Results for “Variational approach” — Page 11

DOE OSTI2025

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗

DOE OSTI2024

Efficient mapping between void shapes and stress fields using Deep Convolutional Neural Networks with sparse data

Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of advanced materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximize performance. In such scenarios, surrogate models are employed to make the forward mapping computationally efficient to evaluate. However, the high dimensionality of the input microstructure and the output field of interest often renders such surrogate models inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have shown great promise in handling such high-dimensional problems. In this paper, a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic, high-dimensional and expensive-to-query, FEM model. We consider two deep CNN architectures, a modified convolutional autoencoder framework with a fully connected bottleneck and a UNet CNN, and compare their accuracy in predicting the von Mises stress field for any given input void shape in the FEM model. Additionally, a sensitivity analysis study is performed using the two approaches, where the variation in the prediction accuracy on unseen test data is studied through numerical experiments by varying the number of training samples from 20 to 100.

surrogate modeling; convolutional neural networks;↗

DOE OSTI2024

High-precision Galaxy Clustering Predictions from Small-volume Hydrodynamical Simulations via Control Variates

Abstract Cosmological simulations of galaxy formation are an invaluable tool for understanding galaxy formation and its impact on cosmological parameter inference from large-scale structures. However, their high computational cost is a significant obstacle for running simulations that probe cosmological volumes comparable to those analyzed by contemporary large-scale structure experiments. In this work, we explore the possibility of obtaining high-precision galaxy clustering predictions from small-volume hydrodynamical simulations such as MillenniumTNG and FLAMINGO via control variates. In this approach, the hydrodynamical full-physics simulation is paired with a matched low-resolution gravity-only simulation. By learning the galaxy–halo connection from the hydrodynamical simulation and applying it to the gravity-only counterpart, one obtains a galaxy population that closely mimics the one in the more expensive simulation. One can then construct an estimator of galaxy clustering that combines the clustering amplitudes in the small-volume hydrodynamical and gravity-only simulations with clustering amplitudes in a large-volume gravity-only simulation. Depending on the galaxy sample, clustering statistic, and scale, this galaxy clustering estimator can have an effective volume of up to around 100 times the volume of the original hydrodynamical simulation in the nonlinear regime. With this approach, we can construct galaxy clustering predictions from existing simulations that are precise enough for mock analyses of next-generation large-scale structure surveys such as the Dark Energy Spectroscopic Instrument and the Legacy Survey of Space and Time.

Doytcheva, Alexandra (ORCID:0009000111254888)↗

NASA NTRS1972

Monte Carlo Simulation of Nonlinear Radiation Induced Plasmas

A Monte Carlo simulation model for radiation induced plasmas with nonlinear properties due to recombination was, employing a piecewise linearized predict-correct iterative technique. Several important variance reduction techniques were developed and incorporated into the model, including an antithetic variates technique. This approach is especially efficient for plasma systems with inhomogeneous media, multidimensions, and irregular boundaries. The Monte Carlo code developed has been applied to the determination of the electron energy distribution function and related parameters for a noble gas plasma created by alpha-particle irradiation. The characteristics of the radiation induced plasma involved are given.

Wang, B. S.↗

NASA NTRS1974

The outgassing and pressures in a spacecraft

The parameters that affect the internal pressure, i.e., the effective flow conductances of the internal volumes, their time constants and outgassing sources are examined. The objectives are to estimate the internal pressure of the spacecraft during the first several days after launch and to evaluate the responses of the volume to external pressure variations. The general approach followed is to (1) establish the various flow paths from a compartment to the low pressure regions; (2) calculate the conductances and combined effective conductances for these paths; (3) estimate the material outgassing rates in each volume from a general knowledge of materials used in the spacecraft; and (4) establish the pressure vs time in these compartments. The results of these techniques have been compared with experimental results obtained during thermal vacuum test of the spacecraft.

Scialdone, J. J.↗

NASA NTRS1976

Structural dynamics, stability, and control of helicopters

The dynamic synthesis of a helicopter is reported. The method of approach is a variation of the component mode synthesis in the sense that it regards the aircraft as an assemblage of interconnected substructures. The equations of motion are derived in general form by means of the Lagrangian formulation in conjunction with an orderly kinematical procedure that takes into account the superposition of motion of various substructures, thus circumventing constraint problems.

