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Reduced-order Modeling for Spacecraft Thermal-structural Applications

Leveraging the speed of reduced-order models (ROMs), thermal analysis teams have previously had access to rapid optimization, sensitivity studies, rapid model correlation, and uncertainty quantification, to name a few. An advantage of the developed approach is its relative robustness, which enabled expansion to include structural models in addition to thermal models leading to both rapid thermal-structural and rapid structural-only analyses. This method was tested for a sample thermal-structural application and showed good performance. It was then applied to a complex NASA mission and showed how ROMs could be used to quickly evaluate system uncertainties. Finally, these methods were applied to a structural-only application and used to better optimize and understand the structural design.

Derek Hengeveld

Integrated Modeling for Payload Test of the Roman Space Telescope

The Nancy Grace Roman Telescope (RST) is a NASA observatory designed to unravel the secrets of dark energy and dark matter, search for and image exoplanets, and explore many topics in infrared optics. Scheduled to launch in no earlier than October 2026, this 2.4 meter aperture telescope has a field of view 100 times greater than the Hubble Space Telescope. The mission is currently in its construction phase, where integrated modeling between thermal, structural, and optical models of the observatory is necessary to demonstrate science quality images over the range of operational parameters. This presentation discusses the most recent integrated modeling analysis cycle for Roman, including model correlation with our instrument level testing. We include a discussion on improved processes of the handling of the various flows of data between the modeling disciplines and discipline specific monte-carlo analysis predictions. We will finish with the predicted uncertainties and expected performance for our upcoming observatory alignment verification test using machine learning algorithms.

telescope

Attention-based explainability for structure–property relationships

Machine learning methods are emerging as a universal paradigm for constructing correlative structure–property relationships in materials science based on multimodal characterization. However, this necessitates the development of methods for the physical interpretability of the resulting correlative models. Here, we demonstrate the potential of attention-based neural networks for revealing structure–property relationships and the underlying physical mechanisms, using the ferroelectric properties of PbTiO3 thin films as a case study. Through the analysis of attention scores, we disentangle the influence of distinct domain patterns on the polarization switching process. The attention-based Transformer model is explored both as a direct interpretability tool and as a surrogate for explaining representations learned via unsupervised machine learning, enabling the identification of physically grounded correlations. We compare attention-derived interpretability scores with classical SHapley Additive exPlanations analysis and show that, in contrast to applications in natural language processing, attention mechanisms in materials science exhibit high efficiency in highlighting meaningful structural features.

Slautin, Boris [Independent Researcher]

Single and Multi-Node Modeling of Direct, Submerged, and Self-Pressurization of A Cryogenic Propellant Tank Using Nodal Tools

The pressurization of cryogenic propellant tanks will always be an important process so long as cryogenic liquids are being considered as fuel sources or used for other in-space applications. Pressure control of the tank ullage is necessary for managing propellant flowrates to an engine or a receiver tank, and modeling of the process is used to predict the pressurant requirements and the amount of propellant boiloff. Direct ullage pressurization is the more traditional approach to tank pressurization, as the physics are straight-forward, and ample test (flight) data have been collected and analyzed over the past several decades. Submerged injection pressurization is an alternate method for tank pressurization and has been shown to reduce pressurant requirements, subcool the propellant, and reduce the risk of ullage collapse. Additionally, the pressurant gas entering the ullage is usually much colder when using the submerged pressurization approach, resulting in reduced propellant boiloff. These benefits are at the expense of vaporizing a small percentage of the propellent. Both tank pressurization methods are viable options for current and future space missions, and it is important to have the capability of analyzing the tank ullage conditions for both approaches. Our previous work has demonstrated the development of a Generalized Fluid System Simulation Program (GFSSP) model, which contains a thermodynamic equilibrium heat and mass transfer subroutine capable of effectively analyzing both direct and submerged pressurization systems [1-2]. This subroutine has most recently been enhanced to include the non-equilibrium effect of pressurant dissolution into the propellant. To date the ullage has always been represented as a single node, and although the simulated single-node temperatures have good comparison with the volume-averaged ullage temperatures computed from test data, the physics of the thermal stratification in the ullage were never captured, and adjustment factors in the model were required. The purpose of this paper is to introduce the development of a multi-node ullage model using GFSSP and to discuss the improvements of the simulated ullage temperature distribution and its resulting effects on ullage heat transfer processes. Test data from the Cryogenic Propellant Storage and Transfer Engineering Developmental Unit (CPST EDU) was used for model validation. For additional comparison, a Thermal Desktop (TD) model was also developed to analyze the CPST EDU direct ullage pressurization tests using both a single node and multi-node approach. The model includes the direct pressurant line, vent line, fill/drain line, and a TD FloCAD Compartment. The TD FloCAD Compartment is employed to represent the liquid and ullage as single volumes inside the tank, to include a liquid/vapor interface, and to generate network level objects such as lumps (analogous to nodes in GFSSP), paths, and ties between the fluid and thermal elements. An established heat load on the model tank was leveraged from a pre-existing higher-fidelity model correlated to CPST EDU test data.

