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At least 613 records · Page 34

SynGenics Optimization System (SynOptSys)

The SynGenics Optimization System (SynOptSys) software application optimizes a product with respect to multiple, competing criteria using statistical Design of Experiments, Response-Surface Methodology, and the Desirability Optimization Methodology. The user is not required to be skilled in the underlying math; thus, SynOptSys can help designers and product developers overcome the barriers that prevent them from using powerful techniques to develop better pro ducts in a less costly manner. SynOpt-Sys is applicable to the design of any product or process with multiple criteria to meet, and at least two factors that influence achievement of those criteria. The user begins with a selected solution principle or system concept and a set of criteria that needs to be satisfied. The criteria may be expressed in terms of documented desirements or defined responses that the future system needs to achieve. Documented desirements can be imported into SynOptSys or created and documented directly within SynOptSys. Subsequent steps include identifying factors, specifying model order for each response, designing the experiment, running the experiment and gathering the data, analyzing the results, and determining the specifications for the optimized system. The user may also enter textual information as the project progresses. Data is easily edited within SynOptSys, and the software design enables full traceability within any step in the process, and facilitates reporting as needed. SynOptSys is unique in the way responses are defined and the nuances of the goodness associated with changes in response values for each of the responses of interest. The Desirability Optimization Methodology provides the basis of this novel feature. Moreover, this is a complete, guided design and optimization process tool with embedded math that can remain invisible to the user. It is not a standalone statistical program; it is a design and optimization system.

Ventresca, Carol↗

Use of Soft Computing Technologies For Rocket Engine Control

The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to further improve overall engine system reliability and performance. Specifically, this will be presented by enhancing rocket engine control and engine health management (EHM) using SCT coupled with conventional control technologies, and sound software engineering practices used in Marshall s Flight Software Group. The principle goals are to improve software management, software development time and maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control and EHM methodologies, but to provide alternative design choices for control, EHM, implementation, performance, and sustaining engineering. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion, software engineering for embedded systems, and soft computing technologies (i.e., neural networks, fuzzy logic, and Bayesian belief networks), much of which is presented in this paper. The first targeted demonstration rocket engine platform is the MC-1 (formerly FASTRAC Engine) which is simulated with hardware and software in the Marshall Avionics & Software Testbed laboratory that

Trevino, Luis C.↗

ACES: Space shuttle flight software analysis expert system

The Analysis Criteria Evaluation System (ACES) is a knowledge based expert system that automates the final certification of the Space Shuttle onboard flight software. Guidance, navigation and control of the Space Shuttle through all its flight phases are accomplished by a complex onboard flight software system. This software is reconfigured for each flight to allow thousands of mission-specific parameters to be introduced and must therefore be thoroughly certified prior to each flight. This certification is performed in ground simulations by executing the software in the flight computers. Flight trajectories from liftoff to landing, including abort scenarios, are simulated and the results are stored for analysis. The current methodology of performing this analysis is repetitive and requires many man-hours. The ultimate goals of ACES are to capture the knowledge of the current experts and improve the quality and reduce the manpower required to certify the Space Shuttle onboard flight software.

Satterwhite, R. Scott↗

Methodology for the Elimination of Reflection and System Vibration Effects in Particle Image Velocimetry Data Processing

