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DOE OSTI2013

Enhancement of NEST capabilities for simulating low-energy recoils in liquid xenon

The Noble Element Simulation Technique (NEST) is an extensive collection of models explaining both the scintillation light and ionization yields of noble elements as a function of particle type (nuclear recoils, electron recoils, alphas), electric field, and incident energy or energy loss (dE/dx). It is packaged as C++ code for Geant4 that implements said models, overriding the default model which does not account for certain complexities, such as the reduction in yields for nuclear recoils (NR) compared to electron recoils (ER). We present in this paper improvements to the existing NEST models and updates to the code which make the package even more realistic and turn it into a more full-fledged Monte Carlo simulation. All available liquid xenon data on NR and ER to date have been taken into consideration in arriving at the current models. Finally and furthermore, NEST addresses the question of the magnitude of the light and charge yields of nuclear recoils, including their electric field dependence, thereby helping to understand the capabilities of liquid xenon detectors for detection or exclusion of a low-mass dark matter WIMP.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2021

Quality Control Methods for Advanced Metering Infrastructure Data

While urban-scale building energy modeling is becoming increasingly common, it currently lacks standards, guidelines, or empirical validation against measured data. Empirical validation necessary to enable best practices is becoming increasingly tractable. The growing prevalence of advanced metering infrastructure has led to significant data regarding the energy consumption within individual buildings, but is something utilities and countries are still struggling to analyze and use wisely. In partnership with the Electric Power Board of Chattanooga, Tennessee, a crude OpenStudio/EnergyPlus model of over 178,000 buildings has been created and used to compare simulated energy against actual, 15-min, whole-building electrical consumption of each building. In this study, classifying building type is treated as a use case for quantifying performance associated with smart meter data. This article attempts to provide guidance for working with advanced metering infrastructure for buildings related to: quality control, pathological data classifications, statistical metrics on performance, a methodology for classifying building types, and assess accuracy. Advanced metering infrastructure was used to collect whole-building electricity consumption for 178,333 buildings, define equations for common data issues (missing values, zeros, and spiking), propose a new method for assigning building type, and empirically validate gaps between real buildings and existing prototypes using industry-standard accuracy metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Atomistic simulations of tungsten surface evolution under low-energy neon implantation

Tungsten is a candidate material for the divertor of fusion reactors, where it will be subject to a high flux of particles coming from the fusion plasma as well as a significant heat load. Under helium plasma exposure in fusion-reactor-like conditions, a nanostructured morphology is known to form on the tungsten surface in certain temperature and incident energy ranges, although the formation mechanism is not fully established. A recent experimental study (Yajima et al 2013 Plasma Sci. Technol. 15 282-6) using neon or argon exposure did not produce similar nanostructure. Here, this article presents molecular dynamics simulations of neon implantation in tungsten aimed at investigating the surface evolution and elucidating the role of noble gas mass in fuzz formation. Finally, in contrast to helium, neon impacts can sputter both tungsten and previously implanted neon atoms. The shorter range of neon ions, along with sputtering, limit the formation of large bubbles and likely prevents nanostructure formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Assessment of Existing OpenStudio Measures: Reviews, Interviews, and Future Developments

OpenStudio Measure development is continuously in progress and greatly propelled by the collaborative efforts within the building energy modeling community. To ensure the widespread adoption and benefit of OpenStudio Measures, developers must understand the current status of Measure development and the needs of OpenStudio Measure users. The first step involves a comprehensive review of existing content to prevent redundancy and gain insights into how OpenStudio Measures are used in the building energy modeling community. This knowledge can then be integrated into the Measure development process, and the expertise of practitioners and OpenStudio Measure users can be leveraged to shape future Measures. Numerous OpenStudio Measures have been created and shared on the Building Component Library (BCL). The BCL is an open-source repository housing various OpenStudio-related resources, including building component blocks, descriptive metadata, and Measures describing modifications to building energy models. The OpenStudio Measures in BCL encompass a wide range of energy conservation Measures from basic lighting power reduction to complex HVAC model transformation. They also enable users to generate customized reports and facilitate the integration of energy simulation with other analytical processes. This report presents review of 272 currently available OpenStudio Measures in BCL. The OpenStudio Measures were reviewed by category and subcategory. These Measures are summarized by their functionalities and keywords. To gain insights into how OpenStudio Measures are used in building energy modeling community, interviews were conducted. A total of 12 interview responses were collected from 6 individuals in the industry and 6 individuals in academia. The knowledge acquired from reviewing the existing Measures and interview results will be integrated into the Measure development process, and the expertise of practitioners and OpenStudio Measure users will be leveraged to shape future Measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

A Comprehensive Analysis of Energy and Daylighting Impact of Window Shading Systems and Control Strategies on Commercial Buildings in the United States

