk in 400m events compared to 100m events.

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Bi-2212 tapes were fabricated using a powder-in-tube method and their superconducting properties were measured as a function of heat treatment. The tapes were heated to temperature, T1 (884-915 °C), and kept at that temperature for 20 min to induce partial (incongruent) melting. The samples were cooled to T2 with a ramp rate of 120 °C h-1 and then slowly cooled to T3 with a cooling rate, R2, and from T3 to T4 with a cooling rate, R3. The tapes were kept at the temperature T4 for P1 hours and then cooled to room temperature. Both R1 and R2 were chosen between 2 and 8 °C h-1. It was found that the structure and Jc of the tapes depend on the sintering conditions, i.e. T1-4, R1-3 and P1. The highest Jc of 5800 Å cm-2 was obtained at 77 K in a self-field with heat treatment where T1 = 894 and 899 °C, R1 = R2 = 5 °C h-1 and P1 = 6 h were employed. When 0.7% of bend strain, which is equivalent to a bend radius of 5 mm, was applied to the tape, 80% of the initial Jc was sustained.

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Piezoelectric composites comprising an active phase of ferroelectric ceramic and a polymer matrix have recently attracted numerous sensory applications. However, it remains a major challenge to further improve their electromechanical response for advanced applications such as precision control and monitoring systems. We hereby investigated the incorporation of graphene platelets (GnPs) and multi-walled carbon nanotubes (MWNTs), each with various weight fractions, into PZT (lead zirconate titanate)/epoxy composites to produce three-phase nanocomposites. The nanocomposite films show markedly improved piezoelectric coefficients and electromechanical responses (50%) besides an enhancement of ~200% in stiffness. Carbon nanomaterials strengthened the impact of electric field on the PZT particles by appropriately raising the electrical conductivity of epoxy. GnPs have been proved far more promising in improving the poling behavior and dynamic response than MWNTs. The superior dynamic sensitivity of GnP-reinforced composite may be caused by GnPs’ high load transfer efficiency arising from their two-dimensional geometry and good compatibility with the matrix. Reduced acoustic impedance mismatch resulted from the improved thermal conductance may also contribute to the higher sensitivity of GnP-reinforced composite. This research pointed out the potential of employing GnPs to develop highly sensitive piezoelectric composites for sensing applications.

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Background. This study evaluated the time course of recovery of transverse strain in the Achilles and patellar tendons following a bout of resistance exercise. Methods. Seventeen healthy adults underwent sonographic examination of the right patellar (n = 9) or Achilles (n = 8) tendons immediately prior to and following 90 repetitions of weight–bearing exercise. Quadriceps and gastrocnemius exercise were performed against an effective resistance of 175% and 250% body weight, respectively. Sagittal tendon thickness was determined 20 mm from the tendon enthesis and transverse strain was repeatedly monitored over a 24 hour recovery period. Results. Resistance exercise resulted in an immediate decrease in Achilles (t7 = 10.6, P<.01) and patellar (t8 = 8.9, P<.01) tendon thickness, resulting in an average transverse strain of 0.14 ± 0.04 and 0.18 ± 0.05. While the average strain was not significantly different between tendons, older age was associated with a reduced transverse strain response (r=0.63, P<.01). Recovery of transverse strain, in contrast, was prolonged compared with the duration of loading and exponential in nature. The mean primary recovery time was not significantly different between Achilles (6.5 ± 3.2 hours) and patellar (7.1 ± 3.2 hours) tendons and body weight accounted for 62% and 64% of the variation in recovery time, respectively. Discussion. Despite structural and biochemical differences between the Achilles and patellar tendons [1], the mechanisms underlying transverse creep–recovery in vivo appear similar and are highly time dependent. Primary recovery required about 7 hours in healthy tendons, with full recovery requiring up to 24 hours. These in vivo recovery times are similar to those reported for axial creep recovery of the vertebral disc in vitro [2], and may be used clinically to guide physical activity to rest ratios in healthy adults. Optimal ratios for high–stress tendons in clinical populations, however, remain unknown and require further attention in light of the knowledge gained in this study.

