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Dependence of magnetostriction coefficient for diamagnetic materials on change of Fermi surface with momentum and deformation parameter
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Directionally solidified (DS) MAR-M246+Hf was tested in tension and fatigue, at temperatures from 20 C to 1093 C. Tests were performed on (001) oriented specimens at strain rates of 50 % and 0.5 % per minute. In tension, the yield strength was constant up to 704 C, above which the strength dropped off rapidly. A strong dependence of strength on strain rate was seen at the higher temperatures. The deformation mode was observed to change from heterogeneous to homogeneous with increasing temperature. Low Cycle Fatigue tests were done using a fully reversed waveform and total strain control. For a given plastic strain range, lives increased with increasing temperature. For a given temperature strain rate had a strong effect on life. At 704 C, decreasing strain rates decreased life, while at the higher temperatures, decreasing strain rates increased life, for a given plastic strain range. These results could be explained through considerations of the deformation modes and stress levels. At the higher temperatures, marked coarsening caused beneficial stress reductions, but oxidation limited the life. The longitudinal grain boundaries were found to influence slip behavior. The degree of secondary slip adjacent to the boundaries was found to be related to the degree of misorientation between the grains.
The paper concentrates on the relation between microstructural observations of the dislocation structures and the macroscopic deformation responses of both aged and homogenized precipitate-hardened alloys at room temperature. The deformation responses are compared to the cyclic deformation response of an aged precipitate-hardened alloy. Early in the deformation, one deformation band per grain and little evidence of work hardening are observed; with increased deformation, work hardening begins, more bands nucleate, and their spacing becomes similar to that in the aged material. It is pointed out that the degree of coarseness of inhomogeneous deformation is not a result of a softening process within the bands due to precipitate shearing, but it is a function of the amount of work hardening within the bands.
The abilities of six models of notch root behavior are evaluated by comparing them with experimental results over a range of constraints. The models studied are the Neuber model, the Walker modified Neuber model, the Glinka models for plane strain and for plane stress, and two modifications of the Glinka models. Comparisons are made with strains measured at the roots of notches by resistance gages or by laser-based interferometry.
The desirable properties in ceramic matrix composites (CMCs), such as high temperature strength, corrosion resistance, high toughness, low density, or good creep resistance have led to increased use of CMCs in high-speed engine structural components and structures that operate in extreme temperature and hostile aero-thermo-chemical environments. Ceramic matrix composites have been chosen for turbine material in the design of 21 st-century civil propulsion systems to achieve high fuel economy, improved reliability, extended life, and reduced cost. Most commercial CMCs are manufactured using a chemical vapor infiltration (CVI) process. However, a lower cost fabrication known as melt-infiltration process is also providing CMCs marked for use in hot sections of high-speed civil transports. The scope of this paper is to report on the material and mechanical characterization of the CMCs subjected to this process and to predict the behavior through an analytical model. An investigation of the SiC/SiC 8-harness woven composite is ongoing and its tensile strength and fatigue behavior is being characterized for room and elevated temperatures. The investigation is being conducted at below and above the matrix cracking stress once these parameters are identified. Fractography and light microscopy results are being studied to characterize the failure modes resulting from pure uniaxial loading. A numerical model is also being developed to predict the laminate properties by using the constituent material properties and tow undulation.
Trajectory optimization methods using MBH have become well developed during the past decade. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing RVs from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by Englander significantly improves MBH performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness, where efficiency is finding better solutions in less time, and robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive RWs originally developed in the field of statistical physics.
The results of subsonic jet validation cases for the Naval Research Lab's Jet Engine Noise REduction (JENRE) code are reported. Two set points from the Tanna matrix, set point 3 (Ma = 0.5, unheated) and set point 7 (Ma = 0.9, unheated) are attempted on three different meshes. After a brief discussion of the JENRE code and the meshes constructed for this work, the turbulent statistics for the axial velocity are presented and compared to experimental data, with favorable results. Preliminary simulations for set point 23 (Ma = 0.5, Tj=T1 = 1.764) on one of the meshes are also described. Finally, the proposed configuration for the farfield noise prediction with JENRE's Ffowcs-Williams Hawking solver are detailed.
