Small-scale Structures Research Articles

A deep-learning model for the density profiles of subhaloes in IllustrisTNG

ABSTRACT We present a machine-learning-based model for the total density profiles of subhaloes with masses $M \gtrsim 7\times 10^8\, h^{-1}{\rm M}_\odot$ in the IllustrisTNG100 simulation. The model is based on an interpretable variational encoder (IVE) which returns the independent factors of variation in the density profiles within a low-dimensional representation, as well as the predictions for the density profiles themselves. The IVE returns accurate and unbiased predictions on all radial ranges, including the outer region profile where the subhaloes experience tidal stripping; here its fit accuracy exceeds that of the commonly used Einasto profile. The IVE discovers three independent degrees of freedom in the profiles, which can be interpreted in terms of the formation history of the subhaloes. In addition to the two parameters controlling the normalization and inner shape of the profile, the IVE discovers a third parameter that accounts for the impact of tidal stripping on to the subhalo outer profile; this parameter is sensitive to the mass loss experienced by the subhalo after its infall on to its parent halo. Baryonic physics in the IllustrisTNG galaxy formation model does not impact the number of degrees of freedom identified in the profile compared to the pure dark matter expectations, nor their physical interpretation. Our newly proposed profile fit can be used in strong lensing analyses or other observational studies which aim to constrain cosmology from small-scale structures.

An Analysis of F. Chopin’s Music Language in Terms of Melody, Harmony and Rhythm

Frédéric Chopin (1810-1849), one of the composers who reflected and created the spirit of the ‘Romantic Period,’ characterized by increased diversity in style, form, and expression, and the expansion of piano literature, crafted the musical texture in his pieces with a highly personal style, incorporating his unique harmony, flexible formal design, original use of expressive tools, and a free performance technique that didn’t adhere to rigid patterns in rhythm and tempo. Chopin’s distinctive style is particularly visible in the forms he chose for piano music. The flexi-ble forms of his time allowed the composer to create a characteristic style by freely utilizing mu-sical materials. Especially, forms like nocturnes, fantaisies-impromptus, and waltzes, which leave an impression of improvisation, small-scale, and rule-free structures, provided a clear space for the composer’s expressive tools. Indeed, it is possible to identify Chopin’s musical lan-guage, especially through his small-scale pieces. The purpose of this research is to analyze the melody construction, harmony, and rhythms of Frédéric Chopin (1810-1849), focusing on se-lected pieces to provide an interpretation of his musical language based on similarities found in these pieces. Samples from Chopin’s literature, including Op. 27 No. 1, Op. 9 No. 2 and No. 20 Nocturnes, Op. 64 No. 2 Waltz, and Op. 66 Fantaisie-Impromptu, were taken for the study. The research employed a case study design within qualitative research methods, and the obtained data was described descriptively. In conclusion, it was found that Chopin’s harmony encom-passes a wide range from simple chord progressions to complex chords. He created simple yet bel canto melodies inspired by the ‘Italian Opera’ embellishments and used rhythms that priori-tize the clarity of melody rather than a polyrhythmic approach. This study is believed to con-tribute to listening and playing practices due to its exploration of the musical materials in the Turkish literature related to Chopin. Keywords: F. Chopin, melody, rhythm, harmony, music language.

Self-interacting forbidden dark matter under a cannibally co-decaying phase

In a usual dark matter (DM) model without a huge mass difference between the DM and lighter mediator, using the coupling strength suitable for having the correct relic density, the resulting self-interaction becomes several orders of magnitude smaller than that required to interpret the small-scale structures. We present a framework that can offer a solution for this point. We consider a model that contains the vector DM and a heavier but unstable Higgs-like scalar in the hidden sector. When the temperature drops below ~ mDM, the hidden sector, which is thermally decoupled from the visible sector, enters a cannibal phase, during which the DM density is depleted with the out-of-equilibrium decay of the scalar. The favored parameter region, giving the correct relic density and the proper size of self-interactions, shows the scalar-to-DM mass ratio ∈ [1.1, 1.33] and the scalar mass ∈ [9, 114] MeV. A sizable parameter space still survives the most current constraints and can be further probed by the near future NA62 beam dump experiment.