Meirovitch, L.↗

NASA NTRS1987

Development of upwind schemes for the Euler equations

Described are many algorithmic and computational aspects of upwind schemes and their second-order accurate formulations based on Total-Variation-Diminishing (TVD) approaches. An operational unification of the underlying first-order scheme is first presented encompassing Godunov's, Roe's, Osher's, and Split-Flux methods. For higher order versions, the preprocessing and postprocessing approaches to constructing TVD discretizations are considered. TVD formulations can be used to construct relaxation methods for unfactored implicit upwind schemes, which in turn can be exploited to construct space-marching procedures for even the unsteady Euler equations. A major part of the report describes time- and space-marching procedures for solving the Euler equations in 2-D, 3-D, Cartesian, and curvilinear coordinates. Along with many illustrative examples, several results of efficient computations on 3-D supersonic flows with subsonic pockets are presented.

Chakravarthy, Sukumar R.↗

NASA NTRS2002

Study of Fluid Flow Control In Protein Crystallization Using Strong Magnetic Fields

An important component in biotechnology, particularly in the area of protein engineering and rational drug design is the knowledge of the precise three-dimensional molecular structure of proteins. The quality of structural information obtained from X-ray diffraction methods is directly dependent on the degree of perfection of the protein crystals. As a consequence, the growth of high quality macromolecular crystals for diffraction analyses has been the central focus for biochemists, biologists, and bioengineers. Macromolecular crystals are obtained from solutions that contain the crystallizing species in equilibrium with higher aggregates, ions, precipitants, other possible phases of the protein, foreign particles, the walls of the container, and a likely host of other impurities. By changing transport modes in general, i.e., reduction of convection and sedimentation, as is achieved in 'microgravity', researchers have been able to dramatically affect the movement and distribution of macromolecules in the fluid, and thus their transport, formation of crystal nuclei, and adsorption to the crystal surface. While a limited number of high quality crystals from space flights have been obtained, as the recent National Research Council (NRC) review of the NASA microgravity crystallization program pointed out, the scientific approach and research in crystallization of proteins has been mainly empirical yielding inconclusive results. We postulate that we can reduce convection in ground-based experiments and we can understand the different aspects of convection control through the use of strong magnetic fields and field gradients. Whether this limited convection in a magnetic field will provide the environment for the growth of high quality crystals is still a matter of conjecture that our research will address. The approach exploits the variation of fluid magnetic susceptibility with concentration for this purpose and the convective damping is realized by appropriately positioning the crystal growth cell so that the magnetic susceptibility force counteracts terrestrial gravity. The general objective is to test the hypothesis of convective control using a strong magnetic field and magnetic field gradient and to understand the nature of the various forces that come into play. Specifically we aim to delineate causative factors and to quantify them through experiments, analysis and numerical modeling. Once the basic understanding is obtained, the study will focus on testing the hypothesis on proteins of pyruvate dehydrogenase complex (PDC), proteins E1 and E3. Obtaining high crystal quality of these proteins is of great importance to structural biologists since their structures need to be determined.

Ramachandran, N.↗

NASA NTRS2002

Study of Fluid Flow Control in Protein Crystallization using Strong Magnetic Fields

