Ignition delay of 3-carene: single pulse shock tube study

Ignition delay experiments of 3-carene, a biofuel, have been carried out in a single-pulse shock tube for three equivalence ratios, 0.5, 1 and 2. The temperature was varied from 1140 to 1606 K. In the above-mentioned conditions, ignition delay was found to vary from 1.180 ms to 144 mu s. The ignition delay values of 3-carene were found to be lower than those of JP-10, a kerosene-based fuel being considered for hypersonic applications.

Pulse transit time differential measurement by fiber Bragg grating pulse recorder

The present study reports a noninvasive technique for the measurement of the pulse transit time differential (PTTD) from the pulse pressure waveforms obtained at the carotid artery and radial artery using fiber Bragg grating pulse recorders (FBGPR). PTTD is defined as the time difference between the arrivals of a pulse pressure waveform at the carotid and radial arterial sites. The PTTD is investigated as an indicator of variation in the systolic blood pressure. The results are validated against blood pressure variation obtained from a Mindray Patient Monitor. Furthermore, the pulse wave velocity computed from the obtained PTTD is compared with the pulse wave velocity obtained from the color Doppler ultrasound system and is found to be in good agreement. The major advantage of the PTTD measurement via FBGPRs is that the data acquisition system employed can simultaneously acquire pulse pressure waveforms from both FBGPRs placed at carotid and radial arterial sites with a single time scale, which eliminates time synchronization complexity. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

FRP-Confined Clay Brick Masonry Assemblages under Axial Compression: Experimental and Analytical Investigations

Unreinforced masonry (URM) structures that are in need of repair and rehabilitation constitute a significant portion of building stock worldwide. The successful application of fiber-reinforced polymers (FRP) for repair and retrofitting of reinforced-concrete (RC) structures has opened new avenues for strengthening URM structures with FRP materials. The present study analyzes the behavior of FRP-confined masonry prisms under monotonic axial compression. Masonry comprising of burnt clay bricks and cement-sand mortar (generally adopted in the Indian subcontinent) having E-b/E-m ratio less than one is employed in the study. The parameters considered in the study are, (1) masonry bonding pattern, (2) inclination of loading axis to the bed joint, (3) type of FRP (carbon FRP or glass FRP), and (4) grade of FRP fabric. The performance of FRP-confined masonry prisms is compared with unconfined masonry prisms in terms of compressive strength, modulus of elasticity and stress-strain response. The results showed an enhancement in compressive strength, modulus of elasticity, strain at peak stress, and ultimate strain for FRP-confined masonry prisms. The FRP confinement of masonry resulted in reducing the influence of the inclination of the loading axis to the bed joint on the compressive strength and failure pattern. Various analytical models available in the literature for the prediction of compressive strength of FRP-confined masonry are assessed. New coefficients are generated for the analytical model by appending experimental results of the current study with data available in the literature. (C) 2014 American Society of Civil Engineers.

Analysis of Wrist Pulse Signals Using Spatial Features in Time Domain

Wrist pulse signal contains more important information about the health status of a person and pulse signal diagnosis has been employed in oriental medicine since very long time. In this paper we have used signal processing techniques to extract information from wrist pulse signals. For this purpose we have acquired radial artery pulse signals at wrist position noninvasively for different cases of interest. The wrist pulse waveforms have been analyzed using spatial features. Results have been obtained for the case of wrist pulse signals recorded for several subjects before exercise and after exercise. It is shown that the spatial features show statistically significant changes for the two cases and hence they are effective in distinguishing the changes taking place due to exercise. Support vector machine classifier is used to classify between the groups, and a high classification accuracy of 99.71% is achieved. Thus this paper demonstrates the utility of the spatial features in studying wrist pulse signals obtained under various recording conditions. The ability of the model to distinguish changes occurring under two different recording conditions can be potentially used for health care applications.

Statistical Analysis of Wrist Pulse Signals Obtained Under Different Food Intake Conditions

It is well known that wrist pulse signals contain information about the status of health of a person and hence diagnosis based on pulse signals has assumed great importance since long time. In this paper the efficacy of signal processing techniques in extracting useful information from wrist pulse signals has been demonstrated by using signals recorded under two different experimental conditions viz. before lunch condition and after lunch condition. We have used Pearson's product-moment correlation coefficient, which is an effective measure of phase synchronization, in making a statistical analysis of wrist pulse signals. Contour plots and box plots are used to illustrate various differences. Two-sample t-tests show that the correlations show statistically significant differences between the groups. Results show that the correlation coefficient is effective in distinguishing the changes taking place after having lunch. This paper demonstrates the ability of the wrist pulse signals in detecting changes occurring under two different conditions. The study assumes importance in view of limited literature available on the analysis of wrist pulse signals in the case of food intake and also in view of its potential health care applications.