Deep learning-based image segmentation for instantaneous flame front extraction

This paper delves into the methodology employed in examining lean premixed turbulent flame fronts extracted from Planar Laser Induced Fluorescence (PLIF) images at elevated pressures. In such flow regimes, the PLIF signal suffers from significant collisional quenching, typically resulting in image data with low signal-to-noise ratio (SNR). This poses severe difficulties for conventional flame front extraction algorithms based on intensity gradients and requires intense user intervention to yield acceptable results. In this work, we propose Convolutional Neural Network (CNN)-based Deep Learning (DL) models as an alternative to problem specific conventional methods. The pretrained DL models were fine-tuned, employing data augmentation, on a small annotated dataset including a variety of conditions between SNR ≈\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx$$\\end{document} 1.6 to 2.6 and subsequently evaluated. All DL models significantly outperformed the best-scoring conventional implementation both quantitatively and visually, while having similar inference times. IoU-scores and Recall values were found to be up to a factor ≈\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx$$\\end{document} 1.2 and ≈\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx$$\\end{document} 2.5 higher, respectively, with ≈\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx$$\\end{document} 1.15 times improved Precision. Small-scale structures were captured much better with fewer erroneous predictions, becoming particularly pronounced for the lower SNR data investigated. Moreover, by applying artificially modeled noise, it was shown that the range of image conditions in terms of SNR that can be reliably processed extends well beyond the images included in the training data, and satisfactory segmentation performances were found for SNR as low as ≈\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx$$\\end{document} 1.1. The presented DL-based flame front detection algorithm marks a methodology with significantly increased detection performance, while a similar computational effort for inference is achieved and the need for user-based parameter tuning is eliminated. It enables a very accurate extraction of instantaneous flame fronts in large image datasets where supervised processing is infeasible, unlocking unprecedented possibilities for the study of flame dynamics and instability mechanisms at industry-relevant conditions.

Development and Verification of an Improved Wake-Added Turbulence Model in FAST.Farm

We introduce a generalized wake-added turbulence (WAT) model in the multiphysics, multiturbine simulation tool FAST.Farm. The WAT model introduces additional small-scale turbulence that represents the breakdown of vortical structures and shear layers in the wake. The article describes the development, implementation, calibration, and verification of the model. The novelties of the model include support for wake asymmetry, buildup of WAT across the wind farm, and secondary effects of wake-induced turbulence (e.g., wake meandering) driven by smaller-scale turbulence structures that arise from wake breakdown. Large-eddy simulations were run to support the calibration of the WAT parameters and verification of the model. Previous studies hypothesized that the lack of WAT modeling was the source of underprediction of fatigue loads, in particular for cases at low turbulence intensities and/or stable atmospheric boundary layers. This study confirms that the newly implemented WAT model enhances the loads predictions in these cases.

Wooden Spatial Structures Assembled with Disassembly Possible Simple Joints

The authors propose a new clamped joint system that can easily join wooden members together and a wooden spatial structure that utilizes this system. The proposed system can clamp wood members without the need for special joint machining. Two types of clamps have been developed: orthogonal clamps and rotational clamps. A frame system is developed using this joint system, which is a hemispherical dome with a diameter of 5.4 m and its membrane is tensioned using struts. A preliminary framework structural analysis and membrane stress analysis are conducted to confirm the safety of the frame. Full-scale mock-up was constructed to validate the frame model analysis and verify construction procedures. As a combinable structure, a small-scale spatial structure assembled using orthogonal clamps is also described. It is the cube-shaped structure 2.8 m wide consisting of wall and ceiling planes. Single clamp loading tests are conducted to understand the load-deformation relationship of the proposed clamped joint system and full-scale horizontal loading tests have been conducted.

