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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 433 records · Page 24

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Patterns in extracellular enzyme activity and microbial diversity in deep-sea Mediterranean sediments

Deep-sea sediments are populated by diverse microbial communities that derive their nutritional requirements from the degradation of organic matter. Extracellular hydrolytic enzymes play a key role in the survival of microbes by enabling them to access and degrade complex organic compounds that are found in seafloor sediments. Despite their importance, extracellular enzymatic activity is poorly characterized at water depths greater than a few hundred meters where physical properties, such as pressure and temperature, create a unique environment for influencing enzyme behavior. In this work, we investigated microbial communities and enzyme activities in surface sediment collected at four sampling stations in the central Mediterranean Sea at water depths ranging from 800 to 2200 m. Fluorometric assays revealed that extracellular hydrolytic activity varied according to substrate type and water depth which suggests that the distributions of these enzymes within this basin are not homogenous. Furthermore, enzyme activities indicated substantial demand for phosphomonoesters and proteins, with measurable but much lower demand for polysaccharides. Barcoded amplicon sequencing of bacterial and archaeal SSU genes revealed that microbial communities varied across sampling stations and some groups displayed water-depth related trends. Our results demonstrate that heterotrophic capabilities of microbes in deep-sea Mediterranean sediments can differ substantially even within the same region.

16S rRNA↗

DOE OSTI2021

Who is marginalized in energy justice? Amplifying community leader perspectives of energy transitions in Ghana

There is a divide in energy access studies, between technologically-focused modeling papers in engineering and economics, and energy justice frameworks and principles grounded in social sciences. Quantitative computational models are necessary when analyzing energy, and more specifically electricity, systems, as they are technologically-complex systems that can diverge from intuitive patterns. To assure energy justice, these models must be reflective of, and informative to, a wide range of stakeholders, including households and communities alongside utilities, governments, and others. Yet, moving from a qualitative understanding of preferences to quantitative modeling is challenging. In this perspective piece, we pilot the use of the value-focused thinking framework to inform stakeholder engagement. The result is a strategic objective hierarchy that highlights the tradeoffs and the social, economic and technological factors that need to be measured in models. We apply the process in Ghana, using a survey, stakeholder workshops, and follow-up interviews to uncover key tradeoffs and stakeholder-derived objectives. We discuss three key areas that have been rarely, if ever, well-represented in energy models: (1) the relationship between the dynamics of electricity end-use and the technology and economic structure of the system; (2) explicit tradeoffs between electricity access, cost, and reliability as defined by stakeholders; and (3) the definition of new objectives, such as minimizing hazards related to theft. We conclude that this model of engagement provides an opportunity to tie together rigorous qualitative analysis and stakeholder engagement with crucial quantitative models of the electricity system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Classification of US hydropower dams by their modes of operation

A key challenge to understanding ecohydrologic responses to dam regulation is the absence of a universally transferable classification framework for how dams operate. In the present paper, we develop a classification system to organize the modes of operation (MOPs) for U.S. hydropower dams and powerplants. To determine the full diversity of MOPs, we mined federal documents, open-access data repositories, and internet sources. W then used CART classification trees to predict MOPs based on physical characteristics, regulation, and project generation. Finally, we evaluated how much variation MOPs explained in sub-daily discharge patterns for stream gages downstream of hydropower dams. After reviewing information for 721 dams and 597 power plants, we developed a 2-tier hierarchical classification based on 1) the storage and control of flows to powerplants, and 2) the presence of a diversion around the natural stream bed. This resulted in nine tier-1 MOPs representing a continuum of operations from strictly peaking, to reregulating, to run-of-river, and two tier-2 MOPs, representing diversion and integral dam-powerhouse configurations. Although MOPs differed in physical characteristics and energy production, classification trees had low accuracies (<62%), which suggested accurate evaluations of MOPs may require individual attention. MOPs and dam storage explained 20% of the variation in downstream subdaily flow characteristics and showed consistent alterations in subdaily flow patterns from reference streams. Lastly, this standardized classification scheme is important for future research including estimating reservoir operations for large-scale hydrologic models and evaluating project economics, environmental impacts, and mitigation.

