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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

Quantifying Spatial Drought Propagation Potential in North America Using Complex Network Theory

Droughts have a dominant three-dimensional (3-D) spatiotemporal structure typically spanning hundreds of kilometers and often lasting for months to years. Here, we introduced a novel framework to explore the 3-D structure of the evolution of droughts based on network theory concepts. The proposed framework is applied to identify critical source regions responsible for large-scale drought onsets during 1901–2014 for the North American continent using the Standardized Precipitation Evaporation Index (SPEI). We built a spatial network connecting the drought onset timings for the North American continent. Using a spatially weighted network partitioning algorithm, the whole continent is then classified into regional spatial drought networks (RSN), where droughts are more likely to propagate within these regional systems. Finally, a customized network metric was applied to identify locations (source regions) where the drought onsets further propagate to other areas within the regional spatial network. Our results indicated that the West coast, Texas coastal region, and Southeastern Arkansas as major source regions through which atmospheric drought propagates to Western, South Central, and Eastern North America. The formation of drought source regions are due to presence of high pressure ridges and anomalous wind patterns. Furthermore, our results indicate that the drought propagation from these source regions may be due to inadequate moisture transport. The proposed framework can help to develop an early warning detection system for droughts and other spatially extensive extreme events such as heatwaves and floods.

Goutam Konapala↗

Evolving the NASA Near Earth Network for the Next Generation of Human Space Flight

The purpose of this paper is to present the planned development and evolution of the NASA Near Earth Network (NEN) launch communications services in support of the next generation of human space flight programs. Following the final space shuttle mission in 2011, the two NEN launch communications stations were decommissioned. Today, NASA is developing the next generation of human space flight systems focused on exploration missions beyond low-earth orbit, and supporting the emerging market for commercial crew and cargo human space flight services. The NEN is leading a major initiative to develop a modern high data rate launch communications ground architecture with support from the Kennedy Space Center Ground Systems Development and Operations Program and in partnership with the U.S. Air Force (USAF) Eastern Range. This initiative, the NEN Launch Communications Stations (LCS) development project, successfully completed its System Requirements Review in November 2013. This paper provides an overview of the LCS project and a summary of its progress. The LCS ground architecture, concept of operations, and driving requirements to support the new heavy-lift Space Launch System and Orion Multi-Purpose Crew Vehicle for Exploration Mission-1 are presented. Finally, potential future extensions to the ground architecture beyond EM-1 are discussed.

Launch Communications↗

Lie–Poisson Neural Networks (LPNets): Data-based computing of Hamiltonian systems with symmetries

An accurate data-based prediction of the long-term evolution of Hamiltonian systems requires a network that preserves the appropriate structure under each time step. Every Hamiltonian system contains two essential ingredients: the Poisson bracket and the Hamiltonian. Hamiltonian systems with symmetries, whose paradigm examples are the Lie–Poisson systems, have been shown to describe a broad category of physical phenomena, from satellite motion to underwater vehicles, fluids, geophysical applications, complex fluids, and plasma physics. The Poisson bracket in these systems comes from the symmetries, while the Hamiltonian comes from the underlying physics. We view the symmetry of the system as primary, hence the Lie–Poisson bracket is known exactly, whereas the Hamiltonian is regarded as coming from physics and is considered not known, or known approximately. Using this approach, we develop a network based on transformations that exactly preserve the Poisson bracket and the special functions of the Lie–Poisson systems (Casimirs) to machine precision. We present two flavors of such systems: one, where the parameters of transformations are computed from data using a dense neural network (LPNets), and another, where the composition of transformations is used as building blocks (G-LPNets). We also show how to adapt these methods to a larger class of Poisson brackets. We apply the resulting methods to several examples, such as rigid body (satellite) motion, underwater vehicles, a particle in a magnetic field, and others. The methods developed in this paper are important for the construction of accurate data-based methods for simulating the long-term dynamics of physical systems.

