Search NASA⌕ Search

SEARCH · Search NASA

Results for “AE”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

Nonlinear dynamics and transport driven by energetic particle instabilities using a gyro-Landau closure model *

Abstract Energetic particle (EP) destabilized Alfvén eigenmode (AE) instabilities are simulated for a DIII-D experimental case with a pulsed neutral beam using a gyro-Landau moments model which introduces EP phase-mixing effects through closure relations. This provides a computationally efficient reduced model which is applied here in the nonlinear regime over timescales that would be difficult to address with more complete models. The long timescale nonlinear evolution and related collective transport losses are examined including the effects of zonal flow/current generation, nonlinear energy cascades, and EP profile flattening. The model predicts frequencies and mode structures that are consistent with experimental observations. These calculations address issues that have not been considered in previous modelling: the EP critical gradient profile evolution in the presence of zonal flows/currents, and the dynamical nature of the saturated state. A strong level of intermittency is present in the predicted instability-driven transport; this is connected to the zonal flow growth and decay cycles and nonlinear energy transfers. Simulation of intermittent AE-enhanced EP transport will be an important issue for the protection of plasma facing components in the next generation of fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Overview of the TJ-II stellarator research programme towards model validation in fusion plasmas

TJ-II stellarator results on modelling and validation of plasma flow asymmetries due to on-surface potential variations, plasma fuelling physics, Alfvén eigenmodes (AEs) control and stability, the interplay between turbulence and neoclassical (NC) mechanisms and liquid metals are reported. Regarding the validation of the neoclassically predicted potential asymmetries, its impact on the radial electric field along the flux surface has been successfully validated against Doppler reflectometry measurements. Research on the physics and modelling of plasma core fuelling with pellets and tracer encapsulated solid pellet injection has shown that, although post-injection particle radial redistributions can be understood qualitatively from NC mechanisms, turbulence and fluctuations are strongly affected during the ablation process. Advanced analysis tools based on transfer entropy have shown that radial electric fields do not only affect the radial turbulence correlation length but are also capable of reducing the propagation of turbulence from the edge into the scrape-off layer. Direct experimental observation of long range correlated structures show that zonal flow structures are ubiquitous in the whole plasma cross-section in the TJ-II stellarator. Alfvénic activity control strategies using ECRH and ECCD as well as the relation between zonal structures and AEs are reported. Finally, the behaviour of liquid metals exposed to hot and cold plasmas in a capillary porous system container was investigated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Experiments on excitation of Alfvén eigenmodes by alpha-particles with bump-on-tail distribution in JET DTE2 plasmas

Dedicated experiments were performed in JET DTE2 plasmas for obtaining an α-particle bump-on-tail (BOT) distribution aiming at exciting Alfvén eigenmodes (AEs). Neutral beam injection-only heating with modulated power was used so that fusion-born α-particles were the only ions present in the MeV energy range in these DT plasmas. The beam power modulation on a time scale shorter than the α-particle slowing down time was chosen for modulating the α-particle source and thus sustaining a BOT in the α-particle distribution. High-frequency modes in the toroidicity-induced Alfven eigenmode (TAE) frequency range and multiple short-lived modes in a wider frequency range have been detected in these DT discharges with interferometry, soft x-ray cameras, and reflectometry. The modes observed were localised close to the magnetic axis and were not seen in the Mirnov coils. Analysis with the TRANSP and Fokker-Planck FIDIT codes confirms that α-particle distributions with BOT in energy were achieved during some time intervals in these discharges though no clear correlation was found between the times of the high-frequency mode excitation and the BOT time intervals. The combined magneto-hydrodynamic (MHD) and kinetic modelling studies show that the high-frequency mode in the TAE frequency range is best fitted with a TAE of toroidal mode number n= 9. This mode is driven mostly by the on-axis beam ions while the smaller drive due to the pressure gradient of α-particles allows overcoming the marginal stability and exciting the mode. The observed multiple short-lived modes in a wider frequency range are identified as the on-axis kinetic AEs predicted in Rosenbluth and Rutherford.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On FIRE mode in KSTAR

