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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 325 records · Page 18

Effects of Dead‐End Fractures on Non‐Fickian Transport in Three‐Dimensional Discrete Fracture Networks

Abstract Understanding mechanistic causes of non‐Fickian transport in fractured media is important for many hydrogeologic processes and subsurface applications. This study elucidates the effects of dead‐end fractures on non‐Fickian transport in three‐dimensional (3D) fracture networks. Although dead‐end fractures have been identified as low‐velocity regions that could delay solute transport, the direct relation between dead‐end fractures and non‐Fickian transport has been elusive. We systematically generate a large number of 3D discrete fracture networks with different fracture length distributions and fracture densities. We then identify dead‐end fractures using a novel graph‐based method. The effect of dead‐end fractures on solute residence time maximizes at the critical fracture density of the percolation threshold, leading to strong late‐time tailing. As fracture density increases beyond the percolation threshold, the network connectivity increases, and dead‐end fractures diminish. Consequently, the increase in network connectivity leads to a reduction in the degree of late‐time tailing. We also show that dead‐end fractures can inform about main transport paths, such as the mean tortuosity of particle trajectories. This study advances our mechanistic understanding of solute transport in 3D fracture networks.

58 GEOSCIENCES↗

First Measurement of Inclusive Muon Neutrino Charged Current Triple Differential Cross Section on Argon

The field of accelerator neutrino experiments is entering an era of precision oscillation measurements where the remaining unknown neutrino measurements will be determined. The upcoming DUNE and Hyper-K experiments aim to determine the neutrino mass hierarchy and degree of Charge-Parity (CP) violation in the neutrino sector, providing potential insight on the matter-antimatter imbalance observed in the universe. However, these experiments require highly accurate measurements, and neutrino cross section modeling uncertainties may limit their capabilities. Cross section measurements at current- generation experiments can aid the development of neutrino interaction models to reduce these uncertainties. This is especially true for measurements of neutrino energy, as it drives neutrino oscillations and is of key importance to oscillation experiments. The MicroBooNE experiment uses a Liquid Argon Time Projection Chamber (LArTPC) to produce neutrino-argon cross sections as one of its physics goals. The MicroBooNE detector’s fully active volume, precision reconstruction, and calorimetry information are leveraged in the Wire-Cell analysis to produce a muon neutrino selection that is 92% pure while maintaining 68% efficiency. A reconstruction chain featuring a fully 3D charge reconstruction and a graph-based particle trajectory fit are used to produce accurate measurements of lepton kinematics as well as visible hadronic energy produced in a neutrino interaction. This thesis presents the first neutrino-argon triple-differential cross section measurement, targeting inclusive charged-current final states. Wiener SVD unfolding is used to produce a measurement over neutrino energy, muon momentum, and muon scattering angle. A series of constrained goodness of fit tests are used to demonstrate the validity of MicroBooNE’s model in describing the distribution of reconstructed kinematics seen in data to ensure the accuracy of unfolding. The validated unfolding to neutrino energy represents a step forward in the field of neutrino cross sections, and demonstrates the capabilities of the LArTPC detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Implosion dynamics of triple-nozzle gas-puff z pinches on COBRA

Experiments on the 1-MA, 220-ns COBRA generator at Cornell University were conducted to provide detailed measurements of structured cylindrical gas-puff z pinches. In the experiments, a 7 cm diameter triple-nozzle gas valve assembly with concentric outer and inner annular nozzles and a central gas jet initialize the z-pinch load with various working gases, radial density profiles, and externally applied axial magnetic fields. Planar laser-induced fluorescence provides a measure of the initial neutral gas density of the load, while three-frame laser shearing interferometry and multi-frame extreme ultraviolet (XUV) cameras reveal the formation and propagation of a magneto-Rayleigh–Taylor (MRT) unstable shock layer. Implosion trajectories are compared to simple, experimentally informed models and found to be in good agreement. Differences in the structure of the accelerating plasma sheath and evolution of the MRT instability are observed for different gas species and axial magnetic field strengths, correlating with differences in pinch uniformity and x-ray emission. Here, the average instability growth is compared to linear MRT theory predictions using the instantaneous acceleration of the best-fit implosion models and characteristic instability wavelength, with the effective Atwood number and seed perturbation size as fit parameters. For high density argon center jets, ionization prior to the arrival of the imploding plasma sheath suggests a heating mechanism consistent with photoionization by XUV self-emission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Suppressing the enhancement of stimulated Raman scattering in inhomogeneous plasmas by tuning the modulation frequency of a broadband laser

