SEARCH · Engineering Papers

Results for “High Temperature Methods”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 919 records · Page 51

All sources NASA NTRS DOE OSTI

DOE OSTI2023

New coal char-based bricks: Effects of curing temperature, humidity, pressing pressure, and addition of superplasticizer on the physical, mechanical, and thermal properties

Coal char, as a sustainable and eco-friendly material, holds significant potential for use in new construction materials, specifically, coal char-based bricks. This study employed the pre-pressing method to create char bricks containing high char content of 70%. The impact of various curing temperatures (20, 40, 60 °C), humidity levels (15% and 90%), and pressing pressures (3.5, 7, and 10 MPa) on the density, X-ray diffraction, compressive strength, and thermal conductivity of char-based samples were examined. The addition of superplasticizer and the performance of char bricks were assessed by comparing them to traditional clay bricks and corresponding standards. The study discovers that the temperature of 40 °C enhances the early 7-day strength of char brick samples, while the highest 28-day strength is observed in char bricks at a temperature of 20 °C and humidity of 90%. Compared to conventional clay bricks (with density of 1.9 g/cm3, thermal conductivity of 0.39-0.63 W/mK, compressive strength of 10-20 MPa), the proposed char bricks exhibit lower density (~0.8 g/cm 3 ), lower thermal conductivity (0.26-0.35 W/mK), and good performance in compressive strength (up to 15 MPa). Lastly, coal char-based bricks with high char content demonstrate significant advantages over traditional clay bricks, making them a sustainable and environmentally friendly building material option.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A scalable and tunable thermoreversible polymer for 3D human pluripotent stem cell biomanufacturing

Human pluripotent stem cells (hPSCs) are an exciting and promising source to enable cell replacement therapies for a variety of unmet medical needs. Though hPSCs can be successfully derived into numerous physiologically relevant cell types, effective translation to the clinic is limited by challenges in scalable production of high-quality cells, cellular immaturity following the differentiation process, and the use of animal-derived components in culture. To address these limitations, we have developed a fully defined, reproducible, and tunable thermoreversible polymer for high-quality, scalable 3D cell production. Our reproducible synthesis method enables precise control of gelation temperature (24°C–32°C), hydrogel stiffness (100–4000 Pa), and the prevention of any unintended covalent crosslinking. After material optimization, we demonstrated hPSC expansion, pluripotency maintenance, and differentiation into numerous lineages within the hydrogel. Overall, this 3D thermoreversible hydrogel platform has broad applications in scalable, high-quality cell production to overcome the biomanufacturing burden of stem cell therapy.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Residually Stressed Bimaterial Beam Specimen for Measuring Environmentally Assisted Crack Growth

Background: Subcritical crack growth can occur in a brittle material when the stress intensity factor is smaller than the fracture toughness if an oxidizing agent (such as water) is present at the crack tip. Objective: Here we present a novel bi-material beam specimen which can measure environmentally assisted crack growth rates. The specimen is “self-loaded” by residual stress and requires no external loading. Methods: Two materials with different coefficient of thermal expansion are diffusion bonded at high temperature. After cooling to room temperature a subcritical crack is driven by thermal residual stresses. A finite element model is used to design the specimen geometry in terms of material properties in order to achieve the desired crack tip driving force. Results: The specimen is designed so that the crack driving force decreases as the crack extends, thus enabling the measurement of the crack velocity versus driving force relationship with a single test. The method is demonstrated by measuring slow crack growth data in soda lime silicate glass and validated by comparison to previously published data. Conclusions: The self-loaded nature of the specimen makes it ideal for measuring the very low crack velocities needed to predict brittle failure at long lifetimes.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Dislocation half-loop control for optimal V-defect density in GaN-based light emitting diodes

V-defects are morphological defects that typically form on threading dislocations during epitaxial growth of $(0001)$-oriented GaN layers. A V-defect is a hexagonal pyramid-shaped depression with six {$10\bar{1}1$}-oriented sidewalls. These semipolar sidewalls have a lower polarization barrier than the polarization barriers present between the polar c-plane quantum wells and quantum barriers and can laterally inject carriers directly into quantum wells in GaN-based light emitting diodes (LEDs). This is especially important, as the high polarization field in c-plane GaN is a significant factor in the high forward voltage of GaN LEDs. The optimal V-defect density for efficient lateral carrier injection in a GaN LED (∼10 9 cm −2 ) is typically an order of magnitude higher than the threading dislocation density of GaN grown on patterned sapphire substrates (∼10 8 cm −2 ). Pure-edge dislocation loops have been known to exist in GaN, and their formation into large V-defects via low-temperature growth with high Si-doping has recently been studied. Here, in this work, we develop a method for pure-edge threading dislocation half-loop formation and density control via disilane flow, growth temperature, and thickness of the half-loop generation layer. We also develop a method of forming the threading dislocation half-loops into V-defects of comparable size to those originating from substrate threading dislocations.