13 HYDRO ENERGY↗

DOE OSTI2023

Lighting up the LHC with Dark Matter

We show that simultaneously explaining dark matter and the observed value of the muon’s magnetic dipole moment may lead to yet unexplored photon signals at the LHC. We consider the Minimal Supersymmetric Standard Model with electroweakino masses in the few-to-several hundred GeV range, and opposite sign of the Bino mass parameter with respect to both the Higgsino and Wino mass parameters. In such region of parameter space, the spin-independent elastic scattering cross section of a Bino-like dark matter candidate in direct detection experiment is suppressed by cancellations between different amplitudes, and the observed dark matter relic density can be realized via Bino-Wino co-annihilation. Moreover, the observed value of the muon’s magnetic dipole moment can be explained by Bino and Wino loop contributions. Interestingly, “radiative” decays of Wino-like neutralinos into the lightest neutralino and a photon are enhanced, whereas decays into leptons are suppressed. While these decay patterns weaken the reach of multi-lepton searches at the LHC, the radiative decay opens a new window for probing dark matter at the LHC through the exploration of parameter space regions beyond those currently accessible. To complement the current electroweakino searches, we propose searching for a single (soft) photon plus missing transverse energy, accompanied by a hard initial state radiation jet.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

A spatially based area–time inundation index model developed to assess habitat opportunity in tidal–fluvial wetlands and restoration sites

The hydrodynamics of tidal wetland areas in the lower Columbia River floodplain and estuary directly affect habitat opportunity for endangered salmonid fishes. Physical and biological structures and functions in the system are directly affected by inundation patterns influenced by tidal cycles, hydropower operations, river discharge, upriver water withdrawals, climate, and physical barriers such as dikes, culverts, and tide gates. Ongoing ecosystem restoration efforts are intended to increase the opportunity for salmon to access beneficial habitats by hydrologically reconnecting main-stem river channels and diked areas within the historical floodplain. To address the need to evaluate habitat opportunity, a geographic information system-based Area-Time Inundation Index Model (ATIIM) was developed. Additionally, the ATIIM integrates in situ or modeled hourly water-surface elevation (WSE) data and advanced terrain processing of high-resolution elevation data. The ATIIM uses a spatially based wetted-area algorithm to determine site average bankfull elevation, two- and three-dimensional inundation extent, and other site metrics. Hydrological process metrics such as inundation frequency, duration, maximum area, and maximum frequency area can inform evaluation of proposed restoration sites; e.g., determine trade-offs between WSE and habitat opportunity, contrast alternative restoration designs, predict impacts of altered flow regimes, and estimate nutrient and biomass fluxes. In an adaptive management framework, this model can be used to provide standardized site comparisons and effectiveness monitoring of changes in the developmental trajectories of restoration sites. Overall, results are presented for 11 wetlands representative of tidal marshes, tidal forested wetlands, and restoration sites.

42 ENGINEERING↗

DOE OSTI2017

Boundary migration in a 3D deformed microstructure inside an opaque sample

How boundaries surrounding recrystallization grains migrate through the 3D network of dislocation boundaries in deformed crystalline materials is unknown and critical for the resulting recrystallized crystalline materials. Furthermore, by using X-ray Laue diffraction microscopy, we show for the first time the migration pattern of a typical recrystallization boundary through a well-characterized deformation matrix. The data provide a unique possibility to investigate effects of both boundary misorientation and plane normal on the migration, information which cannot be accessed with any other techniques. Our results show that neither of these two parameters can explain the observed migration behavior. Instead we suggest that the subdivision of the deformed microstructure ahead of the boundary plays the dominant role. Our experimental observations challenge the assumptions of existing recrystallization theories, and set the stage for determination of mobilities of recrystallization boundaries.

