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  1. Liquid–vapor phase change including evaporation, boiling, and condensation is a ubiquitous process found in power generation, desalination, thermal management, building heating and cooling, and additive manufacturing. The dynamics of droplets and bubbles during phase change including nucleation, growth, and departure critically influence the thermal transport performance and system efficiency. This review will highlight recent advancements using static and dynamic strategies to manipulate droplets and bubbles for phase change applications and beyond.
    Free, publicly-accessible full text available September 26, 2023
  2. Free, publicly-accessible full text available May 23, 2023
  3. Free, publicly-accessible full text available December 6, 2022
  4. Abstract. The lower-order moments of the drop size distribution (DSD) have generally been considered difficult to retrieve accurately from polarimetric radar data because these data are related to higher-order moments. For example, the 4.6th moment is associated with a specific differential phase and the 6th moment with reflectivity and ratio of high-order moments with differential reflectivity. Thus, conventionally, the emphasis has been to estimate rain rate (3.67th moment) or parameters of the exponential or gamma distribution for the DSD. Many double-moment “bulk” microphysical schemes predict the total number concentration (the 0th moment of the DSD, or M0) and the mixing ratio (or equivalently, the 3rd moment M3). Thus, it is difficult to compare the model outputs directly with polarimetric radar observations or, given the model outputs, forward model the radar observables. This article describes the use of double-moment normalization of DSDs and the resulting stable intrinsic shape that can be fitted by the generalized gamma (G-G) distribution. The two reference moments are M3 and M6, which are shown to be retrievable using the X-band radar reflectivity, differential reflectivity, and specific attenuation (from the iterative correction of measured reflectivity Zh using the total Φdp constraint, i.e., the iterative ZPHI method). Alongmore »with the climatological shape parameters of the G-G fit to the scaled/normalized DSDs, the lower-order moments are then retrieved more accurately than possible hitherto. The importance of measuring the complete DSD from 0.1 mm onwards is emphasized using, in our case, an optical array probe with 50 µm resolution collocated with a two-dimensional video disdrometer with about 170 µm resolution. This avoids small drop truncation and hence the accurate calculation of lower-order moments. A case study of a complex multi-cell storm which traversed an instrumented site near the CSU-CHILL radar is described for which the moments were retrieved from radar and compared with directly computed moments from the complete spectrum measurements using the aforementioned two disdrometers. Our detailed validation analysis of the radar-retrieved moments showed relative bias of the moments M0 through M2 was <15 % in magnitude, with Pearson’s correlation coefficient >0.9. Both radar measurement and parameterization errors were estimated rigorously. We show that the temporal variation of the radar-retrieved mass-weighted mean diameter with M0 resulted in coherent “time tracks” that can potentially lead to studies of precipitation evolution that have not been possible so far.« less
  5. Firewalls are the first line of defense in cyber-security. They prevent malicious and unwanted network traffic entering the perimeters of organizations. The strength of a firewall lies in its policy configuration which is also a crucial task for any security administrator. The scope of Firewall policies have been expanding to address ever changing security requirements of an organization. In this process, new security parameters have been researched and one such parameter is temporal policy. Firewall temporal policy is a firewall policy that allows or denies a network packet based on specified day and time range of the policy in addition to the packet filtering rules. Firewall vendors such as CISCO and Palo Alto have already featured firewall temporal policies in their security products. Inclusion of temporal policies in firewall policies results in additional overhead for storing and scanning Firewall policies. As temporal policies are represented in week days and time, they consume considerable amount of space. In this paper, we present an innovative and efficient method for representing temporal policies which includes compact representation of temporal policies and detection of anomalies using set operations. Our approach significantly reduces the storage requirement and improves the scanning functionality of firewall. We alsomore »present a new method of creating policy sets based on week days.« less