We report on the status of Fast Ion Regulated Enhancement (FIRE) mode experiments in the Korea Superconducting Tokamak Advanced Research. This regime is being developed for high-performance, steady-state operation which features a stationary ion internal transport barrier, enabling a central ion temperature approaching 10 keV to be sustained for up to 50 s, without the need for delicate profile control and with no significant impurity accumulation. As its key novelty lies in the significant contribution of fast ions that stabilize core turbulence, the regime has been named FIRE mode. To achieve this regime, neutral beam injection is applied at moderate power levels near the L–H power threshold, while maintaining low plasma density to avoid the L–H transition. The scenario is typically established in diverted magnetic configurations. The core features of FIRE mode were investigated through power balance analysis and fluctuation measurements, revealing a clear transport bifurcation in the ion channel. At the plasma edge, FIRE mode occasionally exhibits I-mode characteristics, particularly in unfavorable magnetic null configurations with q 95 ∼ 4, including the presence of weakly coherent modes. In terms of MHD activity, sawtooth oscillations are observed but appear to be stabilized during the high-performance phase. Fast ion-driven Alfvénic eigenmodes (AEs), indicated by strong frequency chirping near 200 kHz, are also observed. Additionally, lower-frequency MHD activities, distinct from the fast ion-driven AEs, are present and have some influence on plasma performance. The enhancement of core confinement is primarily attributed to fast ion effects, which were evaluated with respect to dilution, alpha stabilization, and resonant interactions with turbulence using gyrokinetic analyses. Among these, the dilution effect was found to be the most dominant. The characteristics of FIRE mode were compared with those of other hot ion plasma scenarios, such as supershot and hot ion mode. While they share many similarities, FIRE mode is distinguished by the accessibility to conditions with T i ≈ T e , presence of I-mode edge features, and its long-duration sustainment. Predictive simulations of FIRE mode were performed using integrated transport modeling with TRIASSIC, employing the TGLF anomalous transport model. These simulations confirmed the critical role of fast ions in achieving this regime. The future prospect of FIRE mode for application in fusion reactors is discussed, with an emphasis on possibly extending the regime to higher density operation.

FIRE mode↗

Wasserstein normalized autoencoder for anomaly detection

A novel anomaly detection algorithm is presented. The Wasserstein normalized autoencoder (WNAE) is a normalized probabilistic model that minimizes the Wasserstein distance between the learned probability distribution—a Boltzmann distribution where the energy is the reconstruction error of the autoencoder (AE)—and the distribution of the training data. This algorithm has been developed and applied to the identification of semivisible jets—conical sprays of visible standard model (SM) particles and invisible dark matter states—with the CMS experiment at the CERN LHC. Trained on jets of particles from simulated SM processes, the WNAE is shown to learn the probability distribution of the input data in a fully unsupervised fashion, such that it effectively identifies new physics jets as anomalies. The model exhibits stable, convergent training and recovers strong classification performance for a wide range of signals against the selected background process, for which a standard AE fails because of outlier reconstruction. In addition, the model improves upon standard normalized autoencoders while remaining fully agnostic to the signal. The WNAE directly tackles the problem of outlier reconstruction, a common failure mode of autoencoders in anomaly detection tasks.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗

Prevalence of gp160 polymorphisms known to be related to decreased susceptibility to temsavir in different subtypes of HIV-1 in the Los Alamos National Laboratory HIV Sequence Database