Crystallographic defects↗

DOE OSTI2025

Calibrating a finite-strain phase-field model of fracture for bonded granular materials with uncertainty quantification

To study the mechanical behavior of mock high explosives, an experimental and simulation program was developed to calibrate, with quantified uncertainty, a material model of the bonded granular material Idoxuridine and nitroplasticized Estane-5703. This paper reports on the efficacy of such a framework as a generalizable methodology for calibrating material models against experimental data with uncertainty quantification. Additionally, this paper studies the effect of two manufacturing temperatures and three initial granular configurations on the unconfined compressive behavior of the resulting bonded granular materials. In each of these cases, the same calibration framework was used; in that, hundreds of high-fidelity direct numerical simulations using a new, graphics processing unit-enabled, high-performance finite element method software, Ratel, were run to calibrate a finite-strain phase-field fracture model against experimental data. It was found that manufacturing temperature influenced the elastic response of the mock high explosives, with higher temperatures yielding a stiffer response. By contrast, it was found that the initial configuration of the grains had a negligible impact on the overall behavior of the mock high explosives though it remains possible that local damage accumulation within the specimens could be altered by the initial configurations. Overall, the calibration framework was successful at creating well-calibrated models, showing its usefulness as an engineering and scientific tool.

36 MATERIALS SCIENCE↗

NASA NTRS2008

New Optical Constants of Amorphous and Crystalline H2O-ice, 3-20_m

We will present new optical constants forth amorphous and crystalline H2O-ice in the spectral range 3-20 _m. Our new measurements provide high temperature resolution for crystalline H2O-ice, 10 K intervals from 20-150 K, including temperatures relevant to Solar System ices. We have found that the shape of the 3 _m feature in amorphous H2O-ice is strongly dependant on deposition temperature and the high and low density phases of amorphous H2O-ice are not easily distinguishable. We will present methods of measuring the change in band shape with phase and temperature. We acknowledge financial support from the NASA Origins of the Solar System Program and the NASA Planetary Geology and Geophysics Program.

Mastrapa, Rachel Michelle Elizab↗

DOE OSTI2023

Early crystallization of amorphous selenium under high pressure studied by synchrotron XRD method

Abstract The amorphous selenium (a-Se) was studied via x-ray diffraction (XRD) under pressures ranging from ambient pressure up to 30 GPa at room temperature to study its high-pressure behavior. Two compressional experiments on a-Se samples, with and without heat treatment, respectively, were conducted. Contrary to the previous reports that a-Se crystallized abruptly at around 12 GPa, in this work we report an early partially crystallized state at 4.9 GPa before completing the crystallization at around 9.5 GPa based on in-situ high pressure XRD measurements on the a-Se with 70 °C heat treatment. In comparison, crystallization pressure on another a-Se sample without thermal treatment history was observed to be 12.7 GPa, consistent with the previously reported crystallization pressure. Thus, it is proposed in this work that prior heat treatment of a-Se can result in an earlier crystallization under high pressure, which helps to understand the possible mechanism caused by the previous controversial reports on pressure induced crystallization behavior in a-Se.

Physics↗

NASA NTRS1995

Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models

This study outlines a method for the estimation of regional patterns of surface moisture availability (M(sub 0)) and fractional vegetation (Fr) in the presence of spatially variable vegetation cover. The method requires relating variations in satellite-derived (NOAA, Advanced Very High Resolution Radiometer (AVHRR)) surface radiant temperature to a vegetation index (computed from satellite visible and near-infrared data) while coupling this association to an inverse modeling scheme. More than merely furnishing surface soil moisture values, the method constitues a new conceptual and practical approach for combining thermal infrared and vegetation index measurements for incorporating the derived values of M(sub 0) into hydrologic and atmospheric prediction models. Application of the technique is demonstrated for a region in and around the city of Newcastle upon Tyne situated in the northeast of England. A regional estimate of M(sub 0) is derived and is probabbly good for fractional vegetation cover up to 80% before errors in the estimated soil water content become unacceptably large. Moreover, a normalization scheme is suggested from which a nomogram, `universal triangle,' is constructed and is seen to fit the observed data well. The universal triangle also simplifies the inclusion of remotely derived M(sub 0) in hydrology and meteorological models and is perhaps a practicable step toward integrating derived data from satellite measurements in weather forecasting.

