Unified Continuum Damage Model for Matrix Cracking in Composite Rotor Blades

This paper deals with modeling of the first damage mode, matrix micro-cracking, in helicopter rotor/wind turbine blades and how this effects the overall cross-sectional stiffness. The helicopter/wind turbine rotor system operates in a highly dynamic and unsteady environment leading to severe vibratory loads present in the system. Repeated exposure to this loading condition can induce damage in the composite rotor blades. These rotor/turbine blades are generally made of fiber-reinforced laminated composites and exhibit various competing modes of damage such as matrix micro-cracking, delamination, and fiber breakage. There is a need to study the behavior of the composite rotor system under various key damage modes in composite materials for developing Structural Health Monitoring (SHM) system. Each blade is modeled as a beam based on geometrically non-linear 3-D elasticity theory. Each blade thus splits into 2-D analyzes of cross-sections and non-linear 1-D analyzes along the beam reference curves. Two different tools are used here for complete 3-D analysis: VABS for 2-D cross-sectional analysis and GEBT for 1-D beam analysis. The physically-based failure models for matrix in compression and tension loading are used in the present work. Matrix cracking is detected using two failure criterion: Matrix Failure in Compression and Matrix Failure in Tension which are based on the recovered field. A strain variable is set which drives the damage variable for matrix cracking and this damage variable is used to estimate the reduced cross-sectional stiffness. The matrix micro-cracking is performed in two different approaches: (i) Element-wise, and (ii) Node-wise. The procedure presented in this paper is implemented in VABS as matrix micro-cracking modeling module. Three examples are presented to investigate the matrix failure model which illustrate the effect of matrix cracking on cross-sectional stiffness by varying the applied cyclic

Environmental monitoring of bacterial contamination and antibiotic resistance patterns of the fecal coliforms isolated from Cauvery River, a major drinking water source in Karnataka, India

The present study focuses prudent elucidation of microbial pollution and antibiotic sensitivity profiling of the fecal coliforms isolated from River Cauvery, a major drinking water source in Karnataka, India. Water samples were collected from ten hotspots during the year 2011-2012. The physiochemical characteristics and microbial count of water samples collected from most of the hotspots exhibited greater biological oxygen demand and bacterial count especially coliforms in comparison with control samples (p <= 0.01). The antibiotic sensitivity testing was performed using 48 antibiotics against the bacterial isolates by disk-diffusion assay. The current study showed that out of 848 bacterial isolates, 93.51 % (n=793) of the isolates were found to be multidrug-resistant to most of the current generation antibiotics. Among the major isolates, 96.46 % (n=273) of the isolates were found to be multidrug-resistant to 30 antibiotics and they were identified to be Escherichia coli by 16S rDNA gene sequencing. Similarly, 93.85 % (n=107), 94.49 % (n=103), and 90.22 % (n=157) of the isolates exhibited multiple drug resistance to 32, 40, and 37 antibiotics, and they were identified to be Enterobacter cloacae, Pseudomonas trivialis, and Shigella sonnei, respectively. The molecular studies suggested the prevalence of blaTEM genes in all the four isolates and dhfr gene in Escherichia coli and Sh. sonnei. Analogously, most of the other Gram-negative bacteria were found to be multidrug-resistant and the Gram-positive bacteria, Staphylococcus spp. isolated from the water samples were found to be methicillin and vancomycin-resistant Staphylococcus aureus. This is probably the first study elucidating the bacterial pollution and antibiotic sensitivity profiling of fecal coliforms isolated from River Cauvery, Karnataka, India.

Modeling Ultrasonic NDE and Guided Wave based Structural Health Monitoring

Structural Health Monitoring (SHM) systems require integration of non-destructive technologies into structural design and operational processes. Modeling and simulation of complex NDE inspection processes are important aspects in the development and deployment of SHM technologies. Ray tracing techniques are vital simulation tools to visualize the wave path inside a material. These techniques also help in optimizing the location of transducers and their orientation with respect to the zone of interrogation. It helps in increasing the chances of detection and identification of a flaw in that zone. While current state-of-the-art techniques such as ray tracing based on geometric principle help in such visualization, other information such as signal losses due to spherical or cylindrical shape of wave front are rarely taken into consideration. The problem becomes a little more complicated in the case of dispersive guided wave propagation and near-field defect scattering. We review the existing models and tools to perform ultrasonic NDE simulation in structural components. As an initial step, we develop a ray-tracing approach, where phase and spectral information are preserved. This enables one to study wave scattering beyond simple time of flight calculation of rays. Challenges in terms of theory and modelling of defects of various kinds are discussed. Various additional considerations such as signal decay and physics of scattering are reviewed and challenges involved in realistic computational implementation are discussed. Potential application of this approach to SHM system design is highlighted and by applying this to complex structural components such as airframe structures, SHM is demonstrated to provide additional value in terms of lighter weight and/or longevity enhancement resulting from an extension of the damage tolerance design principle not compromising safety and reliability.

