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At least 235 records · Page 13

SSME Bearing and Seal Tester Data Compilation, Analysis and Reporting; and Refinement of the Cryogenic Bearing Analysis Mathematical Model

SRS and NASA/MSFC have developed software with unique capabilities to couple bearing kinematic modeling with high fidelity thermal modeling. The core thermomechanical modeling software was developed by SRS and others in the late 1980's and early 1990's under various different contractual efforts. SRS originally developed software that enabled SHABERTH (Shaft Bearing Thermal Model) and SINDA (Systems Improved Numerical Differencing Analyzer) to exchange data and autonomously allowing bearing component temperature effects to propagate into the steady state bearing mechanical model. A separate contract was issued in 1990 to create a personal computer version of the software. At that time SRS performed major improvements to the code. Both SHABERTH and SINDA were independently ported to the PC and compiled. SRS them integrated the two programs into a single program that was named SINSHA. This was a major code improvement.

Moore, James↗

SSME Bearing and Seal Tester Data Compilation, Analysis, and Reporting; and Refinement of the Cryogenic Bearing Analysis Mathematical Model

SRS and NASA/MSFC have developed software with unique capabilities to couple bearing kinematic modeling with high fidelity thermal modeling. The core thermomechanical modeling software was developed by SRS and others in the late 1980's and early 1990's under various different contractual efforts. SRS originally developed software that enabled SHABERTH (Shaft Bearing Thermal Model) and SINDA (Systems Improved Numerical Differencing Analyzer) to exchange data and autonomously allowing bearing component temperature effects to propagate into the steady state bearing mechanical model. A separate contract was issued in 1990 to create a personal computer version of the software. At that time SRS performed major improvements to the code. Both SHABERTH and SINDA were independently ported to the PC and compiled. SRS them integrated the two programs into a single program that was named SINSHA. This was a major code improvement.

Moore, James↗

High-temperature constitutive modeling

Thermomechanical service conditions for high-temperature levels, thermal transients, and mechanical loads severe enough to cause measurable inelastic deformation are studied. Structural analysis in support of the design of high-temperature components depends strongly on accurate mathematical representations of the nonlinear, hereditary, inelastic behavior of structural alloys at high temperature, particularly in the relatively small strain range. Progress is discussed in the following areas: multiaxial experimentation to provide a basis for high-temperature multiaxial constitutive relationships; nonisothermal testing and theoretical development toward a complete thermomechanically path dependent formulation of viscoplasticity; and development of viscoplastic constitutive model accounting for initial anisotropy.

Robinson, D. N.↗

Polytopic vector analysis in igneous petrology: Application to lunar petrogenesis

Lunar samples represent a heterogeneous assemblage of rocks with complex inter-relationships that are difficult to decipher using standard petrogenetic approaches. These inter-relationships reflect several distinct petrogenetic trends as well as thermomechanical mixing of distinct components. Additional complications arise from the unequal quality of chemical analyses and from the fact that many samples (e.g., breccia clasts) are too small to be representative of the system from which they derived. Polytopic vector analysis (PVA) is a multi-variate procedure used as a tool for exploratory data analysis. PVA allows the analyst to classify samples and clarifies relationships among heterogenous samples with complex petrogenetic histories. It differs from orthogonal factor analysis in that it uses non-orthogonal multivariate sample vectors to extract sample endmember compositions. The output from a Q-mode (sample based) factor analysis is the initial step in PVA. The Q-mode analysis, using criteria established by Miesch and Klovan and Miesch, is used to determine the number of endmembers in the data system. The second step involves determination of endmembers and mixing proportions with all output expressed in the same geochemical variable as the input. The composition of endmembers is derived by analysis of the variability of the data set. Endmembers need not be present in the data set, nor is it necessary for their composition to be known a priori. A set of any endmembers defines a 'polytope' or classification figure (triangle for a three component system, tetrahedron for a four component system, a 'five-tope' in four dimensions for five component system, et cetera).

