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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗
NASA NTRS2005

Wirelessly Controllable Inflated Electroactive Polymer (EAP) Reflectors

Inflatable membrane reflectors are attractive for deployable, large aperture, lightweight optical and microwave systems in micro-gravity space environment. However, any fabrication flaw or temperature variation may results in significant aberration of the surface. Even for a perfectly fabricated inflatable membrane mirror with uniform thickness, theory shows it will form a Hencky curve surface but a desired parabolic or spherical surface. Precision control of the surfaceshape of extremely flexible membrane structures is a critical challenge for the success of this technology. Wirelessly controllable inflated reflectors made of electroactive polymers (EAP) are proposed in this paper. A finite element model was configured to predict the behavior of the inflatable EAP membranes under pre-strains, pressures and distributed electric charges on the surface. To explore the controllability of the inflatable EAP reflectors, an iteration algorism was developed to find the required electric actuation for correcting the aberration of the Hencky curve to the desired parabolic curve. The correction capability of the reflectors with available EAP materials was explored numerically and is presented in this paper.

Electroactive polymer (EAP)↗
DOE OSTI2023

An inexact semismooth Newton method with application to adaptive randomized sketching for dynamic optimization

In many applications, one can only access the inexact gradients and inexact hessian times vector products. Thus it is essential to consider algorithms that can handle such inexact quantities with a guaranteed convergence to solution. An inexact adaptive and provably convergent semismooth Newton method is considered to solve constrained optimization problems. In particular, dynamic optimization problems, which are known to be highly expensive, are the focus. A memory efficient semismooth Newton algorithm is introduced for these problems. The source of efficiency and inexactness is the randomized matrix sketching. Further, applications to optimization problems constrained by partial differential equations are also considered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Graphene bilayers with a twist

Near a magic twist angle, bilayer graphene transforms from a weakly correlated Fermi liquid to a strongly correlated two-dimensional electron system with properties that are extraordinarily sensitive to carrier density and to controllable environmental factors such as the proximity of nearby gates and twist-angle variation. Among other phenomena, magic-angle twisted bilayer graphene hosts superconductivity, interaction-induced insulating states, magnetism, electronic nematicity, linear-in-temperature low-temperature resistivity and quantized anomalous Hall states. Here, we highlight some key research results in this field, point to important questions that remain open and comment on the place of magic-angle twisted bilayer graphene in the strongly correlated quantum matter world.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probing the optical properties and toxicological profile of zinc tungstate nanorods

Zinc tungstate is a semiconductor known for its favorable photocatalytic, photoluminescence, and scintillation properties, coupled with its relatively low cost, reduced toxicity, and high stability in biological and catalytic environments. In particular, zinc tungstate evinces scintillation properties, namely the ability to emit visible light upon absorption of energetic radiation such as x rays, which has led to applications not only as radiation detectors but also for biomedical applications involving the delivery of optical light to deep tissue, such as photodynamic therapy and optogenetics. Here, we report on the synthesis of zinc tungstate nanorods generated via an optimized but facile method, which allows for synthetic control over the aspect ratio of the as-synthesized anisotropic motifs via rational variation of the solution pH. Additionally, we investigate the effect of aspect ratio on their resulting photoluminescent and radioluminescent properties. We further demonstrate the potential of these zinc tungstate nanorods for biomedical applications, such as photodynamic therapy for cancer treatment, by analyzing their toxicological profile within cell lines and neurons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Adjustable collimation for dark-field proton radiography contrast enhancement

A dark-field imaging condition established through pre- and post-object beam collimation has been tested for a variety of different settings at the proton radiography facility (pRad) at Los Alamos National Laboratory. This technique facilitates imaging of thin samples and materials with small areal density changes with 800 MeV protons that would otherwise appear nearly transparent for high energy protons. In the configuration that was examined, the pre-object (upstream) collimator is utilized to remove protons with large scattering angles prior to the target object. The post-object collimation entails a combination of a conventional collimator, which eliminates protons with large scattering angles after target interaction, and an inverse collimator. The inverse collimator removes unscattered protons traveling on the beam axis and those with smaller scattering angles up to a desired angle. This establishes a dark-field condition by permitting solely protons that exhibit scattering angles from target interaction within a designated range to contribute to the image. This study explores the potential of combining different sized collimators for pre- and post-object collimation. The objective is to optimize contrast for a range of samples with minimal areal density variations. A series of dark-field conditions are explored employing a remote-controlled collimator wheel and the contrast-to-noise ratio, spatial resolution, and proton transmission are compared for those combinations. It is found that the contrast-to-noise ratio can be substantially enhanced for thin samples and low areal density objects, thereby facilitating capturing high-contrast images of objects that were previously invisible to high energy protons.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Composition dependence of bulk properties in the Co-intercalated transition metal dichalcogenide $\mathrm{Co_{1/3}TaS_2}$

