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At least 91 records · Page 5

Flux tube models of solar plages

The spectroscopic properties of model solar plages composed of narrow magnetic flux tubes embedded in undisturbed quiet sun are analyzed. The final models are magnetostatic flux tubes for which the level tau5000 = 1 level is 200 km below the same level in the quiet sun; these models are hotter than the quiet sun at all levels and expand by roughly a factor of three between this level and the quiet sun temperature minimum. These models are tested against a wide range of observational constraints. The assumed flux tube diameter is found to be an important parameter for predictions of the center-to-limb variation of the magnetically insensitive lines and of the visible continuum. A diameter of 300 km at tau5000 = 1 is necessary to give qualitative agreement with observations. A model plage consisting of the derived flux tube model embedded in a quiet sun model derived from the Ca II K line wings reproduces this line in plages at the observed value of mu; one of the models also predicts values of disk center plage contrast at 30, 50, 100, and 200 micron wavelength in good agreement with the observations of Jefferies et al. (1982).

Walton, Stephen R.

Effects of Precipitation on Ocean Mixed-Layer Temperature and Salinity as Simulated in a 2-D Coupled Ocean-Cloud Resolving Atmosphere Model

A two-dimensional coupled ocean-cloud resolving atmosphere model is used to investigate possible roles of convective scale ocean disturbances induced by atmospheric precipitation on ocean mixed-layer heat and salt budgets. The model couples a cloud resolving model with an embedded mixed layer-ocean circulation model. Five experiment are performed under imposed large-scale atmospheric forcing in terms of vertical velocity derived from the TOGA COARE observations during a selected seven-day period. The dominant variability of mixed-layer temperature and salinity are simulated by the coupled model with imposed large-scale forcing. The mixed-layer temperatures in the coupled experiments with 1-D and 2-D ocean models show similar variations when salinity effects are not included. When salinity effects are included, however, differences in the domain-mean mixed-layer salinity and temperature between coupled experiments with 1-D and 2-D ocean models could be as large as 0.3 PSU and 0.4 C respectively. Without fresh water effects, the nocturnal heat loss over ocean surface causes deep mixed layers and weak cooling rates so that the nocturnal mixed-layer temperatures tend to be horizontally-uniform. The fresh water flux, however, causes shallow mixed layers over convective areas while the nocturnal heat loss causes deep mixed layer over convection-free areas so that the mixed-layer temperatures have large horizontal fluctuations. Furthermore, fresh water flux exhibits larger spatial fluctuations than surface heat flux because heavy rainfall occurs over convective areas embedded in broad non-convective or clear areas, whereas diurnal signals over whole model areas yield high spatial correlation of surface heat flux. As a result, mixed-layer salinities contribute more to the density differences than do mixed-layer temperatures.

Li, Xiaofan

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

snow

Modeling low cycle fatigue (LCF) of additively manufactured Hastelloy X using An accelerated crystal plasticity fatigue damage model

This paper presents a microstructure-based model for low cycle fatigue (LCF) behavior and life of Nickel-based alloy Hastelloy X manufactured using laser-powder bed fusion (L-PBF) additive manufacturing (AM). AM Hastelloy X, a solution-strengthened alloy, is tested at elevated temperature under fully reversed LCF conditions at different strain levels. A generalized plane strain finite element model is generated from electron backscatter diffraction (EBSD) characterization. The constitutive behavior of the material under fatigue is modeled using crystal plasticity and calibrated with both monotonic tensile and cyclic stress–strain data. The fatigue micro-crack initiation and propagation in the microstructure is modeled using a modified Chaboche fatigue damage model. An embedded boundary condition with a homogenous medium is used to apply the cyclic deformation and prevent numerically introduced over-constraints during fatigue simulation. A ‘cycle-jump’ method is used to accelerate the fatigue simulation and reduce the computational cost. The simulation results are compared to LCF experiments, showing satisfactory matches in cyclic stress behavior and number of cycles to macro-crack initiation for all applied strain ranges. In addition, the model illustrates the potential for quantifying microscale fatigue life impacting factors such as microstructure and surface roughness, which is needed to accurately quantify the reliability of AM components in service.

