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NASA NTRS2001

A Software Tool for Integrated Optical Design Analysis

Design of large precision optical systems requires multi-disciplinary analysis, modeling, and design. Thermal, structural and optical characteristics of the hardware must be accurately understood in order to design a system capable of accomplishing the performance requirements. The interactions between each of the disciplines become stronger as systems are designed lighter weight for space applications. This coupling dictates a concurrent engineering design approach. In the past, integrated modeling tools have been developed that attempt to integrate all of the complex analysis within the framework of a single model. This often results in modeling simplifications and it requires engineering specialist to learn new applications. The software described in this presentation addresses the concurrent engineering task using a different approach. The software tool, Integrated Optical Design Analysis (IODA), uses data fusion technology to enable a cross discipline team of engineering experts to concurrently design an optical system using their standard validated engineering design tools.

Moore, Jim↗

NASA NTRS2015

Determination of Parachute Joint Factors using Seam and Joint Testing

This paper details the methodology for determining the joint factor for all parachute components. This method has been successfully implemented on the Capsule Parachute Assembly System (CPAS) for the NASA Orion crew module for use in determining the margin of safety for each component under peak loads. Also discussed are concepts behind the joint factor and what drives the loss of material strength at joints. The joint factor is defined as a "loss in joint strength...relative to the basic material strength" that occurs when "textiles are connected to each other or to metals." During the CPAS engineering development phase, a conservative joint factor of 0.80 was assumed for each parachute component. In order to refine this factor and eliminate excess conservatism, a seam and joint testing program was implemented as part of the structural validation. This method split each of the parachute structural joints into discrete tensile tests designed to duplicate the loading of each joint. Breaking strength data collected from destructive pull testing was then used to calculate the joint factor in the form of an efficiency. Joint efficiency is the percentage of the base material strength that remains after degradation due to sewing or interaction with other components; it is used interchangeably with joint factor in this paper. Parachute materials vary in type-mainly cord, tape, webbing, and cloth -which require different test fixtures and joint sample construction methods. This paper defines guidelines for designing and testing samples based on materials and test goals. Using the test methodology and analysis approach detailed in this paper, the minimum joint factor for each parachute component can be formulated. The joint factors can then be used to calculate the design factor and margin of safety for that component, a critical part of the design verification process.

Mollmann, Catherine↗

NASA NTRS2016

Human Exploration System Test-Bed for Integration and Advancement (HESTIA) Support of Future NASA Deep-Space Missions

The Engineering Directorate at the NASA - Johnson Space Center is outfitting a 20-Foot diameter hypobaric chamber in Building 7 to support future deep-space Environmental Control & Life Support System (ECLSS) research as part of the Human Exploration System Test-bed for Integration and Advancement (HESTIA) Project. This human-rated chamber is the only NASA facility that has the unique experience, chamber geometry, infrastructure, and support systems capable of conducting this research. The chamber was used to support Gemini, Apollo, and SkyLab Missions. More recently, it was used to conduct 30-, 60-, and 90-day human ECLSS closed-loop testing in the 1990s to support the International Space Station and life support technology development. NASA studies show that both planetary surface and deep-space transit crew habitats will be 3-4 story cylindrical structures driven by human occupancy volumetric needs and launch vehicle constraints. The HESTIA facility offers a 3-story, 20-foot diameter habitat consistent with the studies' recommendations. HESTIA operations follow stringent processes by a certified test team that including human testing. Project management, analysis, design, acquisition, fabrication, assembly and certification of facility build-ups are available to support this research. HESTIA offers close proximity to key stakeholders including astronauts, Human Research Program (who direct space human research for the agency), Mission Operations, Safety & Mission Assurance, and Engineering Directorate. The HESTIA chamber can operate at reduced pressure and elevated oxygen environments including those proposed for deep-space exploration. Data acquisition, power, fluids and other facility resources are available to support a wide range of research. Recently completed HESTIA research consisted of unmanned testing of ECLSS technologies. Eventually, the HESTIA research will include humans for extended durations at reduced pressure and elevated oxygen to demonstrate very high reliability of critical ECLSS and other technologies.

