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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 181 records · Page 10

Baryon acoustic oscillations in the projected cross-correlation function between the eBOSS DR16 quasars and photometric galaxies from the DESI Legacy Imaging Surveys

ABSTRACT We search for the baryon acoustic oscillations in the projected cross-correlation function binned into transverse comoving radius between the SDSS-IV DR16 eBOSS quasars and a dense photometric sample of galaxies selected from the DESI Legacy Imaging Surveys. We estimate the density of the photometric sample of galaxies in this redshift range to be about 2900 deg−2, which is deeper than the official DESI emission line galaxy selection, and the density of the spectroscopic sample is about 20 deg−2. In order to mitigate the systematics related to the use of different imaging surveys close to the detection limit, we use a neural network approach that accounts for complex dependences between the imaging attributes and the observed galaxy density. We find that we are limited by the depth of the imaging surveys that affects the density and purity of the photometric sample and its overlap in redshift with the quasar sample, which thus affects the performance of the method. When cross-correlating the photometric galaxies with quasars in the range 0.6 ≤ z ≤ 1.2, the cross-correlation function can provide better constraints on the comoving angular distance DM (6 per cent precision) compared to the constraint on the spherically averaged distance DV (9 per cent precision) obtained from the autocorrelation. Although not yet competitive, this technique will benefit from the arrival of deeper photometric data from upcoming surveys that will enable it to go beyond the current limitations we have identified in this work.

79 ASTRONOMY AND ASTROPHYSICS↗

Robust superconductivity intertwined with charge density wave and disorder in Pd-intercalated ErTe 3

Pd-intercalated ErTe 3 is studied as a model system to explore the effect of "intertwined" superconducting and charge density wave (CDW) orders. Despite the common wisdom that superconductivity emerges only when CDW is suppressed, we present data from STM and AC susceptibility measurements that show no direct competition between CDW order and superconductivity. Both coexist over most of the intercalation range, with uniform superconductivity over length scales that exceed the superconducting coherence length. This is despite persisting short-range CDW order and increased scattering from the Pd intercalation. While superconductivity is insensitive to local defects in either of the bi-directional CDWs, vestiges of the Fermi-level distortions are observed in the properties of the superconducting state.

36 MATERIALS SCIENCE↗

On the Solution of ℓ 0 -Constrained Sparse Inverse Covariance Estimation Problems

The sparse inverse covariance matrix is used to model conditional dependencies between variables in a graphical model to fit a multivariate Gaussian distribution. Estimating the matrix from data are well known to be computationally expensive for large-scale problems. Sparsity is employed to handle noise in the data and to promote interpretability of a learning model. Although the use of a convex ℓ 1 regularizer to encourage sparsity is common practice, the combinatorial ℓ 0 penalty often has more favorable statistical properties. In this paper, we directly constrain sparsity by specifying a maximally allowable number of nonzeros, in other words, by imposing an ℓ 0 constraint. Here, we introduce an efficient approximate Newton algorithm using warm starts for solving the nonconvex ℓ 0 -constrained inverse covariance learning problem. Numerical experiments on standard data sets show that the performance of the proposed algorithm is competitive with state-of-the-art methods.

$\ell_0$-Constrained↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Utilizing Earth Observations to Understand Landscape Patterns and Assist in Wildlife Management in Iona National Park, Angola

Following the end of the Angolan Civil War (1975-2002), human habitation in Iona National Park has grown exponentially, as has the livestock population. An ongoing drought beginning in 2017 has brought people, livestock, and wildlife into increasing competition for resources within the park. This study used Earth observation data, primarily Landsat and Sentinel imagery, to examine landscape trends to improve wildlife preservation approaches in Iona National Park, Angola. In collaboration with the NGO African Parks, we developed a robust land use and land cover (LULC) classification model using remote sensing data to augment sparse ground-based data in this arid land region. We used Google Earth Engine and a random forest classifier to map vegetation types, water bodies, and potential wildlife habitats. This analysis resulted in a high spatial resolution LULC time-series between 1984-2023, highlighting critical periods of socioecological change over the past 40 years. These results increased the partner’s ability to make scientifically grounded decisions about resource allocation and conservation priorities. This analysis supports the feasibility of applying remote sensing techniques coupled with machine learning models in dry regions, where standard survey methods are frequently limited by accessibility and resource availability. However, we identified limitations in ground-truth data and the difficulty of recognizing certain vegetation types in arid areas. Despite these limitations, the study demonstrated Earth observations' ability to transform wildlife management techniques in distant and data-scarce locations, providing a reproducible foundation for similar ecosystems around the world.