The nickel-base superalloy Inconel 718 (IN 718) is used as a structural material for a variety of components in the space shuttle main engine (SSME) and accounts for more than half of the total weight of this engine. IN 718 is the bill-of-material for the pressure vessels of nickel-hydrogen batteries for the space station. In the case of the space shuttle main engine, structural components are typically subjected to startup and shutdown load transients and occasional overloads in addition to high-frequency vibratory loads from routine operation. The nickel-hydrogen battery cells are prooftested before service and are subjected to fluctuating pressure loads during operation. In both of these applications, the structural material is subjected to a monotonic load initially, which is subsequently followed by fatigue. To assess the life of these structural components, it is necessary to determine the influence of a prior monotonic load on the subsequent fatigue life of the superalloy. An insight into the underlying deformation and damage mechanisms is also required to properly account for the interaction between the prior monotonic load and the subsequent fatigue loading. An experimental investigation was conducted to establish the effect of prior monotonic straining on the subsequent fatigue behavior of wrought, double-aged, IN 718 at room temperature. First, monotonic strain tests and fully-reversed, strain-controlled fatigue tests were conducted on uniform-gage-section IN 718 specimens. Next, fully reversed fatigue tests were conducted under strain control on specimens that were monotonically strained in tension. Results from this investigation indicated that prior monotonic straining reduced the fatigue resistance of the superalloy particularly at the lowest strain range. Some of the tested specimens were sectioned and examined by transmission electron microscopy to reveal typical microstructures as well as the active deformation and damage mechanisms under each of the loading conditions. In monotonically strained specimens, deformation during the subsequent fatigue loading was mainly confined to the deformation bands initiated during the prior monotonic straining. This can cause dislocations to move more readily along the previously activated deformation bands and to pile up near grain boundaries, eventually making the grain boundaries susceptible to fatigue crack initiation. The mechanisms inferred from the microstructural investigation were extremely valuable in interpreting the influence of prior monotonic straining on the subsequent fatigue life of Inconel 718 superalloy.
Shape representation is a central issue in computer graphics and computer-aided geometric design. Many physical phenomena involve curves and surfaces that are monotone (in some directions) or are convex. The corresponding representation problem is given some monotone or convex data, and a monotone or convex interpolant is found. Standard interpolants need not be monotone or convex even though they may match monotone or convex data. Most of the methods of investigation of this problem involve the utilization of quadratic splines or Hermite polynomials. In this investigation, a similar approach is adopted. These methods require derivative information at the given data points. The key to the problem is the selection of the derivative values to be assigned to the given data points. Schemes for choosing derivatives were examined. Along the way, fitting given data points by a conic section has also been investigated as part of the effort to study shape-preserving quadratic splines.
Fatigue life at elevated temperature can be predicted by introducing parametric values obtained from monotonic constitutive behavior into the Universal-Slopes Equation. For directionally solidified MAR-M200+HF at 975 C, these parameters are the maximum stress achievable under entirely plastic (time-independent) and purely creep (time-dependent) conditions and the corresponding inelastic strains, as well as the elastic modulus. For materials which exhibit plasticity/creep interaction, two more pairs of monotonic parameters must be evaluated for fatigue life prediction. This life-prediction method based on the Universal-Slopes Equation, resulted from a constitutive model characterizing monotonic and cyclic data as inelastic strainrate as a function of inelastic strain. Characterizing monotonic data is this way, permitted distinction between different material responses such as strain-hardening, strain-softening, and dynamic recovery effects. Understanding and defining the region of influence of each of these effects facilitated formulation of the constitutive model in relation to the mechanical and microstructural processes occurring in the material under cyclic loading.
We present the basic ideas of the dynamics system of the finite-volume General Circulation Model developed at NASA Goddard Space Flight Center for climate simulations and other applications in meteorology. The dynamics of this model is designed with emphases on conservative and monotonic transport, where the property of Lagrangian conservation is used to maintain the physical consistency of the computational fluid for long-term simulations. As the model benefits from the noise-free solutions of monotonic finite-volume transport schemes, the property of Lagrangian conservation also partly compensates the accuracy of transport for the diffusion effects due to the treatment of monotonicity. By faithfully maintaining the fundamental laws of physics during the computation, this model is able to achieve sufficient accuracy for the global consistency of climate processes. Because the computing algorithms are based on local memory, this model has the advantage of efficiency in parallel computation with distributed memory. Further research is yet desirable to reduce the diffusion effects of monotonic transport for better accuracy, and to mitigate the limitation due to fast-moving gravity waves for better efficiency.
As is well-known, popular high-order methods such as discontinuous Galerkin (DG) and flux reconstruction (FR) tend to generate oscillations near shocks and discontinuities, which can lead to negative pressure or density, ultimately causing code breakdown. For standard second-order methods, one approach to mitigating oscillations is to impose constraints on the calculated slopes, ensuring they do not become excessively steep. This limiting process is rooted in the idea of preserving monotonicity introduced by Van Leer (1974): when the data are monotone, limiting the slopes result in a monotone piecewise linear solution. However, a drawback of this approach is the loss of accuracy near extrema, where the non-monotone solution is somewhat flattened and achieves only first-order accuracy.
