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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 829 records · Page 46

Critical Role of Surface Energy in Guiding Crystallization of Solution-Coated Conjugated Polymer Thin Films

It is well-known that substrate surface properties have a profound impact on morphology of thin films solution coated atop and the resulting solid-state properties. However, design rules for guiding the substrate selection have not yet been established. Such design rules are particularly important for solution coated semiconducting polymers, as the substratedirected thin film morphology can impact charge transport properties by orders of magnitude. We hypothesize that substrate surface energies dictate the thin film morphology by modulating the free energy barrier to heterogeneous nucleation. To test this hypothesis, we systematically vary the substrate surface energy via surface functionalization techniques. We perform in-depth morphology and device characterizations to establish the relationship between substrate surface energy, thin film morphology and charge transport properties, employing a donor-accepter (D-A) conjugated polymer. Here, we find that decreasing the substrate surface energy progressively increases thin film crystallinity, degree of molecular ordering and extent of domain alignment. Notably, the enhanced morphology on the lowest surface energy substrate lead to a 10-fold increase in the charge carrier mobility. We further develop a free energy model relating the substrate surface energy to the penalty of heterogeneous nucleation from solution in the thin film geometry. The model correctly predicts the experimental trend, thereby validating our hypothesis. This work is a significant step towards establishing design rules and understanding the critical role of substrates in determining morphology of solution coated thin films.

36 MATERIALS SCIENCE↗

Generation and representation of synthetic smart meter data

Advanced energy algorithms running at big-data scale will be necessary to identify, realize, and verify energy savings to meet government and utility goals of building energy efficiency. Any algorithm must be well characterized and validated before it is trusted to run at these scales. Smart meter data from real buildings will ultimately be required for the development, testing, and validation of these energy algorithms and processes. However, for initial development and testing, smart meter data are difficult to work with due to privacy restrictions, noise from unknown sources, data accessibility, and other concerns which can complicate algorithm development and validation. This paper describes a new methodology to generate synthetic smart meter data of electricity use in buildings using detailed building energy modeling, which aims to capture the variability and stochastics of real energy use in buildings. The methodology can create datasets tailored to represent specific scenarios with known truth and controllable amounts of synthetic noise. Knowledge of ground truth also allows the development and validation of enhanced processes which leverage building metadata, such as building type or size (floor area), in addition to smart meter data. The methodology described in this paper includes the key influencing factors of real-world building energy use including weather data, occupant-driven loads, building operation and maintenance practices, and special events. Data formats to support workflows leveraging both synthetic meter data and associated metadata are proposed and discussed. Finally, example use cases of the synthetic meter data are described to illustrate potential applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Expansion of chromospheric matter in the gradual phase of solar flares

Interferometric observations at 17 GHz of several small X-ray flares are presented along with soft X-ray observations of preflare active regions to show that a large mass increase accompanies the formation of an X-ray hot region in the corona. The total amount of energy contained in a hot coronal region is estimated, and a model is proposed in which a significant amount of the hot matter is supplied to the corona from the chromosphere during each flare. According to this model, energy produced by some coronal instability is transported by thermal conduction to the chromosphere, where dense gas is heated and subsequently expands into the corona. It is shown that impulsive heating of the chromosphere by nonthermal electrons cannot be the energy source of this model because the total energy supplied to the hot region during the gradual phase must be much greater than that supplied during the impulsive phase.

Ohki, K.↗

Mandating better buildings: a global review of building codes and prospects for improvement in the United States

This paper provides a global overview of the design, implementation, and evolution of building energy codes. Reflecting alternative policy goals, building energy codes differ significantly across the United States, the European Union, and China. This review uncovers numerous innovative practices including greenhouse gas emissions caps per square meter of building space, energy performance certificates with retrofit recommendations, and inclusion of renewable energy to achieve “nearly zero-energy buildings”. These innovations motivated an assessment of an aggressive commercial building code applied to all US states, requiring both new construction and buildings with major modifications to comply with the latest version of the ASHRAE 90.1 Standards. Using the National Energy Modeling System (NEMS), we estimate that by 2035, such building codes in the United States could reduce energy for space heating, cooling, water heating and lighting in commercial buildings by 16%, 15%, 20% and 5%, respectively. Impacts on different fuels and building types, energy rates and bills as well as pollution emission reductions are also examined.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaluation of the Efficacy of Bayesian Calibration: Interim Project Report

This project evaluated the efficacy of applying Bayesian calibration to EnergyPlus building energy models under different levels of data uncertainty. Small, medium, and large office buildings were modeled with input uncertainty consistent with data collection from the three standard ASHRAE audit levels. It was shown that Bayesian calibration both adjusts parameter values closer to the true values, while simultaneously reducing the uncertainty in the parameter values. Consequently, Bayesian-calibrated EnergyPlus models enhance the reliability of energy use predictions by more closely matching monthly utility bills with much reduced uncertainty compared with uncalibrated models.

