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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Design optimization of natural laminar flow fuselages in compressible flow

An optimization method has been developed to design axisymmetric body shapes such as fuselages, nacelles, and external fuel tanks with increased transition Reynolds numbers in subsonic compressible flow. The new design method involves a constraint minimization procedure coupled with analysis of the inviscid and viscous flow regions, and linear stability analysis of the compressible boundary layer. Boundary-layer transition is predicted by a 'hybrid' transition criterion based on Granville's transition criterion and a criterion using linear stability theory coupled with the e(n)-method. A tiptank of a business-jet is used as an example to illustrate that the method can be utilized to design an axisymmetric body shape with extensive natural laminar flow. Boundary layer transition is predicted to occur at a transition Reynolds number of 6.04 x 10 to the 6th on the original tiptank. On the designed body shape, a transition Reynolds number of 7.22 x 10 to the 6th is predicted using compressible linear stability theory coupled with e(n)-method.

Dodbele, Simha S.↗
NASA NTRS1990

Design of laminar flow bodies in compressible flow

An optimization method was developed to design axisymmetric body shapes such as fuselages, nacelles, and external fuel tanks with increased transition Reynolds numbers in subsonic compressible flow. The method involves a constraint minimization procedure coupled with analysis of the inviscid and viscous flow regions, and linear stability analysis of the compressible boundary-layer. Boundary-layer transition is predicted by a 'hybrid' transition criterion based on Granville's transition criterion and a criterion using linear stability theory coupled with the e(sup n)-method. A tiptank of a business jet is used as an example to illustrate that the method can be utilized to design an axisymmetric body shape with extensive natural laminar flow. On the original tiptank boundary layer transition is predicted to occur at a transition Reynolds number of 6.04 x 10 6 on the original tiptank. On the designed body shape a transition Reynolds number of 7.22 x 10 6 is predicted using compressible linear stability theory coupled with e n -method.

Simha S. Dodbele↗
NASA NTRS2015

Hybrid Propulsion In-Situ Resource Utilization Test Facility Results

Hybrid rockets present a promising alternative to conventional chemical propulsion systems for In-Situ Resource Utilization (ISRU) and in-space applications. While they have many benefits for these applications, there are still many small details that require research before they can be adopted into flight systems. A flexible test facility was developed at JPL to test operation of hybrid motors at small scale (5 cm outer diameter fuel grains) over a range of conditions. Specifically, this paper studies two of the major advantages: low temperature performance and throttling. Paraffin-based hybrid rockets are predicted to have good performance at low temperatures. This could significantly decrease the overall system mass by minimizing the thermal conditioning required for Mars or outer planet applications. Therefore, the coefficient of thermal expansion and glass transition of paraffin are discussed. Additionally, deep throttling has been considered for several applications. This was a natural starting point for hotfire testing using the hybrid propulsion ISRU test facility. Additionally, short length to diameter ratio (L/D) fuel grains are tested to determine if these systems can be packaged into geometrically constrained spaces.

Karp, Ashley Chandler↗
DOE OSTI2024

Machine learning for the redox potential prediction of molecules in organic redox flow battery

Here, organic redox flow batteries (ORFB) are recognized as an innovative technology for the large-scale storage of renewable energy. The redox potential of organic redox-active molecules plays a vital role in their performance. Advanced screening techniques like high-throughput experiment and machine learning (ML) have significantly enhanced organic material performance and transformed the field of ORFB. However, the scarcity of experimental data poses a considerable challenge for ML model development in this domain. In our study, we developed lightweight graph-based Gaussian process regression (GPR) models with GPU-accelerated marginalized graph kernel and hybrid kernel to predict the redox potentials of organic redox-active molecules for ORFBs, specifically focusing on small datasets. To evaluate model accuracy, we created a new experimental database of organic redox-active molecules by the data from hundreds of published papers and assembled previous computational datasets. We also considered some key parameters, such as pH conditions and solvent type, to assess their impact on redox potential prediction. Our GPR model predicted redox potentials with high accuracy across all datasets using minimal training data. The study provides powerful tools for molecule screening and design and delivers valuable guidance on designing training datasets for costly experiments.

25 ENERGY STORAGE↗
DOE OSTI2026

Continental-Scale Controls on Hyporheic Respiration Revealed by Knowledge-Guided Machine Learning

Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.