36 MATERIALS SCIENCE

A conservative type-dependent full potential method for the treatment of supersonic flows with embedded subsonic regions

A nonlinear method based on the full potential equation in conservation form, cast in an arbitrary coordinate system, has been developed to treat predominantly supersonic flows with embedded subsonic regions. This type of flow field occurs frequently near the fuselage-canopy junction area and wing leading edge regions for a moderately swept fighter configuration. The method uses the theory of characteristics to accurately monitor the type-dependent flow field. A conservative switching scheme is developed to transition from the supersonic marching algorithm to a subsonic relaxation procedure, and vice versa. An implicit approximate factorization scheme is employed to solve the finite-differenced equation. Results are shown for a few configurations, including a wing-body-wake realistic fighter model having embedded subsonic regions.

Shankar, V.

Assessment of uranium nitride interatomic potentials

Uranium mononitride (UN) is a promising nuclear fuel due to its high fissile density, high thermal conductivity, and suitability for reprocessing. In this study, two uranium nitride interatomic potentials are assessed: Tseplyaev and Starikov's angular-dependent potential and Kocevski et al.'s embedded atom model potential. Predictions of the thermophysical and elastic properties of UN, UN 2 , and α- and β-U 2 N 3 computed using both potentials are assessed and compared to available experimental data. Notably, the Tseplyaev potential performs better with the energetic aspects of UN, e.g., specific heat capacity and point defect formation energies, whereas the Kocevski potential performs better with the structural aspects of UN, e.g., thermal expansion as well as with the elastic properties. The reasons why the Kocevski potential underestimates the UN specific heat are explained by examining the UN phonon properties modeled using both potentials. The Kocevski potential shows better identification of the mechanical stability ranges of UN, UN 2 , and α- and β-U 2 N 3 , reasonably predicting the melting point of UN and predicting stable structures for UN 2 and α- and β-U 2 N 3 . On the other hand, the Tseplyaev potential predicts a premature phase change of both UN and UN 2 and cannot stabilize α- nor β-U 2 N 3 . However, the Kocevski potential cannot predict a stable α-U phase and is thus not suitable for the calculation of formation energies for non-stoichiometric point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Water tunnel flow visualization using a laser

Laser systems for flow visualization in water tunnels (similar to the vapor screen technique used in wind tunnels) can provide two-dimensional cross-sectional views of complex flow fields. This parametric study documents the practical application of the laser-enhanced visualization (LEV) technique to water tunnel testing. Aspects of the study include laser power levels, flow seeding (using flourescent dyes and embedded particulates), model preparation, and photographic techniques. The results of this study are discussed to provide potential users with basic information to aid in the design and setup of an LEV system.

Beckner, C.

Water tunnel flow visualization using a laser

Laser systems for flow visualization in water tunnels (similar to the vapor screen technique used in wind tunnels) can provide two-dimensional cross-sectional views of complex flow fields. This parametric study documents the practical application of the laser-enhanced visualization (LEV) technique to water tunnel testing. Aspects of the study include laser power levels, flow seeding (using fluorescent dyes and embedded particulates), model preparation, and photographic techniques. The results of this study are discussed to provide potential users with basic information to aid in the design and setup of an LEV system.

Curry, R. E.

Is there a strange attractor in the magnetosphere?

This paper reviews recent attempts to determine if some aspects of magnetospheric dynamics, and in particular substorms as measured by AE and AL geomagnetic indices, can be represented by a low-dimensional dynamical system. If true, this result would imply that a small set of ordinary differential equations could describe important aspects of substorm dynamics, greatly simplifying modeling and prediction efforts and providing significant input to more detailed modeling. The "embedding" and "correlation dimension" methods used to investigate the dimensionality of a physical process from a single time series are considered in detail with an emphasis on what can go wrong and what can be done about it. Two main conclusions of this work, which includes some new results on the particular case of AL, are (1) that a low-dimensional and probably strange attractor does exist in magnetospheric dynamics, and (2) that there is no reliable substitute for using large numbers of data points in performing analyses leading to this conclusion.