Study of Wrist Pulse Signals Using a Bi-Modal Gaussian Model

Wrist pulse signals contain important information about the health of a person and hence diagnosis based on pulse signals has assumed great importance. In this paper we demonstrate the efficacy of a two term Gaussian model to extract information from pulse signals. Results have been obtained by conducting experiments on several subjects to record wrist pulse signals for the cases of before exercise and after exercise. Parameters have been extracted from the recorded signals using the model and a paired t-test is performed, which shows that the parameters are significantly different between the two groups. Further, a recursive cluster elimination based support vector machine is used to perform classification between the groups. An average classification accuracy of 99.46% is obtained, along with top classifiers. It is thus shown that the parameters of the Gaussian model show changes across groups and hence the model is effective in distinguishing the changes taking place due to the two different recording conditions. The study has potential applications in healthcare.

Joint Strength and Wall Deformation Characteristics of a Single-Cell Geocell Subjected to Uniaxial Compression

Geocells are three-dimensional expandable panels with a wide range of applications in geotechnical engineering. A geocell is made up of many internally connected single cells. The current study discusses the joint strength and the wall deformation characteristics of a single cell when it is subjected to uniaxial compression. The study helps to understand the causes for the failure of the single cell in a cellular confinement system. Experimental studies were conducted on single cells with cell pockets filled up with three different infill materials, namely silty clay, sand, and the aggregates. The results of the experimental study revealed that the deformation of the geocell wall decreases with the increase in the friction angle of the infill material. Experimental results were also validated using numerical simulations carried out using Lagrangian analysis software. The experiment and the numerical results were found to be in good agreement with each other. A simple analytical model based on the theory of thin cylinders is also proposed to calculate the accumulated strain of the geocell wall. This model operates under a simple elastic solution framework. The proposed model slightly overestimates the strains as compared with experimental and numerical values. (C) 2014 American Society of Civil Engineers.

Study of wrist pulse signals using time domain spatial features

Blood travels throughout the body and thus its flow is modulated by changes in body condition. As a consequence, the wrist pulse signal contains important information about the status of the human body. In this work we have employed signal processing techniques to extract important information from these signals. Radial artery pulse pressure signals are acquired at wrist position noninvasively for several subjects for two cases of interest, viz. before and after exercise, and before and after lunch. Further analysis is performed by fitting a bi-modal Gaussian model to the data and extracting spatial features from the fit. The spatial features show statistically significant (p < 0.001) changes between the groups for both the cases, which indicates that they are effective in distinguishing the changes taking place due to exercise or food intake. Recursive cluster elimination based support vector machine classifier is used to classify between the groups. A high classification accuracy of 99.71% is achieved for the exercise case and 99.94% is achieved for the lunch case. This paper demonstrates the utility of certain spatial features in studying wrist pulse signals obtained under various experimental conditions. The ability of the spatial features in distinguishing changing body conditions can be potentially used for various healthcare applications. (C) 2015 Elsevier Ltd. All rights reserved.

A low-power, low-cost soil-moisture sensor using dual-probe heat-pulse technique

This paper presents the development and testing of an integrated low-power and low-cost dual-probe heat-pulse (DPHP) soil-moisture sensor in view of the electrical power consumed and affordability in developing countries. A DPHP sensor has two probes: a heater and a temperature sensor probe spaced 3 mm apart from the heater probe. Supply voltage of 3.3V is given to the heater-coil having resistance of 33 Omega power consumption of 330 mW, which is among the lowest in this category of sensors. The heater probe is 40 mm long with 2 mm diameter and hence is stiff enough to be inserted into the soil. The parametric finite element simulation study was performed to ensure that the maximum temperature rise is between 1 degrees C and 5 degrees C for wet and dry soils, respectively. The discrepancy between the simulation and experiment is less than 3.2%. The sensor was validated with white clay and tested with red soil samples to detect volumetric water-content ranging from 0% to 30%. The sensor element is integrated with low-power electronics for amplifying the output from thermocouple sensor and TelosB mote for wireless communication. A 3.7V lithium ion battery with capacity of 1150 mAh is used to power the system. The battery is charged by a 6V and 300 mA solar cell array. Readings were taken in 30 min intervals. The life-time of DPHP sensor node is around 3.6 days. The sensor, encased in 30 mm x 20 mm x 10 mm sized box, and integrated with electronics was tested independently in two separate laboratories for validating as well as investigating the dependence of the measurement of soil-moisture on the density of the soil. The difference in the readings while repeating the experiments was found out to be less than 0.01%. Furthermore, the effect of ambient temperature on the measurement of soil-moisture is studied experimentally and computationally. (C) 2015 Elsevier B.V. All rights reserved.