Heo, Yeonsook↗

A biophysical approach to the performance diagnosis of human–building energy interaction: Information (bits) modeling, algorithm, and indicators of energy flow complexity

Highlights: • Energy-related human-building interaction is analyzed at the biophysical system scale. • Energy flow-networking model of environmental building performance is suggested. • Information is suggested as a holistic building performance metric. - Abstract: This article addresses the utmost upstream impacts of human–building energy interaction by proposing a network-based model, algorithms, and indicators. Hypothesizing that human behavior is a key factor for the symbiotic development of building and the geobiosphere system, the author seeks emergy (spelled with an “m”)-information integrated measures to indicate dynamic system-level performance of the interaction with building energy flow topology. To validate the hypothesis and methods, four representative building cases were tested on the building form (envelope) of (i) a building with no occupant intervention (baseline), (ii) a building controlled by responsive human behavior (bioclimatic adaptation), (iii) a building with reinforced insulation and behavior-dominated control (passive design), and (iv) a net-zero energy building (NZEB). The results demonstrate that adaptive human behavior in building operation increases the information content and complexity of energy-flow networking, improving performance and sustainability. Findings also reveal that increasing information, complexity, and power (energy availability over time) parallel the general energetic features of developing biophysical systems (greater feedback, internalization, and recycling of materials and energies). It becames clear that active behavioral response is a dominant agent of sustainable environments even on a far broader system scale.

54 ENVIRONMENTAL SCIENCES↗

Using Dark Matter Haloes to Learn about Cosmic Acceleration: A New Proposal for a Universal Mass Function

Structure formation provides a strong test of any cosmic acceleration model because a successful dark energy model must not inhibit or overpredict the development of observed large-scale structures. Traditional approaches to studies of structure formation in the presence of dark energy or a modified gravity implement a modified Press-Schechter formalism, which relates the linear overdensities to the abundance of dark matter haloes at the same time. We critically examine the universality of the Press-Schechter formalism for different cosmologies, and show that the halo abundance is best correlated with spherical linear overdensity at 94% of collapse (or observation) time. We then extend this argument to ellipsoidal collapse (which decreases the fractional time of best correlation for small haloes), and show that our results agree with deviations from modified Press-Schechter formalism seen in simulated mass functions. This provides a novel universal prescription to measure linear density evolution, based on current and future observations of cluster (or dark matter) halo mass function. In particular, even observations of cluster abundance in a single epoch will constrain the entire history of linear growth of cosmological of perturbations.

Prescod-Weinstein, Chanda↗

Performance evaluation of automated data-driven feature extraction and selection methods for practical and scalable building energy consumption prediction models

Here, this study quantifies the impact of automated feature engineering methods (feature extraction and selection) on the quality and accuracy of machine learning models that predict building energy consumption. The case study compares model performance for three main scenarios: baseline (no feature extraction and selection), feature extraction only, and feature extraction combined with feature selection (filter and/or wrapper methods) for fully trained machine learning models for 200 metered/sub-metered energy measurements across 118 real buildings. For consistency, the same machine learning model architecture (a black box deep learning neural network with probabilistic forecast output) was used for all scenarios. Based on results, all feature engineering methods provided noticeable prediction accuracy improvements (e.g., 29%-68% median prediction improvement) compared to baseline scenarios. However, in this application, feature selection methods provide little practical value due to their limited performance gains and high computational cost. Smarter algorithm development supported by better computational environments will be needed before feature selection methods can reliably and efficiently improve predictive model performance.

