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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 127 records · Page 7

1997/1998 Regional Travel Household Interview Survey

The 1997/1998 Regional Travel—Household Interview Survey was conducted in the 28-county New York-New Jersey-Connecticut metropolitan area, including 12 counties in New York, 14 counties in New Jersey, and 2 counties in Connecticut. The study was jointly funded by the New York Metropolitan Transportation Council and the North Jersey Transportation Planning Authority (NJTPA). The purpose of the survey was to provide information suitable for gaining an in-depth understanding of the travel behavior of households and individuals, as well as the activities, demographics, and other factors that affect such behavior. The survey was a diary-type travel survey, in which detailed travel information and basic demographic and socioeconomic features were collected for each member of the 11,264 participating households during an entire travel day. The sample for analysis of resident-based weekday travel is 10,971 for the entire 28-county metro area. The weekend sample, comprised of 275 households, is restricted to the NJTPA counties of northern New Jersey and compliments the results of the 1995 Nationwide Personal Transportation Survey for the entire area.

1Hz data↗

Time-Energy Uncertainty Relation for Noisy Quantum Metrology

Detection of very weak forces and precise measurement of time are two of the many applications of quantum metrology to science and technology. To sense an unknown physical parameter, one prepares an initial state of a probe system, allows the probe to evolve as governed by a Hamiltonian 𝐻 for some time 𝑡, and then measures the probe. If 𝐻 is known, we can estimate 𝑡 by this method; if 𝑡 is known, we can estimate classical parameters on which 𝐻 depends. The accuracy of a quantum sensor can be limited by either intrinsic quantum noise or by noise arising from the interactions of the probe with its environment. In this work, we introduce and study a fundamental trade-off, which relates the amount by which noise reduces the accuracy of a quantum clock to the amount of information about the energy of the clock that leaks to the environment. Specifically, we consider an idealized scenario in which a party Alice prepares an initial pure state of the clock, allows the clock to evolve for a time that is not precisely known, and then transmits the clock through a noisy channel to a party Bob. Meanwhile, the environment (Eve) receives any information about the clock that is lost during transmission. We prove that Bob’s loss of quantum Fisher information about the elapsed time is equal to Eve’s gain of quantum Fisher information about a complementary energy parameter. We also prove a similar, but more general, trade-off that applies when Bob and Eve wish to estimate the values of parameters associated with two noncommuting observables. We derive the necessary and sufficient conditions for the accuracy of the clock to be unaffected by the noise, which form a subset of the Knill-Laflamme error-correction conditions. A state and its local time-evolution direction, if they satisfy these conditions, are said to form a metrological code. We provide a scheme to construct metrological codes in the stabilizer formalism. We show that there are metrological codes that cannot be written as a quantum error-correcting code with similar distance in which the Hamiltonian acts as a logical operator, potentially offering new schemes for constructing states that do not lose any sensitivity upon application of a noisy channel. We discuss applications of the trade-off relation to sensing using a quantum many-body probe subject to erasure or amplitude-damping noise.

metrology↗

Rational Materials and Structure Design for Improving the Performance and Durability of High Temperature Proton Exchange Membranes (HT-PEMs)

Hydrogen energy as the next-generation clean energy carrier has attracted the attention of both academic and industrial fields. A key limit in the current stage is the operation temperature of hydrogen fuel cells, which lies in the slow development of high-temperature and high-efficiency proton exchange membranes. Currently, much research effort has been devoted to this field, and very innovative material systems have been developed. The authors think it is the right time to make a short summary of the high-temperature proton exchange membranes (HT-PEMs), the fundamentals, and developments, which can help the researchers to clearly and efficiently gain the key information. In this paper, the development of key materials and optimization strategies, the degradation mechanism and possible solutions, and the most common morphology characterization techniques as well as correlations between morphology and overall properties have been systematically summarized.

