In-situ Monitoring the Setting Behavior of Foamed Concrete Using Ultrasonic Pulse Velocity Method

The applicability of ultrasonic pulse velocity （UPV） method to in-situ monitor setting and hardening process of foamed concrete （FC） was systematically investigated. The UPVs of various FC pastes were automatically and continuously measured by a specially designed ultrasonic monitoring apparatus （UMA）. Ultrasonic tests were performed on FC mixtures with different density （300, 500, 800 and 1 000 kg/m3）, and different fly ash contents （0%, 20%, 40% and 60%）. The influence of curing temperatures （20, 40, 60 and 80~C） was also studied. The experimental results show that three characteristic stages can be clearly identified during the setting process of an arbitrary FC paste： dormant stage, acceleration stage, and deceleration stage. Wet density, fly ash content, and curing temperature have great impact on setting behavior. A stepwise increase of the wet density results in shorter dormant stage and larger final UPV. Hydration reaction rate is obviously promoted with an increase in curing temperature. However, the addition fly ash retards the microstn,lcture formation. To aid in comparing with the ultrasonic results, the consistence spread test and Vicat needle test （VNT） were also conducted. A correlation between ultrasonic and VNT results was also established to evaluate the initial and final setting time of the FC mixtures. Finally, certain ranges of UPV with reasonable widths were suggested for the initial and final setting time, respectively.

Accuracy of the ultrasonic cardiac output monitor in healthy term neonates during postnatal circulatory adaptation

Background Echocardiography is regarded as a gold standard for measuring hemodynamic values. The ultrasonic cardiac output monitor （USCOM） is a new method for measuring hemodynamics and could provide non-invasive point of care guidance. So far, there are no published USCOM reference values for neonates, nor has USCOM＇s accuracy been established in this population. We aimed to determine the accuracy and clinical utility of the USCOM in healthy neonates relative to published echocardiographic data, to establish normal hemodynamic parameters that it measures, and to assess the possible role of USCOM as an alternative to echocardiography as a trend monitor. Methods Right and left heart hemodynamics of 90 normal neonates were measured during circulatory adaptation over the first three days of life using the USCOM and automated oscillotonometry. Results Heart rate showed a significant decline from days one to three, from 126 to 120 （P〈0.001）. Systolic, diastolic and mean arterial pressures all increased significantly from 66 to 71 mmHg, 33 to 38 mmHg and 44 to 49 mmHg, respectively （P 〈0.001 in each case）. Right ventricular cardiac index （RV-CI） showed no change with a mean of 5.07 L.minl.m2. Left ventricular cardiac index （LV-CI） declined from 3.43 to 3.00 L.minl.m2 （P 〈0.001）. RV-CI exceeded LV-CI on all three days by a mean of 61%. The systemic vascular resistance index （SVRI）, based on LV-CI, increased significantly over the three days from 1083 to 1403 dyne.sec.cm5.m2 （P 〈0.001）. Conclusions Normal neonatal hemodynamic values, as indicated by USCOM, were established. LV-CI measurement showed excellent agreement with published echocardiographic studies. RV-CI was constant and exceeded LV-CI for all three days of this study. It may be falsely high due to flow velocity measurement errors arising from the pulmonary branch arteries, and may represent a limitation of the USCOM method. The progressive rise of arterial pressure and SVRI despite a declining LV-CI may indicate functional closure of the ductus arteriosus, with the greatest change occurring within the first 24 hours. Evidence of closure of the foramen ovale was not observed.

Battery state-of-charge estimation using machine learning analysis of ultrasonic signatures

The potential of acoustic signatures to be used for State-of-Charge(SoC)estimation is demonstrated using artificial neural network regression models.This approach represents a streamlined method of processing the entire acoustic waveform instead of performing manual,and often arbitrary,waveform peak selection.For applications where computational economy is prioritised,simple metrics of statistical significance are used to formally identify the most informative waveform features.These alone can be exploited for SoC inference.It is further shown that signal portions representing both early and late interfacial reflections can correlate highly with the SoC and be of predictive value,challenging the more common peak selection methods which focus on the latter.Although later echoes represent greater through-thickness coverage,and are intuitively more information-rich,their presence is not guaranteed.Holistic waveform treatment offers a more robust approach to correlating acoustic signatures to electrochemical states.It is further demonstrated that transformation into the frequency domain can reduce the dimensionality of the problem significantly,while also improving the estimation accuracy.Most importantly,it is shown that acoustic signatures can be used as sole model inputs to produce highly accurate SoC estimates,without any complementary voltage information.This makes the method suitable for applications where redundancy and diversification of SoC estimation approaches is needed.Data is obtained experimentally from a 210 mAh LiCoO2/graphite pouch cell.Mean estimation errors as low as 0.75%are achieved on a SoC scale of 0-100%.