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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

MASCOT - MATLAB Stability and Control Toolbox

MASCOT software was created to provide the conceptual aircraft designer accurate predictions of air vehicle stability and control characteristics. The code takes as input mass property data in the form of an inertia tensor, aerodynamic loading data, and propulsion (i.e. thrust) loading data. Using fundamental non-linear equations of motion, MASCOT then calculates vehicle trim and static stability data for any desired flight condition. Common predefined flight conditions are included. The predefined flight conditions include six horizontal and six landing rotation conditions with varying options for engine out, crosswind and sideslip, plus three takeoff rotation conditions. Results are displayed through a unique graphical interface developed to provide stability and control information to the conceptual design engineers using a qualitative scale indicating whether the vehicle has acceptable, marginal, or unacceptable static stability characteristics. This software allows the user to prescribe the vehicle s CG location, mass, and inertia tensor so that any loading configuration between empty weight and maximum take-off weight can be analyzed. The required geometric and aerodynamic data as well as mass and inertia properties may be entered directly, passed through data files, or come from external programs such as Vehicle Sketch Pad (VSP). The current version of MASCOT has been tested with VSP used to compute the required data, which is then passed directly into the program. In VSP, the vehicle geometry is created and manipulated. The aerodynamic coefficients, stability and control derivatives, are calculated using VorLax, which is now available directly within VSP. MASCOT has been written exclusively using the technical computing language MATLAB . This innovation is able to bridge the gap between low-fidelity conceptual design and higher-fidelity stability and control analysis. This new tool enables the conceptual design engineer to include detailed static stability and trim constraints in the conceptual design loop. The unique graphical interface developed for this tool presents the stability data in a format that is understandable by the conceptual designer, yet also provides the detailed quantitative results if desired.

Kenny, Sean↗
DOE OSTI2020

Comparison of plug flow and multi-node stratified tank modeling approaches regarding computational efficiency and accuracy

Residential water heaters contain water stratified by temperature-driven density differences. This implies that a water tank can reach a state in which the top and bottom sections have different temperatures, unless mixing happens. A high degree of thermal stratification can improve the efficiency of some water heaters, by saving the amount of energy required for the heat-up process. Studies of stratification became popular in the 1970s and it remains an active research topic today. The research has led to the development of different models and techniques to better predict and define a stratified tanks behavior. By comparing these models and techniques used previously to describe thermal stratification, the phenomenon could be better understood, exploited, and used to increase efficiency and thermal energy capacity in modern water tanks. From the existing models, we found the one-dimensional standard plug-flow and a multi node model to be appropriate for analyzing the processes of the heat up and cool-down in a water tank. These two models are based on energy balances. This work involved comparing the accuracy and computational effort needed to implement these models. To assess accuracy, we compared both types of existing models to experimental data (also collected in this work) which included a heat up process using an external heat pump. This external process included a layering process that has an eddy diffusivity at five times the rate of thermal diffusion. For this project, we implemented the models in MATLAB, the multi-paradigm numerical computing environment. We quantified model accuracy using the root mean squared error between modeled data and experimental data for six measured tank temperatures. Comparing the accuracy and the computational time taken to run the simulation provides a method to contrast the performance of each model and a way to rate it. The multi node model was run using from 6 to 96 spatial nodes; the plug flow model was run using 1 to 0.001 º C temperature bin sizes. Additionally, timesteps were varied from 4 to 236 s. The results quantify the tradeoff between accuracy and computational time, providing guidance for simulations to intelligently select the best model type and simulation parameters. This research can be used to validate the pre-existing models and possibly improve the modern water tank.