Commercial buildings consume approximately 1.9 EJ of energy in the United States, 50% of which is for heating, cooling, and lighting applications. It is estimated that windows contribute up to 34% of the energy used for heating and cooling. However, window retrofits are not often undertaken to increase energy efficiency because of the high cost and disruptive nature of window installation. Highly efficient window technologies would also need shading devices for glare prevention and visual comfort. An automated window shading system with an appropriate control strategy is a technology that can reduce energy demand, maintain occupant comfort, and enhance the aesthetics and privacy of the built environment. However, the benefits of the automated shades currently used by the shading industry are not well studied. The topic merits an analysis that will help building owners, designers and engineers, and utilities make informed decisions using knowledge of the impact of this technology on energy consumption, peak demand, daylighting, and occupant comfort. This study uses integrated daylight and whole-building energy simulation to evaluate the performance of various control strategies that the shading industry uses in commercial office buildings. The analysis was performed for three different vintages of medium office buildings at six different locations in United States. The results obtained show the control strategies enabled cooling energy savings of up to 40% using exterior shading, and lighting energy savings of up to 25%. The control strategies described can help building engineers and researchers explore different control methods used to control shading in actual buildings but rarely discussed in the literature. This information will give researchers the opportunity to investigate potential improvements in current technologies and their performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Enabling Detailed Energy Analyses via the Technology Performance Exchange: Preprint

One of the key tenets to increasing adoption of energy efficiency solutions in the built environment is improving confidence in energy performance. Current industry practices make extensive use of predictive modeling, often via the use of sophisticated hourly or sub-hourly energy simulation programs, to account for site-specific parameters (e.g., climate zone, hours of operation, and space type) and arrive at a performance estimate. While such methods are highly precise, they invariably provide less than ideal accuracy due to a lack of high-quality, foundational energy performance input data. The Technology Performance Exchange was constructed to allow the transparent sharing of foundational, product-specific energy performance data, and leverages significant, external engineering efforts and a modular architecture to efficiently identify and codify the minimum information necessary to accurately predict product energy performance. This strongly-typed database resource represents a novel solution to a difficult and established problem. One of the most exciting benefits is the way in which the Technology Performance Exchange's application programming interface has been leveraged to integrate contributed foundational data into the Building Component Library. Via a series of scripts, data is automatically translated and parsed into the Building Component Library in a format that is immediately usable to the energy modeling community. This paper (1) presents a high-level overview of the project drivers and the structure of the Technology Performance Exchange; (2) offers a detailed examination of how technologies are incorporated and translated into powerful energy modeling code snippets; and (3) examines several benefits of this robust workflow.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2014

Antisites in III-V semiconductors: Density functional theory calculations

Density functional based simulation, corrected for finite size effects, is used to investigate systematically the formation of antisite defects in III-V semiconductors (III = Al, Ga, and In and V = P, As, and Sb). Different charge states are modelled as a function of the Fermi level and under different growth conditions. The formation energies of group III antisites (III{sub V}{sup q}) decrease with increasing covalent radius of the group V atom though not group III radius, whereas group V antisites (V{sub III}{sup q}) show a consistent decrease in formation energies with increase in group III and group V covalent radii. In general, III{sub V}{sup q} defects dominate under III-rich conditions and V{sub III}{sup q} under V-rich conditions. Comparison with equivalent vacancy formation energy simulations shows that while antisite concentrations are always dominant under stoichiometric conditions, modest variation in growth or doping conditions can lead to a significantly higher concentration of vacancies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Vertical meteorological patterns and their impact on the energy demand of tall buildings

In accordance with the developing economy and growing population, an increasing number of tall buildings have been constructed over the last 20 years. In 2017, there were 144 new buildings worldwide that were 200 m or greater in height; 50% of these buildings were in China. Due to the vertical gradient impact of meteorological parameters, the energy performance of tall buildings differs from that of general buildings. Few studies exist on vertical meteorological changes using measured data at different heights. Most studies on dynamic energy simulation simulate meteorological parameters using models. This study explores vertical meteorological patterns using hourly dry-bulb temperature, relative humidity, and wind speed data from 2007 to 2017 for a 325 m meteorological tower in Beijing. The temperature decreased significantly with increasing altitude (~0.9 °C per 100 m), while the daily temperature difference decreased with increasing altitude. The absolute humidity did not change significantly with height. The wind speed increased with altitude at approximately 2 m/s per 100 m. The building simulation showed that the annual heating load at a height of 320 m increased by 85% from that at 8 m; the annual cooling load decreased by 20%. Such significant differences in thermal loads for 300-m-tall buildings confirm the need to consider vertical meteorological differences in building performance simulations for tall buildings. A greater number of measurement points at different heights improve the simulation accuracy. Finally, guidance on selecting the heights for vertical metrological measurements is provided based on the influences of building thermal loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1970

