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The finite element machine is a prototype computer designed to support parallel solutions to structural analysis problems. The hardware architecture and support software for the machine, initial solution algorithms and test applications, and preliminary results are described.
The Finite Element Machine at the NASA Langley Research Center is a prototype computer designed to support parallel solutions to structural analysis problems. The hardware architecture and support software for the machine, initial solution algorithms and test applications, and preliminary results are described. Directions for future work are presented.
Rhenium diboride (ReB 2 ) exhibits high differential strain due to its puckered boron sheets that impede shear deformation. Here, we demonstrate the use of solid solution formation to enhance the Vickers hardness and differential strain of ReB 2 . ReB 2 -structured solid solutions (Re 0.98 Os 0.02 B 2 and Re 0.98 Ru 0.02 B 2 , noted as “ReOsB 2 ” and “ReRuB 2 ”) were synthesized via arc-melting from the pure elements. In-situ high-pressure radial x-ray diffraction was performed in the diamond anvil cell to study the incompressibility and lattice strain of ReOsB 2 and ReRuB 2 up to ~56 GPa. Both solid solutions exhibit higher incompressibility and differential strain than pure ReB 2 . However, while all lattice planes are strengthened by doping osmium (Os) into the ReB 2 structure, only the weakest ReB 2 lattice plane is enhanced with ruthenium (Ru). These results are in agreement with the Vickers hardness measurements of the two systems, where higher hardness was observed in ReOsB 2 . The combination of high-pressure studies with experimentally observed hardness data provides lattice specific information about the strengthening mechanisms behind the intrinsic hardness enhancement of the ReB 2 system.
Numerical solution of Bhatnagar-Gross-Krook model for shock wave structure problem, noting Chapman-Enskog approximation
Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle x-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures. There are two main challenges in comparing SAXS profiles to RNA structures: the absence of cations essential for stability and charge neutralization in predicted structures and the inadequacy of a single structure to represent RNA’s conformational plasticity. We introduce a solution conformation predictor for RNA (SCOPER) to address these challenges. This pipeline integrates kinematics-based conformational sampling with the innovative deep learning model, IonNet, designed for predicting Mg 2+ ion binding sites. Validated through benchmarking against 14 experimental data sets, SCOPER significantly improved the quality of SAXS profile fits by including Mg 2+ ions and sampling of conformational plasticity. We observe that an increased content of monovalent and bivalent ions leads to decreased RNA plasticity. Therefore, carefully adjusting the plasticity and ion density is crucial to avoid overfitting experimental SAXS data. SCOPER is an efficient tool for accurately validating the solution state of RNAs given an initial, sufficiently accurate structure and provides the corrected atomistic model, including ions.
In this paper, various methods based on convex approximation schemes are discussed that have demonstrated strong potential for efficient solution of structural optimization problems. First, the convex linearization method (Conlin) is briefly described, as well as one of its recent generalizations, the method of moving asymptotes (MMA). Both Conlin and MMA can be interpreted as first-order convex approximation methods that attempt to estimate the curvature of the problem functions on the basis of semiempirical rules. Attention is next directed toward methods that use diagonal second derivatives in order to provide a sound basis for building up high-quality explicit approximations of the behavior constraints. In particular, it is shown how second-order information can be effectively used without demanding a prohibitive computational cost. Various first-order and second-order approaches are compared by applying them to simple problems that have a closed form solution.
Biopolymers such as xanthan gum (XG) and locust bean gum (LBG) hold great potential as eco-friendly alternative soil binders. In this work, we investigated the impact of XG/LBG mixtures on the unconfined compressive strength (UCS) of sand. The high strength of dry biopolymer/sand arises from the cohesion between solid polymer films and sand particles which supported by work of adhesion calculation and soil mechanics measurement. LBG exhibits much lower sand reinforcement efficacy because polymers unevenly distributed within sand matrix. The formation of a core-shell structure in LBG/sand is an interplay of surface free energy and viscoelastic properties of polymer solutions. This structure is altered when LBG mixed with XG at varying ratios as those physical properties changed due to the complexity of polymer chains association. By probing these factors, we aim to elucidate the role of surface energies and polymer physics in governing the strength of the sand/polymer network, thereby contributing to a more comprehensive understanding polymer-sand interface. The low strength of gels (G’ ∼10Pa) cannot solely account for the increased UCS of wet sand over 10 kPa. Instead, the high strength of biopolymer/sand is more likely derived from the granular particles with biopolymers as solid glue.