Fostemsavir, a prodrug of the gp120-directed attachment inhibitor temsavir, is indicated for use in heavily treatment-experienced individuals with MDR HIV-1. Reduced susceptibility to temsavir in the clinic maps to discrete changes at amino acid positions in gp160: S375, M426, M434 and M475.To query the Los Alamos National Laboratory (LANL) HIV Sequence Database for the prevalence of polymorphisms at gp160 positions of interest. Full-length gp160 sequences (N = 7560) were queried for amino acid polymorphisms relative to the subtype B consensus at positions of interest; frequencies were reported for all sequences and among subtypes/circulating recombinant forms (CRFs) with ≥10 isolates in the database. Among 239 subtypes in the database, the 5 most prevalent were B (n = 2651, 35.1%), C (n = 1626, 21.5%), CRF01_AE (n = 674, 8.9%), A1 (n = 273, 3.6%) and CRF02_AG (n = 199, 2.6%). Among all 7560 sequences, the most prevalent amino acids at positions of interest (S 375 , 73.5%; M 426 , 82.1%; M 434 , 88.2%; M 475 , 89.9%) were the same as the subtype B consensus. Specific polymorphisms with the potential to decrease temsavir susceptibility (S 375 H/I/M/N/T/Y, M 426 L/P, M 434 I/K and M475I) were found in <10% of isolates of subtypes D, G, A6, BC, F1, CRF07_BC, CRF08_BC, 02A, CRF06_cpx, F2, 02G and 02B. S 375 H and M 475 I were predominant among CRF01_AE (S375H, 99.3%; M 475 I, 76.3%; consistent with previously reported low temsavir susceptibility of this CRF) and 01B (S 375 H, 71.7%; M 475 I, 49.5%). Analysis of the LANL HIV Sequence Database found a low prevalence of gp160 amino acid polymorphisms with the potential to reduce temsavir susceptibility overall and among most of the common subtypes.

59 BASIC BIOLOGICAL SCIENCES↗

Visualization of Fast Ion Phase-Space Flow Driven by Alfvén Instabilities

Fast ion phase-space flow, driven by Alfven eigenmodes (AEs), is measured by an imaging neutral particle analyzer in the DIII-D tokamak. The flow firstly appears near the minimum safety factor at the injection energy of neutral beams, and then moves radially inward and outward by gaining and losing energy, respectively. The flow trajectories in phase space align well with the intersection lines of the constant magnetic moment surfaces and constant E – (ω/n)P ζ surfaces, where E, P ζ are energy and toroidal canonical momentum of ions; ω and n are angular frequencies and toroidal mode numbers of AEs. It is found that the flow is so destructive that the thermalization of fast ions is no longer observed in regions of strong interaction. Here, the measured phase-space flow is consistent with nonlinear hybrid kinetic-magnetohydrodynamics simulation. Calculations of the relatively narrow phase-space islands reveal that fast ions must transition between different flow trajectories to experience large-scale phase-space transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗

Fast-ion-driven Alfvén eigenmodes during ICRF-heated high β p plasmas on EAST

Fast-ion-driven Alfvén eigenmodes (AEs) are observed during ICRF-heated high-β p plasmas on EAST. Multiple high frequency modes are observed for shot 112670 at f TAE1 ~ 145 kHz, δB/B ~ 4 × 10 –4 and f TAE2 ~ 175 kHz, δB/B ~ 1.2 × 10 –5 measured by high-frequency Mirnov coils, at B 0 ~ 2.45 T, I p ~ 350kA, n e ramp-up from 3.5 × 10 19 to 4 × 10 19 m −3 at P ECRH ~ 2 MW, PLHW ~ 2 MW, and P ICRH ~ 2.1 MW. Here, 37 MHz ICRF minority hydrogen heating scheme, located at plasma core, creates fast ion population which drives TAEs unstable from TORIC + SFFPQL. In the experiment, it is observed that the evolution of mode frequency depends on electron density, following the theoretical TAE frequency characteristic $f_{{{\text{th}}}} = V_{{\text{a}}} /(4\pi qR) \propto \sqrt {n_{{\text{e}}} }$. As the electron density increases, the amplitude of the AE mode progressively diminishes. Higher plasma density shortens the fast-ion slowing-down time, reduces the heating efficiency of minority hydrogen, weakens the high-energy tail, and consequently decreases the fast-ion beta. Based on the diagnostic results from the microwave reflectometer and electron cyclotron emission (ECE) diagnostics, the TAE is located within the plasma core, consistent with the narrower core region of the TAE gap observed in the continuous spectrum.