36 MATERIALS SCIENCE↗

DOE OSTI2024

OpenPATH - Leveraging Technology to Measure Travel Behavior

Shifting transportation to more sustainable modes is a key piece of the decarbonization puzzle. However, mobility behavior and travel patterns are difficult to influence because they are difficult to measure. OpenPATH provides a tool to capture longitudinal behaviors through a smartphone application. Agencies interested in gathering data about a population's travel behavior can set up a deployment of the app customized to the needs of their community. Partners can choose between simple mode and purpose labels or surveys for each trip to balance the level of user engagement with the associated burden. The labels, trip surveys, and an initial demographic survey can all be tailored to the specific context of the deployment. The OpenPATH tool is unique in its open-source nature, ability to gather detailed longitudinal travel data, and design allowing direct engagement with travelers. A valuable technological advancement, this tool enables partners to measure the way changes in the transportation landscape impact their community. The suite of tools includes both public and administrator dashboards. The public dashboard supports continuous data analysis through charts presenting trip information updated daily. The administrator dashboard displays geospatial data and supports data export. Example applications have included e-bike programs; gathering valuable metrics on increased access to opportunities and reduction in VMT, and studies aimed at understanding existing mobility behavior to see where advancements such as electric vehicles could fit into these habits. OpenPATH collects travel data in association with an initial demographic survey, enabling detailed insight into the behavior patterns or impact of a certain program on different populations.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Foundations of an Electric Mobility Strategy for the City of Mexicali

The Foundations of an Electric Mobility Strategy for the city of Mexicali aligns with numerous energy, environmental, and transport plans and will help Mexicali meet multiple related goals. Mexicali’s energy mix, with 28% renewables, already enables plugin electric vehicles (PEVs) to reduce the mass of greenhouse gases (GHGs) per km driven 2/3 below that of their conventional counterparts. This GHG benefit will increase should Mexicali take steps to further increase their share of renewables in their electricity supply. Beyond increasing renewables, Mexicali could possibly deploy PEVs so that electric load is added in the right location (depending on further analysis of substations and feeders) and at the right time (between 21:00 and 11:00) in order to minimize grid upgrade costs. There are a handful of charge timing control mechanisms –at various stages of development– that Mexicali could implement. Transport electrification can facilitate mass transit by powering buses, trains, and small vehicles that get people from their homes or work to the transit stations and vice versa. Mexicali could utilize fleets as early PEV adopters in order to gain acceptance and add electric vehicle supply equipment (EVSE). Recommended prioritization of different types of fleets are suggested in this report: transit buses, school buses, airport ground support equipment (GSE), refuse trucks, taxis, shuttle buses, campus vehicles, delivery trucks, utility trucks, and finally semitrailers. There are a handful of policy options that Mexicali could use to incentivize fleets to purchase PEVs, including mandates, economic incentives, energy performance contracts, waivers to access restrictions, electricity discounts, and EVSE requirements in building codes. Mexicali’s taxi fleet was an early adopter of PEVs and had experienced some challenges—mostly related to the insufficient range of the taxis due to hot weather. In this report, we strategize ways to extend the range of the current electric taxis, including ways to make charging more convenient to the drivers, and more suggestions for appropriate vehicles to purchase in the future. This report also includes the groundwork of geotracking Mexicali’s taxi fleet so that more detailed recommendations can be made in the future. Once fleets have increased PEV acceptance and EVSE installations, the market will be ready to expand to private vehicle owners. In order to do this, more EVSE needs to be installed in the right locations. This mobility strategy lays out general local areas where EVSE could be well utilized, based on traffic patterns, land use, and demographic data. Mexicali could approach businesses within these areas that would likely make suitable hosts, based on how well they can profit from the additional business that EVSE would bring. Mexicali could then adopt a series of purchase incentives (including sales tax waivers or access to high-occupancy vehicles [HOV] lanes) that would encourage private vehicle owners to purchase PEVs. Purchase incentives run the risk of creating equity issues, which can be countered by promoting electrification in mass transit, creating more HOV lanes that have PEV exemptions, and installing EVSEs in underserved communities. Private PEV ownership will require a set of experts that Mexicali can help train, including PEV repair technicians, EVSE installation electricians, and first responders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Chemical Design of Spin Frustration to Realize Topological Spin Glasses