LES-based validation of a dynamic wind farm flow model under unsteady inflow and yaw misalignment

This work presents the validation of an extended version of the control-oriented, dynamic wind farm flow solver SPLINTER. The two-dimensional model is applied to use cases of wake steering by yaw misalignment and inflow wind direction variations and the results are compared to large-eddy simulations (LES). While SPLINTER is able to reproduce the antagonal behaviour of decreasing upstream and increasing downstream turbine power under wake deflection, a systematic deviation of the downstream power is detected and quantified, which is connected to underrepresented three-dimensional wake effects. In case of changing inflow wind direction, SPLINTER is capable of computing movement and shape of the bending wakes. The model smooths small-scale turbulent structures and disturbances and does not reproduce wake meandering, but manages to describe the evolution of the mean flow, which is tested by averaging over an ensemble of LES and comparing the resulting flow fields and turbine power time series. Under dynamic inflow conditions, SPLINTER is able to predict at which time intervals and at which rates downstream turbines will be influenced by wakes, which can improve the accuracy of short-term power and load forecasting and enables its application to online model predictive wind farm control.

Super-resolution reconstruction of turbulent flows with a hybrid framework of attention

In a plethora of research endeavors concerning flow fields, acquiring high-resolution data is paramount. However, obtaining high-resolution turbulence data invariably requires substantial computational resources. Although super-resolution reconstruction of turbulent fields has emerged as a salient technique for detail extraction, conventional interpolation methods pose a significant challenge in reconstructing small-scale structures, often resulting in overly smooth outcomes. In this study, we propose a novel hybrid framework of spatially-adaptive feature attention (HSAFA) for the high-quality reconstruction of turbulent fields. This framework is characterized by the implementation of multidimensional feature fusion, which enhances the model's ability to capture details of turbulence. We rigorously applied the proposed model to datasets comprising laminar flow around a square cylinder and turbulent channel flows, with the reconstructed instantaneous velocity fields and statistics subjected to exhaustive and comparative analysis. Our findings demonstrate that HSAFA is capable of effectively reconstructing high-resolution turbulence fields from significantly low-resolution data, covering the range from laminar to turbulent flows.

Large eddy simulation study on drag reduction performance of array-based plasma synthetic jet actuators

Large Eddy Simulation (LES) is first used to investigate the drag reduction effect of an array-based configuration of Plasma Synthetic Jet Actuators (PSJAs) on a hemisphere in supersonic inflow, and analyze the effect of energy allocation and array angle on the drag reduction performance of opposing Plasma Synthetic Jet (PSJ) in this paper. Numerical simulation results have been compared with experimental data, confirming the validity of the simulation method. The results show that different energy allocations have a significant effect on the drag of the hemisphere. However, the effect of the change in array angle on the drag of the hemisphere is not as noticeable as the effect caused by energy allocation. Interference regions between the two PSJAs occur, which undermine the effectiveness of drag reduction. High Turbulent Kinetic Energy (TKE) regions primarily concentrate on the core region of the jet and downstream of the bow shock. The influence of the array angle on TKE is most evident in the downstream region of the exits of the PSJs on both sides. Temporal evolution of the coherent structures reveals that as the PSJ intensity decreases, the large-scale vortices progressively break up into smaller-scale vortices, and energy is also transferred from large-scale structures to small-scale structures.

Efficient dimension-by-dimension adaptive TENO-based limiter and troubled-cell indicator for nodal-based high-order spectral difference method

A new targeted essentially non-oscillatory (TENO) limiter with adaptive dissipation has been developed for the 3rd- and 4th-order spectral difference method. This limiter can potentially be useful for other nodal-based discontinuous high-order methods as well. Unlike traditional WENO limiters for these methods which limit low-order moments one by one, the new limiter is based on a direct convex combination of reconstruction polynomial candidates. This strategy ensures the good computational efficiency for high order reconstructions. The reconstruction stencils only involve nodal values from the target cell and its neighbors sharing faces with it. The reconstruction employs Hermite polynomials, making the new limiter compact. It can be implemented in a dimension-by-dimension manner for multi-dimensional problems, which is consistent with the spectral difference method. To further enhance efficiency, a TENO-based troubled-cell indicator is also developed to only activate limiters in troubled cells. Extensive one-dimensional and two-dimensional numerical experiments validate the performance of the new TENO-based limiter and indicator. In summary, the limiter is much less dissipative than WENO limiters and can resolve richer small-scale flow structures on coarse meshes. The indicator precisely marks out troubled cells, slightly improving over the KXRCF indicator.

