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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Airloads and Wake Geometry Calculations for an Isolated Tiltrotor Model in a Wind Tunnel

Th tiltrotor aircraft configuration has the potential to revolutionize air transportation by providing an economical combination of vertical take-off and landing capability with efficient, high-speed cruise flight. To achieve this potential it is necessary to have validated analytical tools that will support future tiltrotor aircraft development. These analytical tools must calculate tiltrotor aeromechanical behavior, including performance, structural loads, vibration, and aeroelastic stability, with an accuracy established by correlation with measured tiltrotor data. For many years such correlation has been performed for helicopter rotors (rotors designed for edgewise flight), but correlation activities for tiltrotors have been limited, in part by the absence of appropriate measured data. The recent test of the Tilt Rotor Aeroacoustic Model (TRAM) with a single, U4-scale V-22 rotor in the German-Dutch Wind Tunnel (DNW) now provides an extensive set of aeroacoustic, performance, and structural loads data. This paper will present calculations of airloads, wake geometry, and performance, including correlation with TRAM DNW measurements. The calculations were obtained using CAMRAD II, which is a modern rotorcraft comprehensive analysis, with advanced models intended for application to tiltrotor aircraft as well as helicopters. Comprehensive analyses have received extensive correlation with performance and loads measurements on helicopter rotors. The proposed paper is part of an initial effort to perform an equally extensive correlation with tiltrotor data. The correlation will establish the level of predictive capability achievable with current technology; identify the limitations of the current aerodynamic, wake, and structural models of tiltrotors; and lead to recommendations for research to extend tiltrotor aeromechanics analysis capability. The purpose of the Tilt Rotor Aeroacoustic Model (TRAM) experimental project is to provide data necessary to validate tiltrotor performance and aeroacoustic prediction methodologies and to investigate and demonstrate advanced civil tiltrotor technologies. The TRAM project is a key part of the NASA Short Haul Civil Tiltrotor (SHCT) project. The SHCT project is an element of the Aviation Systems Capacity Initiative within NASA. In April-May 1998 the TRAM was tested in the isolated rotor configuration at the Large Low-speed Facility of the German-Dutch Wind Tunnels (DNW). A preparatory test was conducted in December 1997. These tests were the first comprehensive aeroacoustic test for a tiltrotor, including not only noise and performance data, but airload and wake measurements as well. The TRAM can also be tested in a fill-span configuration, incorporating both rotors Lnd a fuselage model. The wind tunnel installation of the TRAM isolated rotor is shown. The rotor tested in the DNW was a 1/4-scale (9.5 ft diameter) model of the right-hand V-22 proprotor. The rotor and nacelle assembly was attached to an acoustically-treated, isolated rotor test stand through a mechanical pivot (the nacelle conversion axis). The TRAM was analyzed using the rotorcraft comprehensive analysis CAMRAD II. CAMRAD II is an aeromechanical analysis of helicopters and rotorcraft that incorporates a combination of advanced technologies, including multibody dynamics, nonlinear finite elements, and rotorcraft aerodynamics. The trim task finds the equilibrium solution (constant or periodic) for a steady state operating condition, in this case a rotor operating in a wind tunnel. For wind tunnel operation, the thrust and flapping are trimmed to target values. The aerodynamic model includes a wake analysis to calculate the rotor nonuniform induced-velocities, using a free wake geometry. The paper will present the results of CAMRAD II calculations compared to the TRAM DNW measurements for hover performance, helicopter mode performance, and helicopter mode airloads. An example of the hover performance results, comparing both mearements and calculations for the JVX (large scale) and TRAM (small scale) rotors, is shown. An example of the helicopter mode performance, showing the influence of the aerodynamic model (particularly the stall delay model) on the calculated power, induced power, and profile power is also shown. An example of the helicopter mode airloads, showing the influence of various wake and aerodynamic models on the calculations, is shown. Good correlation with measured airloads is obtained using the multiple-trailer wake model. The paper will present additional results, and describe and discuss the aerodynamic behavior in detail.

