Tight Load Balancing via Randomized Local Search

We consider the following balls-into-bins process with $n$ bins and $m$ balls: each ball is equipped with a mutually independent exponential clock of rate 1. Whenever a ball's clock rings, the ball samples a random bin and moves there if the number of balls in the sampled bin is smaller than in its current bin. This simple process models a typical load balancing problem where users (balls) seek a selfish improvement of their assignment to resources (bins). From a game theoretic perspective, this is a randomized approach to the well-known Koutsoupias-Papadimitriou model, while it is known as randomized local search (RLS) in load balancing literature. Up to now, the best bound on the expected time to reach perfect balance was $O\left({(\ln n)}^2+\ln(n)\cdot n^2/m\right)$ due to Ganesh, Lilienthal, Manjunath, Proutiere, and Simatos (Load balancing via random local search in closed and open systems, Queueing Systems, 2012). We improve this to an asymptotically tight $O\left(\ln(n)+n^2/m\right)$. Our analysis is based on the crucial observation that performing "destructive moves" (reversals of RLS moves) cannot decrease the balancing time. This allows us to simplify problem instances and to ignore "inconvenient moves" in the analysis.Comment: 24 pages, 3 figures, preliminary version appeared in proceedings of 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS'17

Compression-compression fatigue of Pd_(43)Ni_(10)Cu_(27)P_(20) metallic glass foam

Compression-compression fatigue testing of metallic-glass foam is performed. A stress-life curve is constructed, which reveals an endurance limit at a fatigue ratio of about 0.1. The origin of fatigue resistance of this foam is identified to be the tendency of intracellular struts to undergo elastic and reversible buckling, while the fatigue process is understood to advance by anelastic strut buckling leading to localized plasticity (shear banding) and ultimate strut fracture. Curves of peak and valley strain versus number of cycles coupled with plots of hysteresis loops and estimates of energy dissipation at various loading cycles confirm the four stages of foam-fatigue

Alloying and Processing Effects on the Aqueous Corrosion Behavior of High-Entropy Alloys

The effects of metallurgical factors on the aqueous corrosion behavior of high-entropy alloys (HEAs) are reviewed in this article. Alloying (e.g., Al and Cu) and processing (e.g., heat treatments) effects on the aqueous corrosion behavior of HEAs, including passive film formation, galvanic corrosion, and pitting corrosion, are discussed in detail. Corrosion rates of HEAs are calculated using electrochemical measurements and the weight-loss method. Available experimental corrosion data of HEAs in two common solutions [sulfuric acid (0.5 M H$_{2}$SO$_{4}$) and salt water (3.5 weight percent, wt.%, NaCl)], such as the corrosion potential (E$_{corr}$), corrosion current density (i$_{corr}$), pitting potential (E$_{pit}$), and passive region (ΔE), are summarized and compared with conventional corrosion-resistant alloys. Possible directions of future work on the corrosion behavior of HEAs are suggested

Nindestructive Evaluation of Metal Matrix Composite Products with Implanted Defects

The Westinghouse Science and Technology Center has undertaken a program to develop nondestructive evaluation (NDE) techniques for characterizing the internal structure of SiC particle-reinforced aluminum matrix composites at critical stages during fabrication [1–5]. Because of the large number of processing variables in the manufacture of metal matrix composites (MMC), the likelihood of having detrimental discontinuities is high. The detection of potential defects early in the processing cycle would increase the overall system yield, lower costs, and enhance final product quality [4]. The aim of this investigation was to develop and conduct NDE at various stages of MMC fabrication, correlate the results with microstructural characterization, and establish qualified product quality assurance processes. A large-scale billet was fabricated specially using powder metallurgy techniques to facilitate this objective. The billet contained implanted silicon-carbide particle and aluminum powder clusters as inspection targets. The billet was subsequently extruded into a primary cylindrical extrusion, and finally into a flat plate. The NDE objectives included evaluating the detectability and mapping the implanted defects through each of the processing steps. Comprehensive evaluation of MMC structures requires the use of multiple NDE techniques, including ultrasonic, eddy current, and radiographic testing. This paper concentrates on the results of the ultrasonic investigations. Our experimental approach was: (1) fabricate a MMC billet with intentionally placed inhomogeneities; (2) develop and implement NDE techniques to characterize the MMC internal structure; (3) extend the NDE techniques to intermediate processing and final product forms; and (4) correlate the NDE data with microstructural characterization and mechanical testing results

Physics-Based Machine-Learning Approach for Modeling the Temperature-Dependent Yield Strengths of Medium- or High-Entropy Alloys

Machine learning is becoming a powerful tool to predict temperature-dependent yield strengths (YS) of structural materials, particularly for multi-principal-element systems. However, successful machine-learning predictions depend on the use of reasonable machine-learning models. Here, we present a comprehensive and up-to-date overview of a bilinear log model for predicting temperature-dependent YS of medium-entropy or high-entropy alloys (MEAs or HEAs). In this model, a break temperature, Tbreak, is introduced, which can guide the design of MEAs or HEAs with attractive high-temperature properties. Unlike assuming black-box structures, our model is based on the underlying physics, incorporated in form of a priori information. A technique of global optimization is employed to enable the concurrent optimization of model parameters over low- and high-temperature regimes, showing that the break temperature is consistent across YS and ultimate strength for a variety of HEA compositions. A high-level comparison between YS of MEAs/HEAs and those of nickel-based superalloys reveal superior strength properties of selected refractory HEAs. For reliable operations, the temperature of a structural component, such as a turbine blade, made from refractory alloys may need to stay below Tbreak. Once above Tbreak, phase transformations may start taking place, and the alloy may begin losing structural integrity