506 research outputs found

    Hydrodynamic signatures of stationary Marangoni-driven surfactant transport

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    We experimentally study steady Marangoni-driven surfactant transport on the interface of a deep water layer. Using hydrodynamic measurements, and without using any knowledge of the surfactant physico-chemical properties, we show that sodium dodecyl sulphate and Tergitol 15-S-9 introduced in low concentrations result in a flow driven by adsorbed surfactant. At higher surfactant concentration, the flow is dominated by the dissolved surfactant. Using Camphoric acid, whose properties are {\it a priori} unknown, we demonstrate this method's efficacy by showing its spreading is adsorption dominated

    The Atmosphere-Ocean Interface Layer of NASA's Goddard Earth Observing System Model and Data Assimilation System Volume 51

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    The Goddard Earth Observing System (GEOS) general circulation model (GCM) includes modules for sea surface temperature (SST) diurnal warming and cool-skin layers. To support the application of a coupled atmosphere-ocean data assimilation capability, the GCM needs to be flexible enough to support both coupled atmosphere ocean general circulation model (AOGCM) and atmosphere-only (AGCM) configurations, with only minor configuration changes at the user interface. This document presents a formulation of an atmosphere-ocean interface layer (AOIL) that serves this purpose. Previous work by Akella et al. (2017) described a version of a model for near-surface temperature variations, including both both diurnal warming and cool-skin effects, that has been used since 2017 in the near-real-time GEOS FP (forward processing) weather analysis and forecasting system. The diurnal cycle of SST in that version of the GEOS atmospheric data assimilation system (ADAS) undergoes a sharp decay in the late afternoon (local time). The updated AOIL presented here includes a modification of the similarity function used in the diurnal warming model. Results from offline model runs illustrate an improvement in the near-surface (less than 0:5m depth) diurnal cycle compared to the original formulation. The new formulation requires minimal parameter tuning, and the improvements are robust across long (several month) simulation periods. This new model formulation, however, retains some deficiences from the previous module, such as a small warm bias in calm wind conditions for water depths below 1m. Our future work would include surface salinification and sea-ice into the AOIL

    The 5f localization/delocalization in square and hexagonal americium monolayers: A FP-LAPW electronic structure study

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    The electronic and geometrical properties of bulk americium and square and hexagonal americium monolayers have been studied with the full-potential linearized augmented plane wave (FP-LAPW) method. The effects of several common approximations are examined: (1) non-spin polarization (NSP) vs. spin polarization (SP); (2) scalar-relativity (no spin-orbit coupling (NSO)) vs. full-relativity (i.e., with spin-orbit (SO) coupling included); (3) local-density approximation (LDA) vs. generalized-gradient approximation (GGA). Our results indicate that both spin polarization and spin orbit coupling play important roles in determining the geometrical and electronic properties of americium bulk and monolayers. A compression of both americium square and hexagonal monolayers compared to the americium bulk is also observed. In general, the LDA is found to underestimate the equilibrium lattice constant and give a larger total energy compared to the GGA calculations. While spin orbit coupling shows a similar effect on both square and hexagonal monolayer calculations regardless of the model, GGA versus LDA, an unusual spin polarization effect on both square and hexagonal monolayers is found in the LDA results as compared with the GGA results. The 5f delocalization transition of americium is employed to explain our observed unusual spin polarization effect. In addition, our results at the LDA level of theory indicate a possible 5f delocalization could happen in the americium surface within the same Am II (fcc crystal structure) phase, unlike the usually reported americium 5f delocalization which is associated with crystal structure change. The similarities and dissimilarities between the properties of an Am monolayer and a Pu monolayer are discussed in detail.Comment: 22 pages, 8 figure

    Combined local-density and dynamical mean field theory calculations for the compressed lanthanides Ce, Pr, and Nd

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    This paper reports calculations for compressed Ce (4f^1), Pr (4f^2), and Nd (4f^3) using a combination of the local-density approximation (LDA) and dynamical mean field theory (DMFT), or LDA+DMFT. The 4f moment, spectra, and the total energy among other properties are examined as functions of volume and atomic number for an assumed face-centered cubic (fcc) structure.Comment: 15 pages, 9 figure