Marmolejo, Jose↗

NASA NTRS2004

Eccentric loading of microtensile specimens

Ceramic materials have a lower density than most metals and are capable of performing at extremely high temperatures. The utility of these materials is obvious; however, the fracture strength of brittle materials is not easily predicted and often varies greatly. Characteristically, brittle materials lack ductility and do not yield as other materials. Ceramics materials are naturally populated with microscopic cracks due to fabrication techniques. Upon application of a load, stress concentration occurs at the root of these cracks and fracture will eventually occur at some not easily predicted strength. In order to use ceramics in any application some design methodology must exist from which a component can be placed into service. This design methodology is CARES/LIFE (Ceramics Analysis and Reliability Evaluation of Structures) which has been developed and refined at NASA over the last several decades. The CARES/LIFE computer program predicts the probability of failure of a ceramic component over its service life. CARES combines finite element results from a commercial FE (finite element) package such as ANSYS and experimental results to compute the abovementioned probability of failure. Over the course of several tests CARES has had great success in predicting the life of various ceramic components and has been used throughout industry. The latest challenge is to verify that CARES is valid for MEMS (Micro-Electro Mechanical Systems). To investigate a series of microtensile specimens were fractured in the laboratory. From this data, material parameters were determined and used to predict a distribution of strength for other specimens that exhibit a known stress concentration. If the prediction matches the experimental results then these parameters can be applied to a desired component outside of the laboratory. During testing nearly half of the tensile Specimens fractured at a location that was not expected and hence not captured in the FE model. It has been my duty to investigate the nature of this phenomenon in hopes of finding a better correlation between theory and empirical results. To investigate I built complete FE models of all of the tensile specimens using ANSYS. It is suspected that some misalignment naturally occurs during testing and thus additional bending stresses are present in the specimens. I modeled this eccentric loading and ran several FE trials using ANSYS/PDS (a probabilistic design system in ANSYS). My objective this summer has been familiarize myself with the CARES/LIFE program in hopes of using it in conjunction with ANSYS to help verify that CARES is applicable to MEMS-scale (greater that 1 micron, less than 1 millimeter) components.

Trapp, Mark A.↗

NASA NTRS1994

Associated with aerospace vehicles development of methodologies for the estimation of thermal properties

Thermal stress analyses are an important aspect in the development of aerospace vehicles at NASA-LaRC. These analyses require knowledge of the temperature distributions within the vehicle structures which consequently necessitates the need for accurate thermal property data. The overall goal of this ongoing research effort is to develop methodologies for the estimation of the thermal property data needed to describe the temperature responses of these complex structures. The research strategy undertaken utilizes a building block approach. The idea here is to first focus on the development of property estimation methodologies for relatively simple conditions, such as isotropic materials at constant temperatures, and then systematically modify the technique for the analysis of more and more complex systems, such as anisotropic multi-component systems. The estimation methodology utilized is a statistically based method which incorporates experimental data and a mathematical model of the system. Several aspects of this overall research effort were investigated during the time of the ASEE summer program. One important aspect involved the calibration of the estimation procedure for the estimation of the thermal properties through the thickness of a standard material. Transient experiments were conducted using a Pyrex standard at various temperatures, and then the thermal properties (thermal conductivity and volumetric heat capacity) were estimated at each temperature. Confidence regions for the estimated values were also determined. These results were then compared to documented values. Another set of experimental tests were conducted on carbon composite samples at different temperatures. Again, the thermal properties were estimated for each temperature, and the results were compared with values obtained using another technique. In both sets of experiments, a 10-15 percent off-set between the estimated values and the previously determined values was found. Another effort was related to the development of the experimental techniques. Initial experiments required a resistance heater placed between two samples. The design was modified such that the heater was placed on the surface of only one sample, as would be necessary in the analysis of built up structures. Experiments using the modified technique were conducted on the composite sample used previously at different temperatures. The results were within 5 percent of those found using two samples. Finally, an initial heat transfer analysis, including conduction, convection and radiation components, was completed on a titanium sandwich structural sample. Experiments utilizing this sample are currently being designed and will be used to first estimate the material's effective thermal conductivity and later to determine the properties associated with each individual heat transfer component.