Pan, C. Y. [Chinese Academy of Sciences, Hefei (Ch↗

Laboratory colonization by Dirofilaria immitis alters the microbiome of female Aedes aegypti mosquitoes

Background: The ability of blood-feeding arthropods to successfully acquire and transmit pathogens of medical and veterinary importance has been shown to be interfered with, or enhanced by, the arthropod’s native microbiome. Mosquitoes transmit viruses, protozoan and filarial nematodes, the majority of which contribute to the 17% of infectious disease cases worldwide. Diroflaria immitis, a mosquito-transmitted filarial nematodes of dogs and cats, is vectored by several mosquito species including Aedes aegypti. Methods: In this study, we investigated the impact of D. immitis colonization on the microbiome of laboratory reared female Ae. aegypti. Metagenomic analysis of the V3–V4 variable region of the microbial 16S RNA gene was used for identification of the microbial differences down to species level. Results: We generated a total of 1068 OTUs representing 16 phyla, 181 genera and 271 bacterial species. Overall, in order of abundance, Proteobacteria, Bacteroidetes, Actinobacteria and Firmicutes were the most represented phylum with D. immitis-infected mosquitoes having more of Proteobacteria (71%) than uninfected mosquitoes (56.9%). An interesting finding in this study is the detection of Klebsiella oxytoca in relatively similar abundance in infected and uninfected mosquitoes, suggesting a possible endosymbiotic relationship, and has been previously shown to indirectly compete for nutrients with fungi on domestic housefly eggs and larvae. While D. immitis colonization has no effect on the overall species richness, we identified significant differences in the composition of selected bacterial genera and phyla between the two groups. We also reported distinct compositional and phylogenetic differences in the individual bacterial species when commonly identified bacteria were compared. Conclusions: To the best of our knowledge, this is the first study to understand the impact of a filarial infection on the microbiome of its mosquito vector. Further studies are required to identify bacteria species that could play an important role in the mosquito biology. While the microbiome composition of Ae. aegypti mosquito have been previously reported, our study shows that in an effort to establish itself, a filarial nematode modifies and alters the overall microbial diversity within its mosquito host.

54 ENVIRONMENTAL SCIENCES↗

Utah FORGE: Slide-Hold-Slide Experiments on Gneiss at Increased Temperature

Included are data from triaxial, single-inclined-fracture friction experiments. The experiments were performed with slide-hold-slide protocol on Utah FORGE gneiss at increased temperature. With a ~10 MPa normal stress, temperatures vary between experiments from room temperature up to 163 Celsius. Hold times vary during experiment from ~10^1 to ~10^5 seconds. Measured are the frictional response upon reactivation after a hold period, active acoustic data (P-wave velocity and amplitude) and passive acoustic data (acoustic emission occurrence and amplitude). There are two types of datafiles: (1) Datafiles containing the friction data, including the temperature and the active acoustic data measured during the experiment (AEXX_Gneiss_Vp_mixref4). The underscore _Vp means that it includes the Vp or P-wave velocity data, with _mixref meaning that we use a mixed reference point for calculating the P-wave velocity. And (2) the datafiles containing the passive acoustics data, a catalog of the acoustic emissions (AE's) measured during the experiment (AEcatalog_AEXX_runX), where AEXX matches the experiment number and runX denotes which part of the experiment the data was collected, matching the times where active acoustic data was collected. AE catalogs are split in two parts when the file size exceeds 1 GB to aid download/opening times.

