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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Vibrational Bands of the 2-Butyn-1-yl Radical

This article reports the spectroscopic signature of the 2-butyn-1-yl radical. The radical is an isomer of C 4 H 5 and is is likely to be significant to reactions that occur during combustion of fuels, as well as reactions in extraterrestrial environments. In this work, the radical was formed by heating a mixture of 1-bromo-2-butyne and argon to 800 K in a pulsed, microtubular reactor. The resultant radicals and other trace products were trapped in a low-temperature argon matrix. Fourier-transform infrared spectroscopy was used to record seven vibrational bands of the 2-butyn-1-yl radical. In conclusion, the experimentally observed frequencies and intensities of the seven vibrational bands were found to be consistent with computational predictions from the literature and also new calculations done in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Room-Temperature Optical Detection of 14 CO 2 below the Natural Abundance with Two-Color Cavity Ring-Down Spectroscopy

Radiocarbon’s natural production, radiative decay, and isotopic rarity make it a unique tool to probe carbonaceous systems in the life and earth sciences. However, the difficulty of current radiocarbon ( 14 C) detection methods limits scientific adoption. Here, two-color cavity ring-down spectroscopy detects 14 CO 2 in room-temperature samples with an accuracy of one-tenth the natural abundance in 3 min. The intracavity pump–probe measurement uses two cavity-enhanced lasers to cancel out cavity ring-down rate fluctuations and strong one-photon absorption interference (>10 000 1/s) from hot-band transitions of CO 2 isotopologues. Selective, room-temperature detection of small 14 CO 2 absorption signals (<1 1/s) reduces the technical and operational burdens for cavity-enhanced measurements of radiocarbon, which can benefit a wide range of applications like biomedical research and field-detection of combusted fossil fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Zeolite-promoted platinum catalyst for efficient reduction of nitrogen oxides with hydrogen

Internal combustion engine fueled by carbon-free hydrogen (H 2 -ICE) offers a promising alternative for sustainable transportation. Herein, we report a facile and universal strategy through the physical mixing of Pt catalyst with zeolites to significantly improve the catalytic performance in the selective catalytic reduction of nitrogen oxides (NO x ) with H 2 (H 2 -SCR), a process aiming at NO x removal from H 2 -ICE. Via the physical mixing of Pt/TiO 2 with Y zeolite (Pt/TiO 2 + Y), a remarkable enhancement of NO x reduction activity and N 2 selectivity was simultaneously achieved. The incorporation of Y zeolite effectively captured the in-situ generated water, fostering a water-rich environment surrounding the Pt active sites. This environment weakened the NO adsorption while concurrently promoting the H 2 activation, leading to the strikingly elevated H 2 -SCR activity and N 2 selectivity on Pt/TiO 2 + Y catalyst. This study provides a unique, easy and sustainable physical mixing approach to achieve proficient heterogeneous catalysis for environmental applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Using Machine Learning Tools to Predict Compressor Stall

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.

42 ENGINEERING↗
DOE OSTI2020

Numerical Investigation of a Central Fuel Property Hypothesis Under Boosted Spark-Ignition Conditions

In the present work, a central fuel property hypothesis (CFPH), which states that fuel properties are sufficient to provide an indication of a fuel’s performance irrespective of its chemical composition, was numerically investigated. In particular, the objective of the study was to determine whether Research Octane Number (RON) and Motor Octane Number (MON), as fuel properties, are sufficient to describe a fuel’s knock-limited performance under boosted spark-ignition (SI) conditions within the framework of CFPH. To this end, four TPRF-bioblendstock surrogates having different compositions but matched RON (=98) and MON (=90), were first generated using a non-linear regression model based on artificial neural network (ANN). Additionally, three unconventional bioblendstocks were included in the analysis: di-isobutylene (DIB), isobutanol, and Anisole. Skeletal reaction mechanisms were generated for the TPRF-DIB, TPRF-isobutanol, and TPRF-anisole blends from a detailed kinetic mechanism. Thereafter, numerical simulations were performed for the fuel surrogates using the skeletal mechanisms and a virtual cooperative fuel research (CFR) engine model, under a representative boosted operating condition. In the computational fluid dynamics (CFD) model, the G-equation approach was employed to track the turbulent flame front and the well-stirred reactor model combined with the multi-zone binning strategy was used to capture auto-ignition in the end-gas. In addition, laminar flame speed (LFS) was tabulated for each blend as a function of pressure, temperature, and equivalence ratio a priori, and the lookup tables were used to prescribe laminar flame speed as an input to the G-equation model. Parametric spark timing sweeps were performed for each fuel blend to determine the corresponding knock-limited spark advance (KLSA) and 50% burn point (CA50) at the respective KLSA timing. It was observed that despite same RON, MON, and engine operating conditions, the TPRF-anisole blend exhibited markedly different knock-limited performance from the other three blends. This deviation from the octane index (OI) expectation was shown to be caused by differences in laminar flame speed. However, it was found that relatively large fuel-specific differences in LFS (>20%) would have to be present to cause any appreciable deviation from the OI framework. Otherwise, RON and MON would still be robust enough to predict a fuel’s knock-limited performance.