Toward Cosmological Simulations of the Magnetized Intracluster Medium with Resolved Coulomb Collision Scale

We present the first results of one extremely high-resolution, nonradiative magnetohydrodynamical cosmological zoom-in simulation of a massive cluster with a virial mass of M vir = 2.0 × 1015 solar masses. We adopt a mass resolution of 4 × 105 M ⊙ with a maximum spatial resolution of around 250 pc in the central regions of the cluster. We follow the detailed amplification process in a resolved small-scale turbulent dynamo in the intracluster medium (ICM) with strong exponential growth until redshift 4, after which the field grows weakly in the adiabatic compression limit until redshift 2. The energy in the field is slightly reduced as the system approaches redshift zero in agreement with adiabatic decompression. The field structure is highly turbulent in the center and shows field reversals on a length scale of a few tens of kiloparsecs and an anticorrelation between the radial and angular field components in the central region that is ordered by small-scale turbulent dynamo action. The large-scale field on megaparsec scales is almost isotropic, indicating that the structure formation process in massive galaxy cluster formation suppresses any memory of both the initial field configuration and the amplified morphology via the turbulent dynamo. We demonstrate that extremely high-resolution simulations of the magnetized ICM are within reach that can simultaneously resolve the small-scale magnetic field structure, which is of major importance for the injection of and transport of cosmic rays in the ICM. This work is a major cornerstone for follow-up studies with an on-the-fly treatment of cosmic rays to model in detail electron-synchrotron and gamma-ray emissions.

A novel dynamic stiffness matrix for the nonlocal vibration characteristics of porous functionally graded nanoplates on elastic foundation with small-scale effects

The present paper deals with the development of a dynamic stiffness matrix to evaluate the free vibration response of functionally graded nanoplate (FG-nP) resting on the Winkler-Pasternak elastic foundation. The complete mathematical modeling of the dynamic stiffness matrix for nanostructures is given for the first time. The equation of motion for rectangular FG-nP plates supported on an elastic foundation is derived using Hamilton’s principle in conjunction with nonlocal elasticity theory. The non-local theory is incorporated to account for the size effect in the small-scale plate. The effective material property of the porous FG-nP has been calculated using three recently developed models of porosity. The developed dynamic stiffness matrix is solved using the Wittrick-Williams algorithm to extract the natural frequencies of the FG-nP. The variation of natural frequencies with the change of numerical values, such as nonlocal parameter, aspect ratio, elastic foundation parameters, and porosity volume fraction is analyzed. The validity and accuracy of the results are confirmed through comparison with the available literature. The use of non-local theory in dynamic stiffness analysis is shown to be effective in predicting the natural frequency of the FG-nP on a Winkler-Pasternak elastic foundation, providing new insights into the dynamic behavior of small-scale structures.

HCN as a probe of the inner disc in a candidate proto-brown dwarf

ABSTRACT The detection of Keplerian rotation is rare among Class 0 protostellar systems. We have investigated the high-density tracer HCN as a probe of the inner disc in a Class 0 proto-brown dwarf candidate. Our ALMA high angular resolution observations show the peak in the HCN (3–2) line emission arises from a compact component near the proto-brown dwarf with a small bar-like structure and a deconvolved size of ∼50 au. Radiative transfer modelling indicates that this HCN feature is tracing the innermost, dense regions in the proto-brown dwarf where a small Keplerian disc is expected to be present. The limited velocity resolution of the observations, however, makes it difficult to confirm the rotational kinematics of this feature. A brightening in the HCN emission towards the core centre suggests that HCN can survive in the gas phase in the inner, dense regions of the proto-brown dwarf. In contrast, modelling of the HCO+ (3–2) line emission indicates that it originates from the outer pseudo-disc/envelope region and is centrally depleted. HCN line emission can reveal the small-scale structures and can be an efficient observational tool to study the inner disc properties in such faint compact objects where spatially resolving the disc is nearly impossible.

