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At least 217 records · Page 12

C/NOFS Satellite Electric Field and Plasma Density Observations of Plasma Instabilities Below the Equatorial F-Peak -- Evidence for Approximately 500 km-Scale Spread-F "Precursor" Waves Driven by Zonal Shear Flow and km-Scale, Narrow-Banded Irregularities

As solar activity has increased, the ionosphere F-peak has been elevated on numerous occasions above the C/NOFS satellite perigee of 400km. In particular, during the month of April, 2011, the satellite consistently journeyed below the F-peak whenever the orbit was in the region of the South Atlantic anomaly after sunset. During these passes, data from the electric field and plasma density probes on the satellite have revealed two types of instabilities which had not previously been observed in the C/NOFS data set (to our knowledge): The first is evidence for 400-500km-scale bottomside "undulations" that appear in the density and electric field data. In one case, these large scale waves are associated with a strong shear in the zonal E x B flow, as evidenced by variations in the meridional (outward) electric fields observed above and below the F-peak. These undulations are devoid of smaller scale structures in the early evening, yet appear at later local times along the same orbit associated with fully-developed spread-F with smaller scale structures. This suggests that they may be precursor waves for spread-F, driven by a collisional shear instability, following ideas advanced previously by researchers using data from the Jicamarca radar. A second new result (for C/NOFS) is the appearance of km-scale irregularities that are a common feature in the electric field and plasma density data that also appear when the satellite is below the F -peak at night. The vector electric field instrument on C/NOFS clearly shows that the electric field component of these waves is strongest in the zonal direction. These waves are strongly correlated with simultaneous observations of plasma density oscillations and appear both with, and without, evidence of larger-scale spread-F depletions. These km-scale, quasi-coherent waves strongly resemble the bottomside, sinusoidal irregularities reported in the Atmosphere Explorer satellite data set by Valladares et al. [JGR, 88, 8025, 1983]. We interpret these new observations in terms of fundamental plasma instabilities associated with the unstable, nighttime equatorial ionosphere.

Pfaff, R.↗

Self Induced Buoyant Blow Off in Upward Flame Spread on Thin Solid Fuels

Upward flame spread experiments were conducted on a thin fabric cloth consisting of 75% cotton and 25% fiberglass. The sample is sandwiched symmetrically with stainless steel plates with the exposed width varying between 2 to 8.8 cm from test to test and >1.5m tall. The bottom edge was ignited resulting in a symmetric two sided flame. For the narrower samples (. 5cm), two sided flame growth would proceed until reaching some limiting value (15-30 cm depending on sample width). Fluctuation or instability of the flame base on one side would initially become visible and then the flame base would retreat downstream and cause extinguishment on one side. Detailed examination of the still images shows that the fuel continues to vaporize from the extinguished side due to the thermally thin nature of the fuel. But, due to the remaining inert fiberglass mesh, which acts as a flashback arrestor, the extinguished side was not able to be reignited by the remaining flame. The remaining flame would then shrink in length due to the reduced heat transfer to the solid to a shorter length. The one-sided flame will spread stably with a constant speed and a constant flame length to the end of the sample. A constant length flame implies that the pyrolysis front and the burnt out fronts move at the same speed. For the wider samples (. 7cm), no one-sided extinction is observed. Two-sided flames spread all the way to the top of the sample. For these wider widths, the flames are still growing and have not reached their limiting length if it exists. Care was taken to minimize the amount of non-symmetries in the experimental configuration. Repeated tests show that blow-off can occur on either side of the sample. The flame growth is observed to be very symmetric during the growth phase and grew to significant length (>10cm) before extinction of the flame on one side. Our proposed explanation of this unusual phenomenon (i.e. stronger two ]sided flame cannot exist but weaker one-sided flame can) is as follows: The observed one-sided extinction is a blow- off induced by buoyant entrainment. It is known that the flammable diffusion flame regime is bounded by quenching and blow ]off limits when varying incoming air velocity. The narrowest samples tested (between 2 and 5 cm) begin within the flammable range, but as the flame grows, the buoyancy driven air velocity increases at the neighborhood of the flame base. The initially stable flame crosses the extinguishment boundary resulting in a flame blow-off. When one-side of the flame extinguishes, the remaining side shrinks due to the reduced heat transfer to the solid. This reduces the induced velocity and the flame becomes stable. It is proposed that this may have implications to upward flame growth beyond this experiment.

