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NASA NTRS2012

Robust, Practical Adaptive Control for Launch Vehicles

A modern mechanization of a classical adaptive control concept is presented with an application to launch vehicle attitude control systems. Due to a rigorous flight certification environment, many adaptive control concepts are infeasible when applied to high-risk aerospace systems; methods of stability analysis are either intractable for high complexity models or cannot be reconciled in light of classical requirements. Furthermore, many adaptive techniques appearing in the literature are not suitable for application to conditionally stable systems with complex flexible-body dynamics, as is often the case with launch vehicles. The present technique is a multiplicative forward loop gain adaptive law similar to that used for the NASA X-15 flight research vehicle. In digital implementation with several novel features, it is well-suited to application on aerodynamically unstable launch vehicles with thrust vector control via augmentation of the baseline attitude/attitude-rate feedback control scheme. The approach is compatible with standard design features of autopilots for launch vehicles, including phase stabilization of lateral bending and slosh via linear filters. In addition, the method of assessing flight control stability via classical gain and phase margins is not affected under reasonable assumptions. The algorithm s ability to recover from certain unstable operating regimes can in fact be understood in terms of frequency-domain criteria. Finally, simulation results are presented that confirm the ability of the algorithm to improve performance and robustness in realistic failure scenarios.

Orr, Jeb. S.↗

NASA NTRS2015

Contemporary Impact Analysis Methodology for Planetary Sample Return Missions

Development of an Earth entry vehicle and the methodology created to evaluate the vehicle's impact landing response when returning to Earth is reported. NASA's future Mars Sample Return Mission requires a robust vehicle to return Martian samples back to Earth for analysis. The Earth entry vehicle is a proposed solution to this Mars mission requirement. During Earth reentry, the vehicle slows within the atmosphere and then impacts the ground at its terminal velocity. To protect the Martian samples, a spherical energy absorber called an impact sphere is under development. The impact sphere is composed of hybrid composite and crushable foam elements that endure large plastic deformations during impact and cause a highly nonlinear vehicle response. The developed analysis methodology captures a range of complex structural interactions and much of the failure physics that occurs during impact. Numerical models were created and benchmarked against experimental tests conducted at NASA Langley Research Center. The postimpact structural damage assessment showed close correlation between simulation predictions and experimental results. Acceleration, velocity, displacement, damage modes, and failure mechanisms were all effectively captured. These investigations demonstrate that the Earth entry vehicle has great potential in facilitating future sample return missions.

Perino, Scott V.↗

NASA NTRS2016

Compatibility Assessment Tool

In support of ground system development for the Space Launch System (SLS), engineers are tasked with building immense engineering models of extreme complexity. The various systems require rigorous analysis of pneumatics, hydraulic, cryogenic, and hypergolic systems. There are certain standards that each of these systems must meet, in the form of pressure vessel system (PVS) certification reports. These reports can be hundreds of pages long, and require many hours to compile. Traditionally, each component is analyzed individually, often utilizing hand calculations in the design process. The objective of this opportunity is to perform these analyses in an integrated fashion with the parametric CADCAE environment. This allows for systems to be analyzed on an assembly level in a semi-automated fashion, which greatly improves accuracy and efficiency. To accomplish this, component specific parameters were stored in the Windchill database to individual Creo Parametric models based on spec control drawings. These parameters were then accessed by using the Prime Analysis within Creo Parametric. MathCAD Prime spreadsheets were created that automatically extracted these parameters, performed calculations, and generated reports. The reports described component compatibility based on local conditions such as pressure, temperature, density, and flow rates. The reports also determined component pairing compatibility, such as properly sizing relief valves with regulators. The reports stored the input conditions that were used to determine compatibility to increase traceability of component selection. The desired workflow for using this tool would begin with a Creo Schematics diagram of a PVS system. This schematic would store local conditions and locations of components. The schematic would then populate an assembly within Creo Parametric, using Windchill database parts. These parts would have their attributes already assigned, and the MathCAD spreadsheets could begin running through database parts to determine which components would be suited for specific locations within the assembly. This eliminates a significant amount of time from the design process, and makes initial analysis assessments more accurate. Each component that would be checked for a location within the assembly would generate a report, showing whether the component was compatible. These reports could be used to generate the PVS report without the need to perform the same analysis multiple times. This process also has the potential to be expanded upon to further automate PVS reports. The integration of software codes or macros could be used to automatically check through hundreds of parts for each location on the schematic. If the software could recognize which type of component would be necessary for each location, it is possible that simply starting the macro could completely choose all the components needed for the schematic, and in turn the system. This would save many hours of work initially selecting components, which could end up saving money. Overall, this process helps to automate initial component selections for PVS systems to fit local design specifications. These selections will automatically generate reports showing how the design criteria are met by the specific component that was chosen. These reports will contribute to easier compilation of the PVS certification reports, which currently take a great amount of time and effort to produce.