Johnson, Wayne↗
NASA NTRS2014

Passive Thermal Control for the Low Density Supersonic Decelerator (LDSD) Test Vehicle Spin Motors Sub-System

Future missions to Mars will require improved entry, descent, and landing (EDL) technology over the Viking-heritage systems which recently landed the largest payload to date, the 900 kg Mars Science Laboratory. As a result, NASA's Low Density Supersonic Decelerator (LDSD) project is working to advance the state of the art in Mars EDL systems by developing and testing three key technologies which will enable heavier payloads and higher altitude landing sites on the red planet. These technologies consist of a large 33.5 m diameter Supersonic Disk Sail (SSDS) parachute and two different Supersonic Inflatable Aerodynamic Decelerator (SIAD) devices - a robotic class that inflates to a 6 m diameter torus (SIAD-R), and an exploration class that inflates to an 8 m diameter isotensoid (SIADE). All three technologies will be demonstrated on test vehicles at high earth altitudes in order to simulate the Mars EDL environment. Each vehicle will be carried to altitude by a large helium balloon, released, spun up using spin motors to stabilize the vehicle's trajectory, and accelerated to supersonic speeds using a large solid rocket motor. The vehicle will then be spun down using another set of spin motors, and will deploy either the SIAD-R or SIAD-E, followed by the SSDS parachute until the vehicle lands in the ocean. Component level testing and bounding analysis are used to ensure the survival of system components in extreme thermal environments and predict temperatures throughout the flight. This paper presents a general description of the thermal testing, model correlation, and analysis of the spin motor passive thermal control sub-system to maintain spin motor performance, prescribed vehicle trajectory, and structural integrity of the test vehicle. The spin motor subsystem is predicted to meet its requirements with margin.

thermal analysis↗
DOE OSTI2024

INSPIRED: Inelastic neutron scattering prediction for instantaneous results and experimental design

Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Scalable & Non-Destructive Characterization Strategy to Study Semiconductor/Dielectric Interfaces and Predict Wafer-Level Device Performance

The defect density present at the dielectric-semiconductor interface in an MOS structure directly influences the channel carrier characteristics in semiconductor devices, especially in wide bandgap material systems used in power devices. While these trap defects are typically quantified through electrical characterization of MOS-capacitor test structures, this treatment offers very little insight into the physical nature of interface defects. Such shortcomings demand a physical characterization strategy to guide fabrication optimization. X-ray photoelectron spectroscopy (XPS) is suggested as a viable technique to determine chemical data for dielectric interfaces formed using atomic layer deposition (ALD) on GaN substrates. Previously, 1-D XPS characterization has confirmed the presence of a Ga x O y interlayer between ALD dielectrics and the GaN substrate. In this work, XPS data is serially collected to form 2-D images of an ALD-Al 2 O 3 /GaN interface as a proof-of-concept experiment for in-situ XPS quality monitoring during ALD processing. The information provided by this work reveals some of the challenges for incorporating XPS characterization as an in-situ strategy during fabrication of GaN-based devices. Separately, electrical mapping of a 2-D array of ALD-Al 2 O 3 /GaN MOS-capacitor devices provide a means to quantify the spatial variations in interface quality across a single wafer. Physical characterization techniques, such as time-of-flight secondary ion mass spectroscopy, provide additional chemical information about the Al 2 O 3 /Ga x O y /GaN structure that complement the electrical mapping results. This analysis shows that a higher Ga x O y content correlates with higher interface state defects for trap energies deep in the band gap.

42 ENGINEERING↗
DOE OSTI2026

Augmenting Molecular Graphs with Geometries via Machine Learning Interatomic Potentials

Accurate molecular property predictions require 3D geometries, which are typically obtained using expensive methods such as density functional theory (DFT). Here, we attempt to obtain molecular geometries by relying solely on machine learning interatomic potential (MLIP) models. To this end, we first curate a large-scale molecular relaxation dataset comprising 3.5 million molecules and 300 million snapshots. Then MLIP pre-trained models are trained with supervised learning to predict energy and forces given 3D molecular structures. Once trained, we show that the pre-trained models can be used in different ways to obtain geometries either explicitly or implicitly. First, it can be used to obtain approximate low-energy 3D geometries via geometry optimization. While these geometries do not consistently reach DFT-level chemical accuracy or convergence, they can still improve downstream performance compared to non-relaxed structures. To mitigate potential biases and enhance downstream predictions, we introduce geometry fine-tuning based on the relaxed 3D geometries. Second, the pre-trained models can be directly fine-tuned for property prediction when ground truth 3D geometries are available. Our results demonstrate that MLIP pre-trained models trained on relaxation data can learn transferable molecular representations to improve downstream molecular property prediction and can provide practically valuable but approximate molecular geometries that benefit property predictions. Our code is publicly available at: https://github.com/divelab/AIRS/.