Zheng, Jianqiu↗
DOE OSTI2024

Engineering Small HOMO–LUMO Gaps in Polycyclic Aromatic Hydrocarbons with Topologically Protected States

Topological phases in laterally confined low-dimensional nanographenes have emerged as versatile design tools that can imbue otherwise unremarkable materials with exotic band structures ranging from topological semiconductors and quantum dots to intrinsically metallic bands. The periodic boundary conditions that define the topology of a given lattice have thus far prevented the translation of this technology to the quasi-zero-dimensional (0D) domain of small molecular structures. Here, we describe the synthesis of a polycyclic aromatic hydrocarbon (PAH) featuring two localized zero modes (ZMs) formed by the topological junction interface between a trivial and nontrivial phase within a single molecule. First-principles density functional theory calculations predict a strong hybridization between adjacent ZMs that gives rise to an exceptionally small HOMO–LUMO gap. Scanning tunneling microscopy and spectroscopy corroborate the molecular structure of 9/7/9-double quantum dots and reveal an experimental quasiparticle gap of 0.16 eV, corresponding to a carbon-based small molecule long-wavelength infrared (LWIR) absorber.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

MHD stability of negative triangularity DIII-D plasmas

Abstract Negative triangularity (NT) experiments in DIII-D point to an emergent reactor scenario free of sawteeth, endowed with benign, nondisruptive n = 2 tearing modes, which experience q min ⩾ 1 similar to the positive triangularity hybrid scenario. Plasmas exhibiting this behavior attain β N > 3 , high enough to reconsider long held views of NT stability. Ideal MHD and tearing stability analysis of well-diagnosed equilibrium reconstructions of experimental hybrid-like plasmas predict that among shape parameters, MHD stability limits are only sensitive to average triangularity. Operation is predicted to be possible at β N relevant to upcoming tokamaks and commercial NT reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

ExaWind: A multifidelity modeling and simulation environment for wind energy

We introduce the open-source ExaWind modeling and simulation environment for wind energy. The primary physics codes of ExaWind are Nalu-Wind and OpenFAST. Nalu-Wind is a wind-focused computational fluid dynamics (CFD) code that is coupled to the whole-turbine simulation code OpenFAST. The ExaWind environment was created under U.S. Department of Energy funding to achieve the highest-fidelity simulations of wind turbines and wind farms to date, with the goal of enabling disruptive changes to turbine and plant design and operation. Innovation will be gleaned through better understanding of the complex flow dynamics in wind farms, including wake evolution and the impact of wakes on downstream turbines and turbulent flow from complex terrain. High-fidelity predictive simulations employ hybrid turbulence models, geometry/boundary-layer-resolving CFD meshes, atmospheric turbulence, nonlinear structural dynamics, and fluid-structure interaction. While there is an emphasis on very high-fidelity simulations (e.g., blade resolved with full fluid-structure coupling), the ExaWind environment supports lower-fidelity modeling capabilities including actuator-line and -disk methods. Important in the development of ExaWind codes is that the codes scale well on today's largest petascale supercomputers and on the next-generation platforms that will enable exascale computing.

17 WIND ENERGY↗
DOE OSTI2022

Control and Calibration of GlueX Central Drift Chamber Using Gaussian Process Regression

The Gluonic Excitations (GlueX) experiment is designed to search for exotic hybrid mesons using photoproduction, and to study the hybrid meson spectrum predicted from Lattice Quantum Chromodynamics. For the first time, the GlueX Central Drift Chamber was controlled autonomously using machine learning (ML) to calibrate in real time while recording cosmic ray tracks. We demonstrate the ability of a Gaussian Process to predict the gain correction calibration factor used to determine a high voltage setting that will stabilize the CDC gain in response to changing environmental conditions; this is in contrast to the traditional, computationally expensive method of calibrating raw data after data collection is complete.

McSpadden, Helen↗
DOE OSTI2025

An Efficient Storage-Driven Machine Learning Model for Performance in the Era of Multimodal Scientific Data

Scientific workflows are increasingly relying on machine learning (ML), simulation, and hybrid techniques to predict, understand, and optimize the behavior of complex experiments. High-performance computing has greatly improved researchers’ ability to acquire diverse data modalities in these workflows. Recent studies suggest that the performance of machine learning models can be improved by integrating data from various sources. Unfortunately, these workloads pose unprecedent pressure on the network storage to meet the demands associated with accessing these multimodal data. To mitigate the impact of intensive IO, we propose a solution that utilizes a multi-tier High-Performance Computing (HPC) distributed storage and data processing framework, placing computation where the data resides for better performance. By adopting this project, the scientific community will gain new opportunities to explore multimodal storage-driven possibilities, integrating multiple scientific data sources with advanced streaming frameworks. Additionally, our framework effectively utilizes computing resources and bridges the gaps identified by HPC experts. Our proposed approach tackles scalability and persistence challenges by leveraging native persistency, which has posed difficulties in traditional approaches. Furthermore, we seek to enhance fault-tolerance and load-balance of computations by leveraging real-time streaming in diverse scientific computing environments, thereby propelling advanced scientific computing research into the next generation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Synthetic Pathways to gamma-Graphyne and Related Allotropes of Carbon