Water Quality and the First-Flush Effect in Roof-Based Rainwater Harvesting, Part II: First Flush

Rainwater runoff samples from a range of roofing materials were temporally collected from 19 small-scale roof structures and two commercial buildings through simulated and actual storm events, and the concentrations of polycyclic aromatic hydrocarbons (PAHs), phosphorus flame retardants (PFLs), and pyrethroid insecticides and other water quality parameters were analyzed. In Part I of this research, the concentrations of these contaminants in roof runoff and soils receiving runoff from a range of roofing materials were evaluated. In Part II, recommendations have been developed for a first-flush exclusion to improve the quality of water harvesting for nonpotable uses. Recommendations focus on a first-flush diversion based on mass removals of total suspended solids (TSS) and PAHs linked to conductivity measurements throughout a storm event. Additionally, an upper-confidence limit (UCL) was constructed to determine the minimum diversion required to obtain 50, 75, 90, and 95% mass removal of TSS and PAH contaminants. The majority of TSS were produced during the initial 1.2 mm of runoff. Likewise, the majority of PAHs were removed during the initial 1.2 mm of runoff, except for the asphalt shingle roofs, where high PAHs were observed after 6 mm of runoff. The Texas Water Development Board (TWDB)-recommended first-flush diversion of one gallon for every 100 square feet of rooftop was not always adequate for removing 50% of TSS and PAHs from the roofs. Rainwater runoff conductivity decreased drastically between 1.2 to 2.4 mm of rainwater runoff. Diverting the first flush based on conductivity has the potential to also divert the majority of TSS and PAHs in roof runoff.

Influence of subtle inherited basement structures on thin-skinned thrust systems: The Caledonian Thrust Front in Lapland (CaTFLap)

Thin-skinned fold-thrust belts are defined by an extensive detachment surface, “the sole thrust’. The sole thrust is typically assumed to be sub-planar beneath the fold-thrust belt. The model of a planar sole thrust and, by inference, planar basement is often applied rather uncritically, whereas experimental and field studies show that basement topography is not only varied but crucial for the geometrical and kinematic evolution of fold-thrust belts. Basement topography controls on the thrust dynamics remains the least well understood parameter in fold-thrust belts, and more case studies are needed to underpin further understanding. We present field evidence from the well-exposed Caledonian Thrust Front in Lapland, showing the influence of inherited, orogen-perpendicular basement structures on the subsequent structural evolution of the Caledonian sole thrust and its underlying sedimentary rocks. Inherited orogen-perpendicular basement structures created open corrugations in the foreland that directed thrust allochthons and controlled the geometry and strain state of the sole thrust and associated rocks. We propose that even relatively small-scale structures can have a significant control on the geometry and strain state of an evolving thrust system, and that variations in thrust geometries are not simply explained by inversion or coincidental heterogeneous internal thickening (imbrication) of thrust-related units.

Joule Heating rate at high-latitudes by Swarm and ground-based observations compared to MHD simulations

We compare Joule Heating rates as derived from ground-based magnetic field and all-sky camera data, from Low Earth Orbit satellite data (ESA Swarm) and from a MHD simulation (GUMICS-5) with each other in a case study of an auroral arc system. The observational estimates of Joule Heating rates provide information on regional scales and with high spatial resolution (10–100 km). Their comparison with global MHD results is conducted for a quiet time interval of a few minutes, just before a magnetic substorm. Analysis of the ground-based observations yields electric field with dominating North-South component pointing towards the arcs and having maxima values in the range 20–35 V/km. Combining these values with Pedersen conductance estimates from optical data (5–10 S) yields Joule Heating rates in the range 2.5–3.5 mW/m2. Swarm electric field measurements are consistent in their direction and intensity with the ground-based estimates. They also show that heating is increased particularly in the region where the conductance is low. The total amount of Joule heating in the area between the Swarm A and C satellite footprints while crossing the all-sky camera field of view is estimated to be 46 MW and the total amount energy dissipation during the 80 s overflight is around 3.6 GJ (1000 kWh). GUMICS-5 estimate of the peak Joule Heating in the magnetic local time sector of the arc system is smaller than that from the ground-based data with a factor of 2.9. Comparisons of GUMICS-5 results with Space Weather Modeling Framework (SWMF), shows that the latter gives on average larger heating rates being thus more consistent with our regional observations. However, both MHD-codes yield smaller Joule Heating rates around the time of the arcs and during the following substorm than the CTIP-e code. CTIP-e has a more detailed description of ionosphere-thermosphere interactions than the MHD-codes and its convection electric field is enhanced with a randomly varying additional component mimicking small scale structures. GUMICS-SWMF comparisons of global Joule Heating patterns in the Northern polar area reveal that the two simulations have significant differences in their spatial distribution of heating rates. Main cause for these deviations is the difference in the derivation of ionospheric Pedersen conductance. Our results emphasize the fact that future estimates of the global energetics in the magnetosphere–ionosphere–thermosphere system require better knowledge on ionospheric conductivities, both by new measurement concepts and by better understanding on the background physics controlling conductivity variations.