Johnston, Michael C.↗

Evaluating Observational Constraints on Intermodel Spread in Cloud, Temperature, and Humidity Feedbacks

Uncertainty in climate feedbacks is the primary source of the spread in projected surface temperature responses to anthropogenic forcing. Cloud feedback persistently appears as the main source of disagreement in future projections while the combined lapse-rate plus water vapor (LR+WV) feedback is a smaller (30%), but non-trivial source of uncertainty in climate sensitivity. Here we attempt to observationally constrain the feedbacks in an effort to reduce the irintermodel uncertainties. The observed interannual variation provides a useful constraint on the long-term cloud feedback, as evidenced by the consistency of global-mean values and regional contributions to the intermodal spread on both interannual and long-term timescales. However, interannual variability does not serve to constrain the long-term LR+WV feedback spread, which we find is dominated by the varying tropical relative humidity (RH) response to interhemispheric warming differences under clear-sky conditions and the RH-fixed LR feedback under all-sky conditions

radiative feedbacks↗

Determining the Cause of Reduced Concurrent Flame Spread over Thin Solid Fuels in Low Pressure and Low Gravity

The spread of flames over the surface of solid combustible materials is affected by the environmental conditions. Variables such as flow velocity, oxygen concentration, ambient pressure, partial gravity or microgravity, may change the material flammability and influence the fire dynamics. This is an important fire safety issue for space exploration vehicles and space habitats which will very likely have different environments than those currently used on the International Space Station, such as reduced pressure and enriched oxygen concentration (SEA). However, testing experimentally the materials to be used and qualified for space exploration under these conditions is a difficult and expensive task. Here, numerical modeling is used to understand the dominant physico-chemical processes on the concurrent flame spread over thin fabrics under reduced ambient pressure (and in turn, buoyancy) and variable gravitational conditions. The numerical model uses the Fire Dynamics Simulator (FDS6) code with a single-step Arrhenius reaction rate for the solid phase decomposition. Different models are tested for the gas phase combustion kinetics. The model results are validated with experimental results obtained at similar reduced ambient pressure and flow conditions at 1 g. It is shown that as ambient pressure is reduced the flame spread rate over a thin fabric is also reduced, both experimentally and numerically. Numerical results are compared to an analytical approach previously developed to explain the experimental trends. Further interpretation of the model results provides information regarding the physics of the process and how they are affected by the lower pressure environments and gravity conditions. The results of this work provide guidance for potential on-earth testing for fire safety design in spacecraft and space habitats.

Fire Safety↗

Determining the Cause of Reduced Concurrent Flame Spread over Thin Solid Fuels in Low Pressure and Low Gravity

The spread of flames over the surface of solid combustible materials is affected by the environmental conditions. Variables such as flow velocity, oxygen concentration, ambient pressure, partial gravity or microgravity, may change the material flammability and influence the fire dynamics. This is an important fire safety issue for space exploration vehicles and space habitats which will very likely have different environments than those currently used on the International Space Station, such as reduced pressure and enriched oxygen concentration (SEA). However, testing experimentally the materials to be used and qualified for space exploration under these conditions is a difficult and expensive task. Here, numerical modeling is used to understand the dominant physico-chemical processes on the concurrent flame spread over thin fabrics under reduced ambient pressure (and in turn, buoyancy) and variable gravitational conditions. The numerical model uses the Fire Dynamics Simulator (FDS6) code with a single-step Arrhenius reaction rate for the solid phase decomposition. Different models are tested for the gas phase combustion kinetics. The model results are validated with experimental results obtained at similar reduced ambient pressure and flow conditions at 1 g. It is shown that as ambient pressure is reduced the flame spread rate over a thin fabric is also reduced, both experimentally and numerically. Numerical results are compared to an analytical approach previously developed to explain the experimental trends. Further interpretation of the model results provides information regarding the physics of the process and how they are affected by the lower pressure environments and gravity conditions. The results of this work provide guidance for potential on-earth testing for fire safety design in spacecraft and space habitats.