A comparative study of failure features in aerospace grade unidirectional and bidirectional woven CFRP composite laminates under four-point bend fatigue loads

Damage mechanisms in unidirectional (UD) and bi-directional (BD) woven carbon fiber reinforced polymer (CFRP) laminates subjected to four point flexure, both in static and fatigue loadings, were studied. The damage progression in composites was monitored by observing the slopes of the load vs. deflection data that represent the stiffness of the given specimen geometry over a number of cycles. It was observed that the unidirectional composites exhibit gradual loss in stiffness whereas the bidirectional woven composites show a relatively quicker loss during stage II of fatigue damage progression. Both, the static and the fatigue failures in unidirectional carbon fiber reinforced polymer composites originates due to generation of cracks on compression face while in bidirectional woven composites the damage ensues from both the compression and the tensile faces. These observations are supported by a detailed fractographic analysis.

Performance Evaluation of Underground Mine Communication and Monitoring Devices: Case Studies

Communication and environmental monitoring play a major role in underground mining both from production and safety point of view. However, underground mining communication as well as monitoring devices encounter several challenges because of the nature of underground features and characteristics. Lack of real time information from underground workings may hamper production and create serious safety risks. Proper communication and monitoring devices are inevitable requirements for better production and improved safety. Communication and environmental monitoring devices are basic element of underground mine infrastructure. This paper describes the performance of communication and monitoring devices being used in underground mines. An attempt has been made to assess the safety risks by these devices which may dictate future research directions.

Non-invasive pressure monitoring by hoop strain using Fiber Bragg Grating sensor

Non-invasive, real-time dynamic monitoring of pressure inside a column with the aid of Fiber Bragg Grating (FBG) sensor is presented in the present work. A bare FBG sensor is adhered on the circumference of a pressure column normal to its axis, which has the ability to acquire the hoop strain induced by the pressure variation inside the column. Pressure induced hoop strain response obtained using FBG sensor is validated against the pressure measurements obtained from conventional pressure gauge. Further, a protrusion setup on the outer surface of the column has been proposed over which a secondary FBG sensor is bonded normal to its axis, in order to increase the gauge length of this FBG sensor. This is carried out in order to validate the variation in sensitivity of the protrusion bonded FBG sensor compared to the bare FBG sensor bonded over the surface. A comparative study is done between the two FBG sensors and a conventional pressure gauge in order to establish the capacity of FBG sensor obtained hoop strain response for pressure monitoring inside the column.

Router Attack toward NoC-enabled MPSoC and Monitoring Countermeasures against such Threat

The growing number of applications and processing units in modern Multiprocessor Systems-on-Chips (MPSoCs) come along with reduced time to market. Different IP cores can come from different vendors, and their trust levels are also different, but typically they use Network-on-Chip (NoC) as their communication infrastructure. An MPSoC can have multiple Trusted Execution Environments (TEEs). Apart from performance, power, and area research in the field of MPSoC, robust and secure system design is also gaining importance in the research community. To build a secure system, the designer must know beforehand all kinds of attack possibilities for the respective system (MPSoC). In this paper we survey the possible attack scenarios on present-day MPSoCs and investigate a new attack scenario, i.e., router attack targeted toward NoC architecture. We show the validity of this attack by analyzing different present-day NoC architectures and show that they are all vulnerable to this type of attack. By launching a router attack, an attacker can control the whole chip very easily, which makes it a very serious issue. Both routing tables and routing logic-based routers are vulnerable to such attacks. In this paper, we address attacks on routing tables. We propose different monitoring-based countermeasures against routing table-based router attack in an MPSoC having multiple TEEs. Synthesis results show that proposed countermeasures, viz. Runtime-monitor, Restart-monitor, Intermediate manager, and Auditor, occupy areas that are 26.6, 22, 0.2, and 12.2 % of a routing table-based router area. Apart from these, we propose Ejection address checker and Local monitoring module inside a router that cause 3.4 and 10.6 % increase of a router area, respectively. Simulation results are also given, which shows effectiveness of proposed monitoring-based countermeasures.

Multiple Spectral Peak Tracking for Heart Rate Monitoring from Photoplethysmography Signal During Intensive Physical Exercise

We propose a multiple initialization based spectral peak tracking (MISPT) technique for heart rate monitoring from photoplethysmography (PPG) signal. MISPT is applied on the PPG signal after removing the motion artifact using an adaptive noise cancellation filter. MISPT yields several estimates of the heart rate trajectory from the spectrogram of the denoised PPG signal which are finally combined using a novel measure called trajectory strength. Multiple initializations help in correcting erroneous heart rate trajectories unlike the typical SPT which uses only single initialization. Experiments on the PPG data from 12 subjects recorded during intensive physical exercise show that the MISPT based heart rate monitoring indeed yields a better heart rate estimate compared to the SPT with single initialization. On the 12 datasets MISPT results in an average absolute error of 1.11 BPM which is lower than 1.28 BPM obtained by the state-of-the-art online heart rate monitoring algorithm.

