SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The purpose of this document is to develop feedstock price values to be used in the United States (U.S.) Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) energy systems studies. This version of the QGESS incorporates electricity and biomass fuel costs and updates and expands the coal and natural gas costs.
The purpose of this document is to develop feedstock price values to be used in the United States (U.S.) Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) energy systems studies. This version of the QGESS incorporates electricity and biomass fuel costs; it updates the coal costs; and it updates and expands the natural gas costs.
Many ports and waterfronts are evaluating alternative electrification efforts, including electrification of passenger and vehicle ferries. In Seattle, the Washington State Department of Transportation, in conjunction with Seattle City Light (the local utility) and the Port of Seattle, are working to deploy a hybrid electric ferry and provide charging at Seattle’s Colman dock. As part of this ferry electrification effort, Seattle City Light is considering including a large battery energy storage system (BESS) to help “buffer” the ferry charging. The “buffer” provides energy arbitrage and spreads out the large amount of power needed to recharge the ferry to times when the ferry is out of the dock – rather than one very large peak for 15 minutes, the battery storage allows it to be a smaller power value over a longer duration. This initial BESS concept served as the jumping off point to explore an expanded microgrid concept via a notional test system that incorporates additional distributed energy resources (DER) and infrastructure upgrades to the local distribution infrastructure at the Seattle Waterfront and neighboring Port of Seattle properties. This case study examined the potential for secondary use of the BESS within a networked microgrid during the scenario of a large-scale power outage, such as a natural disaster.
This dataset contains solid-state 1H and 13C NMR relaxometry data, differential scanning calorimetry (DSC) data, and size exclusion chromatography (SEC/GPC) data supporting the study of sub-glass-transition (sub-Tg) molecular dynamics in a composition- and sequence-controlled series of diphenyl-substituted polysiloxanes (PDMS, 14Ph, 33Ph, 50Ph, 67Ph, and 100Ph; 0–100% diphenylsiloxane content by mole).All solid-state NMR data were acquired on a 200 MHz Bruker Avance III HD spectrometer using a static 7 mm HX probe or a 4 mm HX probe under 4 kHz magic-angle spinning. Raw Bruker TopSpin experiment folders are included for: (1) variable-temperature 1H lineshape measurements used to determine linewidth (FWHM) as a function of temperature across the glass transition; (2) 1H T1 (saturation recovery with solid-echo detection), probing nanosecond-scale dynamics near the 1H Larmor frequency; (3) 1H T1rho (direct spin-lock, 62.5 kHz), probing microsecond-scale segmental dynamics; (4) 13C-detected Lee–Goldburg cross-polarization 1H T1rho (LGCPH T1rho) for 33Ph and 50Ph, resolving aromatic and aliphatic proton environments; and (5) 13C T1 relaxation for 33Ph and 50Ph. Differential scanning calorimetry data (TA Instruments DSC 25, −150 to +120 °C, up to +300 °C for 100Ph, 10 °C/min) are included for all six compositions and support the glass-transition temperatures in Table 1 and Figure 1. Size exclusion chromatography data (Agilent 1200 Series, PL-Gel 300 mixed-C column, THF mobile phase, polystyrene calibration standards) are included for the three synthesized copolymers (33Ph, 50Ph, 67Ph) and support the number-average molecular weights in Table 1. Processed data include per-composition relaxation-time summaries (Excel), curve-fitting and Bloembergen-Purcell-Pound (BPP) model analysis notebooks (Jupyter/Python), and Igor Pro (.pxp) master files used to generate the manuscript's figures.
We present an overview of the Duke Energy Carbon-free Resource Integration Study, with a focus on the production cost modeling results that have come out of the last phase of the analysis.
The rise of real-time information communication through smartphones and wireless networks enabled the growth of ridesharing services. While personal rideshare services (individuals ride alone or with people they know) initially dominated the market, the popularity of pooled ridesharing (individuals share rides with strangers) has grown globally. However, pooled rideshare remains less common in the U.S., where personal vehicle usage is still the norm. Vehicle design and rideshare services may need to be tailored to user preferences to increase pooled rideshare adoption. A national U.S. survey ( N = 5,385) used exploratory and confirmatory factor analyses to identify four key factors influencing riders’ willingness to consider pooled rideshare: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. Understanding and implementing these user-centered design principles and service-related factors may be critical for increasing the future use of pooled rideshare services
Supporting INL’s mission to transform our nation’s energy future, notably through innovative nuclear energy solutions, this project focuses on modeling accidental tolerant fuel. In collaboration with MIT, we modeled with MOOSE-based tools the Lightbridge metallic fuel design. Lightbridge fuel is envisioned to enable higher power output and larger safety margins for both current and advanced nuclear reactors. We present here the advanced meshing capabilities developed and preliminary physics results.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Abstract The power performance and the wind velocity field of an onshore wind farm are predicted with machine learning models and the pseudo‐2D RANS model, then assessed against SCADA data. The wind farm under investigation is one of the sites involved with the American WAKE experimeNt (AWAKEN). The performed simulations enable predictions of the power capture at the farm and turbine levels while providing insights into the effects on power capture associated with wake interactions that operating upstream turbines induce, as well as the variability caused by atmospheric stability. The machine learning models show improved accuracy compared to the pseudo‐2D RANS model in the predictions of turbine power capture and farm power capture with roughly half the normalized error. The machine learning models also entail lower computational costs upon training. Further, the machine learning models provide predictions of the wind turbulence intensity at the turbine level for different wind and atmospheric conditions with very good accuracy, which is difficult to achieve through RANS modeling. Additionally, farm‐to‐farm interactions are noted, with adverse impacts on power predictions from both models.
