An Efficiency-Focused Design of Direct-DC Loads in Buildings

Despite the recent interest in direct current (DC) power distribution in buildings, the market for DC-ready loads remains small. The existing DC loads in various products or research test beds are not always designed to efficiently leverage the benefits of DC. This work addresses a pressing need for a study into the development of efficient DC loads. In particular, it focuses on documenting and demonstrating how to best leverage a DC input to eliminate or improve conversion stages in a load’s power converter. This work identifies how typical building loads can benefit from DC input, including bath fans, refrigerators, task lights, and zone lighting. It then details the development of several prototypes that demonstrate efficiency savings with DC. The most efficient direct-DC loads are explicitly designed for DC from the ground up, rather than from an AC modification

Parallel solution of high-order numerical schemes for solving incompressible flows

A new parallel numerical scheme for solving incompressible steady-state flows is presented. The algorithm uses a finite-difference approach to solving the Navier-Stokes equations. The algorithms are scalable and expandable. They may be used with only two processors or with as many processors as are available. The code is general and expandable. Any size grid may be used. Four processors of the NASA LeRC Hypercluster were used to solve for steady-state flow in a driven square cavity. The Hypercluster was configured in a distributed-memory, hypercube-like architecture. By using a 50-by-50 finite-difference solution grid, an efficiency of 74 percent (a speedup of 2.96) was obtained

Bayesian Semi-parametric Expected Shortfall Forecasting in Financial Markets

Bayesian semi-parametric estimation has proven effective for quantile estimation in general and specifically in financial Value at Risk forecasting. Expected short-fall is a competing tail risk measure, involving a conditional expectation beyond a quantile, that has recently been semi-parametrically estimated via asymmetric least squares and so-called expectiles. An asymmetric Gaussian density is proposed allowing a likelihood to be developed that leads to Bayesian semi-parametric estimation and forecasts of expectiles and expected shortfall. Further, the conditional autoregressive expectile class of model is generalised to two fully nonlinear families. Adaptive Markov chain Monte Carlo sampling schemes are employed for estimation in these families. The proposed models are clearly favoured in an empirical study forecasting eleven financial return series: clear evidence of more accurate expected shortfall forecasting, compared to a range of competing methods is found. Further, the most favoured models are those estimated by Bayesian methods

An Approach for Dynamic Grids

An approach is presented for the generation of two-dimensional, structured, dynamic grids. The grid motion may be due to the motion of the boundaries of the computational domain or to the adaptation of the grid to the transient, physical solution. A time-dependent grid is computed through the time integration of the grid speeds which are computed from a system of grid speed equations. The grid speed equations are derived from the time-differentiation of the grid equations so as to ensure that the dynamic grid maintains the desired qualities of the static grid. The grid equations are the Euler-Lagrange equations derived from a variational statement for the grid. The dynamic grid method is demonstrated for a model problem involving boundary motion, an inviscid flow in a converging-diverging nozzle during startup, and a viscous flow over a flat plate with an impinging shock wave. It is shown that the approach is more accurate for transient flows than an approach in which the grid speeds are computed using a finite difference with respect to time of the grid. However, the approach requires significantly more computational effort

Tolerance Specification of Robot Kinematic Parameters Using an Experimental Design Technique

This paper presents the tolerance specification of robot kinematic parameters using the Taguchi method. The concept of employing inner and outer orthogonal arrays to identify the significant parameters and select the optimal tolerance range for each parameter is proposed. The performance measure based on signal-to-noise ratios (S/N) using the Taguchi method is validated by Monte Carlo simulations. Finally, a step-by-step tolerance specification methodology is developed and illustrated with a planar two-link manipulator and a five-degree-of-freedom Rhino robot

Global magnetohydrodynamic simulation of the 15 March 2013 coronal mass ejection event-Interpretation of the 30-80 MeV proton flux