Shervais, John W.↗

Computational simulation of high temperature metal matrix composites cyclic behavior

A procedure was developed and is described which can be used to computationally simulate the cyclic behavior of high temperature metal matrix composites (HTMMC) and its degradation effects on the structural response. This procedure consists of HTMMC mechanics coupled with a multifactor interaction constituent material relationship and with an incremental iterative nonlinear analysis. The procedure is implemented in a computer code that can be used to computationally simulate the thermomechanical behavior of HTMMC starting from the fabrication process and proceeding through thermomechanical cycling, accounting for the interface/interphase region. Results show that combined thermal/mechanical cycling, the interphase, and in situ matrix properties have significant effects on the structural integrity of HTMMC.

Chamis, C. C.↗

Computational simulation of high-temperature metal matrix composites cyclic behavior

A procedure was developed and is described that can be used to computationally simulate the cyclic behavior of high-temperature metal matrix composites (HTMMC) and its degradation effects on the structural response. This procedure consists of HTMMC mechanics coupled with a multifactor-interaction constituent material relationship and with an incremental iterative nonlinear analysis. The procedure is implemented in a computer code that can be used to computationally simulate the thermomechanical behavior of HTMMC starting from the fabrication process and proceeding through thermomechanical cycling, accounting for the interface/interphase region. Results show that combined thermal/mechanical cycling, the interphase, and in situ matrix properties have significant effects on the structural integrity of HTMMC.

Chamis, Christos C.↗

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗

Modulation of apparent optical properties using arrayed mesoscale structures

In this study, a method for using arrays of mesoscale structures to modify the apparent optical properties of an opaque composite surface has been theoretically demonstrated to both raise and lower the apparent emissivity as compared to the intrinsic properties of the constitutive materials. For design problems where thermomechanical and optical material properties are both of importance, mesoscale surface structuring can greatly expand the design space. Analysis via the net radiosity method herein illustrates the ability to achieve a wide range of spectral apparent optical properties. Notably, a hexagonal array of spheres on a planar surface can raise the apparent emissivity of a planar surface by 50%. Conversely, a hexagonal enclosure of reradiating surfaces, realized by thin adiabatic walls, can reduce the apparent emissivity of a blackbody by half. As this method of modifying apparent optical properties utilizes structures much larger than the wavelengths of interest, the relationship between intrinsic planar emissivity, geometry, and apparent emissivity can be computed semi-analytically at low computational expense. Passive solar cooling, thermophotovoltaic cells, aerodynamic surfaces exposed to intense heating, and solar absorbers are presented as case studies that could benefit from the use of mesoscale structures on opaque surfaces to modify the apparent optical properties.

42 ENGINEERING↗

Stirling engine - Approach for long-term durability assessment

The approach employed by NASA Lewis for the long-term durability assessment of the Stirling engine hot-section components is summarized. The approach consists of: preliminary structural assessment; development of a viscoplastic constitutive model to accurately determine material behavior under high-temperature thermomechanical loads; an experimental program to characterize material constants for the viscoplastic constitutive model; finite-element thermal analysis and structural analysis using a viscoplastic constitutive model to obtain stress/strain/temperature at the critical location of the hot-section components for life assessment; and development of a life prediction model applicable for long-term durability assessment at high temperatures. The approach should aid in the provision of long-term structural durability and reliability of Stirling engines.

Tong, Michael T.↗

Prediction of thermal and mechanical stress-strain responses of TMC's subjected to complex TMF histories

This paper presents an experimental and analytical evaluation of cross-plied laminates of Ti-15V-3Cr-3Al-3Sn (Ti-15-3) matrix reinforced with continuous silicon-carbide fibers (SCS-6) subjected to a complex TMF loading profile. Thermomechanical fatigue test techniques were developed to conduct a simulation of a generic hypersonic flight profile. A micromechanical analysis was used. The analysis predicts the stress-strain response of the laminate and of the constituents in each ply during thermal and mechanical cycling by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature-dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. The fiber transverse modulus was reduced in the analysis to simulate the fiber-matrix interface failures. Excellent correlation was found between measured and predicted laminate stress-strain response due to generic hypersonic flight profile when fiber debonding was modeled.