Gillies, Robert R.↗

NASA NTRS2016

Normalized Temperature Contrast Processing in Infrared Flash Thermography

The paper presents further development in normalized contrast processing used in flash infrared thermography method. Method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided. Methods of converting image contrast to temperature contrast and vice versa are provided. Normalized contrast processing in flash thermography is useful in quantitative analysis of flash thermography data including flaw characterization and comparison of experimental results with simulation. Computation of normalized temperature contrast involves use of flash thermography data acquisition set-up with high reflectivity foil and high emissivity tape such that the foil, tape and test object are imaged simultaneously. Methods of assessing other quantitative parameters such as emissivity of object, afterglow heat flux, reflection temperature change and surface temperature during flash thermography are also provided. Temperature imaging and normalized temperature contrast processing provide certain advantages over normalized image contrast processing by reducing effect of reflected energy in images and measurements, therefore providing better quantitative data. Examples of incorporating afterglow heat-flux and reflection temperature evolution in flash thermography simulation are also discussed.

Koshti, Ajay M.↗

NASA NTRS2016

A Method to Measure and Estimate Normalized Contrast in Infrared Flash Thermography

Koshti, Ajay M.↗

NASA NTRS2013

NASA Tech Briefs, Februrary 2013

Topics covered include: Measurements of Ultra-Stable Oscillator (USO) Allan Deviations in Space; Gaseous Nitrogen Orifice Mass Flow Calculator; Validation of Proposed Metrics for Two-Body Abrasion Scratch Test Analysis Standards; Rover Low Gain Antenna Qualification for Deep Space Thermal Environments; Automated, Ultra-Sterile Solid Sample Handling and Analysis on a Chip; Measuring and Estimating Normalized Contrast in Infrared Flash Thermography; Spectrally and Radiometrically Stable, Wideband, Onboard Calibration Source; High-Reliability Waveguide Vacuum/Pressure Window; Methods of Fabricating Scintillators With Radioisotopes for Beta Battery Applications; Magnetic Shield for Adiabatic Demagnetization Refrigerators (ADR); CMOS-Compatible SOI MESFETS for Radiation-Hardened DC-to-DC Converters; Silicon Heat Pipe Array; Adaptive Phase Delay Generator; High-Temperature, Lightweight, Self-Healing Ceramic Composites for Aircraft Engine Applications; Treatment to Control Adhesion of Silicone-Based Elastomers; High-Temperature Adhesives for Thermally Stable Aero-Assist Technologies; Rockballer Sample Acquisition Tool; Rock Gripper for Sampling, Mobility, Anchoring, and Manipulation; Advanced Magnetic Materials Methods and Numerical Models for Fluidization in Microgravity and Hypogravity; Data Transfer for Multiple Sensor Networks Over a Broad Temperature Range; Using Combustion Synthesis to Reinforce Berms and Other Regolith Structures; Visible-Infrared Hyperspectral Image Projector; Three-Axis Attitude Estimation With a High-Bandwidth Angular Rate Sensor Change_Detection.m; AGATE: Adversarial Game Analysis for Tactical Evaluation; Ionospheric Simulation System for Satellite Observations and Global Assimilative; Modeling Experiments (ISOGAME); An Extensible, User- Modifiable Framework for Planning Activities; Mission Operations Center (MOC) - Precipitation Processing System (PPS) Interface Software System (MPISS); Automated 3D Damaged Cavity Model Builder for Lower Surface Acreage Tile on Orbiter; Mixed Linear/Square-Root Encoded Single-Slope Ramp Provides Low-Noise ADC with High Linearity for Focal Plane Arrays; RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers; Powered Descent Guidance with General Thrust-Pointing Constraints; X-Ray Detection and Processing Models for Spacecraft Navigation and Timing; and Extreme Ionizing-Radiation-Resistant Bacterium

Source record↗

DOE OSTI2022

Machine learning molecular dynamics simulations toward exploration of high-temperature properties of nuclear fuel materials: case study of thorium dioxide

Predicting materials properties of nuclear fuel compounds is a challenging task in materials science. Their thermodynamical behaviors around and above the operational temperature are essential for the design of nuclear reactors. However, they are not easy to measure, because the target temperature range is too high to perform various standard experiments safely and accurately. Moreover, theoretical methods such as first-principles calculations also suffer from the computational limitations in calculating thermodynamical properties due to their high calculation-costs and complicated electronic structures stemming from f-orbital occupations of valence electrons in actinide elements. Here, we demonstrate, for the first time, machine-learning molecular-dynamics to theoretically explore high-temperature thermodynamical properties of a nuclear fuel material, thorium dioxide. The target compound satisfies first-principles calculation accuracy because f-electron occupation coincidentally diminishes and the scheme meets sampling sufficiency because it works at the computational cost of classical molecular-dynamics levels. We prepare a set of training data using first-principles molecular dynamics with small number of atoms, which cannot directly evaluate thermodynamical properties but captures essential atomistic dynamics at the high temperature range. Then, we construct a machine-learning molecular-dynamics potential and carry out large-scale molecular-dynamics calculations. Consequently, we successfully access two kinds of thermodynamic phase transitions, namely the melting and the anomalous λ transition induced by large diffusions of oxygen atoms. Furthermore, we quantitatively reproduce various experimental data in the best agreement manner by selecting a density functional scheme known as SCAN. Our results suggest that the present scale-up simulation-scheme using machine-learning techniques opens up a new pathway on theoretical studies of not only nuclear fuel compounds, but also a variety of similar materials that contain both heavy and light elements, like thorium dioxide.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2026