We revisit the existence of monotonic quantities along renormalization group flows using only the Null Energy Condition and the Ryu-Takayanagi formula for the entanglement entropy of field theories with anti-de Sitter gravity duals. In particular, we consider flows within the same dimension and holographically reprove the c-, F -, and a-theorems in dimensions two, three, and four. We focus on the family of maximally spherical entangling surfaces, define a quasi-constant of motion corresponding to the breaking of conformal invariance, and use a properly defined distance between minimal surfaces to construct a holographic c-function that is monotonic along the flow. We then apply our method to the case of flows across dimensions: there, we reprove the monotonicity of flows from AdS D+1 to AdS 3 and prove the novel case of flows from AdS 5 to AdS 4 .
Neural networks have emerged as powerful tools for mapping between inputs and outputs. However, their black-box nature limits the ability to encode or impose specific structural relationships between inputs and outputs. Many scientific and engineering problems, such as constitutive modeling in solid mechanics, require networks that can enforce convexity, monotonicity, or other structural constraints to ensure physical consistency. Here, we introduce the Input Specific Neural Network (ISNN), a new architecture that enables multiple, distinct constraints to be imposed on different input subsets for scalar-valued outputs. This framework unifies convex, monotone–convex, monotone, and arbitrary mappings within a single network for the first time. Two ISNN architectures with analytical first- and second-order derivatives are developed. We demonstrate the performance on synthetic toy problems, inverse problems in isotropic hyperelasticity, and finite element simulations. ISNNs achieve improved extrapolation behavior, require fewer invariant inputs than standard input convex networks for polyconvex potentials, and enable significant computational savings via manual differentiation. We also show how ISNNs can be used to learn structural relationships between inputs and outputs via a binary gating mechanism. Particularly, ISNNs are employed to model a homogenized anisotropic free energy potential in a decoupled multiscale setting. The network learns whether or not the potential should be modeled as polyconvex and retains only the relevant layers while using the minimum number of inputs. ISNNs provide a flexible foundation for embedding structural priors into neural networks, enhancing both interpretability and stability. They are broadly applicable across computational mechanics and other scientific domains requiring constrained functional relationships.
We develop a Stockmayer fluid model for molecular dynamics simulations of ionic liquids that captures molecular polarization, ionic conductivity, viscosity, and glass transition temperature, using ethylammonium nitrate (EAN) as an example. The ions in EAN are treated as spheres interacting via the Lennard-Jones potential with an embedded point charge and a permanent dipole moment. We show that our simulation results for EAN are consistent with experimental data and then explore the effects of the molecular parameters on the viscosity of ionic liquids. Our results indicate that viscosity monotonically increases with ionic charge and dipole moment but non-monotonically changes with ionic diameter (or molar volume). This non-monotonic trend arises from the competition among the electrostatic interactions, molecular packing, and size asymmetry between the cation and anion. In conclusion, our model also shows that long-lived ion pairs result in higher viscosities.
Abstract In standard cosmology, the cosmic homogeneity scale is the transition scale above which the patterns arising from non-uniformities – such as groups and clusters of galaxies, voids, and filaments – become indistinguishable from a random distribution of sources. Recently, different groups have investigated the feasibility of using such a scale as a cosmological test and arrived at different conclusions. In this paper, we complement and extend these studies by exploring the evolution of the spatial ( $$R_{\textrm{H}}$$ R H ) and angular ( $$\theta _{\textrm{H}}$$ θ H ) homogeneity scales with redshift, assuming a spatially flat, $$\varLambda $$ Λ -Cold Dark Matter universe and linear cosmological perturbation theory. We confirm previous results concerning the non-monotonicity of $$R_{\textrm{H}}$$ R H with the matter density parameter $$\varOmega _{\textrm{m0}}$$ Ω m0 but also show that it exhibits a monotonical behavior with the Hubble constant $$H_{0}$$ H 0 within a large redshift interval. More importantly, we find that, for $$z \gtrsim 0.6$$ z ≳ 0.6 , $$\theta _{\textrm{H}}$$ θ H presents a monotonical behavior with $$\varOmega _{\textrm{m0}}$$ Ω m0 , as well as for $$H_0$$ H 0 the entire redshift interval analyzed. We find also that the angular homogeneity scale is sensitive to $$H_{0}$$ H 0 , especially at higher redshifts. Using the currently available $$\theta _{\textrm{H}}$$ θ H measurements, we illustrate the constraints on the $$\varOmega _{\textrm{m0}}$$ Ω m0 – $$H_{0}$$ H 0 plane through a MCMC analysis and show the feasibility of using the angular homogeneity scale as a new, model-independent way to constrain cosmological parameters.