Power management in networked devices

Networks are one of the most significant developments in computing and a hallmark of modern society. However, along with increasing efficiency and productivity, both at home and in the workplace, networks have costs. One cost is the additional energy that electronic devices consume when attached to networks. Power management, a standard feature of modern PCs, was primarily developed to increase battery lifetime in laptop PCs, which historically were not network-connected when using battery power. Today, however, many laptops are connected to a network - typically a Wi-Fi network - as are the majority of desktop computers. Three key drivers of energy use are induced consumption by devices prevented by network connections from entering low-power states, increasing link data rates that inherently consume more energy for the network interfaces, and proliferation of network-connected displays that actively update and display data when no one is present.     

Bayesian Inference for a New Class of Distributions on Equivalence Classes of Three-Dimensional Orientations With Applications to Materials Science

Experiments in materials science investigating cubic crystalline structures often collect data which are in truth equivalence classes of crystallographically symmetric orientations. These intend to represent how lattice structures of particles are orientated relative to a reference coordinate system. Motivated by a materials science application, we formulate parametric probability models for “unlabeled orientation data.” This amounts to developing models on equivalence classes of three-dimensional rotations. We use a flexible existing model class for random rotations (called uniform-axis-random-spin models) to induce probability distributions on the equivalence classes of rotations. We develop one-sample Bayesian inference for the parameters in these models, and compare this methodology to some likelihood-based approaches. We also contrast the new parametric analysis of unlabeled orientation data with other analyses that proceed as if the data have been preprocessed into honest orientation data. Supplementary materials for this article are available online.     

Energetic analysis of binding of progesterone and 5{beta}-androstane-3,17-dione to anti-progesterone antibody DB3 using molecular dynamics and free energy calculations

Molecular dynamics simulations and molecular mechanics–Poisson–Boltzmannsurface area (MM-PBSA) free energy calculations were used tostudy the energetics of the binding of progesterone (PRG) and5ß-androstane-3,17-dione (5AD) to anti-PRG antibodyDB3. Although the two steroids bind to DB3 in different orientations,their binding affinities are of the same magnitude, 1 nM forPRG and 8 nM for 5AD. The calculated relative binding free energyof the steroids, 8.8 kJ/mol, is in fair agreement with the experimentalenergy, 5.4 kJ/mol. In addition, computational alanine scanningwas applied to study the role of selected amino acid residuesof the ligand-binding site on the steroid cross-reactivity.The electrostatic and van der Waals components of the totalbinding free energies were found to favour more the bindingof PRG, whereas solvation energies were more favourable forthe binding of 5AD. The differences in the free energy componentsare due to the binding of the A rings of the steroids to differentbinding pockets: PRG is bound to a pocket in which electrostaticantibody–steroid interactions are dominating, whereas5AD is bound to a pocket in which van der Waals and hydrophobicinteractions dominate.     

Dynamic thermal modeling of distribution transformers

A comprehensive test program was performed on a 2500-kVA oil natural-air natural cooling mode (ONAN) transformer without external cooling. It is shown that the hot-spot to top-oil temperature gradient depends on the transformer construction. The top-oil time constant formula, which has already been defined and validated in the authors' previous work related to transformers with external cooling, is modified in order to take into account the basic design differences. The results are verified by thermocouple measurements and tests at varying loading current. The hot-spot and top-oil temperature responses predicted by the IEEE Loading Guide, Annex G, are also compared to the measured values.     

Use of advanced composite curves for assessing cost-effective HEN retrofit II. Case studies

In this paper a graphical method for cost-effective heat exchanger network (HEN) retrofit is applied in two cases. The method uses information about the placement of heaters/coolers in the existing HEN to identify the potential for cost-effective retrofit. In Case 1 detailed matrix calculations are compared with the results from the graphical method, and in Case 2 the graphical method is compared with earlier published results.In Case 1, the retrofit investment cost for a certain heat recovery was more than doubled for a HEN with heaters placed at high temperature, in comparison to a HEN with heaters placed at low temperature, although both HENs have the same stream data and utility requirements. In a HEN with heaters placed at both low and high temperatures, the heaters placed low could be detached as cheaply as the case with all heaters at low temperatures. The heaters at high temperatures were cheaper to detach than in the case with all heaters at high temperatures, since the initial changes to heaters at low temperatures keep the total investment cost down.Case 2 demonstrates how the graphical method is used to identify potential heat recovery. The conclusions from this method were compared with detailed calculations. Results showed that the PBP increased by a factor of four, when heat saving increased from the level suggested by the advanced curves to the maximum possible heat recovery.     

Use of advanced composite curves for assessing cost-effective HEN retrofit I: Theory and concepts

This paper presents the theory and concepts of a graphical method for heat exchanger network (HEN) retrofit that gives new insights about the complexity and possible solutions of different retrofit alternatives. The method uses knowledge about the placement of heaters/coolers in the existing HEN to evaluate the potential for cost-effective retrofit. One general result this method predicts is that the closer to the pinch the existing heaters/coolers are located, the higher the potential for cost-effective retrofit. Networks that are badly engineered from a grass-root perspective, prove to be a good basis for cost-effective retrofits.     

Vector S-parameter measurements of the superconductingvortex flow transistor

Vector S-parameter measurements of the superconducting vortex flow transistor (VFT) are presented. The measurements were obtained for frequencies up to 100 MHz on VFTs that had a calculated transmit-time cutoff frequency of 5 GHz. An equivalent circuit model that includes calculations of the VFT transresistance, input inductance, and feedthrough capacitance is derived from these measurements. The measurements are limited to an upper frequency of 100 MHz due to crosstalk in the low-impedance system     

Data network equipment energy use and savings potential in buildings

Network connectivity has become nearly ubiquitous, and the energy use of the equipment required for this connectivity is growing. Network equipment consists of devices that primarily switch and route Internet Protocol (IP) packets from a source to a destination, and this category specifically excludes edge devices like PCs, servers and other sources, and sinks of IP traffic. This paper presents the results of a study of network equipment energy use and includes case studies of networks in a campus, a medium commercial building, and a typical home. The total energy use of network equipment is the product of the stock of equipment in use, the power of each device, and their usage patterns. This information was gathered from market research reports, broadband market penetration studies, field metering, and interviews with network administrators and service providers. We estimate that network equipment in the USA used 18 TWh, or about 1% of building electricity, in 2008 and that consumption is expected to grow at roughly 6% per year to 23 TWh in 2012; world usage in 2008 was 51 TWh. This study shows that office building network switches and residential equipment are the two largest categories of energy use consuming 40% and 30% of the total respectively. We estimate potential energy savings for different scenarios using forecasts of equipment stock and energy use, and savings estimates range from 20% to 50% based on full market penetration of efficient technologies.