The stimulated Raman scattering (SRS) instability can inhibit the performance of laser driven inertial confinement fusion (ICF) implosions by scattering light into unwanted directions or by generating hot electrons that preheat the target fuel. In principle, ICF target designs can avoid parameter regimes conducive to large, linear SRS gains. In practice, kinetic inflation—the nonlinear enhancement of SRS due to electron trapping in the excited plasma wave—makes this difficult. Here we show that laser bandwidth in the form of frequency modulation can either decrease or increase the inflationary SRS (iSRS) threshold in inhomogeneous plasmas depending on the maximum chirp of the laser pulse. The threshold, mapped out by a series of particle-in-cell simulations, exhibits a minimum when the frequency change within the pulse cancels the spatial detuning due to density inhomogeneities along the trajectory of the scattered light. In conclusion, by tuning the pump laser parameters away from this minimum, the iSRS threshold can be larger than at zero bandwidth, providing a path to mitigating kinetic inflation in ignition relevant plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Cellulose synthase-like D movement in the plasma membrane requires enzymatic activity

Cellulose Synthase-Like D (CSLD) proteins, important for tip growth and cell division, are known to generate β-1,4-glucan. However, whether they are propelled in the membrane as the glucan chains they produce assemble into microfibrils is unknown. To address this, we endogenously tagged all eight CSLDs in Physcomitrium patens and discovered that they all localize to the apex of tip-growing cells and to the cell plate during cytokinesis. Actin is required to target CSLD to cell tips concomitant with cell expansion, but not to cell plates, which depend on actin and CSLD for structural support. Like Cellulose Synthase (CESA), CSLD requires catalytic activity to move in the plasma membrane. We discovered that CSLD moves significantly faster, with shorter duration and less linear trajectories than CESA. In contrast to CESA, CSLD movement was insensitive to the cellulose synthesis inhibitor isoxaben, suggesting that CSLD and CESA function within different complexes possibly producing structurally distinct cellulose microfibrils.

59 BASIC BIOLOGICAL SCIENCES↗

Divergent Evolution of Early Terrestrial Fungi Reveals the Evolution of Mucormycosis Pathogenicity Factors

Abstract Fungi have evolved over millions of years and their species diversity is predicted to be the second largest on the earth. Fungi have cross-kingdom interactions with many organisms that have mutually shaped their evolutionary trajectories. Zygomycete fungi hold a pivotal position in the fungal tree of life and provide important perspectives on the early evolution of fungi from aquatic to terrestrial environments. Phylogenomic analyses have found that zygomycete fungi diversified into two separate clades, the Mucoromycota which are frequently associated with plants and Zoopagomycota that are commonly animal-associated fungi. Genetic elements that contributed to the fitness and divergence of these lineages may have been shaped by the varied interactions these fungi have had with plants, animals, bacteria, and other microbes. To investigate this, we performed comparative genomic analyses of the two clades of zygomycetes in the context of Kingdom Fungi, benefiting from our generation of a new collection of zygomycete genomes, including nine produced for this study. We identified lineage-specific genomic content that may contribute to the disparate biology observed in these zygomycetes. Our findings include the discovery of undescribed diversity in CotH, a Mucormycosis pathogenicity factor, which was found in a broad set of zygomycetes. Reconciliation analysis identified multiple duplication events and an expansion of CotH copies throughout the Mucoromycotina, Mortierellomycotina, Neocallimastigomycota, and Basidiobolus lineages. A kingdom-level phylogenomic analysis also identified new evolutionary relationships within the subphyla of Mucoromycota and Zoopagomycota, including supporting the sister-clade relationship between Glomeromycotina and Mortierellomycotina and the placement of Basidiobolus as sister to other Zoopagomycota lineages.

