Experimental correlations for transient soot measurement in diesel exhaust aerosol with light extinction, electrical mobility and diffusion charger sensor techniques

A study of soot measurement deviation using a diffusion charger sensor with three dilution ratios was conducted in order to obtain an optimum setting that can be used to obtain accurate measurements in terms of soot mass emitted by a light-duty diesel engine under transient operating conditions. The paper includes three experimental phases: an experimental validation of the measurement settings in steady-state operating conditions; evaluation of the proposed setting under the New European Driving Cycle; and a study of correlations for different measurement techniques. These correlations provide a reliable tool for estimating soot emission from light extinction measurement or from accumulation particle mode concentration. There are several methods and correlations to estimate soot concentration in the literature but most of them were assessed for steady-state operating points. In this case, the correlations are obtained by more than 4000 points measured in transient conditions. The results of the new two correlations, with less than 4% deviation from the reference measurement, are presented in this paper.Bermúdez, V.; Pastor Soriano, JV.; López, JJ.; Campos, D. (2014). Experimental correlations for transient soot measurement in diesel exhaust aerosol with light extinction, electrical mobility and diffusion charger sensor techniques. Measurement Science and Technology. 25(6):1-13. doi:10.1088/0957-0233/25/6/065204S113256Davidson, C. I., Phalen, R. F., & Solomon, P. A. (2005). Airborne Particulate Matter and Human Health: A Review. Aerosol Science and Technology, 39(8), 737-749. doi:10.1080/02786820500191348Pope, C. A., Bates, D. V., & Raizenne, M. E. (1995). Health effects of particulate air pollution: time for reassessment? Environmental Health Perspectives, 103(5), 472-480. doi:10.1289/ehp.95103472Giechaskiel, B., Dilara, P., Sandbach, E., & Andersson, J. (2008). Particle measurement programme (PMP) light-duty inter-laboratory exercise: comparison of different particle number measurement systems. Measurement Science and Technology, 19(9), 095401. doi:10.1088/0957-0233/19/9/095401Park, K., Kittelson, D. B., & McMurry, P. H. (2004). Structural Properties of Diesel Exhaust Particles Measured by Transmission Electron Microscopy (TEM): Relationships to Particle Mass and Mobility. Aerosol Science and Technology, 38(9), 881-889. doi:10.1080/027868290505189LUO, C.-H., LEE, W.-M., & LIAW, J.-J. (2009). Morphological and semi-quantitative characteristics of diesel soot agglomerates emitted from commercial vehicles and a dynamometer. Journal of Environmental Sciences, 21(4), 452-457. doi:10.1016/s1001-0742(08)62291-3Matti Maricq, M. (2007). Chemical characterization of particulate emissions from diesel engines: A review. Journal of Aerosol Science, 38(11), 1079-1118. doi:10.1016/j.jaerosci.2007.08.001Smith, O. I. (1981). Fundamentals of soot formation in flames with application to diesel engine particulate emissions. Progress in Energy and Combustion Science, 7(4), 275-291. doi:10.1016/0360-1285(81)90002-2Haynes, B. S., & Wagner, H. G. (1981). Soot formation. Progress in Energy and Combustion Science, 7(4), 229-273. doi:10.1016/0360-1285(81)90001-0Bockhorn, H. (Ed.). (1994). Soot Formation in Combustion. Springer Series in Chemical Physics. doi:10.1007/978-3-642-85167-4Tree, D. R., & Svensson, K. I. (2007). Soot processes in compression ignition engines. Progress in Energy and Combustion Science, 33(3), 272-309. doi:10.1016/j.pecs.2006.03.002Kennedy, I. M. (1997). Models of soot formation and oxidation. Progress in Energy and Combustion Science, 23(2), 95-132. doi:10.1016/s0360-1285(97)00007-5Buonanno, G., Dell’Isola, M., Stabile, L., & Viola, A. (2011). Critical