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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Methods for structural design at elevated temperatures

A procedure which can be used to design elevated temperature structures is discussed. The desired goal is to have the same confidence in the structural integrity at elevated temperature as the factor of safety gives on mechanical loads at room temperature. Methods of design and analysis for creep, creep rupture, and creep buckling are presented. Example problems are included to illustrate the analytical methods. Creep data for some common structural materials are presented. Appendix B is description, user's manual, and listing for the creep analysis program. The program predicts time to a given creep or to creep rupture for a material subjected to a specified stress-temperature-time spectrum. Fatigue at elevated temperature is discussed. Methods of analysis for high stress-low cycle fatigue, fatigue below the creep range, and fatigue in the creep range are included. The interaction of thermal fatigue and mechanical loads is considered, and a detailed approach to fatigue analysis is given for structures operating below the creep range.

Ellison, A. M.↗
NASA NTRS1974

Numerical evaluation of electromagnetic fields due to dipole antennas in the presence of stratified media

Two numerical methods are used to evaluate the integrals that express the em fields due to dipole antennas radiating in the presence of a stratified medium. The first method is a direct integration by means of Simpson's rule. The second method is indirect and approximates the kernel of the integral by means of the fast Fourier transform. In contrast to previous analytical methods that applied only to two-layer cases the numerical methods can be used for any arbitrary number of layers with general properties.

Tsang, L.↗
NASA NTRS1975

Simulation of aircraft crash and its validation

A joint FAA/NASA program is discussed which is aimed at developing a reliable technology for the design of crashworthy light aircraft. This program encompasses the development of analytical methods, the definition of a survivable crash envelope, and the design of improved seat and restraint systems. A facility for full-scale crash-simulation testing is described along with the test method and results of five full-scale crash tests of twin-engine light aircraft. The major goals of the analytical portion of the program are outlined, including the development and validation of the analytical technique using simplified structural specimens that approximate aircraft components, as well as the mathematical modeling of the complete airframe and its subsequent dynamic analysis by substructuring and matrix reduction techniques.

Alfaro-Bou, E.↗
NASA NTRS1981

Effects of solid particles suspended in fluid flow through an axial flow compressor stage

An approximate method for calculating the flow properties of gas-particle mixture flowing over blades in a cascade is studied. Using an analytical method, the solid particle trajectory and location of collisions between the solid particles and the blade surfaces are determined. In addition an experimental investigation of the trajectories and velocities of solid particles suspended in a fluid passing through an axial flow compressor cascade was performed. The cascade blades were made of 2024 aluminum alloy and the solid particles used were quartz sand with average diameter of 165 microns. The following parameters were investigated: blade pressure distribution, and total pressure loss coefficient, both depending on the degree of erosion. In addition, a theoretical estimation of the blade erosion is compared with the experimental data.

Tabakoff, W.↗
NASA NTRS1981

An influence coefficient method for the application of the modal technique to wing flutter suppression of the DAST ARW-1 wing

The methods used to compute the mass, structural stiffness, and aerodynamic forces in the form of influence coefficient matrices as applied to a flutter analysis of the Drones for Aerodynamic and Structural Testing (DAST) Aeroelastic Research Wing. The DAST wing was chosen because wind tunnel flutter test data and zero speed vibration data of the modes and frequencies exist and are available for comparison. A derivation of the equations of motion that can be used to apply the modal method for flutter suppression is included. A comparison of the open loop flutter predictions with both wind tunnel data and other analytical methods is presented.

Pines, S.↗
NASA NTRS2002

Acoustic and Laser Doppler Anemometer Results for Confluent and 12-Lobed E(exp 3) Mixer Exhaust Systems for Subsonic Jet Noise Reduction

The research described in this report has been funded by NASA Glenn Research Center as part of the Advanced Subsonic Technologies (AST) initiative. The program operates under the Large Engine Technologies (LET) as Task Order #3 1. Task Order 31 is a three year research program divided into three subtasks. Subtask A develops the experimental acoustic and aerodynamic subsonic mixed flow exhaust system databases. Subtask B seeks to develop and assess CFD-based aero-acoustic methods for subsonic mixed flow exhaust systems. Subtask B relies on the data obtained from Subtask A to direct and calibrate the aero-acoustic methods development. Subtask C then seeks to utilize both the aero-acoustic data bases developed in Subtask A and the analytical methods developed in Subtask B to define improved subsonic mixed-flow exhaust systems. The mixed flow systems defined in Subtask C will be experimentally demonstrated for improved noise reduction in a scale model aero-acoustic test conducted similarly to the test performed in Subtask A. The overall object of this Task Order is to develop and demonstrate the technology to define a -3EPNdB exhaust system relative to 1992 exhaust system technology.

Salikuddin, M.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-13635-DND

Objectives of AePW: Assess state-of-the-art Computational Aeroelasticity (CAe) methods as practical tools for the prediction of static and dynamic aeroelastic phenomena and responses on relevant geometries. - Perform comparative computational studies on selected test cases - Identify errors & uncertainties in computational aeroelastic methods - Identify gaps in existing aeroelastic databases - Provide roadmap of path forward (additional existing data sets, new experimental data sets, and analytical methods developments).