97 MATHEMATICS AND COMPUTING↗

Recovery Act: Advanced Interaction, Computation, and Visualization Tools for Sustainable Building Design

Current building energy simulation technology requires excessive labor, time and expertise to create building energy models, excessive computational time for accurate simulations and difficulties with the interpretation of the results. These deficiencies can be ameliorated using modern graphical user interfaces and algorithms which take advantage of modern computer architectures and display capabilities. To prove this hypothesis, we developed an experimental test bed for building energy simulation. This novel test bed environment offers an easy-to-use interactive graphical interface, provides access to innovative simulation modules that run at accelerated computational speeds, and presents new graphics visualization methods to interpret simulation results. Our system offers the promise of dramatic ease of use in comparison with currently available building energy simulation tools. Its modular structure makes it suitable for early stage building design, as a research platform for the investigation of new simulation methods, and as a tool for teaching concepts of sustainable design. Improvements in the accuracy and execution speed of many of the simulation modules are based on the modification of advanced computer graphics rendering algorithms. Significant performance improvements are demonstrated in several computationally expensive energy simulation modules. The incorporation of these modern graphical techniques should advance the state of the art in the domain of whole building energy analysis and building performance simulation, particularly at the conceptual design stage when decisions have the greatest impact. More importantly, these better simulation tools will enable the transition from prescriptive to performative energy codes, resulting in better, more efficient designs for our future built environment.

99 GENERAL AND MISCELLANEOUS↗

Energy Prediction Impact of the Space Level Occupancy Schedule for a Primary School

By using the same occupant schedule for all spaces, a building level occupancy schedule in building energy modelling can reduce the cost and time of data collection, especially for large-scale simulations or when detailed occupancy data cannot be obtained. However, by describing the unique occupancy status in each space, a space level schedule can better reflect real-world scenarios. This research investigates the energy prediction impact of a space level occupancy schedule for primary school modelling in 16 ASHRAE climate zones. The results show that when switched from a building level to a space level occupancy schedule, the energy prediction difference is between -1.0% and 0.8%. Generally, the predicted building energy consumption using a space level occupancy schedule is higher than when using a building level occupancy schedule in hot and warm climate zones, but lower in other climate zones.

building energy model↗

Development of Fleet Energy Savings Evaluation Tools for Smart Mobility: Smart Vehicle Energy Technology (SVET) Model for Passenger Fleets and Freight Fleet Level Energy Estimation Tool (FFLEET) for Freight Fleets

As part of the U.S. Department of Energy’s (DOE) Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Initiative, the Oak Ridge National Laboratory (ORNL) led a study to develop web-based tools intended to enable vehicle fleet operators, including both passenger and freight fleets, to quantify the energy savings achievable by implementing advanced transportation technologies. By developing a profile of a fleet’s existing vehicle inventory and providing data about how and where the vehicles are driven, fuel consumption can be calculated for the entire fleet and users can perform “what if” scenarios to evaluate the energy savings that can be realized when replacing existing vehicles and implementing new technologies.

33 ADVANCED PROPULSION SYSTEMS↗

Incorporating an Interactive Fire Plume-Rise Model in the DOE's Energy Exascale Earth System Model Version 1 (E3SMv1) and Examining Aerosol Radiative Effect

The vertical distribution of biomass burning aerosol (BBA) is important in regulating their impacts on weather and climate. The plume-rise process affects the injection height of BBA and interacts with the air parcel lifting and cloud processes. However, these processes are not represented in most global climate models. In this study, we replaced the fixed vertical profiles of monthly BBA emissions in the Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) with an interactive fire plume-rise model. The vertical distribution of BBA emissions was calculated as a function of ambient thermodynamic conditions from the host E3SMv1, with distributions of fire sizes and sensible heat fluxes derived from the observations. The maximum fire radiative power (FRP) technique was used to determine the fire size. Scaling-FRP technique is used to calculate the wildfire heat release. Daily BBA emission, superimposed with a fire diurnal cycle retrieved from the satellite observation, was included in model simulations. The model shows improved agreement with satellite retrievals and in situ measurement during the National Oceanic and Atmospheric Administration Wildfire Experiment for Cloud chemistry, Aerosol absorption, and Nitrogen campaign. The model-observation comparison demonstrates the importance of the plume-rise model and fire diurnal cycle assumption in determining the BBA fields. We also find that E3SMv1 with new features produces a larger carbonaceous aerosol burden, leading to 0.13 W m –2 warming at the top of atmosphere compared to the default E3SMv1. This highlights the importance of accurately representing the BBA injection height and indicates a no-linear nature in the BBA-induced radiative effect.