An important component in biotechnology, particularly in the area of protein engineering and rational drug design is the knowledge of the precise three-dimensional molecular structure of proteins. The quality of structural information obtained from X-ray diffraction methods is directly dependent on the degree of perfection of the protein crystals. As a consequence, the growth of high quality macromolecular crystals for diffraction analyses has been the central focus for biochemists, biologists, and bioengineers. Macromolecular crystals are obtained from solutions that contain the crystallizing species in equilibrium with higher aggregates, ions, precipitants, other possible phases of the protein, foreign particles, the walls of the container, and a likely host of other impurities. By changing transport modes in general, i.e., reduction of convection and sedimentation, as is achieved in "microgravity", researchers have been able to dramatically affect the movement and distribution of macromolecules in the fluid, and thus their transport, formation of crystal nuclei, and adsorption to the crystal surface. While a limited number of high quality crystals from space flights have been obtained, as the recent National Research Council (NRC) review of the NASA microgravity crystallization program pointed out, the scientific approach and research in crystallization of proteins has been mainly empirical yielding inconclusive results. We postulate that we can reduce convection in ground-based experiments and we can understand the different aspects of convection control through the use of strong magnetic fields and field gradients. Whether this limited convection in a magnetic field will provide the environment for the growth of high quality crystals is still a matter of conjecture that our research will address. The approach exploits the variation of fluid magnetic susceptibility with concentration for this purpose and the convective damping is realized by appropriately positioning the crystal growth cell so that the magnetic susceptibility force counteracts terrestrial gravity. The general objective is to test the hypothesis of convective control using a strong magnetic field and magnetic field gradient and to understand the nature of the various forces that come into play. Specifically we aim to delineate causative factors and to quantify them through experiments, analysis and numerical modeling. Once the basic understanding is obtained, the study will focus on testing the hypothesis on proteins of pyruvate dehydrogenase complex (PDC), proteins E1 and E3. Obtaining high crystal quality of these proteins is of great importance to structural biologists since their structures need to be determined. Specific goals for the investigation are: 1. To develop an understanding of convection control in diamagnetic fluids with concentration gradients through experimentation and numerical modeling. Specifically solutal buoyancy driven convection due to crystal growth will be considered. 2. To develop predictive measures for successful crystallization in a magnetic field using analyses and numerical modeling for use in future protein crystal growth experiments. This will establish criteria that can be used to estimate the efficacy of magnetic field flow damping on crystallization of candidate proteins. 3. To demonstrate the understanding of convection damping by high magnetic fields to a class of proteins that is of interest and whose structure is as yet not determined. 4. To compare quantitatively, the quality of the grown crystals with and without a magnetic field. X-ray diffraction techniques will be used for the comparative studies. In a preliminary set of experiments, we studied crystal dissolution effects in a 5 Tesla magnet available at NASA Marshall Space Flight Center (MSFC). Using a Schlieren setup, a 1mm crystal of Alum (Aluminum-Potassium Sulfate) was introduced in a 75% saturated solution and the resulting dissolution plume was observed. The experiment was conducted both in the presence and absence of a magnetic field gradient. The magnet produces a gradient field of approx. 1 Tesla2/cm. Image analysis of the recorded images indicated an enhanced plume velocity that was of the order of the measurement limit. For this experiment, both the gradient and gravity fields are in the same direction resulting in an enhanced effective gravity that tends to accelerate the observed plume velocity. While the results are not conclusive, pending further tests, it clearly points out the inadequacy of the MSFC magnet for conducting protein crystallization experiments and the need for a stronger magnet. In spacebased experiments, however, where the gravitational effects are small, only a weak magnetic field will be required to control or mitigate the effects of convective contamination.

Ramachandran, Narayanan↗

NASA NTRS2002

Thermal Imaging of Convecting Opaque Fluids using Ultrasound

An ultrasound technique has been developed to non-intrusively image temperature fields in small-scale systems of opaque fluids undergoing convection. Fluids such as molten metals, semiconductors, and polymers are central to many industrial processes, and are often found in situations where natural convection occurs, or where thermal gradients are otherwise important. However, typical thermal and velocimetric diagnostic techniques rely upon transparency of the fluid and container, or require the addition of seed particles, or require mounting probes inside the fluid, all of which either fail altogether in opaque fluids, or necessitate significant invasion of the flow and/or modification of the walls of the container to allow access to the fluid. The idea behind our work is to use the temperature dependence of sound velocity, and the ease of propagation of ultrasound through fluids and solids, to probe the thermal fields of convecting opaque fluids non-intrusively and without the use of seed particles. The technique involves the timing of the return echoes from ultrasound pulses, a variation on an approach used previously in large-scale systems.

Xu, Hongzhou↗

NASA NTRS2002

Countering Solutal Buoyant Convection with High Magnetic Fields

An important component in biotechnology, particularly in the area of protein engineering and rational drug design is the knowledge of the precise three-dimensional molecular structure of proteins. The quality of structural information obtained from X-ray diffraction methods is directly dependent on the degree of perfection of the protein crystals. As a consequence, the growth of high quality macromolecular crystals for diffraction analyses has been the central focus for biochemist, biologists, and bioengineers. Macromolecular crystals are obtained from solutions that contain the crystallizing species in equilibrium with higher aggregates, ions, precipitant, other possible phases of the protein, foreign particles, the walls of the container, and a likely host of other impurities. By changing transport modes in general, i.e., reduction of convection and sedimentation, as is achieved in microgravity, we have been able to dramatically effect the movement and distribution of macromolecules in the fluid, and thus their transport, formation of crystal nuclei, and adsorption to the crystal surface. While a limited number of high quality crystals from space flights have been obtained, as the recent National Research Council (NRC) review of the NASA microgravity crystallization program pointed out, the scientific approach and research in crystallization of proteins has been mainly empirical yielding inconclusive results. We postulate that we can reduce convection in ground-based experiments and we can understand the different aspects of convection control through the use of strong magnetic fields and field gradients. We postulate that limited convection in a magnetic field will provide the environment for the growth of high quality crystals. The approach exploits the variation of fluid magnetic susceptibility with concentration for this purpose and the convective damping is realized by appropriately positioning the crystal growth cell so that the magnetic susceptibility force counteracts terrestrial gravity. The general objective is to test the hypothesis of convective control using a strong magnetic field and magnetic field gradient and to understand the nature of the various forces that come into play. Specifically we aim to delineate causative factors and to quantify them through experiments, analysis and numerical modeling. The paper will report on the current status of the investigation and discuss results from the experimental and modeling efforts.