Fu, Cong [Texas A & M Univ., College Station, TX (↗
NASA NTRS2007

The Road to Mach 10: A History of the X-43A Hypersonic Flight Test Program at NASA Dryden...Toward the Future

In terms of technology, the X-43A/Hyper-X represented a singular milestone. After nearly a half century of high hopes, studies, wind tunnel tests, proposals, and canceled projects, a scramjet-powered vehicle had flown. The performance of the engine qualified the scramjet design tools and scaling laws. In turn, the theoretical calculations and ground testing could be used to design more advanced engine concepts. Just as important, both the scramjet and vehicle systems had successfully operated in the variable temperatures and densities of the atmosphere. The X-43A systems were able to maintain the exact flight conditions necessary for the scramjet to operate properly. Control deflections to correct the engine-induced moments were close to pre-flight predictions. When the unexpected occurred, such as when the vehicle pitched up during the cowl opening on the second flight, the control system was sufficiently designed to correct the situation. The airframe and wing structure, the thermal protection material, and the internal conditions of the X-43A performed largely as predicted. The HXLV thermal anomaly during the ascent on the third flight and "the Mach 8 unpleasantness" during the descent indicated that the HXLV and X-43A were not as resilient to aerodynamic heating as expected. The X-43A 's airframe drag and lift both were slightly higher than predicted, but still within preflight uncertainty predictions. The stability and control were as predicted, as was the boundary layer transition. The biggest aerodynamic worry before the flight was the separation of the HXLV and the X- 43A. After all was said and done, this went exactly as predicted, proving that non-symmetrical/high-dynamic pressure stage separations could be performed. This in turn meant that two-stage-to-orbit vehicles employing this technology were feasible. The Hyper-X program also served as a training ground for a new generation of scramjet and hypersonic researchers. This included both NASA and contractor personnel, providing them with experience in ground testing and component development; vehicle design, construction, integration, system checkout, and, ultimately, flight testing and data analysis. Additionally, researchers learned the practical details of running a project within finite budget and time limits, about the ambiguousness of risk assessment, and about the need to spend a significant amount of time and effort dealing with engineering problems, such as those with the FAS, that have nothing to do with the project's research goals. Finally, all those who worked on the X-43A project now know what it is like to spend years transforming an idea into a functional vehicle, only for it to be lost in a matter of seconds. And then to go through years of work to correct the problems, to face the possibility that still more might exist, and finally to savor the triumph of two successful flights. For those who will work on the hypersonic projects that emerge in coming years, these experiences may prove to be the most valuable of all.

Peebles, Curtis↗
DOE OSTI2021

Predicting Energetics Materials’ Crystalline Density from Chemical Structure by Machine Learning

To expedite new molecular compound development, a long-sought goal within the chemistry community has been to predict molecules’ bulk properties of interest a priori to synthesis from a chemical structure alone. In this work, we demonstrate that machine learning methods can indeed be used to directly learn the relationship between chemical structures and bulk crystalline properties of molecules, even in the absence of any crystal structure information or quantum mechanical calculations. We focus specifically on a class of organic compounds categorized as energetic materials called high explosives (HE) and predicting their crystalline density. An ongoing challenge within the chemistry machine learning community is deciding how best to featurize molecules as inputs into machine learning models—whether expert handcrafted features or learned molecular representations via graph-based neural network models—yield better results and why. We evaluate both types of representations in combination with a number of machine learning models to predict the crystalline densities of HE-like molecules curated from the Cambridge Structural Database, and we report the performance and pros and cons of our methods. Our message passing neural network (MPNN) based models with learned molecular representations generally perform best, outperforming current state-of-the-art methods at predicting crystalline density and performing well even when testing on a data set not representative of the training data. However, these models are traditionally considered black boxes and less easily interpretable. Here, to address this common challenge, we also provide a comparison analysis between our MPNN-based model and models with fixed feature representations that provides insights as to what features are learned by the MPNN to accurately predict density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Chemical looping air separation with Sr 0.8 Ca0.2Fe 0.9 Co 0.1 O 3-δ perovskite sorbent: Packed bed modeling, verification, and optimization