Egbert, James Allen↗

NASA NTRS2010

Impact of Spacecraft Shielding on Direct Ionization Soft Error Rates for Sub-130 nm Technologies

We use ray tracing software to model various levels of spacecraft shielding complexity and energy deposition pulse height analysis to study how it affects the direct ionization soft error rate of microelectronic components in space. The analysis incorporates the galactic cosmic ray background, trapped proton, and solar heavy ion environments as well as the October 1989 and July 2000 solar particle events.

Pellish, Jonathan A.↗

NASA NTRS2017

Improvements to Wire Bundle Thermal Modeling for Ampacity Determination

Abstract - Determining current carrying capacity (ampacity) of wire bundles in aerospace vehicles is critical not only to safety but also to efficient design. Published standards provide guidance on determining wire bundle ampacity but offer little flexibility for configurations where wire bundles of mixed gauges and currents are employed with various external insulation jacket surface properties. Thermal modeling has been employed in an attempt to develop techniques to assist in ampacity determination for these complex configurations. An earlier tool allowed analysis of wire bundle configurations but was constrained to configurations comprised of less than 50 elements. Additionally, for vacuum analyses, configurations with very low emittance external jackets suffered from numerical instability in the solution. A new thermal modeler is presented allowing for larger configurations and is not constrained by low bundle jacket surface infrared emittance calculations. Formulation of key internal radiation and interface conductance parameters is discussed including the effects of temperature and ambient air pressure on wire-to-wire thermal conductance. Test cases comparing model-predicted ampacity and that calculated from standards documents are presented.

Steven L Rickman↗

NASA NTRSDate not supplied

LLMs and GenAI Tools to Depict Contributions of Human Systems to Spaceflight Tasks Execution

Recent advancements in Artificial Intelligence and Machine Learning (AI/ML) technologies, particularly Large Language Models (LLMs) capable of sophisticated syntax analysis, offer substantial potential in automating complex processes, thereby saving time and human resources. This study explores the development of an LLM-driven model designed to analyze and categorize a diverse set of Mars mission tasks into 18 predefined Human System Task Categories (HSTCs) based on their textual descriptions. As part of developing the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA projects Performance Risk Model (PRisM) proof-of-concept, we established a framework to project performance scores from small-scale tests onto a preliminary list of Mars tasks. The foundation of our model was a comprehensive spreadsheet populated by NASA experts and clinicians, which detailed each Mars task alongside binary indicators of HSTC involvement. This dataset enabled the initial application of supervised ML, training and testing on existing HSTC labels. The HSTCs were originally defined from a medical system perspective, focusing on task impairments due to deteriorated human health. To expand our model's scope to include categories impacting performance, we face the challenge of generating binary labels (0 or 1) for new categories without pre-existing data. We address this by employing Generative AI (GenAI) software to determine whether a given task involved a new category by asking, "Does task A involve using category B?" We validate our approach by comparing the GenAI's binary classifications with the expert-provided labels for existing HSTCs. Notably, we utilize Ollama [4], a locally hosted GenAI tool that does not require cloud access, thus safeguarding NASA's proprietary data from unauthorized exposure. This study demonstrates the feasibility of leveraging cutting-edge AI tools to advance research, paving the way for automation and rapid decision-making in space exploration.