Bulnes, Fernando Karg↗
DOE OSTI2019

Assessment of Calibration Approaches for the Stress Relaxation Test

Advanced manufacturing technologies are enabling the next generation of superalloys for extreme temperatures, pressures, and longevity. There is a need for Accelerated Creep Test (ACT) methods to reduce the time needed to implement new creep resistant superalloys. Without the development of ACTs, the qualification of new superalloys using conventional creep tests can take 11+ years corresponding to the 100,000-hour service life of long-lived turbomachinery components. A refined stress relaxation test (SRT) is introduced to succeed real-time conventional creep tests (CCTs). The stress relaxation test generates extensive stress versus creep-strain-rate data within a single specimen. Since the specimen is held below the elastic limit and relatively little creep deformation has occurred, several SRTs at different temperatures can be performed using a single specimen. To obtain data, specimens are rapidly loaded in force-control to just below the elastic limit. The specimen is switched to displacement-control and held at a fixed displacement while stress relaxation occurs. This generates a stress versus time curve that must be converted into stress versus creep-strain-rate. The stress versus creep-strain-rate curves are utilized to calculate creep activation energy and produce a creep-strain-rate master curve. The objective of this study is to determine the best calibration approach for SRT: regression of stress, regression of creep strain, and the finite difference of creep strain. It is recommended that the differentiation be applied; however, finite difference applied to the raw data produces inconsistent calculations of the creep-strain-rate. In this study, a MATLAB algorithm is written to evaluate all three calibration options where, stress and creep deformation are regressed into natural logarithm functions. The resulting creep-strain-rate curves are compared to determine the most reliable and consistent method. Analyzing and evaluating the results the regression of stress and regression or creep strain calibration methods prove to provide accurate results. These methods will help replace CCTs by conducting less expensive ACTs, while increasing the overall efficiency of the development of new materials.

36 MATERIALS SCIENCE↗
DOE OSTI2016

TU-FG-201-07: Development of SRS Conical Collimator Collision Prediction Software for Radiation Treatment Safety

Purpose: Stereotactic radiosurgery (SRS) treatments using conical collimators can potentially result in gantry collision with treatment table due to limited collision-clear spaces. An in-house software was developed to help the SRS treatment planner mitigate potential SRS conical collimator (Varian Medical System, Palo Alto, CA) collisions with the treatment table. This software was designed to remove treatment re-planning secondary to unexpected collisions. Methods: A BrainLAB SRS ICT Frameless Extension used for SRS treatments in our clinic was mathematically modelled using surface points registered to the 3D co-ordinate space of the couch extension. The surface points are transformed based on the treatment isocenter point and potential collisions are determined in 3D space for couch and gantry angle combinations. The distance between the SRS conical collimators and LINAC isocenter is known. The collision detection model was programmed in MATLAB (Mathwork, Natick, MA) to display graphical plots of the calculations, and the plotted data is used to avoid the gantry and couch angle combinations that would likely result in a collision. We have utilized the cone collision tool for 23 SRS cone treatment plans (8 retrospective and 15 prospective for 10 patients). Results: Twenty one plans strongly agreed with the software tool prediction for collision. However, in two plans, a collision was observed with a 0.5 cm margin when the software predicted no collision. Therefore, additional margins were added to the clearance criteria in the program to achieve a lower risk of actual collisions. Conclusion: Our in-house developed collision check software successfully avoided SRS cone re-planning by 91.3% due to a reduction in cone collisions with the treatment table. Future developments to our software will include a CT image data set based collision prediction model as well as a beam angle optimization tool to avoid normal critical tissues as well as previously treated lesions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Fault detection in PV systems

A practical fault detection approach for PV systems intended for online implementation is developed. The fault detection model here is built using artificial neural network. initially the photovoltaic system is simulated using MATLAB software and output power is collected for various combinations of irradiance and temperature. Data is first collected for normal operating condition and then four types of faults are simulated and data are collected for faulty conditions. Four faults are considered here and they are: Line to Line faults with a small voltage difference, Line to line faults with a large voltage difference, degradation fault and open-circuit fault. This data is then used to train the neural network and to develop the fault detection model. The fault detection model takes irradiance, temperature and power as the input and accurately gives the type of fault in the PV system as the output. This system is a generalized one as any PV module datasheet can be used to simulate the Photovoltaic system and also this fault detection system can be implemented online with the use of data acquisition system.