pressurization

PM 2.5 Concentrations over Major Metropolitan Regions Inferred from Airborne High Spectral Resolution Lidar Measurements Using Machine Learning Regression

We use measurements of near-surface aerosol backscatter, extinction, and depolarization acquired by four NASA Langley Research Center airborne High Spectral Resolution Lidars (HSRLs) to develop a machine learning regression methodology to infer PM2.5 concentrations at the surface and aloft. These airborne HSRL measurements were acquired over major metropolitan regions in the United States and Asia during more than 170 flights since 2010. Hourly surface PM2.5 measurements from the EPA air quality system and similar networks in other countries acquired within 10 km and 15 minutes of these near-surface HSRL measurements are used to train models that compute PM2.5 concentrations from the HSRL measurements. We examine several regression methods and find that exponential Gaussian Process algorithms consistently give the best performance in terms of the lowest root-mean-square (RMS) errors and the highest correlations. Model performance varies significantly depending on various combinations of HSRL aerosol measurements (e.g., aerosol backscatter, extinction, depolarization, backscatter color ratios, lidar ratios, aerosol optical thickness) and retrievals (e.g., mixed layer height, aerosol type) used in the regressions. Models that use near-surface measurements of aerosol backscatter and aerosol intensive properties such as depolarization, backscatter color ratio, and lidar ratio typically give the best performance with RMS errors around 4 mg/m3 and correlation coefficients above 0.9. HSRL measurements were often acquired when the aircraft flew systematic “raster-scan” patterns for several hours over these cities. These flight patterns enabled measurements of the spatial, temporal, and vertical variabilities in the distributions of aerosol backscatter and aerosol intensive properties and allowed us to derive the corresponding variabilities in PM2.5 concentrations. We present examples of such variabilities over urban areas in the United States as well as Asia. We describe also how the distribution of surface PM2.5 varies with aerosol type and use these retrievals to examine model simulations of surface PM2.5 in these metropolitan regions. We also discuss how this methodology may be applied to measurements from satellite lidars such as CALIOP on CALIPSO and ATLID on EarthCARE.

lidar

Modeling and a correlation algorithm for spaceborne SAR signals

A mathematical model of a spaceborne synthetic aperture radar (SAR) response is presented. Thhe associated SAR system performance, in terms of the resolution capability, is also discussed. The analysis of spaceborne SAR target response indicates that the SAR correlation problem is a two-dimensional one with a linear shift-variant response function. A new digital processing algorithm is proposed here in order to realize an economical digital SAR correlation system. The proposed algorithm treats the two-dimensional correlation by a combination of frequency domain fast correlation in the azimuth dimension and a time-domain convolver type of operation in the range dimension. Finally, digitally correlated SEASAT satellite SAR imagery is used in an exemplary sense to validate the SAR response model and the new digital processing technique developed.

Wu, C.