08 HYDROGEN↗

Characteristics of an Introduced Walleye Population with Implications for Suppression

Abstract The management of introduced fishes, including Walleye Sander vitreus, whether for control or enhancement, requires understanding of population dynamics at the invasion front. Walleye recently established in the Pend Oreille basin, Idaho, threaten the existing salmonid-based fish community and associated recreational fishery. Therefore, the objectives of this study were to describe population growth and associated life history characteristics. Walleye were sampled in October of 2011, 2014, and 2017 using a standardized gill netting survey protocol to describe trends in relative abundance and evaluate population dynamics. Relative abundance increased exponentially from 1.4 to 4.3 fish/net over the 6-year monitoring period. This population was characterized by fast somatic growth, robust body condition, and early age at maturity at or near the biological maxima for Walleye. Among the survey years, mean length at age 2 varied for female (359–441 mm) and male (358–426 mm) Walleye and relative weight varied from 91 to 98. The sampled Walleye matured at 1 to 4 years of age, and recruitment became more consistent as abundance increased. These density-dependent metrics suggest that the Walleye population is still at low density relative to carrying capacity. The information that was gained from this study was used to better understand potential risks and guide management decisions related to experimental population suppression that is now underway. Suppression under these conditions must overcome the recruitment capabilities of the population. We conclude that natural mortality is likely regulated by density-dependent processes. Therefore, at current (low) density, fishing mortality may be entirely additive and compensation is unlikely to further complicate management.

Ryan, Robert G.↗

Chapter 13: Time-of-Flight Secondary-Ion Mass Spectrometry and Atom Probe Tomography

Time-of-flight secondary-ion mass spectrometry (TOF-SIMS) and atom probe tomography (APT) have many similarities. Both detect the chemical makeup of a solid material at ppm or better sensitivity, while retaining the spatial location information from the signal. Both use a similar principle to measure a signal associated with a given charged secondary ion—the flight time it takes a secondary ion to reach the detector after it is generated. Both are destructive techniques—albeit destructive of very small volumes—because the signal measured is generated by the removal of material from the sample itself. Importantly, both techniques require ultra-high vacuum (UHV) to ensure that the secondary ions, once generated, can reach the detector without collision with other atoms in the gas phase. In the case of TOF-SIMS, the samples can vary from several mm to several inches in size, whereas for APT, the samples are cones several hundred microns in size that are prepared in a special manner (covered in detail later in the chapter). We will discuss the basic fundamentals of each technique and cover several examples of the technique applied to photovoltaic materials, which should give a good idea of the types of information one can gain from TOF-SIMS and APT and how they are complementary as they both operate at different length scales: at the hundreds of microns to hundreds of nanometer scale for TOF-SIMS and at the nanometer to a few angstroms scale for APT.

41 EE - Solar Energy Technologies Office (EE-4S)↗

A device for volatile organic compound (VOC) analysis from skin using heated dynamic headspace sampling

Abstract Human skin is an important source of volatile organic compounds (VOCs) offering noninvasive methods to gain clinical metabolite information. This work was focused on the development of a skin sampling device based on a dynamic headspace sampling method with the addition of temperature to increase VOC metabolite recovery. The device preconcentrates skin VOC emissions onto a sorbent substrate, which can either be preserved for offline analysis or attached to a real time sensor downstream. In this work, skin VOC samples were analyzed offline using thermal desorption-gas chromatography-mass spectrometry. A list of 10 common skin VOCs was pre-selected to optimize parameters of sampling time, sampling temperature, and sorbent selection. Overall, this study highlights an effective skin VOC sampling technology with a heating dimension (40 °C, rather than 30 °C or no heating) with a sampling time of 15 min (rather than 5 or 30 mins) and onto Tenax TA sorbent (rather than PDMS), which collectively increases the recovery of compounds with lower vapor pressure and decreases the observed variability in skin VOC measurements. Finally, a list of 79 skin VOC compounds were detected and identified within a cohort of 20 young, healthy volunteers.

Biochemistry & Molecular Biology↗

Accelerating the development of a sustainable bioenergy portfolio through stable isotopes

Bioenergy could help limit global warming to 2°C above pre-industrial levels while supplying almost a fourth of the world's renewable energy needs by 2050. However, the deployment of bioenergy raises concerns that adoption at meaningful scales may lead to unintended negative environmental consequences. Meanwhile, the full consolidation of a bioenergy industry is currently challenged by a sufficient, resilient, and resource-efficient biomass supply and an effective conversion process. Here, we provide a comprehensive analysis of how stable isotope approaches have accelerated the development of a robust bioeconomy by advancing knowledge about environmental sustainability, feedstock development, and biological conversion. We show that advances in stable isotope research have generated crucial information to (1) gain mechanistic insight into the potential of bioenergy crops to mitigate climate change as well as their impact on water and nutrient cycling; (2) develop high-yielding, resilient feedstocks that produce high-value bioproducts in planta; and (3) engineer microbes to enhance feedstock conversion to bioenergy products. Further, we highlight knowledge gaps that could benefit from future research facilitated by stable isotope approaches. We conclude that advances in mechanistic knowledge and innovations within the field of stable isotopes in cross-disciplinary research actions will greatly contribute to breaking down the barriers to establishing a robust bioeconomy.