Johnson, W. S.↗

Packaging Technology for SiC High Temperature Circuits Operable up to 500 Degrees Centigrade

New high temperature low power 8-pin packages have been fabricated using commercial fabrication service. These packages are made of aluminum nitride and 96 percent alumina with Au metallization. The new design of these packages provides the chips inside with EM shielding. Wirebond geometry control has been achieved for precise mechanical tests. Au wirebond samples with 45 degree heel-angle have been tested using wireloop test module. The geometry control improves the consistency of measurement of the wireloop breaking point.Also reported on is a parametric study of the thermomechanical reliability of a Au thick-film based SiC die-attach assembly using nonlinear finite element analysis (FEA) was conducted to optimize the die-attach thermo-mechanical performance for operation at temperatures from room temperature to 500 degrees Centigrade. This parametric study centered on material selection, structure design and process control.

Chen, Lian-Yu↗

Preliminary Analysis of the 30-m UltraBoom Flight Test

Future NASA missions require long, ultra-lightweight booms to enable solar sails, large sunshields, and other gossamer-type spacecraft structures. The space experiment discussed in this paper will flight validate the non-traditional ultra lightweight rigidizable, inflatable, isogrid structure utilizing graphite shape memory polymer (GR/SMP) called UltraBoom(TradeMark). The focus of this paper is the analysis of the 3-m ground test article. The primary objective of the mission is to show that a combination of ground testing and analysis can predict the on-orbit performance of an ultra lightweight boom that is scalable, predictable, and thermomechanically stable.

UltraBoom↗

Prototype Modeling for a Light-Trapping Planar-Cavity Enclosed Particle Solar Receiver

Concentrating solar thermal (CST) systems present a promising avenue for affordable and reliable energy production. Solar receivers are key components that determine the efficiency and longevity of these systems. Particle-based solar receivers have emerged as a compelling alternative to traditional technologies, offering several advantages that address limitations in current CST systems. This is especially true as next-generation CST technologies target applications including electricity generation, thermochemical processes, and industrial process heat, many of which necessitate higher operating temperatures than current commercial molten salt systems. Molten-salt thermal energy storage (TES) systems, commonly used in CSP, face challenges related to freezing and corrosion. Particle-based TES systems, in contrast, do not experience these issues, as particles are stable at high temperatures, exceeding 1000 degrees Celsius. This capability allows for a wider range of applications, including those requiring higher temperatures for industrial processes and efficient electricity generation. A novel innovation in particle-based solar receiver technology is the light-trapping planar cavity receiver (LTPCR) configuration developed by NREL. The LTPCR design consists of small cavity-like structures using opaque planar surfaces, enabling efficient capture and absorption of solar energy. A high incident flux concentration at the cavity aperture is absorbed on the receiver walls, and subsequently transferred to particles on the inside of cavities. The particles flow through the system, forming a fluidized bed inside of the receiver panels, effectively capturing the absorbed solar heat. Air is used as a fluidizing medium in this process to enhance particle heat transfer and mixing. The effectiveness of this design lies in its ability to manage solar flux conditions and ensure high solar-to-thermal receiver efficiency. A 100-kW prototype is currently being tested at the King Saud University in Saudi Arabia to assess the receiver performance. A range of modeling analyses for the optical, thermal, and mechanical effects were conducted to assess the performance of the receiver under on-sun conditions. The solar flux resulting from the KSU heliostat field was modeled using NREL SolTrace software and produced up to 600 kW/m2 at the receiver aperture. The solar flux absorbed on the receiver walls was then used within a computational fluid dynamics (CFD) model to predict wall temperature distributions along with radiation and convection loss. A two-phase CFD model was developed for the fluidized bed of silica sand inside the receiver panels to predict local wall-to-particle heat transfer coefficients, particle temperature distributions, and outlet temperature of the particles. We have also conducted analyses to understand the thermomechanical behavior of these innovative enclosed light-trapping solar receivers optimized for particle heating. We used finite element analysis (FEA) to predict the receiver's performance using temperature distributions obtained from CFD and based on the resulting stress profiles, evaluated creep-fatigue damage with a goal of achieving a 30-year service life. Analysis showed a significant impact of the particle-to-wall heat transfer coefficients (HTCs) on receiver performance, with higher HTCs resulting in reduced stress and increased lifespan. For instance, when using Inconel 740H, increasing the HTC from 800 W/m2 K to 1400 W/m2 K increased the creep life from 4,000 hours to over 100,000 hours. This highlights the importance of understanding and optimizing heat transfer in the design of high-efficiency receivers.

