Engineering topics

Zhu, Yanqiu

Publications and source records attributed to Zhu, Yanqiu.

5 records

DOE OSTI2024

Embedding Reverse Electron Transfer Between Stably Bare Cu Nanoparticles and Cation‐Vacancy CuWO 4

Cu nanoparticles (NPs) have attracted widespread attention in electronics, energy, and catalysis. However, conventionally synthesized Cu NPs face some challenges such as surface passivation and agglomeration in applications, which impairs their functionalities in the physicochemical properties. Here, the issues above by engineering an embedded interface of stably bare Cu NPs on the cation-vacancy CuWO 4 support is addressed, which induces the strong metal-support interactions and reverse electron transfer. Various atomic-scale analyses directly demonstrate the unique electronic structure of the embedded Cu NPs with negative charge and anion oxygen protective layer, which mitigates the typical degradation pathways such as oxidation in ambient air, high-temperature agglomeration, and CO poisoning adsorption. Kinetics and in situ spectroscopic studies unveil that the embedded electron-enriched Cu NPs follow the typical Eley-Rideal mechanism in CO oxidation, contrasting the Langmuir-Hinshelwood mechanism on the traditional Cu NPs. This mechanistic shift is driven by the Coulombic repulsion in anion oxygen layer, enabling its direct reaction with gaseous CO to form the easily desorbed monodentate carbonate.

Cu nanoparticles↗

NASA NTRS2007

Cloud Motion Vectors from MISR using Sub-pixel Enhancements

The operational retrieval of height-resolved cloud motion vectors by the Multiangle Imaging SpectroRadiometer on the Terra satellite has been significantly improved by using sub-pixel approaches to co-registration and disparity assessment, and by imposing stronger quality control based on the agreement between independent forward and aft triplet retrievals. Analysis of the fore-aft differences indicates that CMVs pass the basic operational quality control 67% of the time, with rms differences - in speed of 2.4 m/s, in direction of 17 deg, and in height assignment of 290 m. The use of enhanced quality control thresholds reduces these rms values to 1.5 m/s, 17 deg and 165 m, respectively, at the cost of reduced coverage to 45%. Use of the enhanced thresholds also eliminates a tendency for the rms differences to increase with height. Comparison of CMVs from an earlier operational version that had slightly weaker quality control, with 6-hour forecast winds from the Global Modeling and Assimilation Office yielded very low bias values and an rms vector difference that ranged from 5 m/s for low clouds to 10 m/s for high clouds.

Davies, Roger↗

NASA NTRS2002

Evaluation of the DAO Retrospective Data Assimilation System

We have developed and implemented a retrospective data assimilation system (RDAS) as an upgrade to the operational DAO/Terra data assimilation system. This formulation aims at improving analysis over filter analysis by the dynamically consistent incorporation of observation information past a given analysis time. The current implementation of the RDAS uses the adjoint of the tangent linear model of a simplified version of the Terra general circulation model and extensions to the physical-space statistical analysis system to propagate observation information back in time. The RDAS adopts the same assumptions of the regular data assimilation system, particularly, no explicit propagation of error covariances are involved therefore rendering a procedure that is computationally affordable. In this study, we show results of experiments conducted to investigate the performance of the 6-hour (lag-1) RDAS. Statistical results obtained over one month during a winter season indicate that the RDAS represents considerable improvement over the regular assimilation. Plans for implementation of the RDAS capability in our new finite-volume data assimilation system will also be presented at the time of the conference.

Zhu, Yanqiu↗

NASA NTRS2000

The DAO Retrospective Data Assimilation System

The fixed-lag Kalman smoother of Cohn et al. (1994), or a version of a more computationally feasible approximation of it developed by Todling et al. (1998), is under implementation at the Data Assimilation Office (DAO) to build a retrospective data assimilation system (RDAS). The initial version of the RDAS uses the physical-space statistical analysis system and a modification of the incremental analysis update (IAU) procedure of Bloom et al. (1996); a follow up version of the RDAS Nill require the use of the adjoint of the DAO general circulation model (developed by Y. Yang and M Navon). The retrospective procedure is designed to produce improved analyses as well as improved assimilated fields consequently providing an improved climate representation through data assimilation.

Todling, Richardo↗

NASA NTRS1999

The Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

The Kalman filter is the optimal filter in the presence of known Gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions (e.g., Miller 1994). Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz (1963) model as well as more realistic models of the oceans (Evensen and van Leeuwen 1996) and atmosphere (Houtekamer and Mitchell 1998). A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter equations to allow for correct update of the ensemble members (Burgers 1998). The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to quite puzzling in that results of state estimate are worse than for their filter analogue (Evensen 1997). In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use Lorenz (1963) model to test and compare the behavior of a variety implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Zhu, Yanqiu↗