Ramachandran, N.↗

NASA NTRS2003

Using Strong Magnetic Fields to Control Solutal Convection

An important component in biotechnology, particularly in the area of protein engineering and rational drug design is the knowledge of the precise three-dimensional molecular structure of proteins. The quality of structural information obtained from X-ray diffraction methods is directly dependent on the degree of perfection of the protein crystals. As a consequence, the growth of high quality macromolecular crystals for diffraction analyses has been the central focus for biochemists, biologists, and bioengineers. Macromolecular crystals are obtained from solutions that contain the crystallizing species in equilibrium with higher aggregates, ions, precipitants, other possible phases of the protein, foreign particles, the walls of the container, and a likely host of other impurities. By changing transport modes in general, i.e., reduction of convection and sedimentation, as is achieved in microgravity , we have been able to dramatically affect the movement and distribution of macromolecules in the fluid, and thus their transport, formation of crystal nuclei, and adsorption to the crystal surface. While a limited number of high quality crystals from space flights have been obtained, as the recent National Research Council (NRC) review of the NASA microgravity crystallization program pointed out, the scientific approach and research in crystallization of proteins has been mainly empirical yielding inconclusive results. We postulate that we can reduce convection in ground-based experiments and we can understand the different aspects of convection control through the use of strong magnetic fields and field gradients. We postulate that limited convection in a magnetic field will provide the environment for the growth of high quality crystals. The approach exploits the variation of fluid magnetic susceptibility with concentration for this purpose and the convective damping is realized by appropriately positioning the crystal growth cell so that the magnetic susceptibility force counteracts terrestrial gravity. The general objective is to test the hypothesis of convective control using a strong magnetic field and magnetic field gradient and to understand the nature of the various forces that come into play. Specifically we aim to delineate causative factors and to quantify them through experiments, analysis and numerical modeling. The paper will report on the experimental results using paramagnetic salts and solutions in magnetic fields and compare them to analytical predictions.

Ramachandran, N.↗

NASA NTRS2004

Measured Fluid Flow in an Active H2O-CO2 Geothermal Well as an Analog to Fluid Flow in Fractures on Mars: Preliminary Report

Water in the Earth's crust generally contains dissolved gases such as CO2. Models for both 'Blue Mars' (H2O-driven processes) and 'White Mars' (CO2-driven processes) predict liquid H2O with dissolved CO2 at depth. The fate of dissolved CO2 as this mixture rises toward the surface has not been quantitatively explored. Our approach is a variation on NASA's 'Follow the Water' as we 'Follow the Fluid' from depth to the surface in hydrothermal areas on Earth and extrapolate our results to Mars. This is a preliminary report on a field study of fluid flow in a producing geothermal well. For proprietary reasons, the name and location of this well cannot be revealed, so we have named it 'Earth1' for this study.

Kieffer, Susan W.↗

NASA NTRS2004

Magnetic Control of Convection during Protein Crystallization

An important component in biotechnology, particularly in the area of protein engineering and rational drug design is the knowledge of the precise three-dimensional molecular structure of proteins. The quality of structural information obtained from X-ray diffraction methods is directly dependent on the degree of perfection of the protein crystals. As a consequence, the growth of high quality macromolecular Crystals for diffraction analyses has been the central focus for bio-chemists, biologists, and bioengineers. Macromolecular crystals are obtained from solutions that contain the crystallizing species in equilibrium with higher aggregates, ions, precipitants, other possible phases of the protein, foreign particles, the walls of container, and a likely host of other impurities. By changing transport modes in general, i.e., reduction of convection and Sedimentation as is achieved in "microgravity", we have been able to dramatically affect the movement and distribution of macromolecules in the fluid, and thus their transport, f o d o n of crystal nuclei, and adsorption to the crystal surface. While a limited number of high quality crystals from space flights have been obtained, as the recent National Research Council (NRC) review of the NASA microgravity crystallization program pointed out, the scientific approach and research in crystallization of proteins has been mainly empirical yielding inconclusive results. We postulate that we can reduce convection in ground-based experiments and we can understand the different aspects of convection control through the use of strong magnetic fields and field gradients. We postulate that limited convection in a magnetic field will provide the environment for the growth of high quality crystals. The approach exploits the variation of fluid magnetic susceptibility with counteracts on for this purpose and the convective damping is realized by appropriately positioning the crystal growth cell so that the magnetic susceptibility force counteract terrestrial gravity. The genera1 objective is to test the hypothesis of convective control using a strong magnetic field and magnetic field gradient and to understand the nature of the various forces that come into play. Specifically we aim to delineate causative factors and to quantify them through experiments, analysis and numerical modeling. The paper will report on the experimental results using paramagentic salts and solutions in magnetic fields and compare them to analyticalpr~ctions.