59 BASIC BIOLOGICAL SCIENCES↗

1994 Portland Household Travel Survey

The Portland Household Travel Survey was conducted under the auspices of the Oregon Department of Transportation to provide information suitable for gaining an in-depth understanding of the activity and travel behavior of both households in metropolitan areas and the individuals within those households. The first round of surveys collected household activity data from the four metropolitan planning organization areas around Portland, plus three extra counties (Marion, Polk, and Yamhill). A total of 11,762 households participated in this study. Each household member was asked to record any activity that lasted 30 minutes or longer, or any activity that required travel for the specified 48-hour period.

1Hz data↗

Datasets for DOE 2021 Communities LEAP Pilot

This submission offers data aligned to each of the four eligibility criteria outlined in the United States Department of Energy (DOE) 2021 Communities LEAP (Local Energy Action Program) Pilot. Please visit the LEAP website (https://www.energy.gov/communitiesLEAP/communities-leap) to learn more about LEAP and gain additional contextual information for how these data may be used. The data provided in the file approximates how the eligibility criteria apply at the census tract level across the United States (U.S.). The excel file available for download provides information pertaining to each of the four criteria outlined (average energy burden, percent low income, historic fossil energy communities) for all census tracts within the 50 U.S. States, the District of Columbia (D.C.), and Puerto Rico. The tabs within the excel file provide a file description, a summary data table (a simplified, easy to use presentation of the four eligibilities criteria), metadata (description, source, and other pertinent details for all variables provided), and a full, detailed data table. Please note that while these data are provided at the census tract level, census tracts do not necessarily have the same physical boundaries as a community but were used as they provide the closest proxy based on publicly available information collected using an empirically robust method. U.S. territories are not listed but are eligible to apply to Communities LEAP. As stated in the Opportunity Announcement, applying communities should describe how they meet the eligibility criteria in their application even if these data do not specifically show that they are eligible.

Communities↗

Datasets for DOE 2023 Communities LEAP

This data is aligned to eligibility criteria outlined in the United States Department of Energy (DOE) 2023 Communities LEAP (Local Energy Action Program). Please visit the LEAP website (https://www.energy.gov/communitiesLEAP/communities-leap) to learn more about LEAP and gain additional contextual information for how these data may be used. The data provided approximates how the eligibility criteria apply at the census tract level across the United States. This EDX submission provides access to information pertaining to each of the four eligibility criteria outlined (average energy burden, percent low income, communities with a historic economic dependence on fossil fuel industrial facilities, and disadvantaged communities) for all census tracts within the 50 U.S. States, the District of Columbia (D.C.), and Puerto Rico. This information can be access in a detailed excel spreadsheet or through the linked interactive web application (https://arcgis.netl.doe.gov/portal/apps/experiencebuilder/experience/?id=2a77f443d72b4a4d82474b3ffe33b8cd). Please note that while these data are provided at the census tract level, census tracts do not necessarily have the same physical boundaries as a community but were used as they provide the closest proxy based on publicly available information collected using an empirically robust method. U.S. territories are not listed but are eligible to apply to Communities LEAP. As stated in the Opportunity Announcement, applying communities should describe how they meet the eligibility criteria in their application even if these data do not specifically show that they are eligible.

2023↗

Sample Preparation for 3D Characterization of Irradiated Fuel

Thorough characterization of nuclear fuel is essential when striving to understand its microstructural evolution in response to varying irradiation conditions. A detailed understanding of the microstructural evolution of irradiated fuel can be useful when predicting the fuel’s response to off-normal conditions and related phenomena such as high burnup fuel fragmentation (HBFF) and fission gas release. This sort of characterization and the study of complex phenomena like HBFF that are related to fuel performance are an important part of the US Department of Energy Office of Nuclear Energy’s Advanced Fuels Campaign (AFC). Multiple characterization techniques are commonly used to perform post-irradiation examination (PIE) analysis on an irradiated fuel sample, but many of these techniques are limited to the 2D surface analysis of the fuel pellet. Although there is a lot of useful information to be gained by analyzing the fuel pellet surface, a 2D analysis provides only an approximation of the nature of the material’s features, such as porosity and grain structure. Therefore, it is critical to analyze the 3D structure of the material, as materials exist and respond to conditions in all three dimensions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