Scott, Elaine P.↗

DOE OSTI2022

Keyhole-mode Microscopy Dataset for Laser Powder-bed Fusion Modeling

Laser powder-bed fusion (LPBF) is an additive manufacturing (AM) technology that uses high-power sintering lasers to precisely construct metal designs. Material is accumulated by selectively sintering regions of a metal powder layer to a growing structure underneath forming a 3D geometry. Certain conditions make fusion in this process to operate in "keyhole-mode," characterized by targeted materials evaporating as plasma. While keyhole-mode operations can produce deeper molten pools than that observed in "conduction-mode", this mode of operation is often undesirable, as its molten regions can collapse on themselves, encapsulating metal vapors and forming cavities. The formation of such cavities negatively affects strength and consistency of the fused materials. To identify and avoid these detrimental effects of keyhole-mode operation, considerable data collection and analysis regarding this mode of operation is needed. Therefore, under the support of the "Open Data Initiative," Lawrence Livermore National Lab is releasing a dataset for analysis of this keyhole effect, and the conditions which transition operation from conduction-mode to keyhole-mode melting. This dataset consists of 600+ micrographs from laser powder-bed single track runs, with differing cross-section angles and input parameters, operating under both normal and keyhole mode operations. This journal documents the collection, organization, and usage of this dataset.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Preliminary modeling of triply periodic minimal surface (TPMS) structures using RELAP5-3D

With the United States Department of Energy (DOE)’s goal of quadrupling the nation’s nuclear energy supply by 2050, and with the Advanced Fuels Campaign pushing for new types of advanced reactor fuels and geometries, the need has arisen for new nuclear fuel designs. One such design is to swap out current nuclear fuel geometries in exchange for another type of geometry, called a Triply Periodic Minimal Surface (TPMS). TPMSs are self-supporting, infinitely repeating lattices—attributes that lend themselves well to additive manufacturing. These surfaces also possess enhanced heat transfer properties thanks to their internal area changes and large surface-area-to-volume ratios. Their drawback, however, is an increased pressure drop. Given the small amount of correlations and data (Reynolds numbers in the 2,000–8,000 range), and the minimal amount of experience so far obtained by modeling TPMS structures using 1D systems codes such as the Reactor Excursion and Leak Analysis Program (RELAP5-3D), further research into this topic was needed. Using data from the University of Wisconsin - Madison (UW), curve fits were created for both a Heat Transfer Coefficient (HTC) correlation and a Darcy friction factor empirical coefficient correlation. The curves’ coefficients and multipliers were then output and utilized in RELAP5-3D models of two upcoming experiments—Flow Loop for INFLUX Pressure drop (FLIP) and Microreactor Agile Non-nuclear Experimental Test (MAGNET)—aimed at increasing the available data for Reynolds numbers to the 16,000–36,000 range for TPMS structures. The models were run under the conditions utilized by a Computational Fluid Dynamics (CFD) analysis performed by another group at Idaho National Laboratory. Only CFD pressure drop values were obtained from the FLIP test, and those values showed that the RELAP5-3D models had a lower rate of pressure increase in comparison to the CFD values. In addition, there seemed to be a vertical shift upward in the pressure drop for both models whenever the TPMS porosity decreased, and the RELAP5-3D models showed a higher vertical shift in comparison to the CFD values. The MAGNET results did not correspond to any CFD or experimental results against which they could be compared, so they were instead compared against the proposed CFD input conditions. These values were then compared with each other to make sure the model seemed to be performing as expected, paving the way for future tests that can be run for the purpose of further analyses and comparisons. The pressure drop increased with temperature and mass flow rate independently. The temperature change would decrease with increasing mass flow rate and temperature, which was just as we expected based on the fact that the lower viscosity and decreased density would result in higher friction and churning losses. The last metric that was assessed was the enthalpy flow change, which increased with increasing mass flow rate and decreasing temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1973