Vortex bursting and associated twist dynamics on helical vortex tubes and vortex rings

The interaction of opposite-signed twist waves on vortex tubes can lead to vortex bursting, a process where the core expands into a double ring-like structure with strong swirling flows. Previous works have studied vortex bursting on rectilinear vortices by axially perturbing the initial core size to generate the twist waves, and observed largely axisymmetric bursting dynamics. In this work, we numerically study bursting on vortical structures with curved centrelines, analysing the interaction between the centreline dynamics, twist wave generation and propagation, and vortex bursting. We focus on axially perturbed helical vortex tubes with small radius-to-pitch ratios up to $0.0625$ , as well as vortex rings with a large radius-to-core size ratio $10$ , both at a circulation-based Reynolds number $5000$ . The results show that though the initial twist wave propagation speeds are relatively unaffected by the curvature and torsion of the centreline, the bursting process is altered significantly compared with rectilinear vortices. The self-induced rotation of the centreline of the helical tube induces a non-axisymmetric distortion of the bursting structure, which rapidly breaks up the vortex core into small-scale helical structures. A similar destabilization of the bursting structure also occurs on vortex rings. The enstrophy increase and accelerated energy decay associated with bursting are predominantly determined by the twist wave strength, rather than the curvature and torsion of the centreline. Combined, our findings imply that bursting could play an important role in transferring and dissipating energy of vortical structures in wakes, and turbulent flows in general.

Experimental dataset investigation of deep recurrent optical flow learning for particle image velocimetry: flow past a circular cylinder

Current optical flow-based neural networks for particle image velocimetry (PIV) are largely trained on synthetic datasets emulating real-world scenarios. While synthetic datasets provide greater control and variation than what can be achieved using experimental datasets for supervised learning, it requires a deeper understanding of how or what factors dictate the learning behaviors of deep neural networks for PIV. In this study, we investigate the performance of the recurrent all-pairs field transforms-PIV (RAFTs-PIV) network, the current state-of-the-art deep learning architecture for PIV, by testing it on unseen experimentally generated datasets. The results from RAFT-PIV are compared with a conventional cross-correlation-based method, Adaptive PIV. The experimental PIV datasets were generated for a typical scenario of flow past a circular cylinder in a rectangular channel. These test datasets encompassed variations in particle diameters, particle seeding densities, and flow speeds, all falling within the parameter range used for training RAFT-PIV. We also explore how different image pre-processing techniques can impact and potentially enhance the performance of RAFT-PIV on real-world datasets. Thorough testing with real-world experimental PIV datasets reveals the resilience of the optical flow-based method’s variations to PIV hyperparameters, in contrast to the conventional PIV technique. The ensemble-averaged root mean squared errors between the RAFT-PIV and Adaptive PIV estimations generally range between 0.5–2 (px) and show a slight reduction as particle densities increase or Reynolds numbers decrease. Furthermore, findings indicate that employing image pre-processing techniques to enhance input particle image quality does not improve RAFT-PIV predictions; instead, it incurs higher computational costs and impacts estimations of small-scale structures.

Earth’s geomagnetic environment—progress and gaps in understanding, prediction, and impacts