JANA2 LDRD (Final Project Report)

The project sought to develop a second generation of the JANA reconstruction framework that leverages modern programming features (C++11 and C++14) while maintaining its basic user centric design. The goals included making the project easy to deploy to large HPC facilities such as NERSC and to include detailed documentation to allow scientists outside of Jefferson Lab to use it at such a facility. This would position JLab to play a key role in the larger Laboratory based computing ecosystem under the ASCR initiative. The experience gained will help inform the design of Exascale class applications for experimental nuclear physics. Developing a next generation JANA provides an advantage over older serial frameworks or ones retro-fitted to provide some multi-threading support. That technique requires significantly more memory than multi-threading which leads to compute jobs being limited by available RAM, and not fully utilizing the available CPU. The smaller memory footprint of multi-threaded programs also leads to increased efficiency due to fewer cache misses. It is for these and other reasons that multi-threading is the more accepted industry standard in the modern era.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Discovering Dark Matter Clumps and Primordial Particles with Galaxies

Cosmological observations and galaxy dynamics seem to imply that five out of six parts in mass of all matter in the universe is composed of dark matter, which is not accounted for by the Standard Model of particles. The cold dark matter (CDM) paradigm has been extremely successful at describing observations on large-cosmological scale. However, many different dark matter candidates have the same observable effects as CDM on large-length scales. One possible avenue to distinguish between these different models is to look on much smaller-length scales, where usually dark matter models become distinguishable. This research developed the theoretical framework and statistical tools needed to map the detailed distribution of dark matter on subgalactic scales using strong gravitational lensing. A second goal of this research was to build new statistical techniques that efficiently exploit the full power of cosmic-structure data from next-generation surveys. Galaxy clustering on large scales provides significant cosmological information through the power spectrum. Additional information can be gained from higher-order statistics. This research provided new ways to understand the initial conditions of the universe from current and upcoming cosmological surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Game Theory in Cybersecurity: A Review of Applications, Models, and Challenges

There are no aspects of society left unchanged by the Internet. From commerce to communication, from entertainment to engineering, every industry and sphere of influence exists in a new state thanks to the advent of the information age. This convenience, rarely controverted, comes with capricious actors, who wish to gain access to these systems for myriad reasons, be it financial, political, or mere intellectual gain. This paper presents information that can help readers to better understand the fundamentals of cybersecurity from a game theory perspective, such as coalitional games, Colonel Blotto systems, or how to find Nash Equilibrium. This paper also reviews how game theory can enhance understanding of cybersecurity through cooperative and non-cooperative methods, such as information sharing, defense modeling, and attacker analysis. The authors use the analysis to serve as a bridge for those in either field who need a way to best comprehend the methodologies of their contrasting fields.

Egan, Matthew↗

Increased power gains from wake steering control using preview wind direction information

Abstract. Yaw controllers typically rely on measurements taken at the wind turbine, resulting in a slow reaction to wind direction changes and subsequent power losses due to misalignments. Delayed yaw action is especially problematic in wake steering operation because it can result in power losses when the yaw misalignment angle deviates from the intended one due to a changing wind direction. This study explores the use of preview wind direction information for wake steering control in a two-turbine setup with a wind speed in the partial load range. For these conditions and a simple yaw controller, results from an engineering model identify an optimum preview time of 90 s. These results are validated by forcing wind direction changes in a large-eddy simulation model. For a set of six simulations with large wind direction changes, the average power gain from wake steering increases from only 0.44 % to 1.32 %. For a second set of six simulations with smaller wind direction changes, the average power gain from wake steering increases from 1.24 % to 1.85 %. Low-frequency fluctuations are shown to have a larger impact on the performance of wake steering and the effectiveness of preview control, in particular, than high-frequency fluctuations. From these results, it is concluded that the benefit of preview wind direction control for wake steering is substantial, making it a topic worth pursuing in future work.