microgravity↗

Learning of networked spreading models from noisy and incomplete data

Recent years have seen a lot of progress in algorithms for learning parameters of spreading dynamics from both full and partial data. Some of the remaining challenges include model selection under the scenarios of unknown network structure, noisy data, missing observations in time, as well as an efficient incorporation of prior information to minimize the number of samples required for an accurate learning. Here, in this work, we introduce a universal learning method based on a scalable dynamic message-passing technique that addresses these challenges often encountered in real data. The algorithm leverages available prior knowledge on the model and on the data, and reconstructs both network structure and parameters of a spreading model. We show that a linear computational complexity of the method with the key model parameters makes the algorithm scalable to large network instances.

97 MATHEMATICS AND COMPUTING↗

Modeling and Experimental Demonstration of Flux Spreading in Light Trapping Planar-Cavity Solar Enclosed Particle Receivers

This study experimentally validates and numerically models the flux-spreading effect in a light-trapping planar-cavity solar receiver) for particle-based concentrating solar power systems. The receiver's shallow cavity with vertical planar walls redistributes concentrated solar flux, reducing peak intensity and achieving uniform heat flux. On-sun tests at National Renewable Energy Laboratory's High-Flux Solar Furnace under flux up to 1500 kW/m2 measured cavity wall temperatures, which were compared with Monte Carlo ray-tracing (SolTrace) and computational numerical simulations. Three angular absorptance models were evaluated: constant absorptance, a Pyromark-based directional model, and a Fresnel-based Cr2O3 model. The Fresnel-derived model showed the best agreement with experiments, achieving high correlation (PC > 0.85), structural similarity (SSIM > 0.98), and signal-to-noise ratios (PSNR > 40 dB), with temperature prediction errors of 1-11%. Results confirm that flux spreading mitigates local overheating and validate the integrated modeling approach, supporting the solar receiver scalability for high-efficiency, high-temperature concentrating solar power applications.

14 SOLAR ENERGY↗

Simulations of flaming combustion and flaming-to-smoldering transition in wildland fire spread at flame scale

Our objective in the present study is to provide basic insights into the coupling between external-gas and solid biomass vegetation processes that control the dynamics of flame spread in wildland fire problems. Here we focus on a modeling approach that resolves processes occurring at vegetation and flame scales, i.e., the formation of flammable vapors due to the thermal degradation of the solid biomass, the subsequent combustion in ambient air, the thermal feedback to the biomass through radiative and convective heat transfer, and the possible transition from flaming combustion (taking place outside of the solid biomass) to smoldering combustion (taking place inside the solid biomass). The capability uses a multiphase combustion framework and treats external-gas processes through a Large Eddy Simulation solver and solid biomass processes through a discrete particle model. The discrete particle model adopts a one-dimensional porous medium formulation, includes descriptions of drying, thermal pyrolysis, oxidative pyrolysis, and char oxidation, as well as a description of the external-gas-to-solid-biomass diffusion of oxygen mass; the discrete particle model thereby provides a treatment of in-depth oxidative processes and allows the simulation of smoldering combustion. The modeling capability is applied to the simulation of fire spread across a surrogate biomass vegetation bed corresponding to a discrete array of cylindrical-shaped, vertically-oriented, pine wood sticks, characterized by a monomodal size distribution, in horizontal flat terrain and under wind-aided conditions. The numerical results demonstrate that the model can simulate successful flaming-to-smoldering transition followed by complete biomass consumption.