Emmanuel Aklie↗

Gas-Phase Composition as a Predictive Metric for Calendar Life Behavior of Next-Generation Silicon Anodes

The expansion of renewable technologies and electrification of the transportation sector is driving increased demand for next-generation battery materials that provide higher power and energy density with superior cycling and calendar life stability. Silicon (Si) has a theoretical capacity nearly 10x that of graphite, and is therefore a promising anode material candidate to meet these rigorous performance demands. While leading Si anode battery demonstrations are approaching target metrics for cycle life, a series of complex and interrelated modes of reactivity lead to reduced calendar life and therefore challenge practical adoption of these materials. Deconvoluting the degradation processes that impact Si calendar life is critical to informing the rational and accelerated design of improved Si materials. In the present work, we employ novel sampling techniques and GC-MS-FID characterization to measure gas-phase composition during initial Si cycling, which we tie to selective mechanisms of Si passivation. We utilize a tiered analysis approach to identify and quantify the gas-phase reaction products associated with three advanced Si material candidates under practical operating conditions. Ex situ analysis of Si powders (pure chemical reactivity) is coupled with nondestructive in situ sampling of Si electrodes in a practical pouch-cell format (coupled chemical and electrochemical reactivity). We link the observed gas-phase species evolution to electrochemical behavior and measured calendar life of the three Si materials. Further, we evaluate the voltage-resolved evolution of gas-phase species for one such Si nanomaterial, where nonmonotonic gas generation implies competition between passivating reaction pathways. The measured gas-phase compositional data serves as a critical input for our advanced electrochemical SEI models to identify favorable vs unfavorable reaction pathways to stabilize Si. In addition to bolstering a fundamental understanding of Si reactivity, the present approach informs specific and quantifiable gas-phase metrics tied to calendar life improvements in Si, which can streamline and accelerate the process of next-generation material development.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗

GLOBE Observer and the GO on a Trail Data Challenge: A Citizen Science Approach to Generating a Global Land Cover Land Use Reference Dataset

Land cover and land use are highly visible indicators of climate change and human disruption to natural processes. While land cover is frequently monitored over a large area using satellite data, ground-based reference data is valuable as a comparison point. The NASA-funded GLOBE Observer (GO) program provides volunteer-collected land cover photos tagged with location, date and time, and, in some cases, land cover type. When making a full land cover observation, volunteers take six photos of the site, one facing north, south, east, and west (N-S-E-W) respectively, one pointing straight up to capture canopy and sky, and one pointing down to document ground cover. Together, the photos document a 100 meter square of land. Volunteers may then optionally tag each N-S-E-W photo with the land cover types present. Volunteers collect the data through a smartphone app, also called GLOBE Observer, resulting in consistent data. While land cover data collected through GLOBE Observer is ongoing, this paper presents the results of a data challenge held between June 1 and October 15, 2019. Called “GO on a Trail,” the challenge focused on collecting land cover observations at designated points along the Lewis and Clark National Historic Trail (LCNHT), which transects approximately 7,900 kilometers of the United States from east to west. The challenge also included an international component in which participants were recognized for the most data collected during the period. The challenge resulted in more than 2800 land cover data points from around the world with just over 900 land cover data points along the LCNHT. The data collected along the LCNHT is largely within a 1,000 meter corridor along the historic route. Internationally, the challenge had strong participation in Australia, where a Scouts Australia team-based competition was conducted in conjunction with GO on a Trail. GLOBE Observer collections can serve as reference data, ground truthing satellite imagery for the improvement and verification of broad land cover maps. Continued collection using this protocol will build a database documenting climate-related land cover and land use change into the future.

