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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,657 records · Page 92

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NASA NTRS2001

Modeling of Fillets in Thin-Walled Structures for Dynamic Analysis

Relatively new developments in manufacturing methods have made it possible to produce machined parts with a wall thickness of less than 0.010". While the parts are being machined. Fillets of relatively large radius to thickness ratios are created by the milling tool. This paper discusses an accurate new technique for finite-element modeling of fillets for dynamic and stiffness analysis using efficient plate elements rather than more computationally intensive, high density solid meshes, A simple filleted cantilever beam of 0.040" thickness, 1.6" length, 1" depth, and 0.250" radius in the corner was modeled using both solid elements and several different plate element geometries. The finite element results were then compared with static and modal testing of a machined sample. The highest-scoring plate element technique uses a bridge of elements that is constructed through the tangent point of the Fillet radius such that the thickness of the element matches tile volume of the fillet. This model produces errors of less than 4.6 percent for static loading and less than 7.4 percent for modal analysis. This simple plate element technique will prove critical for efficient, timely, and accurate dynamic analysis of complex thin-walled structures.

Seugling, Richard M.↗

DOE OSTI2020

Improved band gaps and structural properties from Wannier–Fermi–Löwdin self-interaction corrections for periodic systems

The accurate prediction of band gaps and structural properties in periodic systems continues to be one of the central goals of electronic structure theory. However, band gaps obtained from popular exchange–correlation (XC) functionals (such as LDA and PBE) are severely underestimated partly due to the spurious self-interaction error (SIE) inherent to these functionals. In this work, we present a new formulation and implementation of Wannier function-derived Fermi–Löwdin (WFL) orbitals for correcting the SIE in periodic systems. Since our approach utilizes a variational minimization of the self-interaction energy with respect to the Wannier charge centers (WCC), it is computationally more efficient than the HSE hybrid functional and other self-interaction corrections that require a large number of transformation matrix elements. Here, calculations on several (17 in total) prototypical molecular solids, semiconductors, and wide-bandgap materials show that our WFL self-interaction correction approach gives better band gaps and bulk moduli compared to semilocal functionals, largely due to the partial removal of self-interaction errors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Ansatz-Free Hamiltonian Learning with Heisenberg-Limited Scaling

Learning the unknown interactions that govern a quantum system is crucial for quantum information processing, device benchmarking, and quantum sensing. The problem, known as Hamiltonian learning, is well understood under the assumption that interactions are local, but this assumption may not hold for arbitrary Hamiltonians. Previous methods all require high-order inverse polynomial dependency with precision, unable to surpass the standard quantum limit and reach the gold-standard Heisenberg-limited scaling. Whether Heisenberg-limited Hamiltonian learning is possible without prior assumptions about the interaction structures, a challenge we term ansatz-free Hamiltonian learning , remains an open question. In this work, we present a quantum algorithm to learn arbitrary sparse Hamiltonians without any structure constraints using only black-box queries of the system’s real-time evolution and minimal digital controls to attain Heisenberg-limited scaling in estimation error. Our method is also resilient to state-preparation-and-measurement errors, enhancing its practical feasibility. We numerically demonstrate our ansatz-free protocol for learning physical Hamiltonians and validating analog quantum simulations, benchmarking our performance against the state-of-the-art Heisenberg-limited learning approach. Moreover, we establish a fundamental trade-off between total evolution time and quantum control on learning arbitrary interactions, revealing the intrinsic interplay between controllability and total evolution-time complexity for any learning algorithm. These results pave the way for further exploration into Heisenberg-limited Hamiltonian learning in complex quantum systems under minimal assumptions, potentially enabling new benchmarking and verification protocols.

machine learning↗

DOE OSTI2023

Rapid Fabrication of High Frame Rate Multichannel FTIR Spectrometers

Spectrally resolved signals in the short- to mid-wave infrared (SWIR/MWIR) bands at high-temporal resolution are critical for many national security remote sensing missions. Currently available off the shelf technology can achieve either high temporal resolution or high spectral resolution, but rugged instruments that can achieve both simultaneously remain mostly in the realm of one-off R&D projects. This report documents efforts to demonstrate a new technique for designing and building high resolution, high framerate multichannel FTIR (MC-FTIR) spectrometers that operate in the SWIR/MWIR bands. The core optical element in a MC-FTIR spectrometer is an array of statically-tuned lamellar grating interferometers (LGI). In the original MC-FTIR work these arrays were fabricated using a synchrotron x-ray lithography method. We proposed to instead fabricate these LGI arrays using multiphoton lithography (MPL), a 3D printing technique that can fabricate meso-scale structures with sub-micron precision. Although we were able to fabricate LGI arrays of sufficient size using MPL, the realized optical surfaces had unsuitably high optical form errors, precluding their use in a fieldable instrument. Further advancement in MPL technology may eventually enable fabrication of interferometer-grade LGI arrays.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

A Semi-supervised Hybrid Machine Learning Framework for the Qualification of Resistance Spot Welds

• Industries requiring high structural integrity, including automotive, aerospace, and construction, place considerable significance on weld quality classification. • The inspection normally involves human expertise through predefined quality metrics that are subjective, error-prone, and time-intensive • The challenge to classification model development is the scarcity of labeled data and imbalanced distributions in the data that are labeled. • This work develops a new hybrid methodology that achieves clustering using KMeans++ together with supervised classification to overcome these challenges. • The ensemble-based classifiers were identified as optimal, with accuracy enhancements of up to 8% using the pseudo-labeled dataset. • The work provides practical insight into feature engineering and machine learning integration in industrial quality assurance applications.