17 WIND ENERGY↗

Empirical Study of Effect of Dynamic Travel Time Information on Driver Route Choice Behavior

The objective of this paper is to study the effect of travel time information on day-to-day driver route choice behavior. A real-world experimental study is designed to have participants repeatedly choose between two alternative routes for five origin-destination pairs over multiple days after providing them with dynamically updated travel time information (average travel time and travel time variability). The results demonstrate that historical travel time information enhances behavioral rationality by 10% on average and reduces inertial tendencies to increase risk seeking in the gain domain. Furthermore, expected travel time information is demonstrated to be more effective than travel time variability information in enhancing rational behavior when drivers have limited experiences. After drivers gain sufficient knowledge of routes, however, the difference in behavior associated with the two information types becomes insignificant. The results also demonstrate that, when drivers lack experience, the faster less reliable route is more attractive than the slower more reliable route. However, with cumulative experiences, drivers become more willing to take the more reliable route given that they are reluctant to become risk seekers once experience is gained. Furthermore, the effect of information on driver behavior differs significantly by participant and trip, which is, to a large extent, dependent on personal traits and trip characteristics.

99 GENERAL AND MISCELLANEOUS↗

Hybrid magnonics: Physics, circuits, and applications for coherent information processing

Hybrid dynamic systems have recently gained interest with respect to both fundamental physics and device applications, particularly with their potential for coherent information processing. In this work, we will focus on the recent rapid developments of magnon-based hybrid systems, which seek to combine magnonic excitations with diverse excitations for transformative applications in devices, circuits, and information processing. Key to their promising potentials is that magnons are highly tunable excitations and can be easily engineered to couple with various dynamic media and platforms. The capability of reaching strong coupling with many different excitations has positioned magnons well for studying solid-state coherent dynamics and exploiting unique functionality. In addition, with their gigahertz frequency bandwidth and the ease of fabrication and miniaturization, magnonic devices and systems can be conveniently integrated into microwave circuits for mimicking a broad range of device concepts that have been applied in microwave electronics, photonics, and quantum information. We will discuss a few potential directions for advancing magnon hybrid systems, including on-chip geometry, novel coherent magnonic functionality, and coherent transduction between different platforms. As a future outlook, we will discuss the opportunities and challenges of magnonic hybrid systems for their applications in quantum information and magnonic logic.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Considerations for using Privacy Preserving Machine Learning Techniques for Safeguards

In international nuclear safeguards, the International Atomic Energy Agency (IAEA) is tasked with inspecting and verifying nuclear facilities and their activities. Data analytics and machine learning to support inspections require large amounts of data that nuclear facility operators may consider proprietary or sensitive, so the IAEA may not have full access. Allowing computation over private data without compromising its security therefore has value for safeguards inspections and analysis. Privacy-preserving machine learning (PPML) consists of security-focused techniques that allow data analytics and machine learning algorithms to run on sensitive data without revealing it. This includes ideas like homomorphic encryption (HE), secure multiparty computation (SMPC), and secure enclaves. HE allows algorithms and mathematical operations to be conducted directly on the encrypted data instead of first decrypting it. With SMPC, multiple entities collaboratively compute over distributed data such that no party is able to directly view any others’ original data. Secure enclaves allow computation to take place in a separate and heavily blocked-off section of a CPU. Techniques like these allow for several potential use cases in which the security of data is essential. With SMPC, machine learning models can be trained over the input data from multiple entities, resulting in a model that all users can benefit from without leaking the input data from any particular entity. With SMPC or a zero-knowledge proof (ZKP), an algorithm returning some single answer or truth value can be run on someone else’s data without ever needing to see that data, potentially allowing for verification or proof of some underlying question. HE can allow for outsourcing computation on data to a hostile or untrusted environment. Although most of the research in this field resides within the health and financial domains, tools from PPML may have similar applications in nuclear safeguards. Allowing the IAEA to compute over proprietary information, such as process models and raw sensor data using PPML techniques, provides the baseline for running complex analytics without needing direct unencrypted access to the underlying data, maintaining its privacy. Important limitations to consider for these techniques include the efficiency and level of security required. The security of HE and SMPC come at the cost of speed—the significant amount of overhead means that algorithms implemented in these protocols and encryption schemes are slower than when run on plaintext. Additionally, several important parameters determine what techniques or protocols are used based on the security requirements. SMPC protocols may need to be selected for resistance against a party that attempts to deviate from the protocol to distort the result or gain access to additional information, and a protocol secure against these attacks may further increase the overhead of the algorithm.

97 MATHEMATICS AND COMPUTING↗