Mona Matar↗

DOE OSTI2022

Contextual Active Online Model Selection with Expert Advice

How can we collect the most useful labels to learn a model selection policy, when presented with arbitrary heterogeneous data streams? In this paper, we formulate this task as a contextual active model selection problem, where at each round the learner receives an unlabeled data point along with a context. The goal is to output the best model for any given context without obtaining an excessive amount of labels. In particular, we focus on the task of selecting pre-trained classifiers, and propose a contextual active model selection algorithm (CAMS), which relies on a novel uncertainty sampling query criterion defined on a given policy class for adaptive model selection. In comparison to prior art, our algorithm does not assume a globally optimal model. We provide rigorous theoretical analysis for the regret and query complexity under both adversarial and stochastic settings. Our experiments on several benchmark classification datasets demonstrate the algorithm’s effectiveness in terms of both regret and query complexity. Notably, to achieve the same accuracy, CAMS incurs less than 10% of the label cost when compared to the best online model selection baselines on CIFAR10.

Liu, Xuefeng↗

NASA NTRS1986

Computational engine structural analysis

A significant research activity at the NASA Lewis Research Center is the computational simulation of complex multidisciplinary engine structural problems. This simulation is performed using computational engine structural analysis (CESA) which consists of integrated multidisciplinary computer codes in conjunction with computer post-processing for problem-specific application. A variety of the computational simulations of specific cases are described in some detail in this paper. These case studies include: (1) aeroelastic behavior of bladed rotors, (2) high velocity impact of fan blades, (3) blade-loss transient response, (4) rotor/stator/squeeze-film/bearing interaction, (5) blade-fragment/rotor-burst containment, and (6) structural behavior of advanced swept turboprops. These representative case studies are selected to demonstrate the breath of the problems analyzed and the role of the computer including post-processing and graphical display of voluminous output data.

Chamis, C. C.↗

NASA NTRS1986

Computational engine structural analysis

Chamis, C. C.↗

DOE OSTI2023

Many-Body Effects in Aqueous Systems: Synergies Between Interaction Analysis Techniques and Force Field Development

Interaction analysis techniques, including the many-body expansion (MBE), symmetry-adapted perturbation theory, and energy decomposition analysis, allow for an intuitive understanding of complex molecular interactions. We review these methods by first providing a historical context for the study of many-body interactions and discussing how nonadditivities emerge from Hamiltonians containing strictly pairwise-additive interactions. We then elaborate on the synergy between these interaction analysis techniques and the development of advanced force fields aimed at accurately reproducing the Born–Oppenheimer potential energy surface. In particular, we focus on ab initio–based force fields that aim to explicitly reproduce many-body terms and are fitted to high-level electronic structure results. These force fields generally incorporate many-body effects through ( a) parameterization of distributed multipoles, ( b) explicit fitting of the MBE, ( c) inclusion of many-atom features in a neural network, and ( d) coarse-graining of many-body terms into an effective two-body term. We also discuss the emerging use of the MBE to improve the accuracy and speed of ab initio molecular dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1980

Transonic Flow Field Analysis for Wing-Fuselage Configurations

A computational method for simulating the aerodynamics of wing-fuselage configurations at transonic speeds is developed. The finite difference scheme is characterized by a multiple embedded mesh system coupled with a modified or extended small disturbance flow equation. This approach permits a high degree of computational resolution in addition to coordinate system flexibility for treating complex realistic aircraft shapes. To augment the analysis method and permit applications to a wide range of practical engineering design problems, an arbitrary fuselage geometry modeling system is incorporated as well as methodology for computing wing viscous effects. Configuration drag is broken down into its friction, wave, and lift induced components. Typical computed results for isolated bodies, isolated wings, and wing-body combinations are presented. The results are correlated with experimental data. A computer code which employs this methodology is described.