01 COAL, LIGNITE, AND PEAT↗

Density fluctuation statistics and turbulence spreading at the edge of L–mode plasmas

Long-wavelength density fluctuations ($k{\rho _i}$ <1) are studied using beam emission spectroscopy (BES) at the edge of DIII-D L-mode plasmas (ρ = 0.88–1.1) in scenarios with electron cyclotron heating (ECH) power ramp (P ECH up to 1.5 MW), neutral beam injection (NBI) power ramp (P NBI up to 2.5 MW), and injected torque scan (-1 < T inj <0.6 Nm). We find that broadband turbulent density fluctuations (ƒ ~ 20–120 kHz) have a non-Gaussian distribution. The skewness of $\delta n/n$ changes sign from negative at ρ < 0.95–0.97 to positive at ρ > 0.97, indicating the prevalence of density 'voids' at inner radii and density 'blobs' at outer radii and outside of the separatrix. The turbulence intensity flux $\left\langle {{{\tilde v}_{\text{r}}}{{\tilde n}^2}} \right\rangle$ is calculated to characterize turbulence spreading at the plasma edge. During ECH/NBI power ramps and at counter-I p injected torque, $\left\langle {{{\tilde v}_{\text{r}}}{{\tilde n}^2}} \right\rangle$ is directed inward inside the separatrix, which is evidence of inward spreading of turbulence intensity from the edge gradient region caused by the inner propagation of density 'voids'. Significantly weaker $\left\langle {{{\tilde v}_{\text{r}}}{{\tilde n}^2}} \right\rangle$ is observed with co-I p torque. A correlation between co-I p torque, turbulence intensity $\delta n/n$ at ρ = 0.97, and increased srape-off layer (SOL) heat flux decay length ${\lambda _q}$ is found in the torque scan scenario, showing that edge turbulence plays a material role in determining the SOL conditions and heat flux width.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Materials and technologies for interstellar flights and intra-galactic spread of life

Small automated spaceships are capable to deliver seeds, frozen ova and gametes to other planetary systems. A spaceship can be equipped with a freezer containing reproductive cells, an artificial uterus, a robotic nursery and school, and a collection of instruments and equipment. The whole spaceship will be frozen during a long interstellar flight. Approaching another star, a spaceship will generate electricity from light, warm up, slow down and land on a suitable planet (if any), give birth to a human, provide care and education. After schooling, the human will vacate the spaceship and either build more space for living (using local materials) or die. A vacant spaceship will supply more people, one at a time. Hopefully, they will collectively create a sustainable colony on a remote planet. Our Milky Way galaxy has hundreds billion stars (i.e., more stars than humans on Earth). Mass production of spacecrafts for intragalactic spread of life will make each spaceship cheaper, will improve employment and purposeful production on Earth, and will spread human life beyond the Solar System. If any spaceship will miss its target stellar system, it will fly to the next one, retaining ability to bring life to another planet. Which materials and technologies are needed for the interstellar life propagation? Materials age during a long interstellar flight, which can last from 10^4 to 10^10 years. We evaluate the computational methods (such as C2NEB, available from https://lib.dr.iastate.edu/ameslab_software/1) that are suitable for addressing materials aging at low temperatures and high radiation levels during the appropriately long-time scales.

Technologies↗

Probabilistic Discrete‐Time Models for Spreading Processes in Complex Networks: A Review

Abstract Research into network dynamics of spreading processes typically employs both discrete and continuous time methodologies. Although each approach offers distinct insights, integrating them can be challenging, particularly when maintaining coherence across different time scales. This review focuses on the Microscopic Markov Chain Approach (MMCA), a probabilistic f ramework originally designed for epidemic modeling. MMCA uses discrete dynamics to compute the probabilities of individuals transitioning between epidemiological states. By treating each time step—usually a day—as a discrete event, the approach captures multiple concurrent changes within this time frame. The approach allows to estimate the likelihood of individuals or populations being in specific states, which correspond to distinct epidemiological compartments. This review synthesizes key findings from the application of this approach, providing a comprehensive overview of its utility in understanding epidemic spread.

