This review paper examines mechanisms controlling IGSCC in selected LWR components. Emphasis is placed on identifying material microstructures and microchemistries which promote susceptibility to premature failure. Two important examples are evaluated in some detail: stainless steel pipe cracking and primary-side SCC of alloy 600 steam generator tubing. In each case, grain boundary segregation ...

In this paper we present a high order weighted essentially non-oscillatory (WENO) scheme for solving a multi-class extension of the Lighthill-Whitham-Richards (LWR) model. We first review the multi-class LWR model and present some of its analytical properties. We then present the WENO schemes, which were originally designed for computational fluid dynamics problems and for solving hyperbolic co...

This article is motivated by the practical problem of highway traffic estimation using velocity measurements from GPS enabled mobile devices such as cell phones. In order to simplify the estimation procedure, a velocity model for highway traffic is constructed, which results in a dynamical system in which observation the operator is linear. This article presents a new scalar hyperbolic partial ...

Abstrak.Model matematika arus lalu lintas pertama kali dikembangkan oleh Lighthill, Whitham dan Richards pada tahun 1956 yang dikenal dengan model (LWR). Dalam LWR, fungsi kecepatan adalah unsur terpenting. makalah ini digunakan underwood karena memiliki tingkat kesesuaian terbaik dibadingkan lainnya. Metode beda hingga implisit untuk menemukan solusi numerik LWR Underwood. Konvergensi metode d...

Long welded rails (LWR) are preferred in metro rail systems because they provide a smooth ride. They extremely sturdy, require less maintenance and safe to travel at higher speeds. Rail structure interaction (RSI), especially additional longitudinal stresses rail, is the major concern LWR. UIC standards limitations of stresses. This paper studies characteristics forces long used one Metro Railw...

An algorithm for decomposing large tally data in Monte Carlo particle simulations is proposed, analyzed, and implemented/tested in a production Monte Carlo code, OpenMC. The algorithm relies on disjoint sets of compute processes and servers of which the former simulate particles moving through the geometry and the latter runs in a continuous loop receiving scores from the compute processors and...

We employ a nonlinear, nonparametric method to model the stochastic behavior of changes in several short and long term U.S. interest rates. We apply a nonlinear autoregression to the series using the locally weighted regression (LWR) estimation method, a nearest-neighbor method, and evaluate the forecasting performance with a measure of root mean square error (RMSE). We compare the forecasting ...

Locally weighted regression (LWR) was created as a nonparametric method that can approximate a wide range of functions, is computationally efficient, and can learn continually from very large amounts of incrementally collected data. As an interesting feature, LWR can regress on non-stationary functions, a beneficial property, for instance, in control problems. However, it does not provide a pro...

This paper investigates the application of value-function-based reinforcement learning to a smart energy control system, specifically the task of controlling an HVAC system to minimize energy while satisfying residents’ comfort requirements. In theory, value-function-based reinforcement learning methods can solve control problems such as this one optimally. However, since choosing an appropriat...