59 BASIC BIOLOGICAL SCIENCES↗

Hydrogen and Electric Charging Infrastructure for Heavy-Duty Trucks: A Nationally Scalable Megaregion Assessment

Decarbonizing regional and long-haul freight is challenging due to the limitations of battery-electric commercial vehicles and infrastructure constraints. Hydrogen fuel cell medium- and heavy-duty vehicles (MHDVs) offer a viable alternative, aligning with the decarbonization goals of the Department of Energy and commercial entities. Historically, alternative fuels like compressed natural gas and liquefied propane gas have faced slow adoption due to barriers like infrastructure availability. To avoid similar issues, effective planning and deploying zero-emission hydrogen fueling infrastructure is crucial. This research develops deployment plans for affordable, accessible, and sustainable hydrogen refueling stations, supporting stakeholders in the decarbonized commercial vehicle freight system. It aims to benefit underserved and rural energy-stressed communities by improving air quality, reducing noise pollution, and enhancing energy resiliency. This research also provides a blueprint for replacing diesel in over-the-road Class 8 freight truck applications with hydrogen fueling solutions. The study focuses on the Texas Triangle Megaregion (I-45, I-35, and I-10), the I-10 corridor between San Antonio, TX, and Los Angeles, CA, and the I-5/CA-99 corridors between Los Angeles, CA, and San Francisco, CA. This area represents a significant portion of U.S. heavy-duty freight movement, carrying ~8.5% of the national freight volume. Using the OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport) modeling framework, the study conducts an advanced assessment of commercial vehicles, road and freight networks, and energy systems. The framework integrates data on freight mobility, traffic, weather, and energy pathways to deliver a region-specific, optimized vehicles powertrain architectures, infrastructure deployment solutions, operational logistics, and energy pathways. By considering all vehicle origin-destination pairs utilizing these corridors and all feasible fueling station location options, the framework's genetic algorithm identifies the minimum number and optimal locations of hydrogen refueling stations, ensuring no vehicle is stranded. It also determines fuel schedules and quantities at each station. A roadmap for station deployment based on multiple adoption trajectories ensures a strategic rollout of hydrogen refueling infrastructure.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗

Computation and consequences of high order amplitude- and parameter-dependent tune shifts in storage rings for high precision measurements

Nonlinear effects of the various electric field and magnetic field components of storage rings to confine the particles and bend their trajectory can cause substantial amplitude-dependent tune shifts within the beam. Furthermore, tune shifts are often sensitive to variations of system parameters, e.g. total particle momentum offsets $δp$. Such amplitude- and parameter-dependent tune shifts influence the dynamics and stability of a beam in particle storage rings. Thus, it is critical for high precision measurements to analyze and understand these influences. On this basis, we present in this paper normal form methods for the calculation of high order amplitude and system parameter dependencies of the horizontal and vertical tunes in storage rings using the differential algebra (DA) framework within COSY INFINITY. A storage ring is simulated using COSY INFINITY to generate a DA Poincaré return map describing the transverse phase space behavior after each revolution in the storage ring. The map is expanded around the parameter-dependent closed orbit of the system before transforming the resulting map into normal form coordinates to extract the high order tune dependencies on the phase space amplitude and variation in the system parameters. As a specific example, a storage ring similar to the Storage Ring of the Muon g-2 Experiment at Fermilab (E989) is investigated.

43 PARTICLE ACCELERATORS↗

Permutationally Invariant Polynomial Expansions with Unrestricted Complexity

A general strategy is presented for constructing and validating permutationally invariant polynomial (PIP) expansions for chemical systems of any stoichiometry. Demonstrations are made for three categories of gas-phase dynamics and kinetics: collisional energy-transfer trajectories for predicting pressure-dependent kinetics, three-body collisions for describing transient van der Waals adducts relevant to atmospheric chemistry, and nonthermal reactivity via quasiclassical trajectories. In total, 30 systems are considered with up to 15 atoms and 39 degrees of freedom. Permutational invariance is enforced in PIP expansions with as many as 13 million terms and 13 permutationally distinct atom types by taking advantage of petascale computational resources. The quality of the PIP expansions is demonstrated through the systematic convergence of in-sample and out-of-sample errors with respect to both the number of training data and the order of the expansion, and these errors are shown to predict errors in the dynamics for both reactive and nonreactive applications. Here, the parallelized code distributed as part of this work enables the automation of PIP generation for complex systems with multiple channels and flexible user-defined symmetry constraints and for automatically removing unphysical unconnected terms from the basis set expansions, all of which are required for simulating complex reactive systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interference Provides Clarity: Direct Observation of 2D Materials at Fluid–Fluid Interfaces