Graphynes, two-dimensional carbon lattices combining sp 1 and sp 2 hybridized atoms, were predicted theoretically more than three decades ago, but few structures have been realized to date. These carbons are believed to possess remarkable mechanical and electronic properties, including high charge carrier mobilities comparable to those in graphene (10 4 to 10 5 cm 2 V -1 s -1 ). Unlike graphene, certain graphynes are predicted to be intrinsic semiconductors. Among these intriguing structures, γ-graphyne stands out as the structurally simplest and most symmetric sp 1 /sp 2 lattice. γ-Graphyne was first theorized in 1987. In contrast with graphene, γ-graphyne will be a semiconductor with a small band gap suitable for fabrication of electronic devices. This solves one of the fundamental problems of carbon-based electronics, the necessity for inducing a band gap in graphene. γ-Graphyne has the potential to form the basis for the next generation of carbon-based electronics operating at speeds unattainable by traditional silicon chips. Unlike silicon, γ-graphyne is a direct band gap semiconductor, and it will feature exceptional strength comparable to that of other 2D carbon allotropes. Such combination of properties may enable a new generation of highly efficient, ultra-light and flexible solar cells. Despite being a potentially “magical” material, γ-graphyne remained synthetically elusive for over three decades. The primary goals of this project were: (1) Synthesis of bulk γ-graphyne phases through solution-phase 2D polymerizations; (2) Experimental exploration of the physical and chemical properties of γ-graphyne; and (3) Mechanistic and theoretical studies of the novel chemical transformations developed in Goal 1. Common pyrolytic and vapor-deposition methodologies used for the synthesis of graphitic allotropes are unsuitable for graphyne and other sp 1 -contaning structures, as acetylenes readily convert to graphene and amorphous carbon at high temperatures. In contrast, this proposal is based on solution-based 2D polymerization. The major advantages of this approach over the traditional high temperature techniques are the potential to adjust the structure of the material with atomic precision, and the possibility of using structurally complex and relatively fragile repeat units. The outcomes of this research can revolutionize carbon nanotechnology, expanding the field’s structural toolbox beyond primarily graphitic and benzenoid structures. Understanding the chemistry of sp 1 carbon allotropes can lead to entirely new classes of structures with unique properties, including graphyne ribbons, nanotubes, quantum dots, and heterostructures with other 2D materials. Furthermore, the development of reliable and robust synthetic pathways towards periodic covalent molecular sheets with atomically precise structures shall have a profound impact on chemistry and materials science.

2D polymerization↗
NASA NTRS1995

Assessment of computational models for thermoelectroelastic multilayered plates

A study is made of the accuracy of the steady-state (static) thermoelectroelastic response of multilayered hybrid composite plates predicted by five modeling approaches, based on two-dimensional plate theories. The plates consist of a combination of fiber-reinforced and piezothermoelastic layers. The standard of comparison is taken to be the exact three-dimensional thermoelectroelastic solutions, and the quantities compared include gross response characteristics (e.g., strain energy components, and average through-the-thickness displacements); detailed, through-the-thickness distributions of displacements and stresses; and sensitivity coefficients of the response quantities (derivatives of the response quantities with respect to material parameters of the plate). The modeling approaches considered include first-order theory; third-order theory; discrete-layer theory (with piecewise linear variation of the in-plane displacements, temperature and electric potential, in the thickness direction); and two predictor-corrector procedures.

Tang, Yvette T.↗
NASA NTRS2005

Effect of Silicon Nitride Balls and Rollers on Rolling Bearing Life

Three decades have passed since the introduction of silicon nitride rollers and balls into conventional rolling-element bearings. For a given applied load, the contact (Hertz) stress in a hybrid bearing will be higher than an all-steel rolling-element bearing. The silicon nitride rolling-element life as well as the lives of the steel races were used to determine the resultant bearing life of both hybrid and all-steel bearings. Life factors were determined and reported for hybrid bearings. Under nominal operating speeds, the resultant calculated lives of the deep-groove, angular-contact, and cylindrical roller hybrid bearings with races made of post-1960 bearing steel increased by factors of 3.7, 3.2, and 5.5, respectively, from those calculated using the Lundberg-Palmgren equations. An all-steel bearing under the same load will have a longer life than the equivalent hybrid bearing under the same conditions. Under these conditions, hybrid bearings are predicted to have a lower fatigue life than all-steel bearings by 58 percent for deep-groove bearings, 41 percent for angular-contact bearings, and 28 percent for cylindrical roller bearings.