15 GEOTHERMAL ENERGY↗

Full-Scale Hydrogen Mitigation Installation and Testing at Nevada Solar One

This project was performed under a Cooperative Research & Development Agreement (CRADA) between the National Renewable Energy Laboratory (NREL) and Acciona Energy USA (AE). The purpose was to advance an NREL TRL 3 technology that was developed during the previous CRADA from completed laboratory testing to full-scale process installation and testing at AE's Nevada Solar One (NSO) power plant. The project's objective was to complete full-scale implementation and performance verification of the NREL hydrogen mitigation technology at the Nevada Solar One (NSO) power plant in Boulder City, Nevada.

08 HYDROGEN↗

CRADA Number NFE-17-06866 with Active Energy Systems, Inc. (CRADA Final Report)

Cooperative Research and Development Agreement (CRADA) NFE-17-06866 between Oak Ridge National Laboratory (ORNL) and Active Energy Systems Inc. (AES) focused on studying and modeling a low cost, high efficiency energy storage technology. The successful development of low-cost, high-efficiency energy storage is a significant bottleneck in the implementation of intermittent renewable energy sources such as wind and solar. AES is a startup company developing a heat exchange technology to utilize a low-temperature phase change material (PCM). The work done under this CRADA explored this technology’s ability to augment a heat pump/heat engine device to convert electricity into thermal energy and vice versa, operating to complement the needs of the electric grid. Modeling, design and development of a prototype to prove the technology was successful, but current production economics and market demand make further exploration undesirable.

25 ENERGY STORAGE↗

Creation of Laboratory-scale Testbed for Autonomous Monitoring and Control of Subsurface Systems

This report describes the results of an LDRD project aiming to develop a laboratory-scale testbed for autonomous subsurface monitoring and control systems. Modifications were made to an existing polyaxial loading frame to incorporate electrical resistivity tomography (ERT) and acoustic emission (AE) monitoring systems. This allows engineered subsurface processes to be studied under realistic temperatures and stresses in a scaled-down laboratory environment with similar monitoring systems as are deployed in field-scale systems. The paper outlines some challenges that were faced in implementing the ERT system at the laboratory scale and the solutions that were devised. Results are shown from two demonstration tests—one focusing on the ERT system, and one focusing on the AE system.

42 ENGINEERING↗

Preserving Superconvergence of Spectral Elements for Curved Domains [Slides]

Finite Element Methods (FEM) and Spectral Element Methods (SEM) are crucial for solving partial differential equations (PDEs) on complex geometries. SEM offers superior accuracy due to potential superconvergence for simple domains. Challenges persist for domains with curved boundaries, restricting SEM’s advantages in real-world applications. A proposed solution is the introduction of a novel strategy to enhance accuracy and maintain superconvergence of SEM in curved domains. The strategy includes a mesh-generation procedure with geometrically refined elements near curved boundaries and a post-processing phase using the Adaptive Extended Stencil Finite Element Method (AES-FEM). The method, named AES-FEM post-processed Spectral Element Method (ApSEM), aligns the accuracy of non-tensor-product elements with superconvergent spectral elements.

97 MATHEMATICS AND COMPUTING↗

Energetic Particles - microturbulence interaction thrust (EP SIWG white paper)