14 SOLAR ENERGY↗
NASA NTRS1998

Bi-Level Integrated System Synthesis (BLISS)

BLISS is a method for optimization of engineering systems by decomposition. It separates the system level optimization, having a relatively small number of design variables, from the potentially numerous subsystem optimizations that may each have a large number of local design variables. The subsystem optimizations are autonomous and may be conducted concurrently. Subsystem and system optimizations alternate, linked by sensitivity data, producing a design improvement in each iteration. Starting from a best guess initial design, the method improves that design in iterative cycles, each cycle comprised of two steps. In step one, the system level variables are frozen and the improvement is achieved by separate, concurrent, and autonomous optimizations in the local variable subdomains. In step two, further improvement is sought in the space of the system level variables. Optimum sensitivity data link the second step to the first. The method prototype was implemented using MATLAB and iSIGHT programming software and tested on a simplified, conceptual level supersonic business jet design, and a detailed design of an electronic device. Satisfactory convergence and favorable agreement with the benchmark results were observed. Modularity of the method is intended to fit the human organization and map well on the computing technology of concurrent processing.

Sobieszczanski-Sobieski, Jaroslaw↗
NASA NTRS1998

Bi-Level Integrated System Synthesis (BLISS)

BLISS is a method for optimization of engineering systems by decomposition. It separates the system level optimization, having a relatively small number of design variables, from the potentially numerous sub-system optimizations that may each have a large number of local design variables. The subsystem optimizations are autonomous and may be conducted concurrently. Subsystem and system optimizations alternate, linked by sensitivity data, producing a design improvement in each iteration. Starting from a best guess initial design, the method improves that design in iterative cycles, each cycle comprised of two steps. In step one, the system level variables are frozen and the improvement is achieved by separate, concurrent, and autonomous optimizations in the local variable subdomains. In step two, further improvement is sought in the space of the system level variables. Optimum sensitivity data link the second step to the first. The method prototype was implemented using MATLAB and iSIGHT programming software and tested on a simplified, conceptual level supersonic business jet design, and a detailed design of an electronic device.