Granell, Clara↗

Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behavior

The increasing incidence and severity of wildfires underscores the necessity of accurately predicting their behavior. While high-fidelity models derived from first principles offer physical accuracy, they are too computationally expensive for use in real-time fire response. Low-fidelity models sacrifice some physical accuracy and generalizability via the integration of empirical measurements, but enable real-time simulations for operational use in fire response. Machine learning techniques have demonstrated the ability to bridge these objectives by learning first-principles physics while achieving computational speedups. While deep learning approaches have demonstrated the ability to predict wildfire propagation over large time periods, time-resolved fire-spread predictions are needed for active fire management. Here, in this work, we evaluate the ability of deep learning approaches in accurately modeling the time-resolved dynamics of wildfires. We use an autoregressive process in which a convolutional recurrent deep learning model makes predictions that propagate a wildfire over 15 min increments. We apply the model to four simulated datasets of increasing complexity, containing both field fires with homogeneous fuel distribution as well as real-world topologies sampled from the California region of the United States. We show that even after 100 autoregressive predictions representing more than 24 h of simulated fire spread, the resulting models generate stable and realistic propagation dynamics, achieving a Jaccard score between 0.89 and 0.94 when predicting the resulting fire scar. The inference time of the deep learning models are examined and compared, and directions for future work are discussed.

54 ENVIRONMENTAL SCIENCES↗

Characterization data of an (AlFeNiTiVZr) 1-x Cr x multi-principal element alloy continuous composition spread library

The data provided in this article is related to the research article entitled “Phase stabilization and oxidation of a continuous composition spread multi-principal element (AlFeNiTiVZr) 1-x Cr x alloy”. This data article describes the high-throughput synthesis and characterization processes of an (AlFeNiTiVZr) 1-x Cr x alloy system. Continuous composition spread (CCS) thin-film libraries were synthesized by co-depositing an AlFeNiTiVZr metal alloy target and Cr target via magnetron sputtering. Post-processing was performed on the sample libraries with a vacuum anneal at 873 K and an air anneal at 873 K. Compositional data was determined via WDS in order to verify parameters provided by an in-house sputter model. Crystallographic data was captured via synchrotron diffraction and diffractograms were compared as a function of the change in Cr concentration. These measurements were taken in order to observe phase behavior after oxidation throughout the composition library. Furthermore, vibrational spectrographic data is provided of the oxidized library to show surface speciation along the composition gradient of the alloy system. The structural and oxidative behavior of the (AlFeNiTiVZr) 1-x Cr x alloy can be analysed using the data provided in this article. Additionally, this characterization dataset can be utilized in machine learning algorithms for determining important features and parameters for future hypothesis generation of functional multi-principal element alloys (MPEAs).

36 MATERIALS SCIENCE↗

High-Throughput Characterization of (Fe x Co 1–x ) 3 O 4 Thin-Film Composition Spreads

In this study, thin-film continuous composition spreads of Fe–Co–O were fabricated by reactive cosputtering from elemental Fe and Co targets in reactive Ar/O 2 atmosphere using deposition temperatures ranging from 300 to 700 °C. Fused silica and platinized Si/SiO 2 strips were used as substrates. Ti and Ta were investigated as adhesion layer for Pt and the fabrication of the Fe–Co–O films. The thin-film composition spreads were characterized by high-throughput electron-dispersive X-ray spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, atomic force microscopy, scanning electron microscopy, and optical transmission spectroscopy. The Fe-content ranged from 28 to 72 at. %. The spinel phases Fe 2 CoO 4 and FeCo 2 O 4 could be synthesized and stabilized at all deposition temperatures with a continuous variation in spinel composition in between. The dependence of the film surface microstructure on the deposition temperature and the composition was mapped. Moreover, the band gap values, ranging from 2.41 eV for FeCo 2 O 4 to 2.74 eV for Fe 2 CoO 4 , show a continuous variation with the composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

California wildfire spread derived using VIIRS satellite observations and an object-based tracking system

Changing wildfire regimes in the western US and other fire-prone regions pose considerable risks to human health and ecosystem function. However, our understanding of wildfire behavior is still limited by a lack of data products that systematically quantify fire spread, behavior and impacts. Here we develop a novel object-based system for tracking the progression of individual fires using 375 m Visible Infrared Imaging Radiometer Suite active fire detections. At each half-daily time step, fire pixels are clustered according to their spatial proximity, and are either appended to an existing active fire object or are assigned to a new object. This automatic system allows us to update the attributes of each fire event, delineate the fire perimeter, and identify the active fire front shortly after satellite data acquisition. Using this system, we mapped the history of California fires during 2012–2020. Our approach and data stream may be useful for calibration and evaluation of fire spread models, estimation of near-real-time wildfire emissions, and as means for prescribing initial conditions in fire forecast models.

