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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 649 records · Page 36

Correlation of Electrolyte Volume and Electrochemical Performance in Lithium-Ion Pouch Cells with Graphite Anodes and NMC532 Cathodes

The work herein reports on studies aimed at exploring the correlation between electrolyte volume and electrochemical performance of full cell, pouch-cells consisting of graphite/ Li 1.02 Ni 0.50 Mn 0.29 Co 0.19 O 2 (NMC-532) as the electrodes and 1.2 M LiPF 6 in ethylene carbonate:ethylmethyl carbonate (EC:EMC) as the electrolyte. In addition, it is demonstrated that a minimum electrolyte volume factor of 1.9 times the total pore volume of cell components (cathode, anode, and separator) is needed for long-term cyclability and low impedance. Less electrolyte results in an increase of the measured Ohmic resistances. Increased resistance ratios for charge transfer and passivation layers at cathode, relative to initial values, were 1.5 2.0 after 100 cycles. At the cathode, the resistance from charge transfer was 2-3 times higher than for passivation layers. Lastly, differential voltage analysis showed that anodes were less delithiated after discharging as the cells were cycled.

25 ENERGY STORAGE↗

Bayesian Integration of Isotope Ratios for Geographic Sourcing of Castor Beans

Recent years have seen an increase in the forensic interest associated with the poison ricin, which is extracted from the seeds of the Ricinus communis plant. Both light element (C, N, O, and H) and strontium (Sr) isotope ratios have previously been used to associate organic material with geographic regions of origin. We present a Bayesian integration methodology that can more accurately predict the region of origin for a castor bean than individual models developed independently for light element stable isotopes or Sr isotope ratios. Our results demonstrate a clear improvement in the ability to correctly classify regions based on the integrated model with a class accuracy of 6 0 . 9 {+-} 2 . 1 % versus 5 5 . 9 {+-} 2 . 1 % and 4 0 . 2 {+-} 1 . 8 % for the light element and strontium (Sr) isotope ratios, respectively. In addition, we show graphically the strengths and weaknesses of each dataset in respect to class prediction and how the integration of these datasets strengthens the overall model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.

Biomarker Identification↗

The MAJORANA DEMONSTRATOR Neutrinoless Double-Beta Decay Experiment

The MAJORANA DEMONSTRATOR will search for the neutrinoless double-beta (ββ(0ν)) decay of the isotope 76 Ge with a mixed array of enriched and natural germanium detectors. The observation of this rare decay would indicate that the neutrino is its own antiparticle, demonstrate that lepton number is not conserved, and provide information on the absolute mass scale of the neutrino. The DEMONSTRATOR is being assembled at the 4850-foot level of the Sanford Underground Research Facility in Lead, South Dakota. The array will be situated in a low-background environment and surrounded by passive and active shielding. Here we describe the science goals of the DEMONSTRATOR and the details of its design.

Abgrall, N.↗

GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control system design, and integration of wind power in a smart grid.

agent↗

OPENSTUDIO® [SWR-07-40]

OpenStudio® is a cross-platform (Windows, Mac, and Linux) collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. OpenStudio is an open source (LGPL) project to facilitate community development, extension, and private sector adoption. OpenStudio includes graphical interfaces along with a Software Development Kit (SDK). In addition to the graphical interface, OpenStudio allows building researchers and software developers to quickly get started through its multiple entry levels, including access through C++, Ruby, and C#. Users can leverage the Ruby interface to create OpenStudio Measures that can be easily shared and applied to OpenStudio Models. OPENSTUDIO® IS A REGISTERED TRADEMARK OF ALLIANCE FOR SUSTAINABLE ENERGY, LLC, THE MANAGER AND OPERATOR OF THE NATIONAL RENEWABLE ENERGY LABORATORY.

Ball, Brian↗

OpenStudio® Resources [SWR-07-40]

This repository includes a suite of simulation tests that can be used to validate new OpenStudio® model objects as well as ensure that objects continue to work after they are added. Each new OpenStudio Model object should ideally have two simulation tests associated with it: - a Ruby one which verifies the Ruby API and, - an OSM one that verifies the OSM file can be loaded with future versions of OpenStudio. Both tests should result in a simulation-ready OpenStudio Model that can be simulated using EnergyPlus®. Both of these tests are located in the /model/simulationtests directory, the easiest way to add a new test is to find a related existing test and modify it. When new tests are added they must be added to the model_tests.rb file.

Benne, Kyle↗

Marmot V2

MARMOT is a robust numerical tool for mesoscale modeling of fuel performance developed under the NEAMS Fuels technical area to predict the coevolution of microstructure and properties in fuel and cladding materials. MARMOT accomplishes this using the phase field method coupled with finite strain mechanics and heat conduction. MARMOT is based on the open source Multiphysics Object-Oriented Simulation Environment (MOOSE) and solves the coupled partial differential equations defining the physics using the finite element method. MARMOT is being developed in order to facilitate the development of improved materials models for fuel performance, but it is also being developed as a powerful tool in and of itself for the simulation of mesoscale fuel performance.