Sobieszczanski-Sobieski, Jaroslaw↗
NASA NTRS2016

Simulation Development and Analysis of Crew Vehicle Ascent Abort

NASA's Commercial Crew Program is an integral step in its journey to Mars as it would expedite development of space technologies and open up partnership with U.S. commercial companies. NASA reviews and independent assessment of Commercial Crew Program is fundamental to its success, and being able to model a commercial crew vehicle in a simulation rather than conduct a live test would be a safer, faster, and less expensive way to assess and certify the capabilities of the vehicle. To this end, my project was to determine the feasibility of using a simulation tool named SOMBAT version 2.0 to model a multiple parachute system for Commercial Crew Program simulation. The main tasks assigned to me were to debug and test the main parachute system model, (capable of simulating one to four main parachute bodies), and to utilize a graphical program to animate the simulation results. To begin tackling the first task, I learned how to use SOMBAT by familiarizing myself with its mechanics and by understanding the methods used to tweak its various parameters and outputs. I then used this new knowledge to set up, run, and analyze many different situations within SOMBAT in order to explore the limitations of the parachute model. Some examples of parameters that I varied include the initial velocity and orientation of the falling capsule, the number of main parachutes, and the location where the parachutes were attached to the capsule. Each parameter changed would give a different output, and in some cases, would expose a bug or limitation in the model. A major bug that I discovered was the inability of the model to handle any number of parachutes other than three. I spent quite some time trying to debug the code logically, but was unable to figure it out until my mentor taught me that digital simulation limitations can occur when some approximations are mistakenly assumed for certain in a physical system. This led me to the realization that unlike in all of the programming classes I have taken thus far that focus on pure logic, simulation code focuses on mimicking the physical world with some approximation and can have inaccuracies or numerical instabilities. Learning from my mistake, I adopted new methods to analyze these different simulations. One method the student used was to numerically plot various physical parameters using MATLAB to confirm the mechanical behavior of the system in addition to comparing the data to the output from a separate simulation tool called FAST. By having full control over what was being outputted from the simulation, I could choose which parameters to change and to plot as well as how to plot them, allowing for an in depth analysis of the data. Another method of analysis was to convert the output data into a graphical animation. Unlike the numerical plots, where all of the physical components were displayed separately, this graphical display allows for a combined look at the simulation output that makes it much easier for one to see the physical behavior of the model. The process for converting SOMBAT output for EDGE graphical display had to be developed. With some guidance from other EDGE users, I developed a process and created a script that would easily allow one to display simulations graphically. Another limitation with the SOMBAT model was the inability for the capsule to have the main parachutes instantly deployed with a large angle between the air speed vector and the chutes drag vector. To explore this problem, I had to learn about different coordinate frames used in Guidance, Navigation & Control (J2000, ECEF, ENU, etc.) to describe the motion of a vehicle and about Euler angles (e.g. Roll, Pitch, Yaw) to describe the orientation of the vehicle. With a thorough explanation from my mentor about the description of each coordinate frame, as well as how to use a directional cosine matrix to transform one frame to another, I investigated the problem by simulating different capsule orientations. In the end, I was able to show that this limitation could be avoided if the capsule is initially oriented antiparallel to its velocity vector.

Wong, Chi S.↗
NASA NTRS2014

A Monte Carlo Approach to Modeling the Breakup of the Space Launch System EM-1 Core Stage with an Integrated Blast and Fragment Catalogue

The Liquid Propellant Fragment Overpressure Acceleration Model (L-FOAM) is a tool developed by Bangham Engineering Incorporated (BEi) that produces a representative debris cloud from an exploding liquid-propellant launch vehicle. Here it is applied to the Core Stage (CS) of the National Aeronautics and Space Administration (NASA) Space Launch System (SLS launch vehicle). A combination of Probability Density Functions (PDF) based on empirical data from rocket accidents and applicable tests, as well as SLS specific geometry are combined in a MATLAB script to create unique fragment catalogues each time L-FOAM is run-tailored for a Monte Carlo approach for risk analysis. By accelerating the debris catalogue with the BEi blast model for liquid hydrogen / liquid oxygen explosions, the result is a fully integrated code that models the destruction of the CS at a given point in its trajectory and generates hundreds of individual fragment catalogues with initial imparted velocities. The BEi blast model provides the blast size (radius) and strength (overpressure) as probabilities based on empirical data and anchored with analytical work. The coupling of the L-FOAM catalogue with the BEi blast model is validated with a simulation of the Project PYRO S-IV destruct test. When running a Monte Carlo simulation, L-FOAM can accelerate all catalogues with the same blast (mean blast, 2 σ blast, etc.), or vary the blast size and strength based on their respective probabilities. L-FOAM then propagates these fragments until impact with the earth. Results from L-FOAM include a description of each fragment (dimensions, weight, ballistic coefficient, type and initial location on the rocket), imparted velocity from the blast, and impact data depending on user desired application. LFOAM application is for both near-field (fragment impact to escaping crew capsule) and far-field (fragment ground impact footprint) safety considerations. The user is thus able to use statistics from a Monte Carlo set of L-FOAM catalogues to quantify risk for a multitude of potential CS destruct scenarios. Examples include the effect of warning time on the survivability of an escaping crew capsule or the maximum fragment velocities generated by the ignition of leaking propellants in internal cavities.