    Enabling the Discovery of Recurring Anomalies in Aerospace System Problem Reports using High-Dimensional Clustering Techniques

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    This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining techniques to discover anomalies in free-text reports regarding system health and safety of two aerospace systems. We discuss two problems of significant importance in the aviation industry. The first problem is that of automatic anomaly discovery about an aerospace system through the analysis of tens of thousands of free-text problem reports that are written about the system. The second problem that we address is that of automatic discovery of recurring anomalies, i.e., anomalies that may be described m different ways by different authors, at varying times and under varying conditions, but that are truly about the same part of the system. The intent of recurring anomaly identification is to determine project or system weakness or high-risk issues. The discovery of recurring anomalies is a key goal in building safe, reliable, and cost-effective aerospace systems. We address the anomaly discovery problem on thousands of free-text reports using two strategies: (1) as an unsupervised learning problem where an algorithm takes free-text reports as input and automatically groups them into different bins, where each bin corresponds to a different unknown anomaly category; and (2) as a supervised learning problem where the algorithm classifies the free-text reports into one of a number of known anomaly categories. We then discuss the application of these methods to the problem of discovering recurring anomalies. In fact the special nature of recurring anomalies (very small cluster sizes) requires incorporating new methods and measures to enhance the original approach for anomaly detection. ?& pant 0

    Distributed Adaptive Attitude Synchronization of Multiple Spacecraft

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    This paper addresses the distributed attitude synchronization problem of multiple spacecraft with unknown inertia matrices. Two distributed adaptive controllers are proposed for the cases with and without a virtual leader to which a time-varying reference attitude is assigned. The first controller achieves attitude synchronization for a group of spacecraft with a leaderless communication topology having a directed spanning tree. The second controller guarantees that all spacecraft track the reference attitude if the virtual leader has a directed path to all other spacecraft. Simulation examples are presented to illustrate the effectiveness of the results.Comment: 13 pages, 11 figures. To appear in SCIENCE CHINA Technological Science

    Probabilistic Guarantees for Nonlinear Safety-Critical Optimal Control

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    Leveraging recent developments in black-box risk-aware verification, we provide three algorithms that generate probabilistic guarantees on (1) optimality of solutions, (2) recursive feasibility, and (3) maximum controller runtimes for general nonlinear safety-critical finite-time optimal controllers. These methods forego the usual (perhaps) restrictive assumptions required for typical theoretical guarantees, e.g. terminal set calculation for recursive feasibility in Nonlinear Model Predictive Control, or convexification of optimal controllers to ensure optimality. Furthermore, we show that these methods can directly be applied to hardware systems to generate controller guarantees on their respective systems

    Safety-Critical Controller Verification via Sim2Real Gap Quantification

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    The well-known quote from George Box states that: "All models are wrong, but some are useful." To develop more useful models, we quantify the inaccuracy with which a given model represents a system of interest, so that we may leverage this quantity to facilitate controller synthesis and verification. Specifically, we develop a procedure that identifies a sim2real gap that holds with a minimum probability. Augmenting the nominal model with our identified sim2real gap produces an uncertain model which we prove is an accurate representor of system behavior. We leverage this uncertain model to synthesize and verify a controller in simulation using a probabilistic verification approach. This pipeline produces controllers with an arbitrarily high probability of realizing desired safe behavior on system hardware without requiring hardware testing except for those required for sim2real gap identification. We also showcase our procedure working on two hardware platforms - the Robotarium and a quadruped

    Formal Verification of Safety Critical Autonomous Systems via Bayesian Optimization

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    As control systems become increasingly more complex, there exists a pressing need to find systematic ways of verifying them. To address this concern, there has been significant work in developing test generation schemes for black-box control architectures. These schemes test a black-box control architecture's ability to satisfy its control objectives, when these objectives are expressed as operational specifications through temporal logic formulae. Our work extends these prior, model based results by lower bounding the probability by which the black-box system will satisfy its operational specification, when subject to a pre-specified set of environmental phenomena. We do so by systematically generating tests to minimize a Lipschitz continuous robustness measure for the operational specification. We demonstrate our method with experimental results, wherein we show that our framework can reasonably lower bound the probability of specification satisfaction
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