aspects of the uncertainty budget in the gravimetric PM measurements. Measurement, 44(1), 139-147. doi:10.1016/j.measurement.2010.09.037Symonds, J. P. R., Reavell, K. S. J., Olfert, J. S., Campbell, B. W., & Swift, S. J. (2007). Diesel soot mass calculation in real-time with a differential mobility spectrometer. Journal of Aerosol Science, 38(1), 52-68. doi:10.1016/j.jaerosci.2006.10.001Luque de Castro, M. D., & Priego-Capote, F. (2010). Soxhlet extraction: Past and present panacea. Journal of Chromatography A, 1217(16), 2383-2389. doi:10.1016/j.chroma.2009.11.027Wang, S. C., & Flagan, R. C. (1990). Scanning Electrical Mobility Spectrometer. Aerosol Science and Technology, 13(2), 230-240. doi:10.1080/02786829008959441Snegirev, A. Y., Makhviladze, G. ., & Roberts, J. . (2001). The effect of particle coagulation and fractal structure on the optical properties and detection of smoke. Fire Safety Journal, 36(1), 73-95. doi:10.1016/s0379-7112(00)00037-0Zhou, Z.-Q., Ahmed, T. U., & Y. Choi, M. (1998). Measurement of dimensionless soot extinction constant using a gravimetric sampling technique. Experimental Thermal and Fluid Science, 18(1), 27-32. doi:10.1016/s0894-1777(98)10005-5Arregle, J., Bermúdez, V., Serrano, J. R., & Fuentes, E. (2006). Procedure for engine transient cycle emissions testing in real time. Experimental Thermal and Fluid Science, 30(5), 485-496. doi:10.1016/j.expthermflusci.2005.10.002Bermúdez, V., Luján, J. M., Serrano, J. R., & Pla, B. (2008). Transient particle emission measurement with optical techniques. Measurement Science and Technology, 19(6), 065404. doi:10.1088/0957-0233/19/6/065404Giechaskiel, B., Maricq, M., Ntziachristos, L., Dardiotis, C., Wang, X., Axmann, H., … Schindler, W. (2014). Review of motor vehicle particulate emissions sampling and measurement: From smoke and filter mass to particle number. Journal of Aerosol Science, 67, 48-86. doi:10.1016/j.jaerosci.2013.09.003Lapuerta, M., Armas, O., & Gómez, A. (2003). Diesel Particle Size Distribution Estimation from Digital Image Analysis. Aerosol Science and Technology, 37(4), 369-381. doi:10.1080/02786820300970Desantes, J. M., Bermúdez, V., Molina, S., & Linares, W. G. (2011). Methodology for measuring exhaust aerosol size distributions using an engine test under transient operating conditions. Measurement Science and Technology, 22(11), 115101. doi:10.1088/0957-0233/22/11/115101Roessler, D. M. (1982). Diesel particle mass concentration by optical techniques. Applied Optics, 21(22), 4077. doi:10.1364/ao.21.004077Park, D., Kim, S., An, M., & Hwang, J. (2007). Real-time measurement of submicron aerosol particles having a log-normal size distribution by simultaneously using unipolar diffusion charger and unipolar field charger. Journal of Aerosol Science, 38(12), 1240-1245. doi:10.1016/j.jaerosci.2007.09.00

When the Crypto in Cryptocurrencies Breaks: Bitcoin Security under Broken Primitives

Digital currencies such as Bitcoin rely on cryptographic primitives to operate. However, past experience shows that cryptographic primitives do not last forever: increased computational power and advanced cryptanalysis cause primitives to break and motivate the development of new ones. It is therefore crucial for maintaining trust in a cryptocurrency to anticipate such breakage. We present the first systematic analysis of the effect of broken primitives on Bitcoin. We analyze the ways in which Bitcoin’s core cryptographic building blocks can break and the subsequent effect on the main Bitcoin security guarantees. Our analysis reveals a wide range of possible effects depending on the primitive and type of breakage, ranging from minor privacy violations to a complete breakdown of the currency. Our results lead to several suggestions for the Bitcoin migration plans and insights for other cryptocurrencies in case of broken or weakened cryptographic primitives