The Effect of High Efficiency Building Technologies and PV Generation on the Energy Profiles for Typical US Residences

The penetrations of high efficiency technologies and photovoltaic (PV) generation are increasing in the residential sector. Technologies such as improved insulation and efficient HVAC systems significantly affect the energy profile of a house. This effect varies due to climate characteristics, i.e. temperature, solar radiation, relative humidity, and wind speeds. The effect of other technologies, such as efficient water heaters, lighting, or kitchen appliances, is mainly governed by human behavior, which may be represented by a schedule. This paper studies the performance of both climate-influenced and scheduled household devices among different levels of efficiency through combined computational and experimental methods. Three houses were constructed by the Tennessee Valley Authority and were outfitted with robots that mimicked the occupation of a family. The houses represented three categories of residences, namely, typical builder, retrofit, and near net-zero-energy. With the energy and weather data collected from 2009 to 2014, a total of four house energy models were developed to account for equipment changes throughout the years. The studies performed using these models considered the behavior of the HVAC systems, PV system, and water heaters as well as climate effects

Virtual Power Plant Control for Large Residential Communities Using HVAC Systems for Energy Storage

Heating, ventilation, and air-conditioning (HVAC) systems use the most electricity of any household appliance in residential communities. HVAC system modeling facilitates the study of demand response (DR) at both the residential and power system levels. In this article, the equivalent thermal model of a reference house is proposed. Parameters for the reference house were determined based on the systematic study of experimental data obtained from fully instrumented field demonstrators. Energy storage capacity of HVAC systems is calculated and an equivalent state-of-charge is defined. The uniformity between HVAC systems and battery energy storage system is demonstrated by DR control. The aggregated HVAC load model is based on the reference house and considers a realistic distribution of HVAC parameters derived from one of the largest smart grid field demonstrators in rural America. A sequential DR scheme as part of a virtual power plant control is proposed to reduce both ramping rate and peak power at the aggregated level, while maintaining human comfort according to ASHRAE standards

Demand Response of HVACs in Large Residential Communities Based on Experimental Developments

Heating, ventilation, and air-conditioning (HVAC) systems contribute the largest electricity usage for a residential community. Modeling of the HVAC systems facilitate the study of demand response (DR) at both the residential and the power system level. In this paper, the equivalent thermal model of a reference house was proposed. Parameters for the reference house were determined based on the systematic study of experimental data obtained from fully instrumented field demonstrators. The aggregated HVAC load was modeled based on the reference house while considering a realistic distribution of HVAC parameters derived from data that was provided by one of the largest smart grid field demonstrators in rural America. A sequential DR as part of a Virtual Power Plant (VPP) control was proposed to reduce both ramping rate and peak power at the aggregated level, while maintaining human comfort according to ASHRAE standard

Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses

Despite the fact that the loss functions of deep neural networks are highly non-convex, gradient-based optimization algorithms converge to approximately the same performance from many random initial points. One thread of work has focused on explaining this phenomenon by characterizing the local curvature near critical points of the loss function, where the gradients are near zero, and demonstrating that neural network losses enjoy a no-bad-local-minima property and an abundance of saddle points. We report here that the methods used to find these putative critical points suffer from a bad local minima problem of their own: they often converge to or pass through regions where the gradient norm has a stationary point. We call these gradient-flat regions, since they arise when the gradient is approximately in the kernel of the Hessian, such that the loss is locally approximately linear, or flat, in the direction of the gradient. We describe how the presence of these regions necessitates care in both interpreting past results that claimed to find critical points of neural network losses and in designing second-order methods for optimizing neural networks.Comment: 18 pages, 5 figure

High-throughput small molecule screen identifies inhibitors of aberrant chromatin accessibility

