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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Characterization of Contaminants and Mobility in WMA A-AX Boreholes D0006 and D0008

This study was initiated to determine if subsurface contaminants in the A-AX vadose zone at the Hanford site (boreholes D0006 and D0008) caused corrosion of nearby stainless steel well casings (299-E-24-19, 299-E25-46, and 299-E25-236) and, based on the type and distribution of contaminants, determine if contaminants are from one or more sources including a) the A-104 and/or A-105 tanks, b) the 242A evaporator, and c) the 200-E-286 ditch. A tiered approach was used for characterizing contaminants in vadose zone sediments starting with mobile and total contaminant concentrations (Tier 1), characterizing contaminant speciation (Tier 2), and measuring contaminant leaching (Tier 3). Total and mobile contaminant measurements at seven depths showed elevated sulfate and nitrate in all samples (130 to 280 ft depth), elevated chloride in five depths, and no elevated radionuclides except I-129 in D0006 at 206 to 208 ft depth. If these contaminants were initially acidic, stainless-steel corrosion would occur. However, because sediments likely have a high acid neutralization capacity, an acidic spill would have been neutralized within tens of feet, so casing corrosion would likely occur in shallow sediments. GEL labs data also shows low (but above natural) chromate from shallow to 170 ft depth, then higher chromate to 280 ft, suggesting a surface Cr spill or casing corrosion. GEL labs data also showed evidence of more than one plume, with deep nitrate, sulfate, and chloride migration, but only shallow tritium migration. Tritium should migrate nearly unretarded in the subsurface like nitrate and chloride. Elevated aqueous cations and anions in the D0006 206 to 208' depth pore water (SO 4 2- , NO 3 - , Na + , K + , Ca 2+ , Mg 2+ , Si) could be the result of acid disposal and calcite dissolution at shallow depth, with deeper migration of SO 4 2- , NO 3 - from acids and Ca 2+ and Mg 2+ from calcite. Elevated Si (160 mg/L) indicates dissolution of clays or other silicates, which can also occur in acids. Acid extractable metals did show elevated Cr (but not Fe, Ni, Mo, and Mn) above natural levels, which may indicate stainless-steel well corrosion or transport of metals from a shallow spill. The elevated I-129 in D0006 at 206 to 208' depth was low with 0.34 μg/g in pore water and 1.5 μg/g total extractable I-129 in the sediment, which indicates significant fraction of I-129 was bound in one or more precipitates. Although total I-129 was below detection limits in most extractions due to high molybdate interference, I-127 analysis provided some insight into potential precipitate phases. Total I-127 was mainly extracted by acetate or acetic acid (67%), which may be iodine in calcite. Inorganic carbon measurement identified 1.65% calcite, and total organic carbon (TOC) was below detection limits, so iodine was not associated with organic matter. Nearly all the I-127 was present as iodide. In 1-D leach experiments, I-127 as iodide leached from the sediment within 2 pore volumes. Due to high and dynamic molybdate leaching from the sediment and interference with I-129 analysis, there were few quantifiable I-129 measurements. The calculated molybdate release rates from the sediment suggested Mo was being released from the same precipitate phase, such as molybdate incorporated into calcite. Overall, because there was little radioactive contamination measured in D0006 and D0008 boreholes, potential releases from A-104 and A-105 did not reach this location south of the A tank farm. Elevated cations and anions found in D0006 and D0008 at depth as the result of acidic disposal could cause shallow stainless steel casing corrosion. The nearby 242A evaporator generally contained alkaline waste and tritium, but the nearby 200-E-286 ditch generally contained high Cl - liquid effluent, so these are unlikely to be acidic sources.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2003

The evolution of concepts of vestibular peripheral information processing: toward the dynamic, adaptive, parallel processing macular model

In a letter to Robert Hooke, written on 5 February, 1675, Isaac Newton wrote "If I have seen further than certain other men it is by standing upon the shoulders of giants." In his context, Newton was referring to the work of Galileo and Kepler, who preceded him. However, every field has its own giants, those men and women who went before us and, often with few tools at their disposal, uncovered the facts that enabled later researchers to advance knowledge in a particular area. This review traces the history of the evolution of views from early giants in the field of vestibular research to modern concepts of vestibular organ organization and function. Emphasis will be placed on the mammalian maculae as peripheral processors of linear accelerations acting on the head. This review shows that early, correct findings were sometimes unfortunately disregarded, impeding later investigations into the structure and function of the vestibular organs. The central themes are that the macular organs are highly complex, dynamic, adaptive, distributed parallel processors of information, and that historical references can help us to understand our own place in advancing knowledge about their complicated structure and functions.