Richardson, Erin↗
DOE OSTI2018

DASH Slow Strain Rates from Brady Hot Springs Geothermal Field during PoroTomo Deployment Period

This submission contains slow strain rates summed to radians over 30 second intervals [rad/s] derived from horizontal distributed acoustic sensing measurements (DASH) of Brady geothermal field during PoroTomo deployment (2016-Mar-14 to 2016-Mar-26). There is one file corresponding to each day written in *.mat format for use with Matlab. The format for the binary Matlab .mat files are defined at: https://www.mathworks.com/help/pdf_doc/matlab/matfile_format.pdf. One such file includes the following variables: 'flist': list of raw DASH files used in the summation 'time_tag_mdt': sample time tag in datetime format with hours given in 24-hr format (yyyy/MM/dd HH:mm:ss.SSSSSSS) 'time_tag_uts': sample time tag in Unix time 'strain_rate_summed_over30s_in_radians_per_second': slow strain rates summed over 30 second intervals in units rad/s 'sample_standard_deviation_in_radians_per_second': corresponding sample standard deviation of slow strain rates in units rad/s The PoroTomo final technical report, raw DASH data, and software repository are also available through the links below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software (Extended Analysis)

Tensor decomposition models play an increasingly important role in modern data science applications. One problem of particular interest is fitting a low-rank Canonical Polyadic (CP) tensor decomposition model when the tensor has sparse structure and the tensor elements are nonnegative count data. SparTen is a high-performance C++ library which computes a low-rank decomposition using different solvers: a first-order quasi-Newton or a second-order damped Newton method, along with the appropriate choice of runtime parameters. Since default parameters in SparTen are tuned to experimental results in prior published work on a single real-world dataset conducted using MATLAB implementations of these methods, it remains unclear if the parameter defaults in SparTen are appropriate for general tensor data. Furthermore, it is unknown how sensitive algorithm convergence is to changes in the input parameter values. This report addresses these unresolved issues with large-scale experimentation on three benchmark tensor data sets. Experiments were conducted on several different CPU architectures and replicated with many initial states to establish generalized profiles of algorithm convergence behavior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Analytic reconstruction algorithms for triple-source CT with horizontal data truncation

Purpose: This paper explores a triple-source imaging method with horizontal data truncation to enlarge the field of view (FOV) for big objects. Methods: The study is conducted by using theoretical analysis, mathematical deduction, and numerical simulations. The proposed algorithms are implemented in c + + and MATLAB. While the basic platform is constructed in MATLAB, the computationally intensive segments are coded in c + +, which are linked via a MEX interface. Results: A triple-source circular scanning configuration with horizontal data truncation is developed, where three pairs of x-ray sources and detectors are unevenly distributed on the same circle to cover the whole imaging object. For this triple-source configuration, a fan-beam filtered backprojection-type algorithm is derived for truncated full-scan projections without data rebinning. The algorithm is also extended for horizontally truncated half-scan projections and cone-beam projections in a Feldkamp-type framework. Using their method, the FOV is enlarged twofold to threefold to scan bigger objects with high speed and quality. The numerical simulation results confirm the correctness and effectiveness of the developed algorithms. Conclusions: The triple-source scanning configuration with horizontal data truncation cannot only keep most of the advantages of a traditional multisource system but also cover a larger FOV for big imaging objects. In addition, because the filtering is shift-invariant, the proposed algorithms are very fast and easily parallelized on graphic processing units.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Mass separation of deuterium and helium with conventional quadrupole mass spectrometer by using varied ionization energy