Patterning spins to generate collective behavior is at the core of condensed matter physics. Physicists develop techniques, including the fabrication of magnetic nanostructures and precision layering of materials specifically to engender frustrated lattices. As chemists, we can access such exotic materials through targeted chemical synthesis and create new lattice types by chemical design. Here, in this study, we introduce a new approach to induce magnetic frustration on a modified honeycomb lattice through a competition of alternating antiferromagnetic (AFM) and ferromagnetic (FM) nearest-neighbor interactions. By subtly modulating these two types of interactions through facile synthetic modifications, we created two systems: (1) a topological spin glass and (2) a frustrated spin-canted magnet with low-temperature exchange bias. To design this unconventional magnetic lattice, we used a metal–organic framework (MOF) platform, Ni 3 (pymca) 3 X 3 (NipymcaX where pymca = pyrimidine-2-carboxylato and X = Cl, Br). We isolated two MOFs, NipymcaCl and NipymcaBr, featuring canted Ni 2+ -based moments. Despite this similarity, differences in the single-ion anisotropies of the Ni 2+ spins result in distinct magnetic properties for each material. NipymcaCl is a topological spin glass, while NipymcaBr is a rare frustrated magnet with low-temperature exchange bias. Density functional theory calculations and Monte Carlo simulations on the NipymcaX lattice support the presence of magnetic frustration as a result of alternating AFM and FM interactions. Our calculations enabled us to determine the ground-state spin configuration and the distribution of spin–spin correlations relative to paradigmatic kagomé and triangular lattices. This modified honeycomb lattice is similar to the electronic Kekulé-O phase in graphene and provides a highly tunable platform to realize unconventional spin physics.

Exchange bias↗

DOE OSTI2012

HERCULES: A Pattern Driven Code Transformation System

New parallel computers are emerging, but developing efficient scientific code for them remains difficult. A scientist must manage not only the science-domain complexity but also the performance-optimization complexity. HERCULES is a code transformation system designed to help the scientist to separate the two concerns, which improves code maintenance, and facilitates performance optimization. The system combines three technologies, code patterns, transformation scripts and compiler plugins, to provide the scientist with an environment to quickly implement code transformations that suit his needs. Unlike existing code optimization tools, HERCULES is unique in its focus on user-level accessibility. In this paper we discuss the design, implementation and an initial evaluation of HERCULES.

Computer Science↗

DOE OSTI2012

HERCULES: A Pattern Driven Code Transformation System

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

Mobility Data and Models Informing Smart Cities

This presentation explores the interactions of Emerging Technology, Changing Urban Environments, and Urban Travel Behavior on Mobility and Energy Impacts. Key findings include quantifying impacts of emerging mobility, access and infrastructure associated with new mobility choices and services in urban areas. The results demonstrate new data collection methods and capabilities to understand and identify key levers to improve energy productivity of future mobility systems and of quickly evolving MaaS and COVID-19 contexts to monitor rapidly shifting urban mobility patterns. Under development are mode choice models for new modes versus traditional modes. Initial estimates are developed on the potential of workforce mobility strategies in shaping future energy-efficient mobility system impacts. For mode replacement and workforce mobility, this presentation offers observability into the changes in number of transactions per mode, after ride-hailing/TNC/MaaS introduction and in origins of workforce to enable user need-driven reimagining of efficient mobility systems: Seattle (SEA-TAC) airport: for every 100 new TNC transactions for ground transportation, ~27% replaced transit, 35% replaced parking, 17% replaced car rentals, and 21% replaced taxis. Similarly, at Denver International (DEN), ride-hailing transactions replaced transit, parking, car rental and taxis at a rate of 34.7%, 39.0%, 16.6%, and 9.7%, respectively. A workforce mobility tool, analysis/visualization techniques, and capabilities to understand and identify key job commute needs, new choices in access to job opportunities, and affordability aspects as levers to improve energy productivity of future integrated urban mobility systems.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2014

Quantitative Analysis of Human Salivary Gland-Derived Intact Proteome Using Top-Down Mass Spectrometry