Walt Silva↗
DOE OSTI2021

Data Science Techniques, Assumptions, and Challenges in Alloy Clustering and Property Prediction

Data analytics methods have been increasingly applied to understanding materials chemistry, processing due to the manufacturing approach, and uni-axial and cyclic property relationships in the highly complex space of alloy design. There are several benefits to applying data analytics to this space, including the ability to manage non-linearities in the responses of the alloy attributes and the resulting mechanical properties. However, key difficulties in applying and understanding the results of data analytics include the often lack of reported assumptions and data processing steps necessary to improve interpretation and reproducibility in derived results. In this work, the methods used to generate clustering and correlation analyses for experimental 9% Cr ferritic-martensitic steel data were investigated and the resulting implications for mechanical property predictions were assessed. This work uses principal component analysis, partitioning around medoids, t-SNE, and k-means clustering to investigate trends in composition, processing and microstructure information with creep and tensile properties, building on work done previously using a smaller version of the same dataset. The initial assumptions, preprocessing steps and methods are investigated and outlined in order to depict the fine level of detail required to convey the steps taken to process data and produce analytical results. Here, the variations in the resulting analyses are explored due to the influence of new and more varied data.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Use of machine learning to analyze chemistry card sort tasks

Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student’s organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student’s strategy. Here in this work, we propose new machine learning strategies that leverage a potentially richer source of student thinking: free-form written language justifications associated with student sorts. Using data from a university chemistry card sort task, we use vectorized representations of language and unsupervised learning techniques to generate qualitatively interpretable clusters, which can provide unique insight in how students organize their knowledge. We compared these to machine learning analysis of the students’ sorts themselves. Machine learning-generated clusters revealed different organizational strategies than those built into the task; for example, sorts by difficulty or even discipline. There were also many more categories generated by machine learning for what we would identify as more novice-like sorts and justifications than originally built into the task, suggesting students’ organizational strategies converge when they become more expert-like. Finally, we learned that categories generated by machine learning for students’ justifications did not always match the categories for their sorts, and these cases highlight the need for future research on students’ organizational strategies, both manually and aided by machine learning. In sum, the use of machine learning to analyze results from a card sort task has helped us gain a more nuanced understanding of students’ expertise, and demonstrates a promising tool to add to existing analytic methods for card sorts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Analysis of semivolatile organics in liquid radioactive residue using sorptive stir bar and solvent back-extraction

Current methods for semivolatiles analysis in radioactive samples can produce large volumes of radioactive solvent residue. A method utilizing stir-bar sorptive extraction has been explored in this work for its applicability to radioactive waste samples. This low solvent analytical method may accelerate remediation, minimize hazardous solvent waste, and reduce exposure risk to workers. Organic compounds (polyaromatic hydrocarbons, chlorinated aromatics, and phenolic compounds) were chosen as surrogates for common Liquid Waste System (LWS) contaminants at Savannah River Site (Aiken, SC). Stir-bar extraction parameters (extraction time, matrix modification, and effective pH range) and solvent back extraction parameters (solvent type, volume, and extraction time) were optimized experimentally for the chosen compounds. Affinity of the stir-bar extraction polymer to radionuclides Cs-137 and Am-241 was observed to determine radionuclide concentration effects. The stir-bar method achieved mean recovery of 100 ± 0.7% (1σ), relative to 114 ± 7% using solvent extraction, while reducing weekly method hands-on time by 93.4% and solvent volume consumption by 99.3%. Sensitivity was improved by 378% in simulated tank waste and 278% in real-world LWS matrix, relative to solvent extraction. This work has produced a safe and optimized method for the low solvent analysis of organics in legacy radioactive tank waste by stir-bar sorptive extraction.

GC-MS↗
DOE OSTI2023

PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling of various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

Methods of shield analysis for protection against electrons in space

It is anticipated that many future manned space operations will be radiation limited and that laminated wall structures and the use of new materials will be required to reduce radiation exposure. Methods for electron shield analysis are reviewed in light of anticipated needs in the space program. The most general method is still the Monte Carlo method, which is of limited usefulness for shield analysis due to excessive computer requirements. Methods based on energy deposition coefficients or energy transmission and reflection factors are quite accurate, but are currently limited to aluminum shield material. Analytical methods based on Mar's approximation for the electron transmission factor are relatively general and computer efficient but seriously underestimate shield requirements. A correction to methods using Mar's approximate transmission factor is derived herein and results in a slightly conservative estimate of shield requirements. Techniques for laminated shield design are still lacking.