Zaretsky, Erwin V.↗
DOE OSTI2021

The Role of Interface in Additively Manufactured Interpenetrating Composites

Additively Manufactured Interpenetrating Composites (AMIPCs) are a relatively new metal-metal chain composite in development for use in high energy absorption systems. In this system, reinforcing phase of additively manufactured continuous lattice configurations 316L austenitic stainless-steel is in melt infiltrated with a matrix phase of A356 aluminum-silicon casting alloy. Measurements and observations of this material system have shown that weakly bonded or open/porous interface between the reinforcement and matrix phases exhibits dramatically different mechanical properties of AMIPCs, which is not currently well understood. In this work, Finite Element Models (FEM) are used to model the effects of interfaces between the composite phases. Mechanical tensile tests measurements of various composite volume fractions and varying degrees of casting infiltration are also examined and used to show consistency with the FEM results. The outcome provides insight into material design criteria and performance predictions for new hybrid material systems with exceptional damage tolerance.

Allen, Jason↗
NASA NTRS2013

Auralization of Hybrid Wing Body Aircraft Flyover Noise from System Noise Predictions

System noise assessments of a state-of-the-art reference aircraft (similar to a Boeing 777-200ER with GE90-like turbofan engines) and several hybrid wing body (HWB) aircraft configurations were recently performed using NASA engine and aircraft system analysis tools. The HWB aircraft were sized to an equivalent mission as the reference aircraft and assessments were performed using measurements of airframe shielding from a series of propulsion airframe aeroacoustic experiments. The focus of this work is to auralize flyover noise from the reference aircraft and the best HWB configuration using source noise predictions and shielding data based largely on the earlier assessments. For each aircraft, three flyover conditions are auralized. These correspond to approach, sideline, and cutback operating states, but flown in straight and level flight trajectories. The auralizations are performed using synthesis and simulation tools developed at NASA. Audio and visual presentations are provided to allow the reader to experience the flyover from the perspective of a listener in the simulated environment.

Rizzi, Stephen A.↗
NASA NTRS2005

Measurement and Prediction of the Thermomechanical Response of Shape Memory Alloy Hybrid Composite Beams

Previous work at NASA Langley Research Center (LaRC) involved fabrication and testing of composite beams with embedded, pre-strained shape memory alloy (SMA) ribbons within the beam structures. That study also provided comparison of experimental results with numerical predictions from a research code making use of a new thermoelastic model for shape memory alloy hybrid composite (SMAHC) structures. The previous work showed qualitative validation of the numerical model. However, deficiencies in the experimental-numerical correlation were noted and hypotheses for the discrepancies were given for further investigation. The goal of this work is to refine the experimental measurement and numerical modeling approaches in order to better understand the discrepancies, improve the correlation between prediction and measurement, and provide rigorous quantitative validation of the numerical analysis/design tool. The experimental investigation is refined by a more thorough test procedure and incorporation of higher fidelity measurements such as infrared thermography and projection moire interferometry. The numerical results are produced by a recently commercialized version of the constitutive model as implemented in ABAQUS and are refined by incorporation of additional measured parameters such as geometric imperfection. Thermal buckling, post-buckling, and random responses to thermal and inertial (base acceleration) loads are studied. The results demonstrate the effectiveness of SMAHC structures in controlling static and dynamic responses by adaptive stiffening. Excellent agreement is achieved between the predicted and measured results of the static and dynamic thermomechanical response, thereby providing quantitative validation of the numerical tool.

Davis, Brian↗
DOE OSTI2020

Probabilistic modeling and prediction of out-of-plane unidirectional composite lamina properties

Computational simulation provides an efficient means to predict the behavior of customized hybrid material configurations using validated, physics-based models. One limitation to this approach is the quality and quantity of available data to characterize the many constituent input properties. Therefore, a systematic approach to identify the most influential parameters on the hybrid behavior and quantify the corresponding uncertainty in predictive capabilities is required. Here, an approach using Bayesian multimodel inference and imprecise global sensitivity analysis is presented to investigate the effects of sparse constituent data on the prediction of composite material properties. The methodology allows the identification, using quantified uncertainties, of the most influential constituent material parameters for specified homogenized properties. This sensitivity analysis further enables a dimension reduction when assessing the influence of uncertainties on material properties and can be used to inform testing programs of the constituent properties that require additional testing/data collection in order to minimize uncertainty in macro-scale composite properties. The methodology is specifically demonstrated on the prediction and sensitivity analysis of out-of-plane mechanical properties of a unidirectional lamina.

36 MATERIALS SCIENCE↗