Explore the source record for details and available documents.
Solid base metal oxide catalysts such as MgO offer utility in a wide variety of syntheses from pharmaceuticals to fuels. The (111) facet of MgO shows enhanced, unique properties relative to the other facets. Carbon coatings have emerged as a promising modification to impart metal oxide catalyst stability. Here, we report the synthesis, characterization, and catalytic properties of commercial MgO, MgO(111), and carbon coated derivatives thereof for 2-pentanone condensation. The dimer and trimer products of this reaction can be used as precursors for biofuels upon oxygen removal and thus have relevance in environmental sustainability. Additionally, MgO(111) maintained impressive selectivity towards the dimer product after carbon coating, whereas the other catalysts experienced a decrease in conversion and selectivity as a consequence of the carbon coating. Our findings highlight the catalytic efficacy of MgO(111), provide insight into carbon coating for catalyst stability, and pave the way for continued mechanistic investigations.
The effect of the core–skin structure on the mechanical properties of carbon nanofibers is investigated in large-scale molecular dynamics simulations of tensile deformation of carbon nanofibers with the core–skin and homogeneous structures. Contrary to an established notion of the deleterious effect of the skin layer on the strength of carbon fibers, the presence of a high-quality skin layer is found to increase both the Young’s modulus and tensile strength of the nanofiber. A detailed analysis of the fracture process indicates that the nanofiber strengthening is related to the ability of skin layer to suppress crack nucleation at the core–skin interface. Furthermore, the computational predictions suggest that the design of new approaches to carbon fiber manufacturing and processing leading to the generation of a high-quality skin layer while avoiding the introduction of structural defects at the core–skin interface may yield a significant enhancement of the mechanical properties of carbon fibers.
We report to optimize and extend the service life of polymeric materials in outdoor environments, a domain knowledge-based and data-driven approach was utilized to quantitatively investigate the temporal evolution of degradation modes, mechanisms, and rates under various stepwise accelerated exposure conditions. Six formulations of poly(methyl methacrylate) (PMMA) with different combinations of stabilizing additives, including one unstabilized formulation, were exposed in three accelerated weathering conditions. Degradation was dependent on wavelength as samples in UV light at 340 nm (UVA) exposure showed the most yellowing. The unstabilized PMMA formulation showed much higher yellowness index values (59.5) than stabilized PMMA formulations (2–12). Urbach edge analysis shows a shift toward longer wavelength from 285 to 500 nm with increasing exposure time and an increased absorbance around 400 nm of visible region as the unstabilized samples increase in yellowing. The degradation mechanisms of PMMA were tracked using induced absorbance to dose at specific wavelengths that correspond to known degradation mechanisms. The degradation pathway of PMMA was modeled in a framework using network structural equation modeling (netSEM). netSEM showed changes in degradation pathway as PMMA transition stages of degradation.
Anomalous eutectic formation in undercooled Ni-Sn alloys was investigated by in situ X-ray diffraction and ex situ remelting and annealing experiments. Dynamic recrystallization and partial remelting of primary solids followed by repeated nucleation and growth of eutectic grains in the mushy zone were revealed by time-resolved X-ray diffraction. Ex situ experiments demonstrated that partial remelting of near-equilibrium solidified alloys of eutectic or near-eutectic composition can convert regular lamellar eutectic into anomalous eutectic, whereas high-temperature annealing of splat-quenched alloys of similar composition can convert eutectic or two-phase dendrites into anomalous eutectic. It is concluded that compared to ripening in solid-states, partial remelting of eutectic or two-phase dendrites in a mushy zone provides a more realistic mechanism for anomalous eutectic formation in undercooled solidification of Ni-Sn eutectic alloys. (C) 2020 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Not provided.
Not provided.