42 ENGINEERING↗
DOE OSTI2021

X-Ray Characterization of Real Fuel Sprays for Gasoline Direct Injection

Here, the effects of fuel blend properties on spray and injector performance has been investigated in a side-mount injector for gasoline direct injection (GDI) using two certification fuel blends: Euro 5 and Euro 6. Several X-ray diagnostic techniques were conducted to characterize the injector and spray morphology. Detailed internal geometry of the GDI injector was resolved to 1.8 μm, through the use of hard X-ray tomography. The geometry characterization of this six-hole GDI, side mount injector, quantifies relevant hole and counterbore dimensions and reveals the intricate details within the flow passages, including surface roughness and micron-sized features. Internal valve motion was measured with a temporal resolution of 20 μs and a spatial resolution of 2.0 μs, for three injection pressures and several injector energizing strategies. The needle motion for both fuels exhibits similar lift profiles for common energizing commands. A combination of X-ray radiography and ultra-small-angle X-ray scattering (USAXS) was used to characterize the fuel mass distribution and the droplet sizing, respectively. Tomographic spray radiography revealed the near-nozzle distribution of fuel mass for each of the fuels and the asymmetry produced by the angled nozzles. Under evaporative conditions, the two fuels show minor differences in peak fuel mass distribution during steady injection, though both exhibit fluctuations in injection during the early, transient phase. USAXS measurements of the path-specific surface area of the spray indicated lower peak values for the more evaporative conditions in the near nozzle region.

09 BIOMASS FUELS↗
DOE OSTI2022

Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy (Workshop Report)

The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector. The US industrial sector accounts for 32% of the nation’s primary energy use (including feedstocks), and refining, chemicals, pulp and paper, iron and steel, and food products represent the top energy-consuming sectors. Thermal processing or process heating represents the largest energy use category; it accounts for 63% of all energy use in manufacturing. Additionally, thermal processing is the largest contributor of carbon dioxide (CO2) generation, resulting from combustion of fuels and process related chemical reactions, such as in the case of cement and lime production. The challenge of achieving net-zero industrial GHG emissions is colossal considering the established industrial base that depends mainly on carbon-based processes and energy sources; the time frame and cost to replace carbon-based energy sources and feedstocks; and the long-term outlook for development with large-scale adaptation of alternative non carbon–based technologies. The goals of the DOE Advanced Manufacturing Office Thermal Process Intensification Workshop were as follows: (1) Identify R&D gaps and opportunities to facilitate transformative improvement in industrial thermal processes beyond current technologies and allow for entirely new methods for processing materials; (2) Gain insight into new and innovative approaches to thermally intensify processes, reduce heat demand, harness waste heat, and use fuels and hydrocarbon feedstocks more efficiently; (3) Identify the R&D pathways to thermal process intensification (TPI) with the highest potential for impact and adoption by the industrial sector; (4) Define areas of research, development, and demonstration (RD&D) activities to accelerate development and application of emerging and transformative technologies to intensify thermal processes in industry. The scope and focus of the workshop were defined to meet these goals. Based on the available data for energy use and GHG emissions, the industries that collectively use more than 80% of the total process heating energy consumption were selected as primary focus areas. The chosen industries were combined into the following four groups based on similarities in their thermal processes: high-temperature metal processing (iron and steel industry, alumina-aluminum industry); high-temperature nonmetal and mineral processing (cement and glass industry); medium- to low-temperature thermal processing (food processing and pulp and paper industry as part of forest products sector); and hydrocarbon processing (petroleum refining and chemical industry). Furthermore, all potential TPI technologies associated with the processes defined were considered as part of the workshop. Different types of TPI technologies possible in industrial in the document.

42 ENGINEERING↗
DOE OSTI2025

A Safe Response to Renewable Energy Hazards

The International Association of Fire Fighters (IAFF) and Underwriters Laboratories, LLC (UL) in conjunction with UL Solutions initiated a joint project in 2022 under an agreement with the United States Department of Energy-Office of Energy Efficiency and Renewable Energy (DOE-EERE). This project focused on two separate and important initiatives related to energy efficiency in residential buildings. Initiative 1: Fire Performance on Energy Efficient Exterior Walls. Initiative 2: Firefighting Tactics in Residential Properties with Building Energy Storage Systems (BESS). The project’s first initiative addresses concerns surrounding new technologies with enhanced, energy-efficient exterior walls installed on residential properties. The concerns of fire rapidly traveling vertically up the exterior of these walls were examined. This addressed a growing concern from the first responder community that many times, the fires on the exterior of residential buildings have already evolved into an attic fire by the time of arrival – making it problematic to address the fire scenario. The test plan for Initiative 1 incorporated a modified version of an American Society for Testing and Materials (ASTM) test method, ASTM E2707, Standard Test Method for Determining Fire Penetration of Exterior Wall Assemblies Using a Direct Flame Impingement Exposure, as the foundation of the research. The test method involved a wall structure intended to represent retrofit construction to evaluate how fire would spread vertically or laterally. The second aspect of the UL-IAFF Project focuses on the fire service response to Residential Battery Energy Storage System (RBESS) incidents. These simulation tests were constructed in the large-scale fire test facility at UL Solutions’ Northbrook, IL campus. A baseline test was conducted that involved a test structure with no batteries—shelving units populated with standardized commodities, representing a typical garage with cellulosic and plastic contents. Three additional tests have been conducted to generate data with the contribution of energy storage system (ESS) batteries to compare fire and explosion hazards against the baseline test. Through this work, fire service tactical considerations can be explored. From the data, the team can determine 1) the visual indicators of a residential fire that has involved an RBESS (or, potentially, other large batteries) and 2) the impact of fire service-initiated ventilation of the structure on the fire conditions and explosion risks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