Experimental investigation of a high-intensity RF radiant energy source to simulate the thermal environment in a nuclear light bulb engine

High intensity RF radiant energy source to simulate thermal environment in nuclear light bulb engine

Roman, W. C.↗

DOE OSTI2026

Energy and Comfort Impacts of High Performance Facades in Office Buildings

Building facades have a major effect on energy use, occupant comfort, and well-being. Yet adoption of high-performance facades is often slowed by limited data and unclear cost benefits. To address this gap, Oak Ridge National Laboratory, in collaboration with the Facade Tectonics Institute, conducted whole-building energy simulations to evaluate fenestration technologies for small and medium office buildings across three weather locations: hot (Tampa, Florida, weather zone 2A), mixed (New York, New York, weather zone 4A), and cold (Rochester, Minnesota, weather zone 6A). The simulations included parametric variations in window-to-wall ratio (30%–70%), U-values (0.1–1 Btu/h∙ft 2 ∙°F), solar heat gain coefficients (0.2–0.8), and solar control strategies and devices (e.g., interior shades and switchable glazing). Performance metrics included annual cooling, heating, and total heating, ventilation and air-conditioning (HVAC) energy use intensity, as well as nonenergy factors such as useful daylight illuminance, glare frequency, and thermal comfort during typical office hours (8 a.m.–6 p.m.). Results indicate that cooling energy consumption is most sensitive to solar heat gain coefficient (SHGC) in hot weather, whereas heating energy consumption is strongly influenced by U-value in cold weather. Total HVAC reflects these trade-offs, showing up to 60% difference for a window in total HVAC energy use intensity between different combinations of U-value and SHGC. Daylight dimming generally reduces cooling loads but can increase heating demands in colder locations. Interior solar shades improve useful daylight and reduce discomfort glare, whereas switchable glazing delivers the largest cooling reductions in hot weather but may increase heating loads in winter by limiting passive solar gains. Thermal comfort improves with lower window-to-wall ratios and lower SHGC in hot locations and with lower U-values in cold locations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Computational study of Gleevec and G6G reveals molecular determinants of kinase inhibitor selectivity

Gleevec is a potent inhibitor of Abl tyrosine kinase but not of the highly homologous c-Src kinase. Because the ligand binds to an inactive form of the protein in which an Asp-Phe-Gly structural motif along the activation loop adopts a so-called DFG-out conformation, it was suggested that binding specificity was controlled by a “conformational selection” mechanism. In this context, the binding affinity displayed by the kinase inhibitor G6G poses an intriguing challenge. Although it possesses a chemical core very similar to that of Gleevec, G6G is a potent inhibitor of both Abl and c-Src kinases. Both inhibitors bind to the DFG-out conformation of the kinases, which seems to be in contradiction with the conformational selection mechanism. To address this issue and display the hidden thermodynamic contributions affecting the binding selectivity, molecular dynamics free energy simulations with explicit solvent molecules were carried out. Relative to Gleevec, G6G forms highly favorable van der Waals dispersive interactions upon binding to the kinases via its triazine functional group, which is considerably larger than the corresponding pyridine moiety in Gleevec. Upon binding of G6G to c-Src, these interactions offset the unfavorable free energy cost of the DFG-out conformation. When binding to Abl, however, G6G experiences an unfavorable free energy penalty due to steric clashes with the phosphate-binding loop, yielding an overall binding affinity that is similar to that of Gleevec. Such steric clashes are absent when G6G binds to c-Src, due to the extended conformation of the phosphate-binding loop.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Analysis of Daylighting Requirements within ASHRAE Standard 90.1

Pacific Northwest National Laboratory (PNNL), under the Building Energy Codes Program (BECP) funded by U.S. Department of Energy (DOE), provides support to the ASHRAE/IES/IESNA Standard 90.1(Standard 90.1) Standing Standards Project Committee (SSPC 90.1) and its subcommittees. In an effort to provide the ASHRAE SSPC 90.1 with data that will improve the daylighting and fenestration requirements in the Standard, PNNL collaborated with Heschong Mahone Group (HMG), now part of TRC Solutions. Combining EnergyPlus, a whole-building energy simulation software developed by DOE, with Radiance, a highly accurate illumination modeling software (Ward 1994), the daylighting requirements within Standard 90.1 were analyzed in greater detail. The initial scope of the study was to evaluate the impact of the fraction of window area compared to exterior wall area (window-to-wall ratio (WWR)) on energy consumption when daylighting controls are implemented. This scope was expanded to study the impact of fenestration visible transmittance (VT), electric lighting controls and daylighted area on building energy consumption.