This paper summarizes a method that solves both the three dimensional thin-layer Navier-Stokes equations and the Euler equations using overset structured and solution adaptive unstructured grids with applications to helicopter rotor flowfields. The overset structured grids use an implicit finite-difference method to solve the thin-layer Navier-Stokes/Euler equations while the unstructured grid uses an explicit finite-volume method to solve the Euler equations. Solutions on a helicopter rotor in hover show the ability to accurately convect the rotor wake. However, isotropic subdivision of the tetrahedral mesh rapidly increases the overall problem size.
Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.
For the majority of the water present on earth, the two most important factors influencing its behavior are confinement, in either inorganic or organic matrixes, and the presence of solutes. Here, we investigate the effect of confinement in 3 nm pores on water diffusivity in aqueous solutions with archetypical solutes, a structure making (kosmotrope) NaCl and a structure breaking (chaotrope) KCl, up to 1.0 M in concentration. The water diffusivity in bulk aqueous solutions in such a concentration range is known to decrease very slightly in the presence of NaCl and increase very slightly in the presence of KCl. However, here we observe the water diffusivity in confined H 2 O–KCl increases by a factor of 2 compared to the pure water diffusivity in the same confinement. This unusually strong cumulative effect of confinement and a structure breaking additive may have profound implications for the mobility and transport of aqueous species in nature.
The general problem of solving for the steady state (time domain) dynamic response (i.e., NASTRAN rigid format-8) of a general elastic periodic structure subject to a phase difference loading of the type encountered in traveling wave propagation problems was studied. Two types of structural configurations were considered; in the first type, the structure has a repeating pattern over a span that is long enough to be considered, for all practical purposes, as infinite; in the second type, the structure has structural rotational symmetry in the circumferential direction. The theory and a corresponding set of DMAP instructions which permits the NASTRAN user to automatically alter the rigid format-8 sequence to solve the intended class of problems are presented. Final results are recovered as with any ordinary rigid format-8 solution, except that the results are only printed for the typical periodic segment of the structure. A simple demonstration problem having a known exact solution is used to illustrate the implementation of the procedure.
Understanding the relationships between morphology, fabrication processes, and thermoelectric performance in conducting polymers is essential to the development of high- efficiency organic thermoelectrics as an alternative to commonly used rare metals. Altering the film fabrication process of poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) with the addition of high boiling solvents to the precast solution improves the electrical conductivity and significantly increases its Seebeck value. Neutron scattering monitors the changes in the atomic, nanoscale, and mesoscale morphologies of PEDOT:PSS thin films with the addition of dimethyl sulfoxide (DMSO) to the aqueous solution prior to film formation and with varying fabrication procedures. The neutron scattering results show a decrease in the deuterated PSS domain size along with systematic variations in PEDOT fibril assemblies in the final blend film with the addition of DMSO to the pre-deposition solution. These structural modifications indicate that the increase in conductivity of PEDOT:PSS blends with addition of DMSO reported in the literature can be ascribed to the disruption of solvated PEDOT assemblies by the DMSO, forming smaller PSS domains in the pre-deposition solution and allowing smoother film formation. These improvements are observed significantly with the addition of just 1% DMSO but continue to modestly improve with the addition of up to 5% DMSO to the PEDOT:PSS blend pre-deposition solution. The fact that the variations in the measured morphology are independent of whether the films were deposited by spin or ultrasonic spray casting methods emphasizes the crucial importance of the structure of the blend in the pre-deposition solution in determining the final thin film blend morphology.
Plasma turbulence is a key challenge in understanding transport phenomena in magnetically confined plasmas. This work presents a generalized framework to analyze plasma turbulence that utilizes periodic orbit theory. In periodic orbit theory, doubly periodic solutions (coherent structures) of the governing equation(s) serve as building blocks of the considered turbulent dynamics. To illustrate the concept and method, the particularly simple Kuramoto–Sivashinsky (referred to here as LMRT for the original authors: LaQuey, Mahajan, Rutherford, and Tang) trapped-ion mode toy model is used. By applying numerical optimization techniques to the LMRT equation, we extract coherent spacetime patterns that represent the library of allowable fundamental structures of the equation. These structures provide a framework to systematically describe turbulence as a composition of recurrent solutions, revealing an underlying order within chaotic plasma motion. Although illustrated here using the simplified LMRT model for clarity, this framework provides a general strategy that can be extended to more complex and realistic models of plasma turbulence, including gyrokinetic systems. This offers a new method for predicting and potentially controlling transport processes in fusion plasmas by providing a bridge between nonlinear dynamical systems theory and plasma physics in the form of a generalized framework with which to analyze and understand spatially extended nonlinear partial differential equations.