A methodology to eliminate model reflection and system vibration effects from post processed particle image velocimetry data is presented. Reflection and vibration lead to loss of data, and biased velocity calculations in PIV processing. A series of algorithms were developed to alleviate these problems. Reflections emanating from the model surface caused by the laser light sheet are removed from the PIV images by subtracting an image in which only the reflections are visible from all of the images within a data acquisition set. The result is a set of PIV images where only the seeded particles are apparent. Fiduciary marks painted on the surface of the test model were used as reference points in the images. By locating the centroids of these marks it was possible to shift all of the images to a common reference frame. This image alignment procedure as well as the subtraction of model reflection are performed in a first algorithm. Once the images have been shifted, they are compared with a background image that was recorded under no flow conditions. The second and third algorithms find the coordinates of fiduciary marks in the acquisition set images and the background image and calculate the displacement between these images. The final algorithm shifts all of the images so that fiduciary mark centroids lie in the same location as the background image centroids. This methodology effectively eliminated the effects of vibration so that unbiased data could be used for PIV processing. The PIV data used for this work was generated at the NASA Langley Research Center Quiet Flow Facility. The experiment entailed flow visualization near the flap side edge region of an airfoil model. Commercial PIV software was used for data acquisition and processing. In this paper, the experiment and the PIV acquisition of the data are described. The methodology used to develop the algorithms for reflection and system vibration removal is stated, and the implementation, testing and validation of these algorithms are presented.

Bremmer, David M.↗

Dynamic calibration of differential equations using machine learning, with application to turbulence models

We present a methodology for calibration of parametric ordinary and partial differential equation models, using off-the-shelf software for back-propagation in Neural Networks (NN). As a prototypical example, we consider calibration of a Reynolds-averaged Navier-Stokes (RANS) turbulence closure model, against ground truth data from direct numerical simulations (DNS) of two different turbulent flows. Numerical time integration is represented as a custom NN, where only the RANS model parameters are trainable. A loss function is defined to quantify the mismatch between the NN prediction and the ground truth over a predefined, finite time integration window. This loss function is then minimized using a gradient descent method utilizing the back-propagation algorithm. Furthermore, this dynamic approach to training is to be contrasted with a static approach, wherein a least square regression estimate for parameters is obtained in the limit of an infinitesimal time integration window. In a first test of static and dynamic approaches against ground truth data generated by the model, the former proves to be significantly faster and more accurate than the latter at recovering the parameters. When both calibration approaches are tested against DNS data, for which it is known that the model cannot achieve a perfect fit, the static approach yields a good prediction only for short times, while the dynamic approach results in physical and stable predictions over the entire integration window. After optimization of the dynamic approach for time step, spatial resolution, stability, and physics-based constraints, we obtain a 50% improvement of outcomes over those obtained from the existing, manually calibrated set of parameters, demonstrating the merits of this systematic and automated procedure.

97 MATHEMATICS AND COMPUTING↗

Operator function modeling: An approach to cognitive task analysis in supervisory control systems

In a study of models of operators in complex, automated space systems, an operator function model (OFM) methodology was extended to represent cognitive as well as manual operator activities. Development continued on a software tool called OFMdraw, which facilitates construction of an OFM by permitting construction of a heterarchic network of nodes and arcs. Emphasis was placed on development of OFMspert, an expert system designed both to model human operation and to assist real human operators. The system uses a blackboard method of problem solving to make an on-line representation of operator intentions, called ACTIN (actions interpreter).

Mitchell, Christine M.↗

Embedded parallel processing based ground control systems for small satellite telemetry

The use of networked terminals which utilize embedded processing techniques results in totally integrated, flexible, high speed, reliable, and scalable systems suitable for telemetry and data processing applications such as mission operations centers (MOC). Synergies of these terminals, coupled with the capability of terminal to receive incoming data, allow the viewing of any defined display by any terminal from the start of data acquisition. There is no single point of failure (other than with network input) such as exists with configurations where all input data goes through a single front end processor and then to a serial string of workstations. Missions dedicated to NASA's ozone measurements program utilize the methodologies which are discussed, and result in a multimission configuration of low cost, scalable hardware and software which can be run by one flight operations team with low risk.

Forman, Michael L.↗

Angle Measurement System (AMS) for Establishing Model Pitch and Roll Zero, and Performing Single Axis Angle Comparisons

The angle measurement system (AMS) developed at NASA Langley Research Center (LaRC) is a system for many uses. It was originally developed to check taper fits in the wind tunnel model support system. The system was further developed to measure simultaneous pitch and roll angles using 3 orthogonally mounted accelerometers (3-axis). This 3-axis arrangement is used as a transfer standard from the calibration standard to the wind tunnel facility. It is generally used to establish model pitch and roll zero and performs the in-situ calibration on model attitude devices. The AMS originally used a laptop computer running DOS based software but has recently been upgraded to operate in a windows environment. Other improvements have also been made to the software to enhance its accuracy and add features. This paper will discuss the accuracy and calibration methodologies used in this system and some of the features that have contributed to its popularity.