SIRU utilization. Volume 2: Software description and program documentation

A complete description of the additional analysis, development and evaluation provided for the SIRU system as identified in the requirements for the SIRU utilization program is presented. The SIRU configuration is a modular inertial subsystem with hardware and software features that achieve fault tolerant operational capabilities. The SIRU redundant hardware design is formulated about a six gyro and six accelerometer instrument module package. The modules are mounted in this package so that their measurement input axes form a unique symmetrical pattern that corresponds to the array of perpendiculars to the faces of a regular dodecahedron. This six axes array provides redundant independent sensing and the symmetry enables the formulation of an optimal software redundant data processing structure with self-contained fault detection and isolation (FDI) capabilities. Documentation of the additional software and software modifications required to implement the utilization capabilities includes assembly listings and flow charts

Oehrle, J.↗

NASA NTRS1987

Structural properties of impact ices accreted on aircraft structures

The structural properties of ice accretions formed on aircraft surfaces are studied. The overall objectives are to measure basic structural properties of impact ices and to develop finite element analytical procedures for use in the design of all deicing systems. The Icing Research Tunnel (IRT) was used to produce simulated natural ice accretion over a wide range of icing conditions. Two different test apparatus were used to measure each of the three basic mechanical properties: tensile, shear, and peeling. Data was obtained on both adhesive shear strength of impact ices and peeling forces for various icing conditions. The influences of various icing parameters such as tunnel air temperature and velocity, icing cloud drop size, material substrate, surface temperature at ice/material interface, and ice thickness were studied. A finite element analysis of the shear test apparatus was developed in order to gain more insight in the evaluation of the test data. A comparison with other investigators was made. The result shows that the adhesive shear strength of impact ice typically varies between 40 and 50 psi, with peak strength reaching 120 psi and is not dependent on the kind of substrate used, the thickness of accreted ice, and tunnel temperature below 4 C.

Scavuzzo, R. J.↗

NASA NTRS2000

Photogrammetrically Measured Distortions of Composite Structure Microwave Reflectors at Approximately 90 K

The Microwave Anisotropy Probe (MAP) Observatory, scheduled for a fall 2000 launch, is designed to measure temperature fluctuations (anisotropy) and produce a high sensitivity and high spatial resolution (better than 0.3 deg.) map of the cosmic microwave background (CMB) radiation over the entire sky between 22 and 90 GHz. MAP utilizes back-to-back composite Gregorian telescopes supported on a composite truss structure to focus the microwave signals into 10 differential microwave receivers. Proper position and shape of the telescope reflectors at the operating temperature of approximately 90 K is a critical element to ensuring mission success. We describe the methods and analysis used to validate the in-flight position and shape predictions for the reflectors based on photogrammetric (PG) metrology data taken under vacuum with the reflectors at approximately 90 K. Contour maps showing reflector distortion analytical extrapolations were generated. The resulting reflector distortion data are shown to be crucial to the analytical assessment of the MAP instrument's microwave system in-flight performance.

Mule, Peter↗

NASA NTRS2000

Advanced Transportation System Studies. Technical Area 3: Alternate Propulsion Subsystem Concepts: Executive Summary - Volume 1