Massive black holes and light-element nucleosynthesis in a baryonic universe

We reexamine the model proposed by Gnedin & Ostriker (1992) in which Jeans mass black holes (M(sub BH) approximately = 10(exp 6) solar mass) form shortly after decoupling. There is no nonbaryonic dark matter in this model, but we examine the possibility that Omega(sub b) is considerably larger than given by normal nucleosynthesis. Here we allow for the fact that much of the high baryon-to-photon ratio material will collapse leaving the universe of remaining material with light-element abundances more in accord with the residual baryonic density (approximately = 10(exp -2)) than with Omega(sub 0) and the initial baryonic density (approximately = 10(exp -1)). We find that no reasonable model can be made with random-phase density fluctuations, if the power on scales smaller than 10(exp 6) solar mass is as large as expected. However, phase-correlated models of the type that might occur in connection with topological singularities can be made with Omega(sub b) h(exp 2) = 0.013 +/- 0.001, 0.15 approximately less than Omega(sub 0) approximately less than 0.4, which are either flat (Omega(sub lambda) = 1 - Omega(sub 0)) or open (Omega(sub lambda) = 0) and which satisfy all the observational constraints which we apply, including the large baryon-to-total mass ratio found in the X-ray clusters. The remnant baryon density is thus close to that obtained in the standard picture (Omega(sub b) h(exp 2) = 0.0125 +/- 0.0025; Walker et al. 1991). The spectral index implied for fluctuations in the baryonic isocurvature scenario, -1 less than m less than 0, is in the range expected by other arguments based on large-scale structure and microwave fluctuation constraints. The dark matter in this picture is in the form of massive black holes. Accretion onto them at early epochs releases high-energy photons which significantly heat and reionize the universe. But photodissociation does not materially change light-element abundances. A typical model gives bar-y approximately = 1 x 10(exp -5), n(sub e)/n(sub H)(z = 30) approximately = 0.1, and a diffuse gamma-ray background at 100 keV near the Cosmic Background Explorer Satellite (COBE) limit of the order of 10% of that observed which originates from high-redshift quasars. Reionization in this model occurs at redshift 600 and reaches (H II/H(sub tot) approximately = 0.1-0.2.

Gnedin, Nickolay Y.

Solar Thermal Vacuum Test of Deployable Astromesh Reflector

On September 10, 2008, a 36-hour Solar Thermal Vacuum Test of a 5m deployable mesh reflector was completed in JPL's 25' Space Simulator by the Advanced Deployable Structures Group at JPL. The testing was performed under NASA's Innovative Partnership Program (IPP) as a risk reduction effort for two JPL Decadal Survey Missions: DESDynI and SMAP. The 5.0 m aperture Astromesh reflector was provided by Northrop Grumman Aerospace Systems (NGAS) Astro Aerospace, our IPP industry partner. The testing utilized a state-of-the-art photogrammetry system to measure deformation of the reflector under LN2 cold soak, 0.25 Earth sun, 0.5 sun and 1.0 sun. An intricate network of thermocouples (approximately 200 in total) was used to determine the localized temperature across the mesh as well as on the perimeter truss of the reflector. Half of the reflector was in a fixed shadow to maximize thermal gradients. A mobility system was built for remotely actuating the cryo-vacuum capable photogrammetry camera around the circumference of the Solar Simulator. Photogrammetric resolution of 0.025 mm RMS (0.001") was achieved over the entire 5 meter aperture for each test case. The data will be used for thermo-elastic model correlation and validation, which will benefit the planned Earth Science Missions.

Photogrammetry

Advances in modeling the pressure correlation terms in the second moment equations

In developing turbulence models, various model constraints were proposed in an attempt to make the model equations more general (or universal). The most recent of these are the realizability principle, the linearity principle, the rapid distortion theory, and the material indifference principle. Several issues are discussed concerning these principles and special attention is payed to the realizability principle. Realizability (defined as the requirement of non-negative energy and Schwarz' inequality between any fluctuating quantities) is the basic physical and mathematical principle that any modeled equation should obey. Hence, it is the most universal, important and also the minimal requirement for a model equation to prevent it from producing unphysical results. The principle of realizability is described in detail, the realizability conditions are derived for various turbulence models, and the model forms are proposed for the pressure correlation terms in the second moment equations. Detailed comparisons of various turbulence models with experiments and direct numerical simulations are presented. As a special case of turbulence, the two dimensional two-component turbulence modeling is also discussed.

Shih, Tsan-Hsing

Advances in modeling the pressure correlation terms in the second moment equations

In developing turbulence models, various model constraints were proposed in an attempt to make the model equations more general (or universal). The most recent of these are the realizability principle, the linearity principle, the rapid distortion theory, and the material indifference principle. Several issues are discussed concerning these principles and special attention is payed to the realizability principle. Realizability (defined as the requirement of non-negative energy and Schwarz' inequality between any fluctuating quantities) is the basic physical and mathematical principle that any modeled equation should obey. Hence, it is the most universal, important and also the minimal requirement for a model equation to prevent it from producing unphysical results. The principle of realizability is described in detail, the realizability conditions are derived for various turbulence models, and the model forms are proposed for the pressure correlation terms in the second moment equations. Detailed comparisons of various turbulence models with experiments and direct numerical simulations are presented. As a special case of turbulence, the two dimensional two-component turbulence modeling is also discussed.