The coronal mass ejection (CME) event on 15 March 2013 is one of the few solar events in Cycle 24 that produced a large solar energetic particle (SEP) event and severe geomagnetic activity. Observations of SEP from the ACE spacecraft show a complex time-intensity SEP profile that is not easily understood with current empirical SEP models. In this study, we employ a global three-dimensional (3-D) magnetohydrodynamic (MHD) simulation to help interpret the observations. The simulation is based on the H3DMHD code and incorporates extrapolations of photospheric magnetic field as the inner boundary condition at a solar radial distance (r) of 2.5 solar radii. A Gaussian-shaped velocity pulse is imposed at the inner boundary as a proxy for the complex physical conditions that initiated the CME. It is found that the time-intensity profile of the high-energy (>10 MeV) SEPs can be explained by the evolution of the CME-driven shock and its interaction with the heliospheric current sheet and the nonuniform solar wind. We also demonstrate in more detail that the simulated fast-mode shock Mach number at the magnetically connected shock location is well correlated (r_(cc) ≥ 0.7) with the concurrent 30–80 MeV proton flux. A better correlation occurs when the 30–80 MeV proton flux is scaled by r^(−1.4)(r_(cc) = 0.87). When scaled by r^(−2.8), the correlation for 10–30 MeV proton flux improves significantly from r_(cc) = 0.12 to r_(cc) = 0.73, with 1 h delay. The present study suggests that (1) sector boundary can act as an obstacle to the propagation of SEPs; (2) the background solar wind is an important factor in the variation of IP shock strength and thus plays an important role in manipulation of SEP flux; (3) at least 50% of the variance in SEP flux can be explained by the fast-mode shock Mach number. This study demonstrates that global MHD simulation, despite the limitation implied by its physics-based ideal fluid continuum assumption, can be a viable tool for SEP data analysis

Implications of Air Ingress Induced by Density-Difference Driven Stratified Flow

One of the design basis accidents for the Next Generation Nuclear Plant (NGNP), a high temperature gas-cooled reactor, is air ingress subsequent to a pipe break. Following a postulated double-ended guillotine break in the hot duct, and the subsequent depressurization to nearly reactor cavity pressure levels, air present in the reactor cavity will enter the reactor vessel via density-gradient-driven-stratified flow. Because of the significantly higher molecular weight and lower initial temperature of the reactor cavity air-helium mixture, in contrast to the helium in the reactor vessel, the air-helium mixture in the cavity always has a larger density than the helium discharging from the reactor vessel through the break into the reactor cavity. In the later stages of the helium blowdown, the momentum of the helium flow decreases sufficiently for the heavier cavity air-helium mixture to intrude into the reactor vessel lower plenum through the lower portion of the break. Once it has entered, the heavier gas will pool at the bottom of the lower plenum. From there it will move upwards into the core via diffusion and density-gradient effects that stem from heating the air-helium mixture and from the pressure differences between the reactor cavity and the reactor vessel. This scenario (considering density-gradient-driven stratified flow) is considerably different from the heretofore commonly used scenario that attributes movement of air into the reactor vessel and from thence to the core region via diffusion. When density-gradient-driven stratified flow is considered as a contributing phenomena for air ingress into the reactor vessel, the following factors contribute to a much earlier natural circulation-phase in the reactor vessel: (a) density-gradient-driven stratified flow is a much more rapid mechanism (at least one order of magnitude) for moving air into the reactor vessel lower plenum than diffusion, and consequently, (b) the diffusion dominated phase begins with a much larger flow area and a much shorter distance for air to move into the core than earlier scenarios that attribute all air ingress from the reactor cavity into the core to diffusion only. Hence, consideration of the density-gradient-driven stratified flow phenomena will likely lead to more rapid air ingress into the core and also the presence of more air for core graphite oxidation than the widely-used air ingress attributed solely to diffusion. This paper discusses the density-gradient-driven stratified flow phenomena and the implications of considering this behavior on the progression of the air ingress event. Preliminary calculations are used to underline the importance of considering the density-gradient driven stratified flow phenomena in subsequent validation experiments and software development for analyzing VHTR scenarios