Boppe, C. W.↗

NASA NTRS1992

Finite element analysis of the stiffness of fabric reinforced composites

The objective of this work is the prediction of all three dimensional elastic moduli of textile fabric reinforced composites. The analysis is general enough for use with complex reinforcing geometries and capable of subsequent improvements. It places no restrictions on fabric microgeometry except that the unit cell be determinate and rectangular. The unit cell is divided into rectangular subcells in which the reinforcing geometries are easier to define and analyze. The analysis, based on inhomogeneous finite elements, is applied to a variety of weave, braid, and knit reinforced composites. Some of these predictions are correlated to test data.

Foye, R. L.↗

NASA NTRS2015

Solar Proton Transport within an ICRU Sphere Surrounded by a Complex Shield: Combinatorial Geometry

The 3DHZETRN code, with improved neutron and light ion (Z (is) less than 2) transport procedures, was recently developed and compared to Monte Carlo (MC) simulations using simplified spherical geometries. It was shown that 3DHZETRN agrees with the MC codes to the extent they agree with each other. In the present report, the 3DHZETRN code is extended to enable analysis in general combinatorial geometry. A more complex shielding structure with internal parts surrounding a tissue sphere is considered and compared against MC simulations. It is shown that even in the more complex geometry, 3DHZETRN agrees well with the MC codes and maintains a high degree of computational efficiency.

Wilson, John W.↗

NASA NTRS1986

Sensitivity analysis and approximation methods for general eigenvalue problems

Optimization of dynamic systems involving complex non-hermitian matrices is often computationally expensive. Major contributors to the computational expense are the sensitivity analysis and reanalysis of a modified design. The present work seeks to alleviate this computational burden by identifying efficient sensitivity analysis and approximate reanalysis methods. For the algebraic eigenvalue problem involving non-hermitian matrices, algorithms for sensitivity analysis and approximate reanalysis are classified, compared and evaluated for efficiency and accuracy. Proper eigenvector normalization is discussed. An improved method for calculating derivatives of eigenvectors is proposed based on a more rational normalization condition and taking advantage of matrix sparsity. Important numerical aspects of this method are also discussed. To alleviate the problem of reanalysis, various approximation methods for eigenvalues are proposed and evaluated. Linear and quadratic approximations are based directly on the Taylor series. Several approximation methods are developed based on the generalized Rayleigh quotient for the eigenvalue problem. Approximation methods based on trace theorem give high accuracy without needing any derivatives. Operation counts for the computation of the approximations are given. General recommendations are made for the selection of appropriate approximation technique as a function of the matrix size, number of design variables, number of eigenvalues of interest and the number of design points at which approximation is sought.

Murthy, D. V.↗

DOE OSTI2024

Relating Molecular Properties to the Persistence of Marine Dissolved Organic Matter with Liquid Chromatography–Ultrahigh-Resolution Mass Spectrometry

Marine dissolved organic matter (DOM) contains a complex mixture of small molecules that eludes rapid biological degradation. Spatial and temporal variations in the abundance of DOM reflect the existence of fractions that are removed from the ocean over different time scales, ranging from seconds to millennia. However, it remains unknown whether the intrinsic chemical properties of these organic components relate to their persistence. Here, we elucidate and compare the molecular compositions of distinct DOM fractions with different lability along a water column in the North Atlantic Gyre. Our analysis utilized ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry at 21 T coupled to liquid chromatography and a novel data pipeline developed in CoreMS that generates molecular formula assignments and metrics of isomeric complexity. Clustering analysis binned 14 857 distinct molecular components into groups that correspond to the depth distribution of semilabile, semirefractory, and refractory fractions of DOM. The more labile fractions were concentrated near the ocean surface and contained more aliphatic, hydrophobic, and reduced molecules than the refractory fraction, which occurred uniformly throughout the water column. These findings suggest that processes that selectively remove hydrophobic compounds, such as aggregation and particle sorption, contribute to variable removal rates of marine DOM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Machine learning enabled lineshape analysis in optical two-dimensional coherent spectroscopy