Shih, Tsan-Hsing

Optimal matrix approximants in structural identification

Problems of model correlation and system identification are central in the design, analysis, and control of large space structures. Of the numerous methods that have been proposed, many are based on finding minimal adjustments to a model matrix sufficient to introduce some desirable quality into that matrix. In this work, several of these methods are reviewed, placed in a modern framework, and linked to other previously known ideas in computational linear algebra and optimization. This new framework provides a point of departure for a number of new methods which are introduced here. Significant among these is a method for stiffness matrix adjustment which preserves the sparsity pattern of an original matrix, requires comparatively modest computational resources, and allows robust handling of noisy modal data. Numerical examples are included to illustrate the methods presented herein.

Beattie, C. A.

Application of two creep fatigue life models for the prediction of elevated temperature crack initiation of a nickel base alloy

Cyclic Damage Accumulation (CDA) and Total Strain-Strain Range Partitioning (TS-SRP) models for predicting the creep-fatigue crack initiation life of high temperature alloys are presented. The models differ in their fundamental assumptions regarding the controlling parameters for fatigue crack initiation and in the amount of data required to determine model constants. The CDA model represents a ductility exhaustion approach and uses stress quantities to calculate the cyclic fatigue damage. The TS-SRP model is based on the use of total mechanical strain and earlier concepts of the Strain Range Partitioning Method. Both models were applied to a well controlled fatigue data set at a high temperature nickel base alloy, B1900 + Hf, tested at 1600 F and 1800 F. The tests were divided into a baseline data set required to determine model constants and a verification data set for evaluation of the predictive capability of the models. Both models correlated the baseline data set to within factors of two in life, and predicted the verification data set to within a factor of three or better. In addition, sample calculations to demonstrate the application of each model and discusions of the predictive capabilities and areas requiring further development are presented.

Moreno, V.

A high resolution gravity model for Venus - GVM-1

A spherical harmonic model of the gravitational field of Venus complete to degree and order 50 has been developed using the S-band Doppler tracking data of the Pioneer Venus Orbiter (PVO) collected between 1979 and 1982. The short wavelengths of this model could only be resolved near the PVO periapse location (about 14 deg N latitude), therefore a priori constraints were applied to the model to bias poorly observed coefficients towards zero. The resulting model has a half-wavelength resolution of 400 km near the PVO periapse location, but the resolution degrades to greater than 1000 km near the poles. This gravity model correlates well with a degree 50 spherical harmonic expansion of the Venus topography derived from a combination of Magellan and PVO data. New tracking data from Magellan's gravity mission should provide some improvement to this model, although a complete model of the Venusian gravity field will depend on tracking of Magellan after the circularization of its orbit using aerobraking.

Nerem, R. S.

Residual flexibility test method for verification of constrained structural models

A method is presented for deriving constrained modes and frequencies from a model correlated to a set of free-free test modes and a set of measured residual flexibilities. The method involves a simple modification of the MacNeal and Rubin component mode representation to allow verification of a constrained structural model. Results for two spaceflight structures show quick convergence of constrained modes using an easily measurable set of free-free modes plus the residual flexibility matrix or its boundary partition. This paper further validates the residual flexibility approach as an alternative test/analysis method when fixed-base testing proves impractical.

Admire, John R.

High Fidelity Modeling of Evolutionary Structures in IMOS

A methodology is proposed for testing, modal identification, and model correlation of structures which are assembled in an evolutionary manner. The methodology prescribes initial testing of a base structure without any attached components. The experimental modal properties are used to update the physical properties of the base structure finite element model using a Bayesian Estimation Technique (BET). The BET is implemented in METLAB using IMOS functions. As components are added to the base structure, additional tests are performed. Three testing options are proposed, all of which enable estimation of the physical parameters of the components alone. Furthermore, improvements to the original BET implementation have been made, which contribute to higher fidelity models and more efficient computational times.

structures testing assembling modeling BET Bayesia

Persistent flat band splitting and strong selective band renormalization in a kagome magnet thin film