Understanding of Earth’s geomagnetic environment is critical to mitigating the space weather impacts caused by disruptive geoelectric fields in power lines and other conductors on Earth’s surface. These impacts are the result of a chain of processes driven by the solar wind and linking Earth’s magnetosphere, ionosphere, thermosphere and Earth’s surface. Tremendous progress has been made over the last two decades in understanding the solar wind driving mechanisms, the coupling mechanisms connecting the magnetically controlled regions of near-Earth space, and the impacts of these collective processes on human technologies on Earth’s surface. Studies of solar wind drivers have been focused on understanding the responses of the geomagnetic environment to spatial and temporal variations in the solar wind associated with Coronal Mass Ejections, Corotating Interaction Regions, Interplanetary Shocks, High-Speed Streams, and other interplanetary magnetic field structures. Increasingly sophisticated numerical models are able to simulate the magnetospheric response to the solar wind forcing associated with these structures. Magnetosphere-ionosphere-thermosphere coupling remains a great challenge, although new observations and sophisticated models that can assimilate disparate data sets have improved the ability to specify the electrodynamic properties of the high latitude ionosphere. The temporal and spatial resolution needed to predict the electric fields, conductivities, and currents in the ionosphere is driving the need for further advances. These parameters are intricately tied to auroral phenomena—energy deposition due to Joule heating and precipitating particles, motions of the auroral boundary, and ion outflow. A new view of these auroral processes is emerging that focuses on small-scale structures in the magnetosphere and their ionospheric effects, which may include the rapid variations in current associated with geomagnetically induced currents and the resulting perturbations to geoelectric fields on Earth’s surface. Improvements in model development have paralleled the advancements in understanding, yielding coupled models that better replicate the spatial and temporal scales needed to simulate the interconnected domains. Many realizations of such multi-component systems are under development, each with its own limitations and advantages. Challenges remain in the ability of models to quantify uncertainties introduced by propagation of solar wind parameters, to account for numerical effects in model codes, and to handle the special conditions occurring during extreme events. The impacts to technical systems on the ground are highly sensitive to the local electric properties of Earth’s surface, as well as to the specific technology at risk. Current research is focused on understanding the characteristics of geomagnetic disturbances that are important for geomagnetically induced currents, the development of earth conductivity models, the calculation of geoelectric fields, and the modeling of induced currents in the different affected systems. Assessing and mitigating the risks to technical systems requires quantitative knowledge of the range of values to be expected under all possible geomagnetic and technical conditions. Considering the progress that has been made in studying the chain of events leading to hazardous geomagnetic disturbances, the path forward will require concerted efforts to reveal missing physics, improve modeling capabilities, and deploy new observational assets. New understanding should be targeted to accurately quantify solar wind driving, magnetosphere-ionosphere-thermosphere coupling, and the impacts on specific technologies. The research, modeling, and observations highlighted here provide a framework for constructing a plan by which the international science community can comprehensively address the growing threat to human technologies caused by geomagnetic disturbances.

Tomographic imaging of South Rewa basin, Central India: Implications of Gondwana rifting and Late Cretaceous volcanism

We have imaged thick (3.0–5.0 km) sub-trappean Gondwana sediments deposited in a typical rift-environment of the south Rewa basin in Central India masked by the Deccan basalts. The basalts intrude through the basin forming several dykes, sills, and other intrusions along with large-scale undulations of the basement showing complex geology and tectonic settings due to Late Cretaceous volcanism (∼65 Ma). To delineate complex subsurface geological structures and understand the tectonic settings, we use long-offset seismic reflection data along the N-S trending 127 km Kuvari-Shahdol profile of the basin. The conventional stack and pre-stack time migration techniques fail to image the complex subsurface structures dominated by steeply dipping faults. The steeply dipping faults with small-scale structures are influenced by strong lateral and vertical velocity variations that cause problems in imaging the basin. Hence, a robust tomographic inversion with pre-stack depth migration technique is adopted to image fine-scale subtle subsurface geological structures with smooth velocity variations. The tomographic velocity model and pre-stack depth migration seismic image could decipher basaltic trap thickness, numerous dyke intrusions, alternate horsts and grabens with deposition of thick hydrocarbon-bearing sub-trappean Gondwana rocks along with the basement configuration. The deep basinal faults with highly distorted basement structures represent the intense tectonic activity of this Gondwana rift-basin. The deep-seated hydrocarbon reservoir is discovered with an excellent trapping mechanism forming both pre-rift and syn-rift settings of the rift-basin. The seismic image is further constrained and corroborated by the inversion of residual Bouguer gravity anomaly data to obtain corresponding density model derived from tomographic velocity model. The large basement faults, horsts and grabens, several intrusives like dyke, sill, laccolith, and thick sub-trappean Gondwana formations with Deccan trap cover indicate complex geology and tectonic settings of south Rewa basin forming the Late Cretaceous Volcanic Province of India.