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Non-linear finite deformations of articular cartilages under physiological loading conditions can be attributed to hyperelastic behavior. This paper contains experimental results of indentation tests in finite deformation and proposes an empirical based new generalized hyperelastic constitutive model to account for strain-rate dependency for humeral head cartilage tissues. The generalized model is based on existing hyperelastic constitutive relationships that are extensively used to represent biological tissues in biomechanical literature. The experimental results were obtained for three loading velocities, corresponding to low (1x10-3 s-1), moderate and high strain-rates (1x10-1 s-1), which represent physiological loading rates that are experienced in daily activities such as lifting, holding objects and sporting activities. Hyperelastic material parameters were identified by non linear curve fitting procedure. Analysis demonstrated that the material behavior of cartilage can be effectively decoupled into strain-rate independent(elastic) and dependent parts. Further, experiments conducted using different indenters indicated that the parameters obtained are significantly affected by the indenter size, potentially due to structural inhomogeneity of the tissue. The hyperelastic constitutive model developed in this paper opens a new avenue for the exploration of material properties of cartilage tissues.

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Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.

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In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.

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Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.

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The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research examining effects of uncertainties of generic WSN platform and verifying the capability of SHM-oriented WSNs, particularly on demanding SHM applications like modal analysis and damage identification of real civil structures. This article first reviews the major technical uncertainties of both generic and SHM-oriented WSN platforms and efforts of SHM research community to cope with them. Then, effects of the most inherent WSN uncertainty on the first level of a common Output-only Modal-based Damage Identification (OMDI) approach are intensively investigated. Experimental accelerations collected by a wired sensory system on a benchmark civil structure are initially used as clean data before being contaminated with different levels of data pollutants to simulate practical uncertainties in both WSN platforms. Statistical analyses are comprehensively employed in order to uncover the distribution pattern of the uncertainty influence on the OMDI approach. The result of this research shows that uncertainties of generic WSNs can cause serious impact for level 1 OMDI methods utilizing mode shapes. It also proves that SHM-WSN can substantially lessen the impact and obtain truly structural information without having used costly computation solutions.

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Introduction Stretching of tissue stimulates angiogenesis but increased motion at a fracture site hinders revascularisation. In vitro studies have indicated that mechanical stimuli promote angiogenic responses in endothelial cells, but can either inhibit or enhance responses when applied directly to angiogenesis assays. We anticipated that cyclic tension applied during endothelial network assembly would increase vascular structure formation up to a certain threshold. Methods Fibroblast/HUVEC co-cultures were subjected to cyclic equibiaxial strain (1 Hz; 6 h/day; 7 days) using the FlexerCell FX-4000T system and limiting rings for simultaneous application of multiple strain magnitudes (0–13%). Cells were labelled using anti-PECAM-1, and image analysis provided measures of endothelial network length and numbers of junctions. Results Cyclic stretching had no significant effect on the total length of endothelial networks (P > 0.2) but resulted in a strain-dependent decrease in branching and localised alignments of endothelial structures, which were in turn aligned with the supporting fibroblastic construct. Conclusion The organisation of endothelial networks under cyclic strain is dominated by structural adaptation to the supporting construct. It may be that, in fracture healing, the formation and integrity of the granulation tissue and callus is ultimately critical in revascularisation and its failure under severe strain conditions.

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For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

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This paper presents large, accurately calibrated and time-synchronised datasets, gathered outdoors in controlled environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. It discusses how the data collection process was designed, the conditions in which these datasets have been gathered, and some possible outcomes of their exploitation, in particular for the evaluation of performance of sensors and perception algorithms for UGVs.

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This document describes large, accurately calibrated and time-synchronised datasets, gathered in controlled environmental conditions, using an unmanned ground vehicle equipped with a wide variety of sensors. These sensors include: multiple laser scanners, a millimetre wave radar scanner, a colour camera and an infra-red camera. Full details of the sensors are given, as well as the calibration parameters needed to locate them with respect to each other and to the platform. This report also specifies the format and content of the data, and the conditions in which the data have been gathered. The data collection was made in two different situations of the vehicle: static and dynamic. The static tests consisted of sensing a fixed ’reference’ terrain, containing simple known objects, from a motionless vehicle. For the dynamic tests, data were acquired from a moving vehicle in various environments, mainly rural, including an open area, a semi-urban zone and a natural area with different types of vegetation. For both categories, data have been gathered in controlled environmental conditions, which included the presence of dust, smoke and rain. Most of the environments involved were static, except for a few specific datasets which involve the presence of a walking pedestrian. Finally, this document presents illustrations of the effects of adverse environmental conditions on sensor data, as a first step towards reliability and integrity in autonomous perceptual systems.