Wake-Resolving Acoustic Tomography: Advances through Numerical Covariance Methods

Acoustic tomography offers path-integrated measurements of atmospheric velocity and temperature fluctuations with high spatial resolution. Classical implementations of time-dependent stochastic inversion rely on homogeneous, isotropic covariance models that are poorly suited to the anisotropic structure of wind turbine wakes. By directly estimating heterogeneous covariances from large-eddy simulations (LESs) into the time-dependent stochastic inversion operator, we relax implicit assumptions in the analytical models used historically. Retrievals using these LES-informed models improve agreement with true fields in variance, turbulent kinetic energy, and spectral content compared to analytical and precursor-based covariance models. The results indicate that LES-informed covariance models can enhance the accuracy of acoustic tomography retrievals in complex, anisotropic flows such as wind turbine wakes in some cases and highlight instances where analytical models still offer competitive performance, despite their simplifying assumptions.

17 WIND ENERGY↗

NASA NTRS1995

Pest resistant MoSi.sub.2 materials and method of making

A pest resistant molybdenum disilicide composition is provided for use in high temperature structural applications. The composition includes molybdenum disilicide and silicon nitride and can be used to prepare improved reinforced composites.

Hebsur, Mohan G.↗

NASA NTRS1994

Interlaminar shear test method development for long term durability testing of composites

The high speed civil transport is a commercial aircraft that is expected to carry 300 passengers at Mach 2.4 over a range of more than 6000 nautical miles. With the existing commercial structural material technology (i.e., aluminum) the performance characteristics of the high speed civil transport would not be realized. Therefore there has been a concerted effort in the development of light weight materials capable of withstanding elevated temperatures for long duration. Thermoplastic composite materials are such candidate materials and the understanding of how these materials perform over the long term under harsh environments is essential to safe and effective design. The matrix dominated properties of thermoplastic composites are most affected by both time and temperature. There is currently an effort to perform short term testing to predict long term behavior of in-plane mechanical properties E22 (transverse modulus of elasticity) and G12 (shear modulus). Out-of-plane properties such as E33, G13, and G23 are inherently more difficult to characterize. This is especially true for the out-of-plane shear modulus G23 and hence there is no existing acceptable standard test method. Since G23 is the most matrix dominated property, it is essential that a test method be developed. A shear test methodology is developed to do just that. The test method, called the double notched specimen, along with the previously developed shear gage was tested at room temperature. Mechanical testing confirmed the attributes of the methodology. A finite element parametric study was conducted for specimen optimization. Moire interferometry, a high sensitivity laser optical method, was used for full-field analysis of the specimen. From this work, material parameters will be determined and thus enable the prediction of long term material behavior of laminates subjected to general loading states.

Ifju, Peter G.↗

NASA NTRS1992

The statistical analysis of circadian phase and amplitude in constant-routine core-temperature data

Accurate estimation of the phases and amplitude of the endogenous circadian pacemaker from constant-routine core-temperature series is crucial for making inferences about the properties of the human biological clock from data collected under this protocol. This paper presents a set of statistical methods based on a harmonic-regression-plus-correlated-noise model for estimating the phases and the amplitude of the endogenous circadian pacemaker from constant-routine core-temperature data. The methods include a Bayesian Monte Carlo procedure for computing the uncertainty in these circadian functions. We illustrate the techniques with a detailed study of a single subject's core-temperature series and describe their relationship to other statistical methods for circadian data analysis. In our laboratory, these methods have been successfully used to analyze more than 300 constant routines and provide a highly reliable means of extracting phase and amplitude information from core-temperature data.

NASA Discipline Regulatory Physiology↗

DOE OSTI2026

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process↗

DOE OSTI2022

Aluminum alloy compositions and methods of making and using the same

The present disclosure concerns embodiments of aluminum alloy compositions exhibiting microstructural stability and strength at high temperatures. The disclosed aluminum alloy compositions comprise particular combinations of components that contribute the ability of the compositions to exhibit improved microstructural stability and hot tearing resistance as compared to conventional alloys. Also disclosed herein are embodiments of methods of making and using the alloys.

Shyam, Amit↗