This white paper outlines a strategic approach to Energetic Particle (EP) research, aimed at applying the results to the future burning devices such as ITER. Our goal is to deepen the understanding of the interplay between plasma background microturbulence and diverse species of energetic ions in burning plasma devices. This strategy is poised to advance our knowledge in this crucial area of fusion science, paving the way for significant breakthroughs in plasma physics and fusion energy research. We consider the confinement of energetic ions such as auxiliary heating beams, minority ions from ICRH, and fusion product alpha particles. Recent studies have underscored the potential of EP/microturbulence interaction to enhance fusion plasma performance by stabilizing microturbulence. However, it also poses risks, such as exacerbating Alfvénic eigenmode (AE) instabilities, which could compromise the sustainability of plasma discharge by causing EP losses. The interplay between EPs and background microturbulence is evident in the phenomenon of effective pitch angle scattering, a crucial aspect of the quasilinear (QL) theory. This theory is integral to developing numerically-efficient yet comprehensive and self-consistent approaches, recently employed to investigate the relaxation of energetic particle populations in the holistic modeling of fusion-grade plasmas. The primary objectives of this white paper thrust encompass a dual focus. First is that we need to delve into the mechanisms through which microturbulence engenders effective pitch angle scattering. This investigation will entail the examination of the presence of known or self-consistently predicted spectra of modes accountable for microturbulence. In these explorations, electrostatic microturbulence serves as a logical initial stride towards achieving the trust's objectives. This endeavor is anticipated to yield formulations expressing the parametric dependencies of the effective pitch angle scattering frequency on variables such as thermal plasma electron and/or ion temperatures, as well as their respective thermal conductivities. In our second objective, we aim to delve into the intricate formation of zonal flow (ZF) structures amidst the complex interplay of microturbulence and Alfvenic eigenmodes (AEs). This endeavor poses greater challenges as we seek to unravel the macroscopic manifestations influenced by microturbulence, termed as zonal structures (ZS), stemming from microturbulence-induced ZF. Drawing from this understanding, we anticipate employing a QL approach to yield comprehensive insights into the distribution function of energetic particles (EP) within phase space. This method entails resolving the dominant multidimensional phase space diffusion processes while effectively averaging over the rapid ballistic responses. Nevertheless, substantial strides remain imperative to realize a comprehensive whole-device modeling framework. This entails meticulous verification and validation exercises against experimental observations, as well as rigorous benchmarking against theoretical frameworks and numerical simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Advanced Oxygen-Free Electrolyzer for Ultra-Low-Cost H 2 Storage for Fossil Plants (Final Technical Report)

DOE’s Office of Fossil Energy and Carbon Management has determined that long-duration energy storage solutions co-located with fossil energy assets offer significant benefits to the fossil industry, electric utilities, and customers. T2M Global has developed an Advanced O 2 -Free Electrolyzer System (AES) Technology for low-cost, long-duration H 2 energy storage for fossil plants. The MW-class AES Module conceptual design aims to upgrade stranded assets (dilute/waste syngas streams, excess electricity, and waste heat) at fossil plants to higher value H 2 for additional revenue and greater sustainability. The H 2 energy storage equips fossil plants with the load following capability needed for the lucrative grid-support services market created by Variable Renewable Energy resources.

08 HYDROGEN↗

Quantification of the Crack Evolution Process by Extracting Relevant Signal Components from Wave Propagation and Diffusive Transport Front Measurements

Wave propagation and diffusive transport phenomena in a geological rock sample undergoing crack evolution process are expected to interact with the mechanical discontinuities in the medium. The measurements of the signals associated with these phenomena can be used to assess and monitor the crack-driven micromechanical alterations in the rock. Different wave/diffusion phenomena, such as sonic propagation, pressure diffusion, and acoustic emission (AE), are sensitive to different elements of the mechanical discontinuities generated during the evolution of the crack clusters from initiation to coalescence. Sonic propagation, AE, and pressure diffusion monitoring have the potential to map the crack evolution because the transmitter-receiver arrays can be designed, arranged and tuned to (1) achieve maximum recovery of the scattered waveforms and travel times, (2) capture the later arrivals and multiple reflections, and (3) illuminate large rock volume. However, the structural/topological complexities of the mechanical discontinuities, complex distribution of the stress fields, complex mechanical alterations in media, and fluid redistribution in the crack system pose serious challenges for the detection and modeling of the crack evolution process (from here on, we will use the term ‘crack evolution process’ to mean that the crack evolution occurred under shallow crustal conditions). For purposes of accurately accounting such complexities and heterogeneities in the absence of reliable physical laws, simulation methods, and signal processing techniques, my early-career research proposal will develop and apply novel data-driven machine learning methods to: (1) extract signal components relevant to the various phases of crack evolution and (2) generate a 2D visual map of the crack evolution process.

58 GEOSCIENCES↗