Roberts, D. A.

A flow-control mechanism for distributed systems

A new approach to the rate-based flow control in store-and-forward networks is evaluated. Existing methods display oscillations in the presence of transport delays. The proposed scheme is based on the explicit use of an embedded dynamic model of a store-and-forward buffer in a controller's feedback loop. It is shown that the use of the model eliminates the oscillations caused by the transport delays. The paper presents simulation examples and assesses the applicability of the scheme in the new generation of high-speed photonic networks where transport delays must be considered.

Maitan, J.

Diffuse interstellar bands in reflection nebulae

A Monte Carlo code for radiation transport calculations is used to compare the profiles of the lambda lambda 5780 and 6613 Angstrom diffuse interstellar bands in the transmitted and the reflected light of a star embedded within an optically thin dust cloud. In addition, the behavior of polarization across the bands were calculated. The wavelength dependent complex indices of refraction across the bands were derived from the embedded cavity model. In view of the existence of different families of diffuse interstellar bands the question of other parameters of influence is addressed in short.

Fischer, O.

Certifying Auto-Generated Flight Code

Model-based design and automated code generation are being used increasingly at NASA. Many NASA projects now use MathWorks Simulink and Real-Time Workshop for at least some of their modeling and code development. However, there are substantial obstacles to more widespread adoption of code generators in safety-critical domains. Since code generators are typically not qualified, there is no guarantee that their output is correct, and consequently the generated code still needs to be fully tested and certified. Moreover, the regeneration of code can require complete recertification, which offsets many of the advantages of using a generator. Indeed, manual review of autocode can be more challenging than for hand-written code. Since the direct V&V of code generators is too laborious and complicated due to their complex (and often proprietary) nature, we have developed a generator plug-in to support the certification of the auto-generated code. Specifically, the AutoCert tool supports certification by formally verifying that the generated code is free of different safety violations, by constructing an independently verifiable certificate, and by explaining its analysis in a textual form suitable for code reviews. The generated documentation also contains substantial tracing information, allowing users to trace between model, code, documentation, and V&V artifacts. This enables missions to obtain assurance about the safety and reliability of the code without excessive manual V&V effort and, as a consequence, eases the acceptance of code generators in safety-critical contexts. The generation of explicit certificates and textual reports is particularly well-suited to supporting independent V&V. The primary contribution of this approach is the combination of human-friendly documentation with formal analysis. The key technical idea is to exploit the idiomatic nature of auto-generated code in order to automatically infer logical annotations. The annotation inference algorithm itself is generic, and parametrized with respect to a library of coding patterns that depend on the safety policies and the code generator. The patterns characterize the notions of definitions and uses that are specific to the given safety property. For example, for initialization safety, definitions correspond to variable initializations while uses are statements which read a variable, whereas for array bounds safety, definitions are the array declarations, while uses are statements which access an array variable. The inferred annotations are thus highly dependent on the actual program and the properties being proven. The annotations, themselves, need not be trusted, but are crucial to obtain the automatic formal verification of the safety properties without requiring access to the internals of the code generator. The approach has been applied to both in-house and commercial code generators, but is independent of the particular generator used. It is currently being adapted to flight code generated using MathWorks Real-Time Workshop, an automatic code generator that translates from Simulink/Stateflow models into embedded C code.

Denney, Ewen

Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms

Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model is provided. Then, the paper describes how the model is embedded within the prognostic framework and how the prognostics performance is assessed using observations from run-to-failure experiments