In a previous paper Schaechter proposes using an extended Kalman filter to estimate adaptively the (slowly varying) frequencies and damping ratios of a large space structure. The time varying gains for estimating the frequencies and damping ratios can be determined in closed form so it is not necessary to integrate the matrix Riccati equations. After certain approximations, the time varying adaptive gain can be written as the product of a constant matrix times a matrix derived from the components of the estimated state vector. This is an important savings of computer resources and allows the adaptive filter to be implemented with approximately the same effort as the nonadaptive filter. The success of this new approach for adaptive filtering was demonstrated using synthetic data from a two mode system.
A mathematical model and solution methodologies for analyzing structural response of thin, metallic shell-type structures under large transient, cyclic or static thermomechanical loads is disussed. Among the system responses, which are associated with these load conditions, are thermal buckling and creep buckling. Thus, geometric as well as material-type nonlinearities (of high order) can be anticipated and have been considered in the development of the mathematical model. Furthermore, this was accommodated in the solution procedures. A complete true ab-inito rate theory of kinematics and kinetics for continuum and curved thin structures, without any restriction on the magnitude of the strains or the deformation, was formulated. The time dependence and large strain behavior are incorporated through the introduction of the time rates of the metric and curvature in two coordinate systems, a fixed (spatial) one and a convected (material) coordinate system. The relations between the time derivative and the covariant derivatives (gradients) have been developed for curved space and motion, so that the velocity components supply the connection between the equations of motion and the time rate of change of the metric and curvature tensors.
Within the past 10 years, substantial research in Adaptive Structures is evident and continues its integration into various space experiments and missions. The rapid integration is attributable to solutions Adaptive Structures potentially provides to many anticipated space challenges in large precision space structures and commercial availability of reliable actuator materials. The emphasis of the paper is on space experiments related to Adaptive Structures within the past two years.
Abstract The heterogeneous nuclear ribonucleoprotein (hnRNP) R‐like family is a class of RNA binding proteins in the hnRNP superfamily with diverse functions in RNA processing. Here, we present the 1.90 Å X‐ray crystal structure and solution NMR studies of the first RNA recognition motif (RRM) of human hnRNPR. We find that this domain adopts an extended RRM (eRRM1) featuring a canonical RRM with a structured N‐terminal extension (N ext ) motif that docks against the RRM and extends the β‐sheet surface. The adjoining loop is structured and forms a tryptophan cage motif to position the N ext motif for docking to the RRM. Combining mutagenesis, solution NMR spectroscopy, and thermal denaturation studies, we evaluate the importance of residues in the N ext –RRM interface and adjoining loop on eRRM folding and conformational dynamics. We find that these sites are essential for protein solubility, conformational ordering, and thermal stability. Consistent with their importance, mutations in the N ext –RRM interface and loop are associated with several cancers in a survey of somatic mutations in cancer studies. Sequence and structure comparison of the human hnRNPR eRRM1 to experimentally verified and predicted hnRNPR‐like proteins reveals conserved features in the eRRM.
The long-term goal for this program is to determine the structural and functional relationships of bone proteins and proteins that interact with bone. This information will used to design useful pharmacological compounds that will have a beneficial effect in osteoporotic patients and in the osteoporotic-like effects experienced on long duration space missions. The first phase of this program, funded under a cooperative research agreement with NASA through the Texas Medical Center, aimed to develop powerful recombinant expression systems and purification methods for production of large amounts of target proteins. Proteins expressed in sufficient'amount and purity would be characterized by a variety of structural methods, and made available for crystallization studies. In order to increase the likelihood of crystallization and subsequent high resolution solution of structures, we undertook to develop expression of normal and mutant forms of proteins by bacterial and mammalian cells. In addition to the main goals of this program, we would also be able to provide reagents for other related studies, including development of anti-fibrotic and anti-metastatic therapeutics.