Monolayer particles of two-dimensional (2D) materials represent a scientifically and technologically interesting class of anisotropic particles with colloidal-scale lateral sizes but sub-nanometer thicknesses. This atomic-scale thickness leads to interesting phenomena that can be exploited in next-generation thin-film technologies, and fluid-fluid interfaces provide a potentially scalable platform to confine, assemble, and deposit functional thin films of 2D materials. However, directly observing how these materials interact and assemble into a given film morphology is experimentally challenging because of their sub-nanometer thicknesses. Here, we demonstrate the ability to directly observe graphene, molybdenum disulfide (MoS2), and hexagonal boron nitride (h-BN) particles at fluid-fluid interfaces using interference reflection microscopy (IRM). Monolayer MoS2 and graphene particles demonstrated >10% optical contrast at an air-water interface, which allowed us to quantitatively analyze in situ images of self-assembled MoS2 particles and to map trajectories of interacting graphene particles. Additionally, the Brownian motion of a graphene particle was tracked and analyzed in the context of passive microrheology theory for 2D particle probes. Our results demonstrate how IRM can be used to obtain quantitative spatiotemporal information regarding the self-assembly and dynamics of 2D materials at fluid-fluid interfaces. It will have a significant impact on our ability to investigate systems of atomically thin particles at fluid-fluid interfaces, an area that has fundamental scientific importance and materials science applications but has suffered from a lack of direct, in situ observation techniques.

2D material↗

Atmospheric pion, kaon, and muon fluxes for sub-orbital experiments

Cosmic rays interacting with the Earth's atmosphere generate extensive air showers, which produce Cherenkov, fluorescence and radio emissions. These emissions are key signatures for detection by ground-based, sub-orbital, and satellite-based telescopes aiming to study high energy cosmic ray and neutrino events. However, detectors operating at ground and balloon altitudes are also exposed to a background of atmospheric charged particles, primarily pions, kaons, and muons, that can mimic or obscure the signals from astrophysical sources. In this work, we use coupled cascade equations to calculate the atmospheric pion, kaon and muon fluxes reaching detectors at various altitudes. Our analysis focuses on energies above 10 GeV, where the influence of the Earth's magnetic field on particle trajectories is minimal. We provide angular and energy-resolved flux estimates and discuss their relevance as background for extensive air shower detection. Furthermore, our results are potentially relevant for interpreting data from current and future balloon-borne experiments such as EUSO-SPB2 and for refining trigger and veto strategies in Cherenkov and fluorescence telescopes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

FY23 Year End Report of Delivery Environments Predictive Capabilities Use in Analysis of SRP Programs

As was established in a previous milestone report for FY20, W-13 continues to be tasked with analyses that require knowledge of in-flight environments and require an in-house capability to generate such environments. To this end, FY21 work included obtaining and benchmarking the use of such tools for an in-house capability. With these tools available for analysis tasks, ongoing work has been to continue the development of analysis capabilities and understanding while specifically using the tools for Responsive Development Experiment (ReDX) flights in the Stockpile Responsiveness Program (SRP). In FY23, design and analysis of ReDX flight 3A continued while targeting an FY24 launch date. This report shows that a variety of vehicle characterization and flight analysis tools were used in W-13, under the Delivery Environments Program. This work was performed in order to aid in vehicle design by predicting flight stability, trajectory, and induced environments while adapting to a series of changing internal payload configurations that resulted in significant changes to mass properties and associated flight stability.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Analytical model for the motion and interaction of two-dimensional active nematic defects