90.1↗

DOE OSTI2017

URBANopt (Urban Renewable Building And Neighborhood Optimization) [SWR-16-33]

URBANopt is a user interface for creating and running district and city scale building energy simulations. The framework is built around the OpenStudio Urban Measures which are part of the OpenStudio project. Building footprints, building height, building type, and other data can be imported from public records or other sources. Footprints and locations for new buildings and district systems can also be specified. OpenStudio Measures are used to create starting point energy models and to model energy design features and efficiency measures for each building. URBANopt allows a user to pose several scenarios such as “what if 30% of the commercial retail buildings added roof top solar” or “what if all elementary schools converted to ground source heat pumps” and then visualize the impacts at a district or city scale. URBANopt is capable of modeling existing buildings, new construction, and district energy systems. URBANopt can be used to explore options for achieving Zero Energy across a collection of buildings (e.g., Zero Energy Districts).

Source record↗

DOE OSTI2016

Urban Renewable Building And Neighborhood Optimization

Source record↗

DOE OSTI2016

Energy consumption analysis of constant voltage and constant current operations in capacitive deionization

Here we report our studies to compare energy consumption of a CDI cell in constant voltage (CV) and constant current (CC) operations, with a focus on understanding the underlying physics of consumption patterns. The comparison is conducted under conditions that the CV and CC operations result in the same amounts of input charge and within identical charging phase durations. We present two electrical circuit models to simulate energy consumption in charging phase: one is a simple RC circuit model, and the other a transmission line circuit model. We built and tested a CDI cell to validate the transmission line model, and performed a series of experiments to compare CV versus CC operation under the condition of equal applied charge and charging duration. The experiments show that CC mode consumes energy at 33.8 kJ per mole of ions removed, which is only 28% of CV mode energy consumption (120.6 kJ/mol), but achieves similar level of salt removals. Lastly, together, the models and experiment support our major conclusion that CC is more energy efficient than CV for equal charge and charging duration. The models also suggest that the lower energy consumption of CC in charging is due to its lower resistive dissipation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Flexible Reinforcement Learning Framework for Building Control using EnergyPlus-Modelica Energy Models

In recent years, reinforcement learning (RL) methods have been greatly enhanced by leveraging deep learning approaches. RL methods applied to building control have shown potential in many applications due to their ability to complement or replace conventional methods such as model-based or rule-based controls. However, RL-based building control software is likely tailored either to one target building system or to a specific RL method so that significant additional effort would be required to customize the RL-based controller for use in other building systems or with other RL approaches. Also, RL-based building controls usually depend on building energy simulations to train controllers, so emulating building dynamics (i.e., thermal dynamics and control dynamics) and capturing sub-hourly dynamic profiles are crucial to further the development of effective RL-based building control methods. To address these challenges, we present an open source RL-based control software employing a high-fidelity hybrid EnergyPlus-Modelica building energy model which emulates building dynamics at 1-minute resolution. This software consists of decoupled components (environment, building emulator, control agent, and RL algorithm), which allows for quick prototyping and benchmarking of standard RL algorithms in different systems; for example, a single component can be replaced without revising all of the software. To demonstrate this software framework, we conducted a benchmark study using an EnergyPlus-Modelica building energy model for a Chicago office building with an RL-based controller to dynamically control the chilled water temperature setpoint and the air handling unit supply air temperature setpoint on selected floors.

Lee, Joon-Yong↗

DOE OSTI2013

A Variable Refrigerant Flow Heat Pump Computer Model in EnergyPlus

This paper provides an overview of the variable refrigerant flow heat pump computer model included with the Department of Energy's EnergyPlusTM whole-building energy simulation software. The mathematical model for a variable refrigerant flow heat pump operating in cooling or heating mode, and a detailed model for the variable refrigerant flow direct-expansion (DX) cooling coil are described in detail.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Residential Natural Gas Demand Response Potential during Extreme Cold Events in Electricity-Gas Coupled Energy Systems

In regions where natural gas is used for both power generation and heating buildings, extreme cold weather events can place the electrical system under enormous stress and challenge the ability to meet residential heating and electric demands. Residential demand response has long been used in the power sector to curtail summer electric load, but these types of programs in general have not seen adoption in the natural gas sector during winter months. Natural gas demand response (NG-DR) has garnered interest given recent extreme cold weather events in the United States; however, the magnitude of savings and potential impacts—to occupants and energy markets—are not well understood. We present a case-study analysis of the technical potential for residential natural gas demand response in the northeast United States that utilizes diverse whole-building energy simulations and high-performance computing. Our results show that NG-DR applied to residential heating systems during extreme cold-weather conditions could reduce natural gas demand by 1–29% based on conservative and aggressive strategies, respectively. This indicates a potential to improve the resilience of gas and electric systems during stressful events, which we examine by estimating the impact on energy costs and electricity generation from natural gas. We also explore relationships between hourly indoor temperatures, demand response, and building envelope efficiency.

03 NATURAL GAS↗