There are several notable challenges inherent to fully characterizing the entirety of the human saliva proteome using bottom-up approaches, including polymorphic isoforms, post-translational modifications, unique splice variants, deletions, and truncations. To address these challenges, we have developed a top-down based liquid chromatography-mass spectrometry (LC-MS) approach, which cataloged 20 major human salivary proteins with a total of 83 proteoforms, containing a broad range of post-translational modifications. Among these proteins, several previously reported disease biomarker proteins were identified at the intact protein level, such as beta-2 microglobulin (B2M). In addition, intact glycosylated proteoforms of several saliva proteins were also characterized, including intact N-glycosylated protein prolactin inducible protein (PIP) and O-glycosylated acidic protein rich protein (aPRP). These characterized proteoforms constitute an intact saliva proteoform database, which was used for quantitative comparison of intact salivary proteoforms among six healthy individuals. Human parotid (PS) and submandibular/sublingual gland (SMSL) secretion samples (2 μg of protein each) from six healthy individuals were compared using RPLC coupled with the 12T FTICR mass spectrometer. Significantly different protein and PTM patterns were resolved with high reproducibility between PS and SMSL glands. The results from this study provide further insight into the potential mechanisms of PTM pathways in oral glandular secretion, expanding our knowledge of this complex yet easily accessible fluid. Intact protein LC-MS approach presented herein can potentially be applied for rapid and accurate identification of biomarkers from only a few microliters of human glandular saliva.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2017

Silicone elastomers capable of large isotropic dimensional change

Described herein is a highly effective route towards the controlled and isotropic reduction in size-scale, of complex 3D structures using silicone network polymer chemistry. In particular, a class of silicone structures were developed that once patterned and cured can `shrink` micron scale additive manufactured and lithographically patterned structures by as much as 1 order of magnitude while preserving the dimensions and integrity of these parts. This class of silicone materials is compatible with existing additive manufacture and soft lithographic fabrication processes and will allow access to a hitherto unobtainable dimensionality of fabrication.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Silicone elastomers capable of large isotropic dimensional change

36 MATERIALS SCIENCE↗

DOE OSTI2024

Species-specific ribosomal RNA-FISH identifies interspecies cellular-material exchange, active-cell population dynamics and cellular localization of translation machinery in clostridial cultures and co-cultures

ABSTRACT The development of synthetic microbial consortia in recent years has revealed that complex interspecies interactions, notably the exchange of cytoplasmic material, exist even among organisms that originate from different ecological niches. Although morphogenetic characteristics, viable RNA and protein dyes, and fluorescent reporter proteins have played an essential role in exploring such interactions, we hypothesized that ribosomal RNA-fluorescence in situ hybridization (rRNA-FISH) could be adapted and applied to further investigate interactions in synthetic or semisynthetic consortia. Despite its maturity, several challenges exist in using rRNA-FISH as a tool to quantify individual species population dynamics and interspecies interactions using high-throughput instrumentation such as flow cytometry. In this work, we resolve such challenges and apply rRNA-FISH to double and triple co-cultures of Clostridium acetobutylicum, Clostridium ljungdahlii, and Clostridium kluyveri . In pursuing our goal to capture each organism’s population dynamics, we demonstrate dynamic rRNA, and thus ribosome, exchange between the three species leading to the formation of hybrid cells. We also characterize the localization patterns of the translation machinery in the three species, identifying distinct, dynamic localization patterns among them. Our data also support the use of rRNA-FISH to assess the culture’s health and expansion potential, and, here again, our data find surprising differences among the three species examined. Taken together, our study argues for rRNA-FISH as a valuable and accessible tool for quantitative exploration of interspecies interactions, especially in organisms which cannot be genetically engineered or in consortia where selective pressures to maintain recombinant species cannot be used. IMPORTANCE Though dyes and fluorescent reporter proteins have played an essential role in identifying microbial species in co-cultures, we hypothesized that ribosomal RNA-fluorescence in situ hybridization (rRNA-FISH) could be adapted and applied to quantitatively probe complex interactions between organisms in synthetic consortia. Despite its maturity, several challenges existed before rRNA-FISH could be used to study Clostridium co-cultures of interest. First, species-specific probes for Clostridium acetobutylicum and Clostridium ljungdahlii had not been developed. Second, “state-of-the-art” labeling protocols were tedious and often resulted in sample loss. Third, it was unclear if FISH was compatible with existing fluorescent reporter proteins. We resolved these key challenges and applied the technique to co-cultures of C. acetobutylicum , C. ljungdahlii , and Clostridium kluyveri . We demonstrate that rRNA-FISH is capable of identifying rRNA/ribosome exchange between the three organisms and characterized rRNA localization patterns in each. In combination with flow cytometry, rRNA-FISH can capture sub-population dynamics in co-cultures.