Magnetic kagome materials provide a fascinating playground for exploring the interplay of magnetism, correlation and topology. Many magnetic kagome systems have been reported including the binary Fe m X n (X = Sn, Ge; m:n = 3:1, 3:2, 1:1) family and the rare earth RMn 6 Sn 6 (R = rare earth) family, where their kagome flat bands are calculated to be near the Fermi level in the para magnetic phase. While partially filling a kagome flat band is predicted to give rise to a Stoner-type ferromagnetism, experimental visualization of the mag netic splitting across the ordering temperature has not been reported for any of these systems due to the high ordering temperatures, hence leaving the nature of magnetism in kagome magnets an open question. Here, we probe the electronic structure with angle-resolved photoemission spectroscopy in a kagome magnet thin film FeSn synthesized using molecular beam epitaxy. We identify the exchange-split kagome flat bands, whose splitting persists above the magnetic ordering temperature, indicative of a local moment picture. Such local moments in the presence of the topological flat band are consistent with the compact molecular orbitals predicted in theory. We further observe a large spin-orbital selective band renormalization in the Fe d xy + d x 2 -y 2 spin majority channel reminiscent of the orbital selective correlation effects in the iron based superconductors. Our discovery of the coexistence of local moments with topological flat bands in a kagome system echoes similar findings in magic-angle twisted bilayer graphene, and provides a basis for theoretical effort towards modeling correlation effects in magnetic flat band systems.

36 MATERIALS SCIENCE

2024 Status Report - Fiberboard Properties and Degradation Rates for Storage of 9975 Shipping Package in KAC

Fiberboard assemblies in the 9975 package were identified as susceptible to aging and degradation under long-term storage conditions. Thermal, mechanical, and physical properties have been measured on fiberboard samples aging for up to 19 years at accelerated conditions. The aging environments include elevated temperature up to 250 ºF (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. Accelerated aging results have been analyzed and used to build aging models. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions, and density) to their rate of change in potential storage environments have been developed. Combined with an estimate of the actual conditions the fiberboard experiences in K-Area Complex (KAC), these models allow development of service life predictions.

36 MATERIALS SCIENCE

2025 Status Report - Fiberboard Properties and Degradation Rates for Storage of 9975 Shipping Package in KAC

Fiberboard assemblies in the 9975 package were identified as susceptible to aging and degradation under long-term storage conditions. Thermal, mechanical, and physical properties have been measured on fiberboard samples aging for up to 20 years at accelerated conditions. The aging environments include elevated temperature up to 250 ºF (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. Accelerated aging results have been analyzed and used to build aging models. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions, and density) to their rate of change in potential storage environments have been developed. Combined with an estimate of the actual conditions the fiberboard experiences in K-Area Complex (KAC), these models allow development of service life predictions. KAC completed calculations that supported extending the service life of 9975 packages with 3013 containers in storage from 20 years to 40 years. These calculations addressed the potential for degraded fiberboard properties following 40 years in storage using degradation models. The 40 year storage evaluations assumed the degradation rates from initial values for density, dimensional, and thermal properties were 0.5% per year (i.e., after 40 years, the density, dimensional, and thermal properties of fiberboard were 80% of its initial values). The updated degradation models developed in this report were compared to the assumptions in those calculations, and the current results for fiberboard dimensions, density, axial and radial thermal conductivities, and energy absorption remain consistent with those calculations. Additional data will continue to be collected to permit future refinements to the models and assumptions. Some of the predicted degradation rates presented in this report are purposely high to accelerate aging. These rates relate to environments that do not exist within KAC or are postulated to only occur as upset conditions that are unlikely to persist for an extended period. For a typical package stored in KAC with approximately 10-12 watts internal heat load or less, and ambient temperatures below 90 ºF, the fiberboard assemblies experience storage conditions less severe than any of the aging environments (i.e., under 125 °F) used in this study. Fiberboard in conforming packages with lower internal heat loads should experience little or no degradation and is expected to provide a service life beyond the currently approved 40 year storage period. Packages with higher internal heat loads may not continue to perform their required safety functions beyond 40 years. Ultimately, service life will be determined by the cumulative effect of degradation from all the conditions these packages might encounter. The results and model predictions presented in this report are applicable to 9975 packages with cane or softwood fiberboard overpack assemblies. These degradation models do not address the effects of nonconforming conditions such as the presence of excess moisture and mold or beetle infestations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W