Aagesen, LarryK.↗

Overview of the HI-SCALE Field Campaign: A New Perspective on Shallow Convective Clouds

Shallow convective clouds are common, occurring over many areas of the world, and are an important component in the atmospheric radiation budget. In addition to synoptic and mesoscale meteorological conditions, land-atmosphere interactions and aerosol-radiation-cloud interactions can influence the formation of shallow clouds and their properties. However, these processes exhibit large spatial and temporal variability and occur at the sub-grid scale for all climate and operational forecast models and must be represented by parameterizations. Uncertainties in shallow cloud parameterization predictions arise from many sources, including insufficient coincident data needed to adequately represent the coupling of cloud macrophysical and microphysical properties with inhomogeneity in the surface layer, boundary layer, and aerosol properties. Predictions in the transition of shallow to deep convection and the onset of precipitation are also affected by errors in simulated shallow clouds. Coincident data is a key factor needed to achieve a more complete understanding of the lifecycle of shallow convective clouds and to develop improved model parameterizations. To address these issues, the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the Atmospheric Radiation and Measurement (ARM) Southern Great Plains site in north-central Oklahoma during 2016. We describe the scientific objectives of HI-SCALE as well as the experimental approach, the overall weather conditions during the campaign, and preliminary findings from the measurements. Finally, we discuss the remaining scientific gaps in our understanding of shallow clouds that can be addressed by analysis and modeling studies that use HI-SCALE data including: the effects of heterogeneous land-use, vegetation, and soil moisture conditions on boundary layer mixing and consequently cloud formation; factors that contribute to the transition of shallow to deep convection; the role of cloud population on

Fast, Jerome D.↗

Limited Role of Absolute Humidity in Intraurban Heat Variability

Abstract Monitoring and understanding the variability of heat within cities is important for urban planning and public health, and the number of studies measuring intraurban temperature variability is growing. Recognizing that the physiological effects of heat depend on humidity as well as temperature, measurement campaigns have included measurements of relative humidity alongside temperature. However, the role the spatial structure in humidity, independent from temperature, plays in intraurban heat variability is unknown. Here we use summer temperature and humidity from networks of stationary sensors in multiple cities in the United States to show spatial variations in the absolute humidity within these cities are weak. This variability in absolute humidity plays an insignificant role in the spatial variability of the heat index and humidity index (humidex), and the spatial variability of the heat metrics is dominated by temperature variability. Thus, results from previous studies that considered only intraurban variability in temperature will carry over to intraurban heat variability. Also, this suggests increases in humidity from green infrastructure interventions designed to reduce temperature will be minimal. In addition, a network of sensors that only measures temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location, allowing for lower-cost heat monitoring networks. Significance Statement Monitoring the variability of heat within cities is important for urban planning and public health. While the physiological effects of heat depend on temperature and humidity, it is shown that there are only weak spatial variations in the absolute humidity within nine U.S. cities, and the spatial variability of heat metrics is dominated by temperature variability. This suggests increases in humidity will be minimal resulting from green infrastructure interventions designed to reduce temperature. It also means a network of sensors that only measure temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location.

Meteorology & Atmospheric Sciences↗

The effects of boost pressure on stratification and burn duration of gasoline homogeneous charge compression ignition combustion

This article investigates the effects of intake pressure (boost) on the pre-ignition stratification and burn duration of homogeneous charge compression ignition combustion. Full cycle computational fluid dynamics simulations are performed with gasoline kinetics. An intake pressure sweep is performed while maintaining the same combustion timing and mean composition. The burn duration reduces with increasing boost, even though intake temperature is reduced to hold combustion timing constant. It is shown that the compositional stratification increases with boost whereas thermal stratification decreases. A quasi-dimensional model is employed to assess the effect of compositional stratification, pressure, mean temperature and isolate the effect of thermal stratification on burn duration. The analysis reveals that reducing charge temperature neutralizes the effect of increased boost on reactivity and the shorter burn durations at higher boost are primarily due to the lower thermal stratification. It is shown that higher pressures do not significantly increase the mixing and the lower thermal stratification is due to lower wall heat losses per unit charge mass. A follow-up set of non-reacting simulations with adiabatic walls corroborate this claim by revealing a constant magnitude of thermal stratification across the boost sweep.

Shingne, Prasad S.↗

Control of hybrid boosting in highly diluted internal combustion engines

A novel hybrid system enabling both flexible supercharging and limited torque assist is studied to mitigate transient response challenges of a turbocharged spark ignition engine equipped with low pressure exhaust gas recirculation. The hybrid system, called a power split supercharger (SC), is configured with a planetary gear set that splits the supercharging power between a small low-voltage electric motor and the engine crankshaft. The air path controller relies on the coordination of four actuators on the engine side and three low-level actuators on the hybrid boosting device. A decentralized control scheme is used in this work, in which the master–slave structure of the boost pressure controller decreases the turbo-lag associated with exhaust gas recirculation, while minimizing the SC operation for fuel economy. A vector reference governor is used to prevent compressor surge during engine tip-outs. In addition, the desired intake manifold pressure is modified to provide time for evacuating the exhaust gas recirculation and avoiding misfires when transitioning to low load, while the hybrid capability of the power split SC is used to recuperate the unwanted generated power. All controllers are validated on both a mean value engine model and a high-fidelity engine model. Practical challenges of implementing the vector reference governor to the highly nonlinear engine air path with pressure pulsations originating from the engine reciprocation are discussed and some solutions are proposed.