The Alternate Propulsion Subsystem Concepts contract had seven tasks defined that are reported under this contract deliverable. The tasks were: FAA Restart Study, J-2S Restart Study, Propulsion Database Development. SSME Upper Stage Use. CERs for Liquid Propellant Rocket Engines. Advanced Low Cost Engines, and Tripropellant Comparison Study. The two restart studies, F-1A and J-2S, generated program plans for restarting production of each engine. Special emphasis was placed on determining changes to individual parts due to obsolete materials, changes in OSHA and environmental concerns, new processes available, and any configuration changes to the engines. The Propulsion Database Development task developed a database structure and format which is easy to use and modify while also being comprehensive in the level of detail available. The database structure included extensive engine information and allows for parametric data generation for conceptual engine concepts. The SSME Upper Stage Use task examined the changes needed or desirable to use the SSME as an upper stage engine both in a second stage and in a translunar injection stage. The CERs for Liquid Engines task developed qualitative parametric cost estimating relationships at the engine and major subassembly level for estimating development and production costs of chemical propulsion liquid rocket engines. The Advanced Low Cost Engines task examined propulsion systems for SSTO applications including engine concept definition, mission analysis. trade studies. operating point selection, turbomachinery alternatives, life cycle cost, weight definition. and point design conceptual drawings and component design. The task concentrated on bipropellant engines, but also examined tripropellant engines. The Tripropellant Comparison Study task provided an unambiguous comparison among various tripropellant implementation approaches and cycle choices, and then compared them to similarly designed bipropellant engines in the SSTO mission This volume overviews each of the tasks giving its objectives, main results. and conclusions. More detailed Final Task Reports are available on each individual task.

Levack, Daniel J. H.↗

NASA NTRS2026

Development, Characterization, and Validation of Elevated-Temperature Constitutive Models: Deformation and Damage

This report provides a brief review of experimentally observed hereditary and nonhereditary material behavior along with background information on standard as well as advanced internal state variable constitutive modeling at elevated temperature. A description of exploratory, characterization, and validation testing is presented along with a detailed outline of what constitutes “sufficient” data content (i.e., quality and quantity) for developing or enhancing, characterizing, and validating a particular sophisticated nonlinear time- and history-dependent (hereditary) class of constitutive models known as GVIPS (generalized viscoplasticity with potential structure). The tests described are necessary to reveal a material’s behavior in the reversible (or viscoelastic) and irreversible (or viscoplastic) regimes, for the identification of both deformation and damage model parameters. Results presented are primarily for metallic materials. In all cases, both uniaxial and multiaxial tests are described, and the linkage between the specific tests and the parameters within the model that can be characterized from the results of these tests are also discussed. Discussion is also provided relative to the role information management must play relative to material data collection, analysis, maintenance, and dissemination. The need for such an information system is particularly important as both analyst and designer move toward utilizations of sophisticated, nonlinear time- and history dependent (hereditary) constitutive models. Lastly, the concept of state space and its utility in understanding and establishing constitutive models is addressed throughout. The intent behind this document is to help both the modeler and experimentalist understand each other’s specific points of view and provide guidance for both model development and characterization. Emphasis has been placed on providing the mechanician with information regarding how tests are performed and what issues to be aware of when interpreting results. It is hoped that experimentalists will take away a new perspective on the types of information that modelers and analysts are looking for from them.

Constitutive Modeling↗

NASA NTRS2015

Aeroelastic Analysis of SUGAR Truss-Braced Wing Wind-Tunnel Model Using FUN3D and a Nonlinear Structural Model

Considerable attention has been given in recent years to the design of highly flexible aircraft. The results of numerous studies demonstrate the significant performance benefits of strut-braced wing (SBW) and trussbraced wing (TBW) configurations. Critical aspects of the TBW configuration are its larger aspect ratio, wing span and thinner wings. These aspects increase the importance of considering fluid/structure and control system coupling. This paper presents high-fidelity Navier-Stokes simulations of the dynamic response of the flexible Boeing Subsonic Ultra Green Aircraft Research (SUGAR) truss-braced wing wind-tunnel model. The latest version of the SUGAR TBW finite element model (FEM), v.20, is used in the present simulations. Limit cycle oscillations (LCOs) of the TBW wing/strut/nacelle are simulated at angle-of-attack (AoA) values of -1, 0 and +1 degree. The modal data derived from nonlinear static aeroelastic MSC.Nastran solutions are used at AoAs of -1 and +1 degrees. The LCO amplitude is observed to be dependent on AoA. LCO amplitudes at -1 degree are larger than those at +1 degree. The LCO amplitude at zero degrees is larger than either -1 or +1 degrees. These results correlate well with both wind-tunnel data and the behavior observed in previous studies using linear aerodynamics. The LCO onset at zero degrees AoA has also been computed using unloaded v.20 FEM modes. While the v.20 model increases the dynamic pressure at which LCO onset is observed, it is found that the LCO onset at and above Mach 0.82 is much different than that produced by an earlier version of the FEM, v. 19.