14 SOLAR ENERGY↗

Probabilistic Structural Analysis Methods (PSAM) for Select Space Propulsion System Components

Probabilistic Structural Analysis Methods (PSAM) are described for the probabilistic structural analysis of engine components for current and future space propulsion systems. Components for these systems are subjected to stochastic thermomechanical launch loads. Uncertainties or randomness also occurs in material properties, structural geometry, and boundary conditions. Material property stochasticity, such as in modulus of elasticity or yield strength, exists in every structure and is a consequence of variations in material composition and manufacturing processes. Procedures are outlined for computing the probabilistic structural response or reliability of the structural components. The response variables include static or dynamic deflections, strains, and stresses at one or several locations, natural frequencies, fatigue or creep life, etc. Sample cases illustrates how the PSAM methods and codes simulate input uncertainties and compute probabilistic response or reliability using a finite element model with probabilistic methods.

Source record↗

Spherical Cryogenic Hydrogen Tank Preliminary Design Trade Studies

A structural analysis, sizing optimization, and weight prediction study was performed by Collier Research Corporation and NASA Glenn on a spherical cryogenic hydrogen tank. The tank consisted of an inner and outer wall separated by a vacuum for thermal insulation purposes. HyperSizer (Collier Research and Development Corporation), a commercial automated structural analysis and sizing software package was used to design the lightest feasible tank for a given overall size and thermomechanical loading environment. Weight trade studies were completed for different panel concepts and metallic and composite material systems. Extensive failure analyses were performed for each combination of dimensional variables, materials, and layups to establish the structural integrity of tank designs. Detailed stress and strain fields were computed from operational temperature changes and pressure loads. The inner tank wall is sized by the resulting biaxial tensile stresses which cause it to be strength driven, and leads to an optimum panel concept that need not be stiffened. Conversely, the outer tank wall is sized by a biaxial compressive stress field, induced by the pressure differential between atmospheric pressure and the vacuum between the tanks, thereby causing the design to be stability driven and thus stiffened to prevent buckling. Induced thermal stresses become a major sizing driver when a composite or hybrid composite/metallic material systems are used for the inner tank wall for purposes such as liners to contain the fuel and reduce hydrogen permeation.

Arnold, Steven M.↗

Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of the thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity and X-ray diffraction simulations is used to generate training data for machine-learning (Gaussian process regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

36 MATERIALS SCIENCE↗

Thermomechanical buckling and postbuckling of multilayered composite panels

A study is made of the thermomechanical buckling and postbuckling responses of flat unstiffened composite panels. The panels are subjected to combined temperature change and applied edge displacement. The analysis is based on a first-order shear deformation, von Karman type nonlinear plate theory. A mixed formulation is used with the fundamental unknowns consisting of the generalized displacements and the stress resultants of the plate. An efficient multiple-parameter reduction method is used in conjunction with mixed finite element models, for determining the stability boundary and postbuckling response. The reduction method is also used for evaluating the sensitivity coefficients which measure the sensitivity of the buckling and postbuckling responses to variations in the different lamination and material parameters of the panel. Numerical results are presented showing the effects of variations in the laminate stacking sequence, fiber orientation, number of layers and aspect ratio of the panels on their thermomechanical buckling and postbuckling responses and their sensitivity coefficients.

Noor, Ahmed K.↗

Status of structural analysis of 30 cm diameter ion optics

Three structural finite element programs are compared with theory, experimental data, and each other to evaluate their usefulness for modeling the thermomechanical deflection of ion engine electrodes. Two programs, NASTRAN and MARC, used a Cray XMP and the third, Algor, used an IBM compatible personal computer. The shape of the applied temperature gradient greatly affects off-axis displacement, implying that an accurate temperature distribution is required to analyze new designs. The use of bulk material constants to model the perforated electrodes was investigated. The stress and displacement predictions are shown to be sensitive to the temperature gradient and the Young's modulus, and insensitive to number of nodes, above some minimum value, and the Poisson ratio used. The models are shown to be useful tools for evaluating designs. Experimental measurement of temperatures and displacements was identified as the most critical area for further work.

Macrae, Gregory S.↗