Wilson, J. W.↗
NASA NTRS1988

Fluid mechanics of dynamic stall. I - Unsteady flow concepts

Advanced military aircraft 'supermaneuverability' requirements entail the sustained operation of airfoils at stalled flow conditions. The present work addresses the effects of separated flow on vehicle dynamics; an analytic method is presented which employs static experimental data to predict the separated flow effect on incompressible unsteady aerodynamics. The key parameters in the analytic relationship between steady and nonsteady aerodynamics are the time-lag before a change of flow conditions can affect the separation-induced aerodynamic loads, the accelerated flow effect, and the moving wall effect.

Ericsson, L. E.↗
NASA NTRS1991

Aerodynamic design optimization using sensitivity analysis and computational fluid dynamics

A new and efficient method is presented for aerodynamic design optimization, which is based on a computational fluid dynamics (CFD)-sensitivity analysis algorithm. The method is applied to design a scramjet-afterbody configuration for an optimized axial thrust. The Euler equations are solved for the inviscid analysis of the flow, which in turn provides the objective function and the constraints. The CFD analysis is then coupled with the optimization procedure that uses a constrained minimization method. The sensitivity coefficients, i.e. gradients of the objective function and the constraints, needed for the optimization are obtained using a quasi-analytical method rather than the traditional brute force method of finite difference approximations. During the one-dimensional search of the optimization procedure, an approximate flow analysis (predicted flow) based on a first-order Taylor series expansion is used to reduce the computational cost. Finally, the sensitivity of the optimum objective function to various design parameters, which are kept constant during the optimization, is computed to predict new optimum solutions. The flow analysis of the demonstrative example are compared with the experimental data. It is shown that the method is more efficient than the traditional methods.

Baysal, Oktay↗
NASA NTRS1991

Mechanical and analytical screening of braided composites for transport fuselage applications

The mechanics of materials progress in support of the goal of understanding the application of braided composites in a transport aircraft fuselage are summarized. Composites consisting of both 2-D and 3-D braid patterns are investigated. Both consolidation of commingled graphite/PEEK and resin transfer molding of graphite-epoxy braided composite processes are studied. Mechanical tests were used to examine unnotched tension, open hole tension, compression, compression after impact, in-plane shear, out-of-plane tension, bearing, and crippling. Analytical methods are also developed and applied to predict the stiffness and strengths of test specimens. A preliminary study using the test data and analytical results is performed to assess the applicability of braided composites to a commercial aircraft fuselage.

Fedro, Mark J.↗
NASA NTRS1994

Straddle Design Of Spiral Bevel And Hypoid Gears

Computer-assisted method of analysis of straddle designs for spiral bevel and hypoid gears helps prevent undercutting of gear shafts during cutting of gear teeth. Analytical method and computer program based on equations for surface traced out by motion of head cutter, equation for cylindrical surface of shaft, and equations expressing relationships among coordinate systems fixed to various components of gear-cutting machine tool and gear.

Handschuh, Robert F.↗
DOE OSTI2025

Real-Time Screening for Uranium Enrichment by Paper Spray Ionization Mass Spectrometry for Field Applications

A rapid isotope ratio screening technique for uranium enrichment is demonstrated by utilizing paper spray ionization (PSI) high-resolution mass spectrometry (HRMS). Measurements were conducted using an ambient ionization mass spectrometer coupled to a custom-made JEOL PSI attachment apparatus, with de minimus sample preparation requirements. The current method detection limit for individual isotopes (e.g., 235 U and 238 U) is approximately 50 pg, with subsequent optimization expected to further improve U isotopic sensitivity. The PSI analytical method described herein can support rapid analysis (both in-field and in-lab screening) of isotopes-of-interest, as demonstrated by empirical differentiation of depleted uranium (DU) and low enriched uranium (LEU) analytical aliquots. Furthermore, this analytical workflow holds promise for applications in nuclear forensics, international nuclear safeguards, and nonproliferation missions.

Anions↗
DOE OSTI2025

INTEGRATION OF DATA ANALYTICS WITH SYSTEM HEALTH PROGRAMS

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry developed and regulatory programs. However, these programs have proven to be labor intensive and expensive. There is an opportunity to significantly enhance the collection, analysis, and use of this information to provide more cost-effective plant operation. Additionally, there is an acute industry need to leverage advanced technology to reduce costs and improve operational effectiveness. The goal of this paper is to provide effective and efficient analytical methods and tools to support risk-informed decisions for the equipment reliability and asset management programs at nuclear power plants. This is accomplished by creating a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). Here we are supporting typical system engineer decisions regarding maintenance activity scheduling and component ageing management. This is performed in a risk-informed context where herein the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow. A challenge is that the structure of this workflow strongly depends on the decision that needs to be made, the type of data available, and the constraints that need to be considered. Current methods are designed to provide specific answers to specific problems; however, these methods might prove to be inadequate even when problem settings slightly change (e.g., different types of requirements, additional dependencies between system reliability and economics). We tackled this challenge by designing framework in a flexible and modular fashion such that the user can assemble and customize his/her own workflow that integrates SSC economic lifecycle models (e.g., maintenance and replacement costs), system reliability models, and optimization methods.

97 - MATHEMATICS AND COMPUTING↗