Review, Tutorial↗
DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗
DOE OSTI2022

A high-dimensional neural network potential for molecular dynamics simulations of condensed phase nickel and phase transitions

A high-dimensional neural network interatomic potential was developed and used in molecular dynamics simulations of condensed phase Ni and Ni systems with liquid–solid phase coexistence. The reference data set was generated by sampling the potential energy surface over a broad temperature-pressure domain using ab initio MD simulations to train a unified potential. Excellent agreement was achieved between bulk face-centered cubic nickel thermal expansion simulations and relevant experimental data. The same potential also yields accurate structures and diffusivities in the liquid state. The phase transition between liquid and solid phases was simulated using the two-phase interface method. The predicted melting point temperature is within a few kelvins of the literature value. Here, the general methodology could be applied to describe crystals with much more complex phase behaviors.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2011

Dynamic Shape Reconstruction of Three-Dimensional Frame Structures Using the Inverse Finite Element Method

A robust and efficient computational method for reconstructing the three-dimensional displacement field of truss, beam, and frame structures, using measured surface-strain data, is presented. Known as shape sensing , this inverse problem has important implications for real-time actuation and control of smart structures, and for monitoring of structural integrity. The present formulation, based on the inverse Finite Element Method (iFEM), uses a least-squares variational principle involving strain measures of Timoshenko theory for stretching, torsion, bending, and transverse shear. Two inverse-frame finite elements are derived using interdependent interpolations whose interior degrees-of-freedom are condensed out at the element level. In addition, relationships between the order of kinematic-element interpolations and the number of required strain gauges are established. As an example problem, a thin-walled, circular cross-section cantilevered beam subjected to harmonic excitations in the presence of structural damping is modeled using iFEM; where, to simulate strain-gauge values and to provide reference displacements, a high-fidelity MSC/NASTRAN shell finite element model is used. Examples of low and high-frequency dynamic motion are analyzed and the solution accuracy examined with respect to various levels of discretization and the number of strain gauges.

Gherlone, Marco↗
NASA NTRS2015

Daily Global Mapping of Mars Ozone Column Abundances with MARCI UV Band Imaging

Since November of 2006, The Mars Color Imager (MARCI) onboard the Mars Reconnaissance Orbiter (MRO) has obtained multiple-filter daily global images of Mars centered upon a local time (LT) of 3 pm. Ultraviolet imaging bands placed within (260 nm) and longward (320 nm) of Hartley band (240-300 nm) ozone (O3) absorption support retrievals of atmospheric ozone columns, with detection limits (approximately 1 micrometer-atm) appropriate to mapping elevated O3 abundances at low latitudes around Mars aphelion, and over mid-to-high latitudes during fall/winter/spring seasons. MARCI O3 maps for these regions reveal the detailed spatial (approximately 1 deg lat/long, for 8 x 8 pixel binned resolution) and temporal (daily, with substantial LT coverage at pole) behaviors of water vapor saturation conditions that force large variations in water vapor photolysis products (HOx-OH, HO2, and H) responsible for the catalytic destruction of O3 in the Mars atmosphere. A detailed description of the MARCI O3 data set, including measurement and retrieval characteristics, is provided in conjunction with comparisons to Mars Express SPICAM ozone measurements (Perrier, S. et al. [2006]. J. Geophys. Res. (Planets) 111) and LMD GCM simulated O3 abundances (Lefevre, F. [2004]. J. Geophys. Res. (Planets) 109). Presented aspects of the MARCI ozone mapping data set include aphelion increases in low latitude O3, dynamically evolving high latitude O3 maxima associated with planetary waves and weather fronts during northern early spring, and distinctive winter/spring O3 and CO increases within the Hellas Basin associated with transport of condensation enhanced south polar air mass. Comparisons of coincident MARCI measurements and LMD simulations for ice cloud and O3 columns are considered in the context of potential heterogeneous photochemical processes (Lefevre, F. [2008]. Nature 454, 971-975), which are not strongly evidenced in the MARCI observations. Modest interannual variations are exhibited, most notably a 20% reduction in aphelion low latitude O3 columns following the 2007 perihelic global dust storm.