Bartels, Robert E.↗

DOE OSTI2020

Data-driven Detection and Early Prediction of Thermoacoustic Instability in a Multi-nozzle Combustor

Thermoacoustic instability (TAI) is a critical issue in modern lean-burn gas-turbine combustors, which is induced by a strong coupling between the resonant combustor acoustics and fluctuations in the heat release rate. This instability may lead to high-amplitude pressure waves that generate undesirable noise levels as well as fatigue stresses in mechanical structures of the combustor. The intense pressure fluctuations due to TAI may also cause large flow perturbations and possibly flow reversal that may lead to flame oscillations, flame liftoff, and even flame blow-out. Hence, there is a strong need for exercising control actions in a timely fashion to mitigate the TAI phenomena. Anomaly detection is an essential prerequisite to the design of a good controller and such a detector must be able to reliably predict a forthcoming TAI. To detect and predict the onset of a TAI from an ensemble of pressure time series, this paper investigates three data-driven methods: Fast Fourier transform (FFT), symbolic time series analysis (STSA), and hidden Markov modeling (HMM). The main focus of the paper is to make a comparative evaluation of these three anomaly detection methods for classification of the current regime of operation into stable and unstable categories as well as for real-time identification of precursors to impending instabilities with short-length time series of measured variables (e.g., pressure oscillations). Finally, the results, generated on experimental data from a multi-nozzle combustor apparatus, have been compared to evaluate the performance of FFT, STSA, and HMM methods for TAI analysis.

42 ENGINEERING↗

NASA NTRS1994

A Supersonic Tunnel for Laser and Flow-Seeding Techniques

A supersonic wind tunnel with flow conditions of 3 lbm/s (1.5 kg/s) at a free-stream Mach number of 2.5 was designed and tested to provide an arena for future development work on laser measurement and flow-seeding techniques. The hybrid supersonic nozzle design that was used incorporated the rapid expansion method of propulsive nozzles while it maintained the uniform, disturbance-free flow required in supersonic wind tunnels. A viscous analysis was performed on the tunnel to determine the boundary layer growth characteristics along the flowpath. Appropriate corrections were then made to the contour of the nozzle. Axial pressure distributions were measured and Mach number distributions were calculated based on three independent data reduction methods. A complete uncertainty analysis was performed on the precision error of each method. Complex shock-wave patterns were generated in the flow field by wedges mounted near the roof and floor of the tunnel. The most stable shock structure was determined experimentally by the use of a focusing schlieren system and a novel, laser based dynamic shock position sensor. Three potential measurement regions for future laser and flow-seeding studies were created in the shock structure: deceleration through an oblique shock wave of 50 degrees, strong deceleration through a normal shock wave, and acceleration through a supersonic expansion fan containing 25 degrees of flow turning.

Bruckner, Robert J.↗

NASA NTRS2000

Photogrammetrically Measured Distortions of Composite Structure Microwave Reflectors at -90K

The Microwave Anisotropy Probe (MAP) Observatory, scheduled for a late 2000 launch, is designed to measure temperature fluctuations (anisotropy) and produce a high sensitivity and high spatial resolution (better than 0.3 deg. at 90 GHz.) map of the Cosmic Microwave Background (CMB) radiation over the entire sky between 22 and 90 GHz. MAP utilizes back-to-back composite Gregorian telescopes supported on a composite truss structure to focus the microwave signals into 10 differential microwave receivers. Proper position and shape of the telescope reflectors at the operating temperature of -90 K is a critical element to ensure mission success. We describe the methods and analysis used to validate the in-flight position and shape predictions for the reflectors based on photogrammetric metrology data taken under vacuum with the reflectors at -90 K. Contour maps showing reflector distortion were generated. The resulting reflector distortion data are shown to be crucial to the analytical assessment of the MAP instrument's microwave system in-flight performance.

Mule, Peter↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