Deuterium pressure in deuterium-helium mixture gas is successfully measured by a common quadrupole mass spectrometer (model: RGA200) with a resolution of ∼0.5 atomic mass unit (AMU), by using varied ionization energy together with new developed software and dedicated calibration for RGA200. The new software is developed by using MATLAB with the new functions: electron energy (EE) scanning, deuterium partial pressure measurement, and automatic data saving. RGA200 with new software is calibrated in pure deuterium and pure helium 1.0 × 10{sup −6}–5.0 × 10{sup −2} Pa, and the relation between pressure and ion current of AMU4 under EE = 25 eV and EE = 70 eV is obtained. From the calibration result and RGA200 scanning with varied ionization energy in deuterium and helium mixture gas, both deuterium partial pressures (P{sub D{sub 2}}) and helium partial pressure (P{sub He}) could be obtained. The result shows that deuterium partial pressure could be measured if P{sub D{sub 2}} > 10{sup −6} Pa (limited by ultimate pressure of calibration vessel), and helium pressure could be measured only if P{sub He}/P{sub D{sub 2}} > 0.45, and the measurement error is evaluated as 15%. This method is successfully employed in EAST 2015 summer campaign to monitor deuterium outgassing/desorption during helium discharge cleaning.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Unsupervised Machine Learning for Evaluation of Aging in Explosive Pressed Pellets

This project is an evaluation of the changes in the dimensional geometry of pressed explosive powder pellets when stored for prolonged periods under unmonitored storage conditions. Through the application of Structural Health Monitoring (SHM) techniques, questions to be answered by this investigation are what, if any, effect has the long-term storage of the pellets had on their physical attributes and, if changes have occurred, are the resulting differences of significant magnitude to affect the performance of the pellets. This resulting report includes a summary of the relevant background information, explanation of the SHM approach used to analyze the available data, presentation and discussion of the results, concluding remarks, and an accompanying appendix containing the MATLAB program developed for the project.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Simulation and Analyses of Staging Maneuvers of Next Generation Reusable Launch Vehicles

NASA has initiated a comprehensive stage separation tool development activity to address the technology needed for successful development and operation of next generation reusable launch vehicles. As a part of this activity, ConSep simulation tool is being developed. This paper discusses the application of this tool to the staging maneuvers of two-stage-to-orbit (TSTO) vehicles. Simulation and analyses are performed for two bimese TSTO concepts, one staging at Mach 3 and the other at Mach 6. The TSTO bimese vehicles used in this study are sized for international space station class payload. The proximity and isolated aerodynamic databases used in the simulation were generated using the data from wind tunnel tests conducted at NASA Langley Research Center. ConSep is a MATLAB-based front end to the commercially available ADAMS solver, an industry standard package for solving multi-body dynamic problems.

Pamadi, Bandu N.↗
NASA NTRS2011

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.

Davis, Bruce↗
NASA NTRS2016

Features of the Upgraded Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) Software

The Imaging for Hypersonic Experimental Aeroheating Testing (IHEAT) software is used at the NASA Langley Research Center to analyze global aeroheating data on wind tunnel models tested in the Langley Aerothermodynamics Laboratory. One-dimensional, semi-infinite heating data derived from IHEAT are used in the design of thermal protection systems for hypersonic vehicles that are exposed to severe aeroheating loads, such as reentry vehicles during descent and landing procedures. This software program originally was written in the PV-WAVE(Registered Trademark) programming language to analyze phosphor thermography data from the two-color, relative-intensity system developed at Langley. To increase the efficiency, functionality, and reliability of IHEAT, the program was migrated to MATLAB(Registered Trademark) syntax and compiled as a stand-alone executable file labeled version 4.0. New features of IHEAT 4.0 include the options to perform diagnostic checks of the accuracy of the acquired data during a wind tunnel test, to extract data along a specified multi-segment line following a feature such as a leading edge or a streamline, and to batch process all of the temporal frame data from a wind tunnel run. Results from IHEAT 4.0 were compared on a pixel level to the output images from the legacy software to validate the program. The absolute differences between the heat transfer data output from the two programs were on the order of 10(exp -5) to 10(exp -7). IHEAT 4.0 replaces the PV-WAVE(Registered Trademark) version as the production software for aeroheating experiments conducted in the hypersonic facilities at NASA Langley.

Mason, Michelle L.↗