Clancy, R. Todd↗
DOE OSTI2022

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗
DOE OSTI2025

Multistage nucleation pathway in LiF molten salt mirrors the crystal–melt interface structure

Despite over a century of studies, fundamental questions remain about the processes governing crystal nucleation from melts or solutions. Research over the past three decades has presented mounting evidence for kinetic pathways of crystal nucleation that are more complex than envisioned by the simplest forms of classical theory. Such observations have been presented for colloidal and elemental systems with covalent and metallic bonding. Despite the technological and geochemical importance of molten salts, similar studies for these ionically bonded systems are currently lacking. Here we develop a machine learning interatomic potential for a model ionic system: LiF. The potential features quantum-level accuracy for both liquid and multiple solid polymorphs over wide temperature and pressure ranges and accurately reproduces experimentally measured properties. Thanks to the efficiency of the potential, which enables microsecond-scale molecular dynamics simulations, induction times for nucleation of LiF solids from their melts are computed over a range of undercoolings. With the aid of a set of robust local order parameters established here, the simulations reveal that homogeneous crystal nucleation in undercooled melts preferentially initiates from liquid regions showing slow dynamics and high bond orientational order simultaneously, and the second-shell order of both precritical nuclei and the surface of postcritical nuclei is dominated by hexagonal close packing and body-centered cubic local structure, even though the nucleus core is dominated by face-centered cubic structure corresponding to the stable rocksalt crystal structure. Finally, we establish a connection between the crystallization pathway and the equilibrium crystal-melt interface structure.

Applied Physical Sciences↗
DOE OSTI2021

Enabling Combustion Science Simulations for Future Exascale Machines

Reacting flow simulations for combustion applications require extensive computing capabilities. Leveraging the AMReX library, the Pele suite of combustion simulation tools targets the largest supercomputers available and future exascale machines. We introduce PeleC, the compressible solver in the Pele suite, and detail its capabilities, including complex geometry representation, chemistry integration, and discretization. We present a comparison of development efforts using both OpenACC and AMReX's C++ performance portability framework for execution on multiple GPU architectures. We discuss relevant details that have allowed PeleC to achieve high performance and scalability. PeleC's performance characteristics are measured through relevant simulations on multiple supercomputers. The success of PeleC's design for exascale is exhibited through demonstration of a 160 billion cell simulation and weak scaling onto 100\% of Summit, an NVIDIA-based GPU supercomputer at Oak Ridge National Laboratory. Our results provide confidence that PeleC will enable future combustion science simulations with unprecedented fidelity.

combustion↗
DOE OSTI2020

Three-Dimensional Lead Iodide Perovskitoid Hybrids with High X-ray Photoresponse

Large organic A cations cannot stabilize the 3D perovskite AMX 3 structure because they cannot be accommodated in the cubo-octhedral cage (do not follow the Goldschmidt tolerance factor rule), and they generally template low-dimensional structures. In this paper, we report that the large dication aminomethylpyridinium (AMPY) can template novel 3D structures which resemble conventional perovskites. They have the formula (xAMPY)M 2 I 6 (x = 3 or 4, M = Sn 2+ or Pb 2+ ) which is double of the AMX3 formula. However, because of the steric requirement of the Goldschmidt tolerance factor rule, it is impossible for (xAMPY)M 2 I 6 to form proper perovskite structures. Instead, a combination of corner-sharing and edge-sharing connectivity is adopted in these compounds leading to the new 3D structures. DFT calculations reveal that the compounds are indirect band gap semiconductors with direct band gaps presenting at slightly higher energies and dispersive electronic bands. The indirect band gaps of the Sn and Pb compounds are ~1.7 and 2.0 eV, respectively, which is slightly higher than the corresponding AMI 3 3D perovskites. The Raman spectra for the compounds are diffuse, with a broad rising central peak at very low frequencies around 0 cm –1 , a feature that is characteristic of dynamical lattices, high anharmonicity, and dissipative vibrations very similar to the 3D AMX 3 perovskites. Devices of (3AMPY)Pb 2 I 6 crystals exhibit clear photoresponse under ambient light without applied bias, reflecting a high carrier mobility (μ) and long carrier lifetime (τ). The devices also exhibit sizable X-ray generated photocurrent with a high μτ product of ~1.2×10 -4 cm 2 /V and a X-ray sensitivity of 207 μC∙Gy -1 ∙cm -2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Xcompact3D: An open-source framework for solving turbulence problems on a Cartesian mesh