Data-based modeling↗

Controlled gate networks: theory and application to eigenvalue estimation

We introduce a new scheme for quantum circuit design called controlled gate networks. Rather than trying to reduce the complexity of individual unitary operations, the new strategy is to toggle between all of the unitary operations needed with the fewest number of gates. We present the general theory of controlled gate networks and show that, under quite general conditions, it can significantly reduce the number of two-qubit gates needed to produce linear combinations of unitary operators. The first example we consider is a variational subspace calculation for a two-qubit system. The second example is estimating the eigenvalues of a two-qubit Hamiltonian via the rodeo algorithm (Choi et al. in Phys Rev Lett 127(4):040505, 2021. https://doi.org/10.1103/PhysRevLett.127.040505) using operators that we call controlled reversal gates. We use the Quantinuum H1-2 and IBM Perth devices to realize the quantum circuits. The third example is the application of controlled gate networks to the controlled time evolution of a free nucleon on a three-dimensional lattice. For all of the examples, we show very substantial reductions in the number of two-qubit gates required. Our work demonstrates that controlled gate networks are a useful tool for reducing gate complexity in quantum algorithms for quantum many-body problems such as those relevant to nuclear physics.

Bee-Lindgren, Max [Georgia Institute of Technology↗

The road to the Deep Space Network

The history and current status of the NASA Deep Space Network, a system of 13 antennas of various designs and sizes located around the world to stay in continuous contact with spacecraft out to the edge of the solar system, are reviewed. A major step in the evolution of the Deep Space Network is considered to be the installation of 210-ft-diameter antennas to support sophisticated spacecraft sending data at higher rate back to earth at Goldstone in 1966 and at Tidbinbilla and Robledo de Chevala in 1973. New 340-meter multifrequency beam-waveguide antenna, in which weather sensitive microwave components were to be put in an equipment room, was installed for research and development at Goldstone in 1990.

Waff, Craig B.↗

Deeply conserved synteny and the evolution of metazoan chromosomes

Animal genomes show networks of deeply conserved gene linkages whose phylogenetic scope and chromosomal context remain unclear. Here, we report chromosome-scale conservation of synteny among bilaterians, cnidarians, and sponges and use comparative analysis to reconstruct ancestral chromosomes across major animal groups. Comparisons among diverse metazoans reveal the processes of chromosome evolution that produced contemporary karyotypes from their Precambrian progenitors. On the basis of these findings, we introduce a simple algebraic representation of chromosomal change and use it to establish a unified systematic framework for metazoan chromosome evolution. We find that fusion-with-mixing, a previously unappreciated mode of chromosome change, has played a central role. We find that relicts of several metazoan chromosomal units are preserved in unicellular eukaryotes. These conserved pre-metazoan linkages include the chromosomal unit that encodes the most diverse set of metazoan homeobox genes, suggesting a candidate genomic context for the early diversification of this key gene family.

59 BASIC BIOLOGICAL SCIENCES↗

Using Direct Numerical Simulation of Pore-Level Events to Improve Pore-Network Models for Prediction of Residual Trapping of CO2

Direct numerical simulation and pore-network modeling are common approaches to study the physics of two-phase flow through natural rocks. For assessment of the long-term performance of geological sequestration of CO 2 , it is important to model the full drainage-imbibition cycle to provide an accurate estimate of the trapped CO 2 . While direct numerical simulation using pore geometry from micro-CT rock images accurately models two-phase flow physics, it is computationally prohibitive for large rock volumes. On the other hand, pore-network modeling on networks extracted from micro-CT rock images is computationally efficient but utilizes simplified physics in idealized geometric pore elements. This study uses the lattice-Boltzmann method for direct numerical simulation of CO 2 -brine flow in idealized pore elements to develop a new set of pore-level flow models for the pore-body filling and snap-off events in pore-network modeling of imbibition. Lattice-Boltzmann simulations are conducted on typical idealized pore-network configurations, and the interface evolution and local capillary pressure are evaluated to develop modified equations of local threshold capillary pressure of pore elements as a function of shape factor and other geometrical parameters. The modified equations are then incorporated into a quasi-static pore-network flow solver. The modified model is applied on extracted pore-network of sandstone samples, and saturation of residual trapped CO 2 is computed for a drainage-imbibition cycle. The modified model yields different statistics of pore-level events compared with the original model; in particular, the occurrence of snap-off in pore-throats is reduced resulting in a more frontal displacement pattern along the main injection direction. Compared to the original model, the modified model is in closer agreement with the residual trapped CO 2 obtained from core flow experiments and direct numerical simulation.