Chemical looping air separation (CLAS) represents a promising approach for efficient O 2 production from the air. This present study aims at optimizing the absorber/desorber operations and the separation process with extensive experimental validation. Specifically, a one-dimensional packed bed model was developed to investigate the CLAS operation with a Sr 0.8 Ca 0.2 Fe 0.9 Co 0.1 O 3-δ perovskite sorbent. The redox thermodynamics of perovskite sorbent was measured by TGA and then incorporated into a linear driving force model to describe the O 2 absorption and desorption rates. Both 4-step and 5-step air separation cycle configurations, with various cyclic structures, were performed in a subpilot-scale packed bed. The model predicted O2 purity and productivity were consistent with experimental results, supporting its accuracy and applicability. Parametric analysis and multi-objective optimization were further carried out to assess the performance of CLAS. Both O 2 purity and recovery increased monotonically with the cycle time, airflow rate, steam flow rate, and absorption pressure. Meanwhile, optimal O 2 productivity and power consumption can only be achieved by specific combinations of these parameters. The optimized results showed that CLAS can be highly competitive when compared to conventional pressure swing adsorption (PSA) or cryogenic distillation. The 5-step cycle configuration achieved a minimum power consumption of 118 kW·h for producing 1 ton O 2 with ≥ 95% purity. The maximum O 2 productivity reached 0.0932 g O2 /(g sorbent ·h) with 390 kW·h/ton O 2 of energy consumption (95% pure). The optimization results also indicate that CLAS can potentially be more efficient than cryogenic distillation even when the required O 2 purity is above 99%.

42 ENGINEERING↗
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 OSTI2022

Synthetic genetic circuits as a means of reprogramming plant roots

We report the shape of a plant’s root system influences its ability to reach essential nutrients in the soil and to acquire water during drought. Progress in engineering plant roots to optimize water and nutrient acquisition has been limited by our capacity to design and build genetic programs that alter root growth in a predictable manner. We developed a collection of synthetic transcriptional regulators for plants that can be compiled to create genetic circuits. These circuits control gene expression by performing Boolean logic operations and can be used to predictably alter root structure. This work demonstrates the potential of synthetic genetic circuits to control gene expression across tissues and reprogram plant growth.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1975

Mariner Jupiter/Saturn LCSSE thruster/valve assembly and injection propulsion unit rocket engine assemblies: 0.2-lbf T/VA development and margin limit test report

Thruster valve assemblies (T/VA's) were subjected to the development test program for the combined JPL Low-Cost Standardized Spacecraft Equipment (LCSSE) and Mariner Jupiter/Saturn '77 spacecraft (MJS) programs. The development test program was designed to achieve the following program goals: (1) demonstrate T/VA design compliance with JPL Specifications, (2) to conduct a complete performance Cf map of the T/VA over the full operating range of environment, (3) demonstrate T/VA life capability and characteristics of life margin for steady-state limit cycle and momentum wheel desaturation duty cycles, (4) verification of structural design capability, and (5) generate a computerized performance model capable of predicting T/VA operation over pressures ranging from 420 to 70 psia, propellant temperatures ranging from 140 F to 40 F, pulse widths of 0.008 to steady-state operation with unlimited duty cycle capability, and finally predict the transient performance associated with reactor heatup during any given duty cycle, start temperature, feed pressure, and propellant temperature conditions.

Clark, E. C.↗
NASA NTRS1985

Sensitivity of optimized control systems to minor structural modifications

A procedure for checking whether small changes in a structure have the potential for significant enhancements of its optimized vibration control system is described. The first step in the procedure consists of the calculation of the sensitivity of the parameters of the optimized control system to small changes in the structural parameters. Theh second step consists of the optimization of the structural parameters to produce maximal increase in the performance of the control system with minimal change in the structure. The procedure has been demonstrated for a flexible laboratory structure controlled by several rate-feedback colocated force-actuator velocity-sensor pairs. Significant improvements in the performance of the control system were obtained with small structural modifications. Analytical predictions of such effects have also been validated experimentally.