Hill, John D.↗

DOE OSTI2024

Predicting U.S. federal fleet electric vehicle charging patterns using internal combustion engine vehicle fueling transaction statistics

Utilizing fueling transactions from internal combustion engine vehicles (ICEVs), the authors estimated how frequently midday public charging would be required for U.S. federal fleet battery electric vehicles (BEVs). Fueling transaction summary statistics are more widely available than trip-level telematics data, making this methodology more accessible and transferable to other researchers and fleet managers considering BEV replacements. For example, readers can easily apply a linear model using only the count of back-to-back fueling events at gas stations over 57 straight-line miles apart to predict days exceeding range. This linear regression predicted binned days exceeding 250 miles at 80% accuracy on a hold-out test set from the same fleet as the training data and 66 % accuracy on a new fleet displaying different driving behaviors. The authors additionally provide linear equations for days exceeding 200 and 300 miles as alternative range estimates to account for differences in BEV range and temperature impacts. Beyond the single-feature linear models which readers can apply, the authors tuned and trained other machine learning models on a variety of fueling transaction statistics including consecutive transaction distances, transaction distance from garage, estimated miles traveled from fuel economy and fuel quantity, and transaction periodicity. Utilizing a subset of 1678 light-duty federal fleet vehicles which contained daily vehicle miles traveled (VMT) in addition to fueling statistics, the authors determined which fueling transaction statistics were most relevant in predicting driving days exceeding 250 miles (an approximation of BEV rated driving range). In support of the U.S. federal fleet transition to zero-emission vehicles (ZEVs), the authors used these statistics and machine learning models to predict the frequency of BEV midday charging. After training models on the subset with VMT, the authors predicted days exceeding rated range for 112,902 light-duty vehicles operating in similar circumstances in the federal fleet using a Support Vector Regressor (SVR). In conclusion, they then used the projections as part of the ZEV Planning and Charging (ZPAC) tool to identify optimal candidates for BEVs for the federal fleet. An anonymized version of ZPAC is included in the supplementary materials.

25 ENERGY STORAGE↗

DOE OSTI2023

Approaches for Synthesis and Deployment of Controller Models on Automated Vehicles for Car-following in Mixed Autonomy

This paper describes the software design patterns and vehicle interfaces that were employed to transition vehicle controllers from simulation environments to open-road field experiments. The approach relies on a life cycle that utilizes model-based design and code generation, along with agile software development, and both software and hardware-in-the-loop testing, with additional safety margins. Autonomous designs should consider the dynamics of mixed autonomy in traffic to safely operate among humans. The software that provides a vehicle’s behavior intelligence is often developed through simulation, which may have a mismatch between dynamics, or as a result of a reinforcement learning workflow, which may be a black box with challenges to analyze. In each of these cases, it is important to have research interfaces that provide strongly typed data streams accessible to researchers who are not software experts while continuing to satisfy safety and liveness constraints. This paper describes how we design the hardware platform interfaces and software design process for a mixed autonomy traffic experiment with a leader-follower scenario. Controller synthesis for these vehicles requires clearly articulated vehicle interfaces and software design patterns for successful onboard deployment. Testing strategies for such controllers are also described before algorithms are transitioned to full-scale field experiments with safety operators for the vehicles. Testing strategies include software-in-the-loop simulation testing, hardware-in-the-loop simulation, ghost-car testing, and read-only testing in live traffic. With our approach, we were not only able to validate our controller synthesized in scripts and simulation, but also able to scale deployment to multiple vehicles.

Bhadani, Rahul↗