Spontaneous Hall conductivity has recently been reported in the triangular lattice antiferromagnet Co 1/3 TaS 2 under a zero magnetic field. This phenomenon originates from the distinctive noncoplanar triple-Q magnetic ground state, possessing uniform real-space Berry curvature characterized by scalar spin chirality. We investigated the physical properties of Co 1/3 TaS 2 by judiciously controlling the composition, revealing a drastic change in its bulk properties, even by slight variations in cobalt composition, despite the same crystal structure. For 0.299≤x≤0.325, Co x TaS 2 keeps all the characteristics of the ground state consistent with the previous studies—two antiferromagnetic phase transitions at T N1 and T N2 ( N1 ), a large spontaneous Hall conductivity [σ xy (H=0)], and a weak ferromagnetic moment along the c axis. However, samples with x≥0.330 exhibit distinct bulk properties, including the absence of both σ xy (H=0) and the weak ferromagnetic moment. Our neutron diffraction data reveal that Co x TaS 2 with x≥0.330 develops coplanar helical magnetic order with q m1 =(1/3, 0, 0). This is entirely different from what has been seen in x≤0.325, explaining the observed composition dependence.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Comparative Study of Large Language Model Architectures on Frontier

Large language models (LLMs) have garnered significant attention in both the AI community and beyond. Among these, the Generative Pre-trained Transformer (GPT) has emerged as the dominant architecture, spawning numerous variants. However, these variants have undergone pre-training under diverse conditions, including variations in input data, data preprocessing, and training methodologies, resulting in a lack of controlled comparative studies. Here we meticulously examine two prominent open-sourced GPT architectures, GPT-NeoX and LLaMA, leveraging the computational power of Frontier, the world’s first Exascale supercomputer. Employing the same materials science text corpus and a comprehensive end-to-end pipeline, we conduct a comparative analysis of their training and downstream performance. Our efforts culminate in achieving state-of-the-art performance on a challenging materials science benchmark. Furthermore, we investigate the computation and energy efficiency, and propose a computationally efficient method for architecture design. To our knowledge, these pre-trained models represent the largest available for materials science. Our findings provide practical guidance for building LLMs on HPC platforms.

Yin, Junqi↗
DOE OSTI2021

Adaptive Circuit Learning for Quantum Metrology

Quantum sensing is an important application of emerging quantum technologies. We explore whether a hybrid system of quantum sensors and quantum circuits can surpass the classical limit of sensing. In particular, we use optimization techniques to search for encoder and decoder circuits that scalably improve sensitivity under given application and noise characteristics. Furthermore, our approach uses a variational algorithm that can learn a quantum sensing circuit based on platform-specific control capacity, noise, and signal distribution. The quantum circuit is composed of an encoder which prepares the optimal sensing state and a decoder which gives an output distribution containing information of the signal. We optimize the full circuit to maximize the Signal-to-Noise Ratio (SNR). Furthermore, this learning algorithm can be run on real hardware scalably by using the "parameter-shift" rule which enables gradient evaluation on noisy quantum circuits, avoiding the exponential cost of quantum system simulation. We demonstrate up to 13.12x SNR improvement over existing fixed protocol (GHZ), and 3.19x Classical Fisher Information (CFI) improvement over the classical limit on 15 qubits using IBM quantum computer. More notably, our algorithm overcomes the decreasing performance of existing entanglement-based protocols with increased system sizes.

42 ENGINEERING↗
NASA NTRS1971

Wall attachment, flueric crossover ''AND'' gate

Gate performance is not adversely affected by normal dimensional variations encountered in fabrication and it operates throughout full loading range. Flow from one control must be sufficiently monostable to allow initial attachment and upon switching, return to outer wall. Venting must be adequate.

Hellbaum, R. F.↗
NASA NTRS1973

Optical tracking telescope compensation

In order to minimize the effects of parameter variations in the dynamics of an optical tracking telescope, a model referenced parameter adaptive control system is described that - in conjunction with more traditional forms of compensation - achieves a reduction of rms pointing error by more than a factor of six. The adaptive compensation system utilizes open loop compensation, closed loop compensation, and model reference compensation to provide the precise input to force telescope axis velocity to follow the ideal velocity.

Gilbart, J. W.↗
NASA NTRS1980

Advanced technology for controlling pollutant emissions from supersonic cruise aircraft

Gas turbine engine combustor technology for the reduction of pollutant emissions is summarized. Variations of conventional combustion systems and advanced combustor concepts are discussed. Projected results from far term technology efforts aimed at applying the premixed prevaporized and catalytic combustion techniques to aircraft combustion systems indicate a potential for significant reductions in pollutant emission levels.

Duerr, R. A.↗
NASA NTRS1982

Subjective scaling of mental workload in a multi-task environment

Those factors in a multi-task environment that contribute to the operators' "sense" of mental workload were identified. The subjective judgment as conscious experience of mental effort was decided to be the appropriate method of measurement. Thurstone's law of comparative judgment was employed in order to construct interval scales of subjective mental workload from paired comparisons data. An experimental paradigm (Simulated Multi-Task Decision-Making Environment) was employed to represent the ideal experimentally controlled environment in which human operators were asked to "attend" to different cases of Tulga's decision making tasks. Through various statistical analyses it was found that, in general, a lower number of tasks-to-be-processed per unit time (a condition associated with longer interarrival times), results in a lower mental workload, a higher consistency of judgments within a subject, a higher degree of agreement among the subjects, and larger distances between the cases on the Thurstone scale of subjective mental workload. The effects of various control variables and their interactions, and the different characteristics of the subjects on the variation of subjective mental workload are demonstrated.

Daryanian, B.↗