Kohanpur, Amir H.↗

Networks of electrochemical oxidation of common lithium-ion Battery solvents revealed by NMR spectroscopy

Raising the upper cutoff voltage of lithium-ion batteries (LIBs) to increase energy density often exceeds the electrolyte’s anodic stability limit, accelerating degradation and creating a major durability tradeoff. Designing electrolytes that can sustain long-term high-voltage cycling requires a clearer understanding of the fundamental mechanisms occurring when commercial carbonate solvents oxidize. Here, to this end, simplified single-salt, single-solvent formulations of LiClO 4 and LiPF 6 in dimethyl carbonate (DMC), ethylene carbonate (EC), or ethyl methyl carbonate (EMC) were anodically electrolyzed on inert electrodes and monitored for extended periods of time using 1 H, 13 C, 19 F, and 35 Cl nuclear magnetic resonance (NMR) spectroscopy. The controlled environment of the experiments, coupled to the unique sensitivity of NMR, unveiled novel metastable intermediates and the formation of branching networks of products with temporal evolution. Oxidation of the pristine solvent primarily proceeds through a radical pathway that also produces highly reactive protons but faces competition from a second pathway involving a radical carbocation intermediate. In all cases, the intermediates follow a variety of downstream pathways that can intersect with each other. The concomitant network of reactions represents a significant increase in complexity compared to common descriptions in the literature, yet, critically, it helps explain the wide range of products typically identified in electrolyte oxidation in complete cells. The results highlight the need for refocusing fundamental research on anodic stability to analysis of the hierarchy of reaction networks to better inform efforts to mitigate the detrimental effects on battery performance, including prevention and harvesting of proton and radical products.

Electrolytes↗

Predicting material microstructure evolution via data-driven machine learning

The recent rapid rise in data-driven practices in the materials science domain has led to the development of efficient, generalizable, and accurate approaches for several applications, including: material property prediction, mining (micro)structure- property and (micro)structure-processing relationships, and characterization of material microstructures. Central to the materials science domain is linking microstructure to properties and performance, and critical to building such linkages is understanding how microstructures evolve as a function of environmental exposure or processing conditions (e.g., time, temperature, applied stress or strain, irradiation). This preview article summarizes recent work on the development of recurrent neural networks for predicting spatio-temporal microstructure evolution detailed by Yang et al in their manuscript entitled 'Self-supervised Learning and Prediction of Microstructure Evolution with Recurrent Neural Networks'.

machine learning (ML), materials characterization↗

Space Communications and Navigation (SCaN) Integrated Network Architecture Definition Document (ADD): Executive Summary - Volume 1

The SCaN Program has defined an integrated network architecture that fully meets the Administrator s mandate to the Program, and will result in a NASA infrastructure capable of providing the needed and enabling communications services to future space missions. The integrated network architecture will increase SCaN operational efficiency and interoperability through standardization, commonality and technology infusion. It will enable NASA missions requiring advanced communication and tracking capabilities such as: a. Optical communication b. Antenna arraying c. Lunar and Mars Relays d. Integrated network management (service management and network control) and integrated service execution e. Enhanced tracking for navigation f. Space internetworking with DTN and IP g. End-to-end security h. Enhanced security services Moreover, the SCaN Program has created an Integrated Network Roadmap that depicts an orchestrated and coherent evolution path toward the target architecture, encompassing all aspects that concern network assets (i.e., operations and maintenance, sustaining engineering, upgrade efforts, and major development). This roadmap identifies major NASA ADPs, and shows dependencies and drivers among the various planned undertakings and timelines. The roadmap is scalable to accommodate timely adjustments in response to Agency needs, goals, objectives and funding. Future challenges to implementing this architecture include balancing user mission needs, technology development, and the availability of funding within NASA s priorities. Strategies for addressing these challenges are to: define a flexible architecture, update the architecture periodically, use ADPs to evaluate options and determine when to make decisions, and to engage the stakeholders in these evaluations. In addition, the SCaN Program will evaluate and respond to mission need dates for technical and operational capabilities to be provided by the SCaN integrated network. In that regard, the architecture defined in this ADD is scalable to accommodate programmatic and technical changes.