Here, we develop an approximate, analytical model for the velocity of defects in active nematics by combining recent results for the velocity of topological defects in nematic liquid crystals with the flow field generated from individual defects in active nematics. Importantly, our model takes into account the long-range interactions between defects that result from the flows they produce as well as the orientational coupling between defects inherent in nematics. Our work complements previous studies of active nematic defect motion by introducing a linear approximation that allows us to treat defect interactions as two-body interactions and incorporates the hydrodynamic screening length as a tuning parameter. We show that the model can analytically predict bound states between two +1/2 winding number defects, effective attraction between two –1/2 defects, and the scaling of a critical unbinding length between ±1/2 defects with activity. The model also gives predictions for the trajectories of defects, such as the scattering of +1/2 defects by –1/2 defects at a critical impact parameter that depends on activity. In the presence of circular confinement, the model predicts a braiding motion for three +1/2 defects that was recently seen in experiments, as well as stable and ergodic trajectories for four or more defects.

36 MATERIALS SCIENCE↗

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We suggest a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118-and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118- and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

alternating direction method of multipliers↗

Reconstructing magnetic deflections from sets of proton images using differential evolution

Proton imaging is a powerful technique for imaging electromagnetic fields within an experimental volume, in which spatial variations in proton fluence are a result of deflections to proton trajectories due to interaction with the fields. When deflections are large, proton trajectories can overlap, and this nonlinearity creates regions of greatly increased proton fluence on the image, known as caustics. The formation of caustics has been a persistent barrier to reconstructing the underlying fields from proton images. We have developed a new method for reconstructing the path-integrated magnetic fields, which begins to address the problem posed by caustics. Our method uses multiple proton images of the same object, each image at a different energy, to fill in the information gaps and provide some uniqueness when reconstructing caustic features. We use a differential evolution algorithm to iteratively estimate the underlying deflection function, which accurately reproduces the observed proton fluence at multiple proton energies simultaneously. We test this reconstruction method using synthetic proton images generated for three different, cylindrically symmetric field geometries at various field amplitudes and levels of proton statistics and present reconstruction results from a set of experimental images. Here, the method we propose requires no assumption of deflection linearity and can reliably solve for fields underlying linear, nonlinear, and caustic proton image features for the selected geometries and is shown to be fairly robust to noise in the input proton intensity.

47 OTHER INSTRUMENTATION↗

Acoustic Rocket Signatures Collected by Smartphones

Rockets generate complex acoustic signatures that can be detected over a thousand kilometers from their source. While many far-field acoustic rocket signatures have been collected and released to the public, very few signatures collected at distances less than 100 km are available. This work presents a curated and annotated dataset of acoustic signatures of 243 rocket launches collected by a network of smartphones stationed at distances between 10 and 70 km from the launch sites, resulting in 1089 individual recordings. Due to the frequency dependence of atmospheric attenuation and the relatively short propagation distances, higher-frequency features not preserved in most publicly available data are observed. The signals are time-aligned to allow for different segments of the signal (ignition, launch, trajectory, chronology) to be more easily examined and compared. Initial analysis of the features of these rocket launch stages is performed, observed features are compared to those found in the existing literature, and comparisons between signals from launches of different rocket types are made. The dataset is annotated and made available to the public to aid future analysis of the characteristics and source mechanisms of rocket acoustics as well as applications such as rocket detection and classification models.

33 ADVANCED PROPULSION SYSTEMS↗

EUV debris mitigation using magnetic nulls

Next generation EUV sources for photolithography use light produced by laser-produced plasmas (LPP) from ablated tin droplets. A major challenge for extending the lifetime of these devices is mitigating damage caused by deposition of tin debris on the sensitive collection mirror. Especially difficult to stop are high energy (up to 10 keV) highly charged tin ions created in the plasma. Existing solutions include the use of stopping gas, electric fields, and magnetic fields. One common configuration consists of a magnetic field perpendicular to the EUV emission direction, but such a system can result in ion populations that are trapped rather than removed. Here we investigate a previously unconsidered mitigation geometry consisting of a magnetic null by performing full-orbit integration of the ion trajectories in an EUV system with realistic dimensions and optimize the coil locations for the null configuration. The magnetic null prevents a fraction of ions from hitting the mirror comparable to that of the perpendicular field, but does not trap any ions due to the chaotic nature of ion trajectories that pass close to the null. This technology can potentially improve LPP-based EUV photolithography system efficiency and lifetime and may allow for a different, more efficient formulation of buffer gas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