land cover↗

Atmospheric Research 2014 Technical Highlights

Atmospheric research in the Earth Sciences Division (610) consists of research and technology development programs dedicated to advancing knowledge and understanding of the atmosphere and its interaction with the climate of Earth. The Division's goals are to improve understanding of the dynamics and physical properties of precipitation, clouds, and aerosols; atmospheric chemistry, including the role of natural and anthropogenic trace species on the ozone balance in the stratosphere and the troposphere; and radiative properties of Earth's atmosphere and the influence of solar variability on the Earth's climate. Major research activities are carried out in the Mesoscale Atmospheric Processes Laboratory, the Climate and Radiation Laboratory, the Atmospheric Chemistry and Dynamics Laboratory, and the Wallops Field Support Office. The overall scope of the research covers an end-to-end process, starting with the identification of scientific problems, leading to observation requirements for remote-sensing platforms, technology and retrieval algorithm development; followed by flight projects and satellite missions; and eventually, resulting in data processing, analyses of measurements, and dissemination from flight projects and missions. Instrument scientists conceive, design, develop, and implement ultraviolet, infrared, optical, radar, laser, and lidar technology to remotely sense the atmosphere. Members of the various Laboratories conduct field measurements for satellite sensor calibration and data validation, and carry out numerous modeling activities. These modeling activities include climate model simulations, modeling the chemistry and transport of trace species on regional-to-global scales, cloud resolving models, and developing the next-generation Earth system models. Satellite missions, field campaigns, peer-reviewed publications, and successful proposals are essential at every stage of the research process to meeting our goals and maintaining leadership of the Earth Sciences Division in atmospheric science research. Figure 1.1 shows the 20-year record of peer-reviewed publications and proposals among the various Laboratories. This data shows that the scientific work being conducted in the Laboratories is competitive with the work being done elsewhere in universities and other government agencies. The office of Deputy Director for Atmospheric Research will strive to maintain this record by rigorously monitoring and promoting quality while emphasizing coordination and integration among atmospheric disciplines. Also, an appropriate balance will be maintained between the scientists' responsibility for large collaborative projects and missions and their need to carry out active science research as a principal investigator. This balance allows members of the Laboratories to improve their scientific credentials, and develop leadership potentials. Interdisciplinary research is carried out in collaboration with other laboratories and research groups within the Earth Sciences Division, across the Sciences and Exploration Directorate, and with partners in universities and other government agencies. Members of the Laboratories interact with the general public to support a wide range of interests in the atmospheric sciences. Among other activities, the Laboratories raise the public's awareness of atmospheric science by presenting public lectures and demonstrations, by making scientific data available to wide audiences, by teaching, and by mentoring students and teachers. The Atmosphere Laboratories make substantial efforts to attract and recruit new scientists to the various areas of atmospheric research. We strongly encourage the establishment of partnerships with Federal and state agencies that have operational responsibilities to promote the societal application of our science products. This report describes our role in NASA's mission, provides highlights of our research scope and activities, and summarizes our scientists' major accomplishments during calendar year 2014. The composition of the organization is shown in Figure 1.2 for each code. This report is published in a printed version with an electronic version on our atmospheres Web site, http://atmospheres.gsfc.nasa.gov/.

Technical↗

Frhodo: A program for simulating chemical kinetic measurements and optimizing kinetic mechanisms

Chemical kinetic simulations are frequently used to extract kinetic and mechanistic information from experimental data by fitting simulations to the data. For simple systems of consecutive single channel reactions this is a relatively straightforward task. However, as the complexity of the system increases and particularly for systems involving competitive multi-channel reactions manually optimizing a mechanism to obtain the best fits to a range of experimental data quickly becomes a time-intensive and challenging process, especially when rate coefficients have pressure and temperature dependencies. There is considerable potential for exploiting automated optimization methods to rapidly screen reaction mechanisms and optimize the fit by adjusting rate coefficients within well-defined constraints. A new chemical kinetics simulation program, Frhodo, has been developed for this purpose. The program allows either manual simulation of individual experiments or fully automated optimization against a range of experimental data by adjusting user selected reactions within user defined constraints. Frhodo incorporates machine learning-based optimization routines that work by either minimizing standardized residuals or through Bayesian parameter estimation. Frhodo's optimization capabilities are demonstrated by reexamining two previously studied systems of relevance to combustion. Dissociation of diacetyl followed by recombination of methyl radicals is an example of a sequence of single channel, consecutive reactions. Pyrolysis of 2-methyl furan exemplifies multi-channel, unimolecular reactions that are often encountered and have temperature and pressure dependencies in the rate coefficients of the channels and branching ratios between them. For both systems the optimization routines resulted in solutions similar to the original studies. Finally, comments are made on the strengths and limitations of the approach.

0D simulation↗