Younes, Badri A.↗

User Role Identification in Software Vulnerability Discussions over Social Networks

Understanding and early awareness of software vulnerabilities is vital for preventing and mitigating potential impacts from cybersecurity events. One step toward early characterization of software vulnerabilities may involve analyzing discussion and spread of information in online social networks. Prior work has used information from such discussions over multiple online forums to develop dynamic networks among users followed by analysis of structure, spread, and information evolution. In this work, we advance the state-of-the-art by focusing on data-driven learning of types, roles, and transition of roles exhibited by users over time. In social networks, users take on particular roles based on their actions and structure of the network. Identifying “meaningful” roles can help separate potential users of interest from the larger community, and identify patterns in a network. We will identify and compare roles found in online forums (e.g., Twitter) using techniques such as feature-based Non-negative Matrix Factorization coupled with topological and influence-based measures of centrality. Since users’ activities change over time, we also analyze role evolution in dynamic networks.

Jones, Rebecca D.↗

Emulation and Adversarial Analysis of EV Charging Networks

In the effort of decarbonization and evolution of the modern electrical grid, electric vehicles (EVs) play a key part to transform the grid. However, due to the rapid adoption of EVs and the demand of the charging infrastructure required to power said EVs, risk of a cyber-attack may impose serious consequences. There is a need to analyze and protect the charging ecosystem infrastructure from cyber threats before it reaches wide-scale deployment. In an effort to secure vehicle to grid (V2G) communications, standardization is necessary for continued reliable system operation. The protocol ISO 15118 outlines controls and practices that should be implemented for secure vehicle to grid (V2G) communications. The standard is gaining momentum for American markets as the demand for EV infrastructure grows. The adoption of ISO 15118 in American markets poses several challenges: the deployment of a public key infrastructure (PKI) as outlined within the standard, interoperability of charging different EVs with chargers from different manufactures using the PKI, and scaling the ecosystem to meet the demand while managing risks. This project was created to understand potential cyber and scaling challenges of PKI for EV infrastructure through utilizing a series of emulated components mapping to what exists in the EV ecosystem today, and the components of the PKI that are under development. The key nodes within the emulation that are under development are: electric vehicle (EV), electric vehicle supply equipment (EVSE), charge network operator (CNO), certificate authority (CA), and online certificate status protocol (OCSP) that must all interact using secure and trusted communications. With these emulated components and utilizing orchestration methods to rapidly deploy and scale the components, the ability to analyze risks of the ecosystem and address gaps before the PKI ecosystem is fully deployed to production should yield a more robust and mature production charging infrastructure. Our approach will use a modular architecture of virtual machines within an orchestration platform and will target scales of 100s, 1000s, and 10,000s of entities interacting. The core research questions trying to be answered with this scope of work are: what are the impacts of a rogue CA, what are the risks of certificate revocation list (CRL) management, what is the value of OCSP stapling, what components are vulnerable to DOS attacks, and what test effective payloads may impact the components.

charging ecosystem↗

Introduction to special section: early Mars

Ongoing studies of the evolution of the Martian cratered highlands, the nature of the planet's early climate, and the recent announcement of possible evidence of ancient life in the ALH 84001 meteorite have reinvigorated interest in the conditions that prevailed on Mars during its first billion years of geologic history. To address this interest and assess our current understanding of these issues, the Lunar and Planetary Institute hosted a 4-day Conference on Early Mars in Houston in April of 1997. The papers contained in this special section are a product of that meeting. The purpose of the conference was twofold: (1) to consider how impacts, volcanism, and the presence of abundant water affected the physical and chemical environment that existed on Mars 4 Gyr ago, particularly as it related to the nature of the global climate, the origin of the valley networks, the geologic and mineralogic evolution of the surface, the aqueous geochemistry of groundwater, and the existence of local environments that may have been conducive to the development of indigenous life and the preservation of its signature in the geologic record; and (2) to discuss what observations or experiments might he included in future spacecraft missions to test the ideas and expectations arising from purpose 1. While pertinent issues of early atmospheric and solar evolution were also addressed, the primary discussion at the conference focused on the evidence and constraints provided by the geologic records of Earth, the Moon, and Mars and analysis of the SNC meteorites. The papers contained in this special section span the full range of these topics, including the stability of the early atmosphere to erosion by the solar wind, the geologic environment from which the SNC meteorites originated, geomorphic evidence regarding the nature of the early Martian climate and hydrologic cycle, the potential impact of the past and present environment on the preserved signature of ancient life, and a discussion of the capabilities of a lander-based X ray diffraction and fluorescence instrument to assess the potential for past fossilization from the mineralogy of the current local surface environment. The issues raised at the conference, and by the papers included in this special section, will be the focus of ongoing attention as the intensity and scope of Mars exploration increases over the next decade.