Rogers, Jeremy K. [Savannah River National Laborat↗

DOE OSTI2026

Introduction to and comparison of deep learning and optimization approaches to analytical wake modeling of a tilted wind turbine

This paper introduces innovative optimization and deep learning techniques to enhance the prediction of complex wake dynamics in the downstream wind velocity of tilted wind turbines. Traditional methods for calibrating the Bastankhah wake model often lead to increased errors in wind velocity distribution due to overfitting of the local wake characteristics. To address this issue, we propose an additional global optimization step to reduce errors in wind velocity predictions with respect to various wake parameters. Despite this improvement, the Bastankhah model's axisymmetric Gaussian wake shape limits its accuracy for complex wake structures. Therefore, we also propose a deep learning approach, which demonstrates promising results by accurately modeling complex wake shapes across a broader range of tilt angles with minimal computational cost. The deep learning approach achieves near-identical predictions to high-fidelity large-eddy simulations, representing a promising advancement in wake modeling.

17 WIND ENERGY↗

NASA NTRS1973

Competitive evaluation of failure detection algorithms for strapdown redundant inertial instruments.

Seven algorithms for failure detection, isolation, and correction of strapdown inertial instruments in the dodecahedron configuration are competitively evaluated by means of a digital computer simulation that provides them with identical inputs. Their performance is compared in terms of orientation errors and computer burden. The analytical foundations of the algorithms are presented. The features that are found to contribute to superior performance are use of a definite logical structure, elimination of interaction between failures, different thresholds for first and second failures, use of the 'parity' test signals, and avoidance of iteration loops.

Wilcox, J. C.↗

NASA NTRS1985

A fully implicit scheme for global numerical weather prediction

A fast-slow factored scheme is presented for use with shallow-water primitive equation numerical weather prediction models. The technique was developed to reduce the rotational mode errors which arise when the fast and slow terms of the governing differential equations are treated simultaneously. The method factors out the fast and slow terms along the coordinate directions by means of a modified Crank-Nicolson scheme. A finite-difference spatial discretization is carried out in the zonal and meridional directions to reduce the factorization error to near-zero, and that time steps of 60-90 min can be used to obtain acceptably accurate results, even in the presence of fine spatial structures in the flow.

Augenbaum, J. M.↗

NASA NTRS1988

On the design of the dissipative LQG-type controllers

The design of dissipative linear-quadratic-Gaussian-type compensators for positive real plants is considered. It is shown that if the noise covariance matrices (used as weighting matrices) satisfy certain conditions, the compensator has a strictly positive real transfer function matrix. The stability of the resulting closed-loop system is guaranteed regardless of modeling errors as long as the plant remains positive real. In view of this property, the controller is expected to be useful for vibration suppression in large, flexible space structures.

Lozano-Leal, R.↗

NASA NTRS1991

Combinatorial FSK modulation for power-efficient high-rate communications

Deep-space and satellite communications systems must be capable of conveying high-rate data accurately with low transmitter power, often through dispersive channels. A class of noncoherent Combinatorial Frequency Shift Keying (CFSK) modulation schemes is investigated which address these needs. The bit error rate performance of this class of modulation formats is analyzed and compared to the more traditional modulation types. Candidate modulator, demodulator, and digital signal processing (DSP) hardware structures are examined in detail. System-level issues are also discussed.

Wagner, Paul K.↗

NASA NTRS1991

Combinatorial FSK modulation for power-efficient high-rate communications

Wagner, Paul K.↗

NASA NTRS1993

Automatic specification of reliability models for fault-tolerant computers

The calculation of reliability measures using Markov models is required for life-critical processor-memory-switch structures that have standby redundancy or that are subject to transient or intermittent faults or repair. The task of specifying these models is tedious and prone to human error because of the large number of states and transitions required in any reasonable system. Therefore, model specification is a major analysis bottleneck, and model verification is a major validation problem. The general unfamiliarity of computer architects with Markov modeling techniques further increases the necessity of automating the model specification. Automation requires a general system description language (SDL). For practicality, this SDL should also provide a high level of abstraction and be easy to learn and use. The first attempt to define and implement an SDL with those characteristics is presented. A program named Automated Reliability Modeling (ARM) was constructed as a research vehicle. The ARM program uses a graphical interface as its SDL, and it outputs a Markov reliability model specification formulated for direct use by programs that generate and evaluate the model.