Xcompact3D is a Fortran 90–95 open-source framework designed for fast and accurate simulations of turbulent flows, targeting CPU-based supercomputers. It is an evolution of the flow solver Incompact3D which was initially designed in France in the mid-90’s for serial processors to solve the incompressible Navier–Stokes equations. Incompact3D was then ported to parallel High Performance Computing (HPC) systems in the early 2010’s. Very recently the capabilities of Incompact3D have been extended so that it can now tackle more flow regimes (from incompressible flows to compressible flows at low Mach numbers), resulting in the design of a new user-friendly framework called Xcompact3D. The present manuscript presents an overview of Xcompact3D with a particular focus on its functionalities, its ready-to-run simulations and a few case studies to demonstrate its impact.

17 WIND ENERGY↗
NASA NTRS2005

Dynamical Zodiacal Cloud Models Constrained by High Resolution Spectroscopy of the Zodiacal Light

We have developed a set of self-consistent dynamical models of the Zodiacal cloud, following the orbital evolution of dust particles. Three populations were considered, originating from the Kuiper belt, asteroids and comets. Using the models developed, we investigated how the solar spectrum is changed by scattering by the zodiacal cloud grains and compared the obtained spectra with the observations.

Ipatov, S. I.↗
NASA NTRSDate not supplied

Developing Deep Learning Models for System Remaining Useful Life Predictions: Application to Aircraft Engines

Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process and down stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.

Prognostics↗
DOE OSTI2025

Longitudinal Patterns in Nitrate Revealed Through Drone‐Based Measurements in an Agriculturally Influenced Midwestern U.S. River

Nitrate concentrations in streams and rivers in the Midwestern United States are often elevated, reflecting the predominance of agriculture in the surrounding landscape. Recent advances in technology, including surface water drones and more precise sensors, provide opportunities to investigate nitrate dynamics with high spatial and temporal resolution. We deployed an aquatic drone, the AquaBOT, in a sixth-order, agriculturally influenced river to examine longitudinal patterns in water quality. Our goal was to measure the spatial and temporal heterogeneity in nitrate and nitrate removal processes and determine the influence of tributary inputs on main stem chemistry. We navigated the drone along a 12-km reach of the Des Moines River (Iowa, USA) nine times between June 2021 and August 2022. Across the deployments, mean nitrate concentration was positively related to discharge and was nearly two orders of magnitude higher in spring than summer. We observed contrasting patterns in main stem nitrate, which decreased downstream during some runs (e.g., 3.1–2.7 mg N L −1 in June 2021), demonstrating net nitrate uptake along the reach, and remained constant on other dates. Similarly, tributaries to the Des Moines had a varied influence on riverine nitrate. Tributaries either increased or decreased main stem nitrate concentrations depending on the tributary and the date. Nitrate removal rates were spatially and temporally variable but showed some consistency at the subreach (2 km) scale, with two subreaches often showing elevated rates of nitrate removal across dates. In conclusion, our study reveals nuanced heterogeneity in nitrate dynamics of the Des Moines River despite the homogeneity of agricultural land cover in the watershed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Neural-network learning of SPOD latent dynamics

Here, we aim to reconstruct the latent space dynamics of high dimensional, quasi-stationary systems using model order reduction via the spectral proper orthogonal decomposition (SPOD). The proposed method is based on three fundamental steps: in the first, once that the mean flow field has been subtracted from the realizations (also referred to as snapshots), we compress the data from a high-dimensional representation to a lower dimensional one by constructing the SPOD latent space; in the second, we build the time-dependent coefficients by projecting the snapshots containing the fluctuations onto the SPOD basis and we learn their evolution in time with the aid of recurrent neural networks; in the third, we reconstruct the high-dimensional data from the learnt lower -dimensional representation. The proposed method is demonstrated on two different test cases, namely, a compressible jet flow, and a geophysical problem known as the Madden-Julian Oscillation. An extensive comparison between SPOD and the equivalent POD-based counterpart is provided and differences between the two approaches are highlighted. The numerical results suggest that the proposed model is able to provide low rank predictions of complex statistically stationary data and to provide insights into the evolution of phenomena characterized by specific range of frequencies. The comparison between POD and SPOD surrogate strategies highlights the need for further work on the characterization of the interplay of error between data reduction techniques and neural network forecasts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Design Study of Wafer Seals for Future Hypersonic Vehicles