Optical two-dimensional (2D) coherent spectroscopy excels in studying coupling and dynamics in complex systems. The dynamical information can be learned from lineshape analysis to extract the corresponding linewidth. However, it is usually challenging to fit a 2D spectrum, especially when the homogeneous and inhomogeneous linewidths are comparable. We implemented a machine learning algorithm to analyze 2D spectra to retrieve homogeneous and inhomogeneous linewidths. The algorithm was trained using simulated 2D spectra with known linewidth values. The trained algorithm can analyze both simulated (not used in training) and experimental spectra to extract the homogeneous and inhomogeneous linewidths. Finally, this approach can be potentially applied to 2D spectra with more sophisticated spectral features.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Resolving metal binding properties within subunits of a multimeric enzyme Mnx by surface induced dissociation and native ion mobility mass spectrometry

Multi-subunit enzymes function as coordinated assemblies. Yet most enzymatic assays measure the summed output of all populations in solution and cannot easily differentiate contributions of individual subunits. Native mass spectrometry detects intact protein complexes in the gas phase. Surface induced dissociation further releases subunits from protein complexes while retaining compact conformations and bound ligands. Combined with ion mobility, the released subunits can then be carefully monitored for more in-depth structural analysis. Mnx is a unique bacterial multicopper oxidase complex that oxidizes Mn(II) to form MnO 2 minerals, and is composed of three subunits: MnxG, a multicopper oxidase containing the active site, and two accessory proteins, MnxE and MnxF which also bind copper ions. Other known multicopper oxidases do not require accessory proteins, therefore the functions of MnxE and MnxF are not well understood. Here, we use native mass spectrometry with surface induced dissociation and ion mobility to characterize the metal binding properties of Mnx with two metals, catalytic Cu(II) and Mn(II) substrate. We demonstrate our assay can detect subtle structural changes within each subunit, which are presumably related to the allosteric mechanism. We also noticed that ionic strength and solution composition can impact metal binding and must be carefully investigated for such experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Dinuclear Gold(I) Complexes Bearing Alkyl-Bridged Bis(N-heterocyclic carbene) Ligands as Catalysts for Carboxylative Cyclization of Propargylamine: Synthesis, Structure, and Kinetic and Mechanistic Comparison to the Mononuclear Complex [Au(IPr)Cl]

Eight new dinuclear gold(I) complexes, [Au 2 (L)X 2 ] (1–8), were synthesized using a straightforward synthetic procedure under very mild conditions. The complexes have been characterized by NMR spectroscopy, elemental analysis, and single-crystal X-ray structure analysis. Their catalytic activity was investigated in the carboxylative cyclization of propargylamine (PPA). A superior performance in comparison to [Au(IPr)Cl] (9) was obtained for complexes 1 and 2 having an eight-methylene bridge connecting two NHCs with an arene bearing an isopropyl substituent for X = Cl, Br. This prompted more detailed kinetic and mechanistic studies by FTIR comparing dinuclear complex 2 of X = Cl to complex 9. Fortuitously the FTIR studies allowed monitoring of the formation of the products carbamic acid (CA) and carbamate salt (CS), as well as a key cyclized intermediate first discovered by Ikariya. These data allow additional insight into the mechanism as well as the central role which may be played by Au(I) carbamate formation as a higher energy resting state present in the catalytic cycle. In conclusion, the crystal structures of four of the new complexes and a detailed computational study relevant to the role of carbamic acid (CA) and carbamates in the catalytic cycle are also reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