Liceaga, Carlos A.↗

NASA NTRS1993

Temperature induced distortions in space telescope mirrors

In this paper, it is illustrated how measured instantaneous coefficients of thermal expansion (CTE) can be accurately taken into account when modeling the structural behavior of space based optical systems. In particular, the importance of including CTE spatial variations in the analysis of optical elements is emphasized. A comparison is made between the CTE's of three optical materials commonly used in the construction of space mirrors (ULE, Zerodur, and beryllium). The overall impact that selection of any one of these materials has on thermal distortions is briefly discussed. As an example of how temperature dependent spatial variations in thermal strain can be accurately incorporated in the thermo-structural analysis of a precision optical system, a finite element model is developed, which is used to estimate the thermally induced distortions in the Hubble Space Telescope's (HST) primary mirror. In addition to the structural analysis, the optical aberrations due to thermally induced distortions are also examined. These calculations indicate that thermal distortions in HST's primary mirror contribute mainly to defocus error with a relatively small contribution to spherical aberration.

Nied, H. F.↗

NASA NTRS1993

Modifying real convolutional codes for protecting digital filtering systems

A novel method is proposed for protecting digital filters from temporary and permanent failures that are not easily detected by conventional fault-tolerant computer design principles, on the basis of the error-detecting properties of real convolutional codes. Erroneous behavior is detected by externally comparing the calculated and regenerated parity samples. Great simplifications are obtainable by modifying the code structure to yield simplified parity channels with finite impulse response structures. A matrix equation involving the original parity values of the code and the polynomial of the digital filter's transfer function is formed, and row manipulations separate this equation into a set of homogeneous equations constraining the modifying scaling coefficients and another set which defines the code parity values' implementation.

Redinbo, G. R.↗

NASA NTRS1988

Maximum likelihood identification for large space structures

This paper examines the use of on-orbit identification based on Maximum Likelihood Estimation (MLE) to provide these high-order, high-accuracy control design models for large space structures (LSS's). First, it outlines a general MLE identification algorithm, together with a covariance-analysis procedure to assess algorithm performance in terms of systematic and stochastic errors. Next, it examines various simplifications appropriate for the LSS identification application. Simplified analytical performance results are presented, as are numerical results to support these analyses. Finally, a graphical interpretation of these results is given.

Barrett, Michael F.↗

NASA NTRS1994

Gravitational coefficients and internal structures of the icy Galilean satellites: An assessment of the Galileo Orbiter mission

Simulated radio tracking data from one flyby of Europa, two flybys of Ganymede, and two flybys of Callisto by the Galileo Orbiter yield estimates of the standard errors in the gravitational coefficient J(sub 2) of 44, 8.5, and 12 (in units of 10(exp -6)) for Europa, Ganymede, and Callisto, respectively; errors in C(sub 22) (in units of 10(exp -6)) are 12, 1.7, and 2.1. These errors are sufficiently small that the values of J(sub 2) and C(sub 22) to be measured by Galileo should suffice to determine if the ice and rock in the satellite interiors are uniformly mixed or separated, so long as the bodies are in hydrostatic equilibrium.

Schubert, G.↗

NASA NTRS1997

A Nonlinear Programming Perspective on Sensitivity Calculations for Systems Governed by State Equations

This paper discusses the calculation of sensitivities. or derivatives, for optimization problems involving systems governed by differential equations and other state relations. The subject is examined from the point of view of nonlinear programming, beginning with the analytical structure of the first and second derivatives associated with such problems and the relation of these derivatives to implicit differentiation and equality constrained optimization. We also outline an error analysis of the analytical formulae and compare the results with similar results for finite-difference estimates of derivatives. We then attend to an investigation of the nature of the adjoint method and the adjoint equations and their relation to directions of steepest descent. We illustrate the points discussed with an optimization problem in which the variables are the coefficients in a differential operator.

Lewis, Robert Michael↗

NASA NTRS2003

Protein Crystal Growth With the Aid of Microfluidics

Protein crystallography is one of three well-known methods to obtain the structure of proteins. A major rate limiting step in protein crystallography is protein crystal nucleation and growth, which is still largely a process conducted by trial-and-error methods. Many attempts have been made to improve protein crystal growth by performing growth in microgravity. Although the use of microgravity appears to improve crystal quality in some attempts, this method has been inefficient because several reasons: we lack a fundamental understanding of macromolecular crystal growth in general and of the influence of microgravity in particular, we have to start with crystal growth conditions in microgravity based on conditions on the ground and finally the hardware does not allow for experimental iteration without reloading samples on the ground. To partially accommodate the disadvantages of the current hardware, we have used microfluidic technology (Lab-on-a-Chip devices) to design the concept of a more efficient crystallization device, suitable for use on the International Space Station and in high-throughput applications on the ground. The concept and properties of microfluidics, the application design process, and the advances in protein crystal growth hardware will be discussed in this presentation. Some examples of proteins crystallized in the new hardware will be discussed, including the differences between conventional crystallization versus crystallization in microfluidics.

vanderWoerd, Mark↗