54 ENVIRONMENTAL SCIENCES↗

Conformational spread drives the evolution of the calcium–calmodulin protein kinase II

The calcium calmodulin (Ca 2+ /CaM) dependent protein kinase II (CaMKII) decodes Ca 2+ frequency oscillations. The CaMKIIα isoform is predominantly expressed in the brain and has a central role in learning. I matched residue and organismal evolution with collective motions deduced from the atomic structure of the human CaMKIIα holoenzyme to learn how its ring architecture abets function. Protein dynamic simulations showed its peripheral kinase domains (KDs) are conformationally coupled via lateral spread along the central hub. The underlying β-sheet motions in the hub or association domain (AD) were deconvolved into dynamic couplings based on mutual information. They mapped onto a coevolved residue network to partition the AD into two distinct sectors. A second, energetically stressed sector was added to ancient bacterial enzyme dimers for assembly of the ringed hub. The continued evolution of the holoenzyme after AD–KD fusion targeted the sector’s ring contacts coupled to the KD. Among isoforms, the α isoform emerged last and, it alone, mutated rapidly after the poikilotherm–homeotherm jump to match the evolution of memory. The correlation between dynamics and evolution of the CaMKII AD argues single residue substitutions fine-tune hub conformational spread. The fine-tuning could increase CaMKIIα Ca 2+ frequency response range for complex learning functions.

59 BASIC BIOLOGICAL SCIENCES↗

Photometry, Centroid and Point-spread Function Measurements in the LSST Camera Focal Plane Using Artificial Stars

Abstract The Vera C. Rubin Observatory’s LSST Camera (LSSTCam) pixel response has been characterized using laboratory measurements with a grid of artificial stars. We quantify the contributions to photometry, centroid, point-spread function size, and shape measurement errors due to small anomalies in the LSSTCam CCDs. The main sources of those anomalies are quantum efficiency variations and pixel area variations induced by the amplifier segmentation boundaries and “tree-rings”—circular variations in silicon doping concentration. This laboratory study using artificial stars projected on the sensors shows overall small effects. The residual effects on point-spread function (PSF) size and shape are below 0.1%, meeting the ten-year LSST survey science requirements. However, the CCD mid-line presents distortions that can have a moderate impact on PSF measurements. This feature can be avoided by masking the affected regions. Effects of tree-rings are observed on centroids and PSFs of the artificial stars and the nature of the effect is confirmed by a study of the flat-field response. Nevertheless, further studies of the full-focal plane with stellar data should more completely probe variations and might reveal new features, e.g., wavelength-dependent effects. The results of this study can be used as a guide for the on-sky operation of LSSTCam.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling and design of compact, permanent-magnet transport systems for highly divergent, broad energy spread laser-driven proton beams

Laser-driven (LD) ion acceleration has been explored in a newly constructed short focal length laser beamline at the BELLA petawatt facility (interaction point 2, iP2). For applications utilizing such LD ion beams, a beam transport system is required, which for reasons of compactness be ideally contained within 3 m. While they are generated from a micron-scale source, large divergence and energy spread of LD ion beams present a unique challenge to transporting them compared to beams from conventional accelerators. This study gives an overview of proposed compact transport designs using permanent magnets satisfying different requirements depending on the application for the iP2 laser beamline such as radiation biology, material science, and high-energy density science. These designs are optimized for different parameters such as energy spread and peak proton density according to the application’s need. The various designs consist solely of permanent magnet elements, which can provide high magnetic field gradients on a small footprint. While the field strengths are fixed, we have shown that the beam size is able to be tuned effectively by varying the placement of the magnets. The performance of each design was evaluated based on high-order particle tracking simulations of typical LD proton beams. We also examine the ability of certain configurations to tune and select beam energies, critical for specific applications. A more detailed investigation was carried out for a design to deliver 10 MeV LD accelerated ions for radiation biology applications. With these transport system designs, the iP2 laser beamline is ready to house various application experiments.

43 PARTICLE ACCELERATORS↗