Future hypersonic vehicles require high temperature, dynamic seals in advanced hypersonic engines and on the vehicle airframe to seal the perimeters of movable panels, flaps, and doors. Current seals do not meet the demanding requirements of these applications, so NASA Glenn Research Center is developing improved designs to overcome these shortfalls. An advanced ceramic wafer seal design has shown promise in meeting these needs. Results from a design of experiments study performed on this seal revealed that several installation variables played a role in determining the amount of leakage past the seals. Lower leakage rates were achieved by using a tighter groove width around the seals, a higher seal preload, a tighter wafer height tolerance, and a looser groove length. During flow testing, a seal activating pressure acting behind the wafers combined with simulated vibrations to seat the seals more effectively against the sealing surface and produce lower leakage rates. A seal geometry study revealed comparable leakage for full-scale wafers with 0.125 and 0.25 in. thicknesses. For applications in which lower part counts are desired, fewer 0.25-in.-thick wafers may be able to be used in place of 0.125-in.-thick wafers while achieving similar performance. Tests performed on wafers with a rounded edge (0.5 in. radius) in contact with the sealing surface resulted in flow rates twice as high as those for wafers with a flat edge. Half-size wafers had leakage rates approximately three times higher than those for full-size wafers.

Dunlap, Patrick H.↗
DOE OSTI2025

Optimizing Non-Terrestrial Hybrid RF/FSO Links With Reinforcement Learning: Navigating Through Clouds

In the pursuit of ubiquitous broadband connectivity, there has been a significant shift towards the vertical expansion of communication networks into space, particularly through the exploitation of low Earth orbit (LEO) satellite constellations, which are favored for their relatively low latency. However, this approach faces many challenges that need to be addressed, including atmospheric turbulence, high path loss, and dynamic cloud formations. High-altitude pseudo-satellites (HAPS) have emerged as promising relaying layers between LEO satellites and ground stations, enhancing coverage, latency, and direct terrestrial user connectivity. While radio frequency (RF) bands suffer from congestion and limited bandwidth, free space optical (FSO) communications offer higher data rates, but are susceptible to misalignment and weather-induced signal degradation. To address these challenges, a hybrid RF/FSO approach has been proposed to take advantage of both technologies by dynamic switching between RF and FSO based on propagation channel conditions. This paper introduces a reinforcement learning-based algorithm designed to optimize the trajectory of HAPS, maneuver around cloudy areas, and seamlessly switch between the RF and FSO communication modes to maximize the achievable capacity. The proposed approach aims to maximize system performance by intelligently adapting to environmental conditions and offering a promising solution for next-generation space communication networks.

actor-critic algorithm↗
DOE OSTI2023

3D-printed sheet jet for stable megahertz liquid sample delivery at X-ray free-electron lasers

X-ray free-electron lasers (XFELs) can probe chemical and biological reactions as they unfold with unprecedented spatial and temporal resolution. A principal challenge in this pursuit involves the delivery of samples to the X-ray interaction point in such a way that produces data of the highest possible quality and with maximal efficiency. This is hampered by intrinsic constraints posed by the light source and operation within a beamline environment. For liquid samples, the solution typically involves some form of high-speed liquid jet, capable of keeping up with the rate of X-ray pulses. However, conventional jets are not ideal because of radiation-induced explosions of the jet, as well as their cylindrical geometry combined with the X-ray pointing instability of many beamlines which causes the interaction volume to differ for every pulse. This complicates data analysis and contributes to measurement errors. An alternative geometry is a liquid sheet jet which, with its constant thickness over large areas, eliminates the problems related to X-ray pointing. Since liquid sheets can be made very thin, the radiation-induced explosion is reduced, boosting their stability. These are especially attractive for experiments which benefit from small interaction volumes such as fluctuation X-ray scattering and several types of spectroscopy. Although their use has increased for soft X-ray applications in recent years, there has not yet been wide-scale adoption at XFELs. Here, gas-accelerated liquid sheet jet sample injection is demonstrated at the European XFEL SPB/SFX nano focus beamline. Its performance relative to a conventional liquid jet is evaluated and superior performance across several key factors has been found. This includes a thickness profile ranging from hundreds of nanometres to 60 nm, a fourfold increase in background stability and favorable radiation-induced explosion dynamics at high repetition rates up to 1.13 MHz. Its minute thickness also suggests that ultrafast single-particle solution scattering is a possibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