Ramachandran, N.↗

NASA NTRS2005

Palmer Quest: A Feasible Nuclear Fission "Vision Mission" to the Mars Polar Caps

We are engaged in a NASA Vision Mission study, called Palmer Quest after the American Antarctic explorer Nathaniel Palmer, to assess the presence of life and evaluate the habitability of the basal domain of the Mars polar caps. We address this goal through four objectives: 1. Determine the presence of amino acids, nutrients, and geochemical heterogeneity in the ice sheet. 2. Quantify and characterize the provenance of the amino acids in Mars ice. 3. Assess the stratification of outcropped units for indications of habitable zones. 4. Determine the accumulation of ice, mineralogic material, and amino acids in Mars ice caps over the present epoch. Because of the defined scientific goal for the vision mission, the Palmer Quest focus is astrobiological; however, the results of the study make us optimistic that aggressive multi-platform in-situ missions that address a wide range of objectives, such as climate change, can be supported by variations of the approach used on this mission. Mission Overview: The Palmer Quest baseline

Carsey, F. D.↗

NASA NTRS2014

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗

NASA NTRS2015

Orbit Stability of OSIRIS-REx in the Vicinity of Bennu Using a High-Fidelity Solar Radiation Model

Solar radiation pressure is one of the largest perturbing forces on the OSIRISRex trajectory as it orbits the asteroid Bennu. In this work, we investigate how forces due to solar radiation perturb the OSIRIS-REx trajectory in a high-fidelity model. The model accounts for Bennu's non-spherical gravity field, third-body gravity forces from the Sun and Jupiter, as well as solar radiation forces acting on a simplified spacecraft model. Such high-fidelity simulations indicate significant solar radiation pressure perturbations from the nominal orbit. Modifications to the initial design of the nominal orbit are found using a variation of parameters approach that reduce the perturbation in eccentricity by a factor of one-half.

Williams, Trevor W.↗

NASA NTRS2018

Insight and Evidence Motivating the Simplification of Dual-Analysis Hybrid Systems into Single-Analysis Hybrid Systems

Many hybrid data assimilation systems currently used for NWP employ some form of dual-analysis system approach. Typically a hybrid variational analysis is responsible for creating initial conditions for high-resolution forecasts, and an ensemble analysis system is responsible for creating sample perturbations used to form the flow-dependent part of the background error covariance required in the hybrid analysis component. In many of these, the two analysis components employ different methodologies, e.g., variational and ensemble Kalman filter. In such cases, it is not uncommon to have observations treated rather differently between the two analyses components; recentering of the ensemble analysis around the hybrid analysis is used to compensated for such differences. Furthermore, in many cases, the hybrid variational high-resolution system implements some type of four-dimensional approach, whereas the underlying ensemble system relies on a three-dimensional approach, which again introduces discrepancies in the overall system. Connected to these is the expectation that one can reliably estimate observation impact on forecasts issued from hybrid analyses by using an ensemble approach based on the underlying ensemble strategy of dual-analysis systems. Just the realization that the ensemble analysis makes substantially different use of observations as compared to their hybrid counterpart should serve as enough evidence of the implausibility of such expectation. This presentation assembles numerous anecdotal evidence to illustrate the fact that hybrid dual-analysis systems must, at the very minimum, strive for consistent use of the observations in both analysis sub-components. Simpler than that, this work suggests that hybrid systems can reliably be constructed without the need to employ a dual-analysis approach. In practice, the idea of relying on a single analysis system is appealing from a cost-maintenance perspective. More generally, single-analysis systems avoid contradictions such as having to choose one sub-component to generate performance diagnostics to another, possibly not fully consistent, component.

Todling, Ricardo↗