Haftka, R. T.↗
NASA NTRS1990

The design and flight testing of a long endurance RPV

This paper covers the design process for a long endurance RPV. The 56-pound RPV must operate in the 25-60 knot speed range at low altitudes. An airfoil designed for low-Reynolds-number applications was used with a wing of aspect ratio 22 to reach an estimated L/D(max) of 25. Wing tip feathers were designed to reduce the induced drag. A comparison between the computed aerodynamic predictions and wind-tunnel results is given. The estimated endurance is on the order of 50 hours/gallon of fuel. A three-surface configuration was chosen, and the predicted handling quality and performance results obtained so far are given. The structural challenges in building a lightweight structure for the wing and control surfaces are outlined. The flight test program is currently underway.

Siddiqi, Shahid↗
NASA NTRS1991

Diffusion mechanisms in Ir-coated Re for high-temperature, radiation-cooled rocket thrusters

Materials used for radiation-cooled rocket thrusters must be capable of surviving under extreme conditions of high temperatures and oxidizing environments. Thruster chambers were developed using chemical-vapor-deposited (CVD) Re coated with CVD Ir on the inside surface which is exposed to hot combustion gases. Ir serves as an oxidation barrier protecting the Re which maintains structural integrity at high temperatures. In order to predict and extend the performance limits of these Ir-coated Re thrusters, the diffusion kinetics of CVD materials at temperature are studied. Thruster end ring sections were examined using electron microprobe analysis both before and after exposure to high temperature vacuum environments. The resulting elemental maps for Re, Ir, and Mo in the near-surface region allow identification of diffusion mechanisms operating at these temperatures. Line scans for Ir and Re were fit using a diffusion model to extract relevant diffusion constants. The fastest diffusion process is seen to be grain boundary diffusion with Re diffusing down grain boundaries in the Ir overlayer. The measured dependence of the diffusion rate on temperature will allow prediction of operating lifetimes for these thrusters.

Hamilton, J. C.↗
NASA NTRS1991

Automotive Design

Analytical Design Service Corporation, Ann Arbor, MI, used NASTRAN (a NASA Structural Analysis program that analyzes a design and predicts how parts will perform) in tests of transmissions, engine cooling systems, internal engine parts, and body components. They also use it to design future automobiles. Analytical software can save millions by allowing computer simulated analysis of performance even before prototypes are built.

Source record↗
NASA NTRS2010

Thermal Protection System Cavity Heating for Simplified and Actual Geometries Using Computational Fluid Dynamics Simulations with Unstructured Grids

Thermal Protection System (TPS) Cavity Heating is predicted using Computational Fluid Dynamics (CFD) on unstructured grids for both simplified cavities and actual cavity geometries. Validation was performed using comparisons to wind tunnel experimental results and CFD predictions using structured grids. Full-scale predictions were made for simplified and actual geometry configurations on the Space Shuttle Orbiter in a mission support timeframe.

McCloud, Peter L.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-27111-DND

Rigid aeroshell systems are rapidly approaching the payload limit that current technology can deliver while fitting within the payload envelope of existing launch vehicles. The need for higher entry mass, landing elevation, and more controllability has pushed NASA to improve existing atmospheric entry technologies to further its scientific and exploration capabilities. Hypersonic Inflatable Aerodynamic Decelerators (HIADs) are an emerging technology that allows entry vehicles to deliver larger payloads to higher landing elevations by providing a larger aeroshell diameter than rigid aeroshells. HIADs offer new methods of entry vehicle trajectory control through shape morphing of the inflatable aeroshell. This dissertation explores different concepts of morphing a HIAD by assessing its structural integrity, aerodynamic performance, and systems integration. Analytical models are developed to predict the amount of force required to achieve a desired morphed shape, an actuator and sensor are selected based on performance requirements, and a controller is designed to morph the HIAD through Lift-to-Drag modulation. The actuator and sensor system and controller are then integrated into a small-scale development unit of a HIAD and experimental results are compared to numerical simulations. Conclusions and contributions of this research are presented along with a discussion on further research opportunities of Morphing HIADs.

Adam Milne Slagle↗