Prognostics

Simulations of Solar Jets Confined by Coronal Loops

Coronal jets are collimated, dynamic events that occur over a broad range of spatial scales in the solar corona. In the open magnetic field of coronal holes, jets form quasi-radial spires that can extend far out into the heliosphere, while in closed-field regions the jet outflows are confined to the corona. We explore the application of the embedded-bipole model to jets occurring in closed coronal loops. In this model, magnetic free energy is injected slowly by footpoint motions that introduce twist within the closed dome of the jet source region, and is released rapidly by the onset of an ideal kink-like instability. Two length scales characterize the system: the width (N) of the jet source region and the footpoint separation (L) of the coronal loop that envelops the jet source. We find that both the conditions for initiation and the subsequent dynamics are highly sensitive to the ratio L/N. The longest-lasting and most energetic jets occur along long coronal loops with large L/N ratios, and share many of the features of open-field jets, while smaller L/N ratios produce shorter-duration, less energetic jets that are affected by reflections from the far-loop footpoint. We quantify the transition between these behaviors and show that our model replicates key qualitative and quantitative aspects of both quiet Sun and active-region loop jets. We also find that there connection between the closed dome and surrounding coronal loop is very extensive: the cumulative reconnected flux at least matches the total flux beneath the dome for small L/N, and is more than double that value for large L/N.

Wyper, P. F.

BERT-E: An Earth Science Specific Language Model for Domain-Specific Downstream Tasks

Language models are fast approaching human-like understanding of natural language. They have been shown to perform equally, if not better than humans in a myriad of language tasks such as next sentence prediction, question answering, entity extraction etc. Part of the success of the models are owed to the fact that they have been trained on varied natural language text over the internet. By virtue of this, the models do not contain the semantic information present in Earth science literature. Hence, there is a lot of room for improvement when using these models for earth science specific tasks. In this work, we showcase our approach on developing Earth science specific language models. Furthermore, we justify the need for such a model by using the embeddings generated by the model to perform a domain specific downstream task that performs better than a generic model.

Prasanna Koirala

NEAR: Neural Embeddings for Amino acid Relationships

Protein language models (PLMs) have recently demonstrated potential to supplant classical protein database search methods based on sequence alignment, but are slower than common alignment-based tools and appear to be prone to a high rate of false labeling. Here, we present NEAR, a method based on neural representation learning that is designed to improve both speed and accuracy of search for likely homologs in a large protein sequence database. NEAR’s ResNet embedding model is trained using contrastive learning guided by trusted sequence alignments. It computes per-residue embeddings for target and query protein sequences, and identifies alignment candidates with a pipeline consisting of residue-level k-NN search and a simple neighbor aggregation scheme. Tests on a benchmark consisting of trusted remote homologs and randomly shuffled decoy sequences reveal that NEAR substantially improves accuracy relative to state-of-the-art PLMs, with lower memory requirements and faster embedding and search speed. While these results suggest that the NEAR model may be useful for standalone homology detection with increased sensitivity over standard alignment-based methods, in this manuscript we focus on a more straightforward analysis of the model’s value as a high-speed pre-filter for sensitive annotation. In that context, NEAR is at least 5x faster than the pre-filter currently used in the widely-used profile hidden Markov model (pHMM) search tool HMMER3, and also outperforms the pre-filter used in our fast pHMM tool, nail.

59 BASIC BIOLOGICAL SCIENCES

Thermal Modeling and Limitations for Power Electronics Embedded in Medium-Voltage Cables

As next-generation energy technologies gain traction and power demand increases, the existing electrical infrastructure faces significant stress, prompting innovative solutions to enhance the grid's capacity and lifespan. This work explores the possibility of embedding medium-voltage (MV) power electronics directly inline with the cable, and the resulting thermal challenges. Since the majority of power distribution cables installed in the U.S. are passively cooled, the work focuses primarily on passive cooling, with an emphasis on the limitations of axial heat spreading within the cable. To date, literature on axial spreading of high incident heat loads on cables and cable environments is limited, typically reporting cases with <10 W of incident heat load. This work will explore the considerations, limits, and tradeoffs of cable-embedded heat loads significantly larger than the cable losses. Both external and internal effects are modeled analytically in nondimensional terms via a Biot number analysis, allowing fundamental limits and tradeoffs to be derived. The work culminates in the design and experimental validation of a cable-embedded thermal system capable of passively dissipating 300 W of heat from a coaxial SiC mosfet switch module over a length of 20 cm, thus validating the possibility of MV cable-embedded power electronics from a thermal standpoint.

24 POWER TRANSMISSION AND DISTRIBUTION