NASA Center ARC↗

The subsurface hydrologic response of Mars to the thermal evolution of its early crust

The Martian valley networks and outflow channels provide persuasive evidence that large bodies of groundwater were present on Mars throughout much of its early geologic history. However, little attention was focused on how these volatile reservoirs may have responded to the thermal evolution of the early Martian crust. In this regard, one process that has likely been of critical importance to the subsurface hydrologic evolution of Mars is thermal vapor diffusion. Various aspects of the thermal vapor diffusion process on Mars are discussed.

Clifford, S. M.↗

Polymorphism and Negative Linear Compressibility in Pyrazine-d4

Pyrazine (1,4-diazine) is a widely used linker in coordination polymers, molecular magnets, and metal–organic frameworks, yet its solid-state polymorphism is controlled by weak C–H···N interactions. Using variable-temperature and high-pressure neutron diffraction, a previously unrecognized low-temperature transition to phase IV is identified, showing that the form stabilized under pressure can also be accessed below ∼90 K at ambient pressure in the perdeuterated compound. The transition from phase III → IV involves a symmetry-breaking lattice distortion driven by the reorganization of C–H···N hydrogen bonds, accompanied by negative linear compressibility, which is primarily accommodated through the reduction in void-space within the structure. Structural analysis reveals that while the overall monoclinic framework of phase IV is preserved under both temperature and pressure routes, the evolution of hydrogen-bonded network is distinct depending on the pathway taken. These results establish pyrazine as a model molecular solid for studying pressure–temperature polymorphism and demonstrate how weak directional interactions can produce anomalous mechanical responses in organic crystals.

Ridley, Christopher J. [Oak Ridge National Laborat↗

Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications

Molecular Dynamics (MD) simulations are used to understand the effects of corrosion on metallic materials in salt brine. Reactive force fields in classical MD enable accurate modeling of bond formation and breakage in the aqueous medium and at the metal-electrolyte interface, while also facilitating dynamic partial charge equilibration. However, MD simulations are computationally intensive and unsuitable for modeling the long time scales characteristic of corrosive phenomena. To address this, we develop reduced-order machine learning models that provide accurate and efficient predictions of charge density in corrosive environments. Specifically, we use Long Short-Term Memory (LSTM) networks to forecast charge density evolution based on atomic environments represented by Smooth Overlap of Atomic Positions (SOAP) descriptors. A physics-informed loss function enforces charge neutrality and electronegativity equivalence. The atomic charges predicted by the deep learning model trained on this work were obtained two orders of magnitude faster than those from molecular dynamics (MD) simulations, with an error of less than 3% compared to the MD-obtained charges, even in extrapolative scenarios, while adhering to physical constraints. This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.

Atomistic models↗

Present and future of $\mathcal{C}$osmo $\mathcal{L}$attice

We discuss the present state and planned updates of Cosmo Lattice, a cutting-edge code for lattice simulations of non-linear dynamics of scalar-gauge field theories in an expanding background. We first review the current capabilities of the code, including the simulation of interacting singlet scalars and of Abelian and non-Abelian scalar-gauge theories. We also comment on new features recently implemented, such as the simulation of gravitational waves from scalar and gauge fields. Secondly, we discuss new extensions of Cosmo Lattice that we plan to release publicly. We comment on new physics modules, which include axion-gauge interactions $\phi F\tilde{F}$, non-minimal gravitational couplings $\phi ^2R$, creation and evolution of cosmic-defect networks, and magnetohydrodynamics. Finally, we also discuss new technical features, including evolvers for non-canonical interactions, arbitrary initial conditions, simulations in 2+1 dimensions, and higher-accuracy spatial derivatives.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