54 ENVIRONMENTAL SCIENCES↗

ComStock/COVID-19: U.S. Commercial Building Stock Analysis of COVID-19 Mitigation Strategies

ComStock is a DOE platform, with NREL as the lead developer, that models the U.S. commercial building stock using OpenStudio/EnergyPlus to perform physics-based building energy modeling simulations. The ASHRAE Epidemic Taskforce (ASHRAE-ETF) has released several COVID-19 mitigation strategies for commercial buildings. ComStock was used to analyze the impact of four strategies on the existing commercial building stock. These strategies are upgrading to MERV-13 filters, disabling demand control ventilation (DCV), increasing minimum outdoor air to 100%, and HVAC flushing mode operation. Results show the impact of each measure on energy consumption, electric consumption, gas consumption and peak electric.

30 DIRECT ENERGY CONVERSION↗

Microstructure modeling of nuclear structural materials: Recent progress and future directions

Modeling and simulation of microstructures are essential to understand the complex responses and behaviors of nuclear materials in extreme environments. The needs to assess the extended life operation as well as the growing interest in accelerating nuclear materials development and qualification have stimulated the use of high-fidelity multiscale models aided by empirical and ab initio data. This paper reviews the role of various models across different length and time scales in investigating irradiation effects on microstructure evolution and degradation, in particular the embrittlement caused by radiation induced or enhanced formation of nanoscale chemical heterogeneities. The strength and limitations of these models, including classical rate theories, cluster dynamics, phase-field methods, and atomistic models informed by ab initio energies, are discussed with seminal examples. Challenges regarding the lack of thermo-kinetic data and theoretical treatments considering chemical complexities and magnetic excitations, as well as the stabilizing effect by excess point defects in nuclear structural materials are presented, along with potential solutions based on ab initio informed surrogate energy models and statistical sampling by Monte Carlo simulations. Further, the review then highlights the opportunities to leverage the advantages of different methods by establishing hybrid models by shared variables or coupled codes and applications. Finally, the review concludes with forward-looking remarks on how the use of physics-based models can aid the improvement of machine-learning models of property degradation and vice versa.

36 MATERIALS SCIENCE↗

Higher dimensional strange quark matter solutions in self creation cosmology

In this study, we have generalized the higher dimensional flat Friedmann-Robertson-Walker (FRW) universe solutions for a cloud of string with perfect fluid attached strange quark matter (SQM) in Self Creation Cosmology (SCC). We have obtained that the cloud of string with perfect fluid does not survive and the string tension density vanishes for this model. However, we get dark energy model for strange quark matter with positive density and negative pressure in self creation cosmology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Rates and Mechanisms of Oil Shale Pyrolysis: A Chemical Structure Approach

Three pristine Utah Green River oil shale samples were obtained and used for analysis by the combined research groups at the University of Utah and Brigham Young University. Oil shale samples were first demineralized and the separated kerogen and extracted bitumen samples were then studied by a host of techniques including high resolution liquid-state carbon-13 NMR, solid-state magic angle sample spinning 13C NMR, GC/MS, FTIR, and pyrolysis. Bitumen was extracted from the shale using methanol/dichloromethane and analyzed using high resolution 13C NMR liquid state spectroscopy, showing carbon aromaticities of 7 to 11%. The three parent shales and the demineralized kerogens were each analyzed with solid-state 13C NMR spectroscopy. Carbon aromaticity of the kerogen was 23-24%, with 10-12 aromatic carbons per cluster. Crushed samples of Green River oil shale and its kerogen extract were pyrolyzed at heating rates from 1 to 10 K/min at pressures of 1 and 40 bar and temperatures up to 1000°C. The transient pyrolysis data were fit with a first-order model and a Distributed Activation Energy Model (DAEM). The demineralized kerogen was pyrolyzed at 10 K/min in nitrogen at atmospheric pressure at temperatures up to 525°C, and the pyrolysis products (light gas, tar, and char) were analyzed using 13C NMR, GC/MS, and FTIR. Details of the kerogen pyrolysis have been modeled by a modified version of the chemical percolation devolatilization (CPD) model that has been widely used to model coal combustion/pyrolysis. This refined CPD model has been successful in predicting the char, tar, and gas yields of the three shale samples during pyrolysis. This set of experiments and associated modeling represents the most sophisticated and complete analysis available for a given set of oil shale samples.

Fletcher, Thomas↗