Engineering↗

Cycle-to-cycle variability in spark-assisted compression ignition engines near optimal mean combustion phasing

Stoichiometric spark-assisted compression ignition (SACI) combustion with exhaust gas recirculation (EGR) dilution has demonstrated higher part-load thermal efficiencies compared to spark-ignited engines, while maintaining ultra-low tailpipe emissions. However, SACI is often characterized by high cyclic variability in heat release or torque output, which poses a challenge to its implementation in light-duty vehicles. This paper presents an experimental investigation of cyclic variability in stoichiometric SACI combustion under EGR-dilute conditions, while maintaining mean combustion phasing (θ 50 ) near optimal timing for thermal efficiency. The present work focuses on SACI conditions where the flame-based heat release fraction is between approximately 10% and 40% of the overall heat release, and therefore contributes significantly to the combustion process. For the SACI conditions examined, the variability in θ 50 was driven by variability in autoignition timing, which in turn correlated with the start of measurable heat release (θ 02 ). High variability in θ 50 caused unstable work output due to very late combustion with poor or no end-gas autoignition. The use of a high ignition energy dual-coil offset ignition system had negligible impact in reducing θ 50 variability. Analysis of experimental data from close to 1000 operating conditions showed that the magnitude of θ 50 variability correlates with the flame-based heat release fraction ([Formula: see text]), for a large range of intake pressures, spark timings and exhaust gas recirculation levels. For the SACI conditions examined, combustion phasing variability was largely determined by flame-based combustion and particularly the initial flame formation (θ IGN-02 ), and minimally by the end-gas autoignition heat release. The analysis also demonstrated that θ 50 variability is amplified as the contribution of the flame to the overall heat release increases.

Engineering↗

Optimizing the fuel efficiency of an opposed piston engine for electric power generation

This paper investigates the optimal crankshaft motion for an opposed piston (OP) engine in a novel hybrid architecture to maximize fuel efficiency. The OP engine was selected for this work due to its inherent thermodynamic benefits and the balanced nature of the engine which can achieve downsizing through reducing the number of cylinders rather than the individual cylinder volume. The typical geartrain required on an OP engine was exchanged for two electric motors, reducing friction loss and decoupling the crankshafts. Using the motors to control the crankshaft motion profiles, this architecture introduces capabilities to dynamically vary compression ratio, combustion volume, and scavenging dynamics. To leverage these opportunities, an optimization scheme was developed utilizing nonlinear optimization of a 0-D model to compute the crankshaft motion profile that maximizes the work generated by the system. This optimization was then iteratively coupled with a high fidelity model which supplies the cylinder flow boundary conditions. This iterative approach reduces the model complexity used in the optimal control problem (OCP) while capturing the gas exchange dynamics critical to the 2-stroke cycle of the OP engine. By using the rate of change of motor torque as the input to the OCP, the torque fluctuation in a single cycle can be limited to ensure tracking feasibility. The results show crankshaft velocity slows during the compression stroke and conversely accelerates during the expansion stroke, reducing the peak motor torque required for control and thus reducing the motor losses. The extended residence time at top dead center, however, leads to an increase in heat transfer, illustrating the trade-off between the work extraction efficiency and the indicated engine efficiency.

Engineering↗

Porous media properties of reticulated shape memory polymer foams and mock embolic coils for aneurysm treatment

Background: Shape memory polymer (SMP) foams are being investigated as an alternative aneurysm treatment method to embolic coils. The goal of both techniques is the reduction of blood flow into the aneurysm and the subsequent formation of a stable thrombus, which prevents future aneurysm rupture. The purpose of this study is to experimentally determine the parameters, permeability and form factor, which are related to the flow resistance imposed by both media when subjected to a pressure gradient. Methods: The porous media properties—permeability and form factor—of SMP foams and mock embolic coils (MECs) were measured with a pressure gradient method by means of an in vitro closed flow loop. We implemented the Forchheimer-Hazen-Dupuit-Darcy equation to calculate these properties. Mechanically-reticulated SMP foams were fabricated with average cell sizes of 0.7E-3 and 1.1E-3 m, while the MECs were arranged with volumetric packing densities of 11-28%. Results: The permeability of the SMP foams was an order of magnitude lower than that of the MECs. The form factor differed by up to two orders of magnitude and was higher for the SMP foams in all cases. The maximum flow rate of all samples tested was within the inertial laminar flow regime, with Reynolds numbers ranging between 1 and 35. Conclusions: The SMP foams impose a greater resistance to fluid flow compared to MECs, which is a result of increased viscous and inertial losses. These results suggest that aneurysms treated with SMP foam will have flow conditions more favorable for blood stasis than those treated with embolic coils having packing densities ≤ 28%.

36 MATERIALS SCIENCE↗