Amperometric acetylcholinesterase biosensor for pesticides monitoring utilising iron oxide nanoparticles and poly(indole-5-carboxylic acid)

A new electrochemical sensing device was constructed for determination of pesticides. In this report, acetylcholinesterase was bioconjugated onto hybrid nanocomposite, i.e. iron oxide nanoparticles and poly(indole-5-carboxylic acid) (Fe(3)O(4)NPs/Pin5COOH) was deposited electrochemically on glassy carbon electrode. Fe(3)O(4)NPs was showed as an amplified sensing interface at lower voltage which makes the sensor more sensitive and specific. The enzyme inhibition by pesticides was detected within concentrations ranges between 0.1-60 and 1.5-70 nM for malathion and chlorpyrifos, respectively, under optimal experimental conditions (sodium phosphate buffer, pH 7.0 and 25 degrees C). Biosensor determined the pesticides level in water samples (spiked) with satisfactory accuracy (96%-100%). Sensor showed good storage stability and retained 50% of its initial activity within 70 days at 4 degrees C.

Ultrasonic Guided Wave Sensor Network Optimization for Monitoring Rivet Line

Guided waves using piezo-electric wafer active sensors (PWAS) is one of the useful techniques of damage detection. Sensor network optimization with minimal network hardware footprint and maximal area of coverage remains a challenging problem. PWAS sensors are placed at discrete locations in order to inspect damages in plates and the idea has the potential to be extended to assembled structures. Various actuator-sensor configurations are possible within the network in order to identify and locate damages. In this paper we present a correlation based approach to monitor cracks emanating from rivet line using a simulated guided wave signal whose sensor is operating in pulse echo mode. Discussions regarding the identification of phase change due to reflections from the crack are also discussed in this paper.

Aircraft Composite Structure Preventive Maintenance

In this paper, a methodology to reduce composite structure maintenance operational cost using SHM systems is adressed. Based on SHM real-time data, in-service structure lifetime prognostic and remaining useful lifetime (RUL) can be performed. Maintenance timetable can be therefore predicted by optimizing inspection times. A probabilistic ap-proach is combined with phenomenological fatigue damage models for composite mate-rials to perform maintenance cost-effectiveness of composite structure. A Monte Carlo method is used to estimate the probability of failure of composite structures and com-pute the average number of composite structure components to be replaced over the component lifetime. The replacement frequency of a given structure component over the aircraft lifetime is assessed. A first application of aeronautical composite structure maintenance is considered. Two composite models to predict the fatigue life and several laminates have been used. Our study shows that maintenance cost-effectiveness depends on material and fatigue loading applied.

Design of a Wearable Remote Neonatal Health Monitoring Device

In this text we present the design of a wearable health monitoring device capable of remotely monitoring health parameters of neonates for the first few weeks after birth. The device is primarily aimed at continuously tracking the skin temperature to indicate the onset of hypothermia in newborns. A medical grade thermistor is responsible for temperature measurement and is directly interfaced to a microcontroller with an integrated bluetooth low energy radio. An inertial sensor is also present in the device to facilitate breathing rate measurement which has been discussed briefly. Sensed data is transferred securely over bluetooth low energy radio to a nearby gateway, which relays the information to a central database for real time monitoring. Low power optimizations at both the circuit and software levels ensure a prolonged battery life. The device is packaged in a baby friendly, water proof housing and is easily sterilizable and reusable.

Toward a High-Resolution Monitoring of Continental Surface Water Extent and Dynamics, at Global Scale: from GIEMS (Global Inundation Extent from Multi-Satellites) to SWOT (Surface Water Ocean Topography)

Up to now, high-resolution mapping of surface water extent from satellites has only been available for a few regions, over limited time periods. The extension of the temporal and spatial coverage was difficult, due to the limitation of the remote sensing technique e.g., the interaction of the radiation with vegetation or cloud for visible observations or the temporal sampling with the synthetic aperture radar (SAR)]. The advantages and the limitations of the various satellite techniques are reviewed. The need to have a global and consistent estimate of the water surfaces over long time periods triggered the development of a multi-satellite methodology to obtain consistent surface water all over the globe, regardless of the environments. The Global Inundation Extent from Multi-satellites (GIEMS) combines the complementary strengths of satellite observations from the visible to the microwave, to produce a low-resolution monthly dataset () of surface water extent and dynamics. Downscaling algorithms are now developed and applied to GIEMS, using high-spatial-resolution information from visible, near-infrared, and synthetic aperture radar (SAR) satellite images, or from digital elevation models. Preliminary products are available down to 500-m spatial resolution. This work bridges the gaps and prepares for the future NASA/CNES Surface Water Ocean Topography (SWOT) mission to be launched in 2020. SWOT will delineate surface water extent estimates and their water storage with an unprecedented spatial resolution and accuracy, thanks to a SAR in an interferometry mode. When available, the SWOT data will be adopted to downscale GIEMS, to produce a long time series of water surfaces at global scale, consistent with the SWOT observations.