Transcriptional regulators lacking enzymatic activity or binding pockets with targetable molecular features have typically been considered “undruggable,” and a reductionist approach based on identification of their molecular targets has largely failed. We have demonstrated that the Ewing sarcoma chimeric transcription factor, EWSR1-FLI1, maintains accessible chromatin at disease-specific regions. We adapted formaldehyde-assisted isolation of regulatory elements (FAIRE), an assay for accessible chromatin, to screen an epigenetically targeted small molecule library for compounds that reverse the disease-associated signature. This approach can be applied broadly for discovery of chromatin-based developmental therapeutics and offers significant advantages because it does not require the selection of a single molecular target. Using this approach, we identified a specific class of compounds with therapeutic potential

The Cold Peace: Russo-Western Relations as a Mimetic Cold War

In 1989–1991 the geo-ideological contestation between two blocs was swept away, together with the ideology of civil war and its concomitant Cold War played out on the larger stage. Paradoxically, while the domestic sources of Cold War confrontation have been transcended, its external manifestations remain in the form of a ‘legacy’ geopolitical contest between the dominant hegemonic power (the United States) and a number of potential rising great powers, of which Russia is one. The post-revolutionary era is thus one of a ‘cold peace’. A cold peace is a mimetic cold war. In other words, while a cold war accepts the logic of conflict in the international system and between certain protagonists in particular, a cold peace reproduces the behavioural patterns of a cold war but suppresses acceptance of the logic of behaviour. A cold peace is accompanied by a singular stress on notions of victimhood for some and undigested and bitter victory for others. The perceived victim status of one set of actors provides the seedbed for renewed conflict, while the ‘victory’ of the others cannot be consolidated in some sort of relatively unchallenged post-conflict order. The ‘universalism’ of the victors is now challenged by Russia's neo-revisionist policy, including not so much the defence of Westphalian notions of sovereignty but the espousal of an international system with room for multiple systems (the Schmittean pluriverse)

Utilizing computed tomography volumetry for size matching prior to lung transplantation: A case series

BACKGROUND: Appropriate size matching between donor and recipient is critical for successful pulmonary transplantation. Although surrogate measurements such as height and gender are often utilized to approximate predicted lung volume, these methods provide only a gross estimation with wide variability and poor predictive value. CASE DESCRIPTION: A single center exploratory study was conducted in which four patients underwent lung transplantation (LT) with pre-operative computed tomography (CT) volumetry obtained in both the donor and recipient to facilitate decision making regarding organ size and suitability. In four cases in which CT volumetry was used, the lung volumes calculated using surrogate measurements significantly overestimated both donor and recipient lung volumes quantified by CT volumetric analysis. All recipients underwent successful LT without necessary graft downsizing. CONCLUSIONS: This is an initial report of prospectively utilizing CT volumetry as an adjunct to decision-making regarding suitability of donor lungs. In these cases, CT volumetry facilitated the confident acceptance of donor lungs that were initially predicted to be oversized based on other clinical measures

Modeling Transport in Gas Chromatography Columns for the Micro-ChemLab

The gas chromatography (GC) column is a critical component in the microsystem for chemical detection ({mu}ChemLab{trademark}) being developed at Sandia. The goal is to etch a meter-long GC column onto a 1-cm{sup 2} silicon chip while maintaining good chromatographic performance. Our design strategy is to use a modeling and simulation approach. We have developed an analytical tool that models the transport and surface interaction process to achieve an optimized design of the GC column. This analytical tool has a flow module and a separation module. The flow module considers both the compressibility and slip flow effects that may significantly influence the gas transport in a long and narrow column. The separation module models analyte transport and physico-chemical interaction with the coated surface in the GC column. It predicts the column efficiency and performance. Results of our analysis will be presented in this paper. In addition to the analytical tool, we have also developed a time-dependent adsorption/desorption model and incorporated this model into a computational fluid dynamics (CFD) code to simulate analyte transport and separation process in GC columns. CFD simulations can capture the complex three-dimensional flow and transport dynamics, whereas the analytical tool cannot. Different column geometries have been studied, and results will be presented in this paper. Overall we have demonstrated that the modeling and simulation approach can guide the design of the GC column and will reduce the number of iterations in the device development