Crawford, Bradley L.↗

Mastering HPC Runtime Prediction: From Observing Patterns to a Methodological Approach: Preprint

The continual expansion of high-performance computing (HPC) brings with it an increasing need for efficiency. Heavy investment in energy, hardware, and software infrastructure to support peta- and exascale computing requires the optimization of existing systems and, wherever possible, the discernment and adoption of best-practices towards these goals. Such is the case for runtime prediction. When a job is submitted to an HPC system, an estimate of its runtime is provided by the user in the form of "requested wallclock''. Error in this user-provided estimate can lead to jobs being prematurely killed by the scheduler, increased wait time on the queue, and decreased system utilization. More than fifteen years of research has been directed at mitigating these effects by using data-driven runtime predictions. Codified here is a set of commonalities and insights emerging from this body of work, which we present as recommendations and best practices. These practices are combined into a methodological approach described and evaluated on an 11-million-job dataset from the National Renewable Energy Laboratory's petascale HPC system, Eagle. This dataset and the accompanying codebase have been released to the public domain for the benefit of the wider HPC research community.

high performance computing↗

An unstructured-grid software system for solving complex aerodynamic problems

A coordinated effort has been underway over the past four years to elevate unstructured-grid methodology to a mature level. The goal of this endeavor is to provide a validated capability to non-expert users for performing rapid aerodynamic analysis and design of complex configurations. The Euler component of the system is well developed, and is impacting a broad spectrum of engineering needs with capabilities such as rapid grid generation and inviscid flow analysis, inverse design, interactive boundary layers, and propulsion effects. Progress is also being made in the more tenuous Navier-Stokes component of the system. A robust grid generator is under development for constructing quality thin-layer tetrahedral grids, along with a companion Navier-Stokes flow solver. This paper presents an overview of this effort, along with a perspective on the present and future status of the methodology.

Frink, Neal T.↗

A Methodology for Writing High Quality Requirements Specification and Evaluating Existing Ones

Requirements development and management have always been critical in the implementation of software systems; engineers are unable to build what analysts can't define. It is generally accepted that the earlier in the life cycle potential risks are identified the easier it is to eliminate or manage the conditions that introduce that risk. Problems that are not found until testing are approximately 14 times more costly to fix than if the problem was found in the requirement phase. The requirements specification, as the first tangible representation of the capability to be produced, establishes the basis for all of the project's engineering management and assurance functions. If the quality of the requirements specification is poor it can give rise to risks in all areas of the project. Recently, automated tools have become available to support requirements management. The use of these tools not only provides support in the definition and tracing of requirements, but it also opens the door to effective use of metrics in characterizing and assessing the quality of the requirement specifications.

Rosenberg, Linda↗

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗

Use of Soft Computing Technologies for a Qualitative and Reliable Engine Control System for Propulsion Systems

The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to improve overall vehicle system safety, reliability, and rocket engine performance by development of a qualitative and reliable engine control system (QRECS). Specifically, this will be addressed by enhancing rocket engine control using SCT, innovative data mining tools, and sound software engineering practices used in Marshall's Flight Software Group (FSG). The principle goals for addressing the issue of quality are to improve software management, software development time, software maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control methodologies, but to provide alternative design choices for control, implementation, performance, and sustaining engineering, all relative to addressing the issue of reliability. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion (system level), software engineering for embedded flight software systems, and soft computing technologies (i.e., neural networks, fuzzy logic, data mining, and Bayesian belief networks); some of which are briefed in this paper. For this effort, the targeted demonstration rocket engine testbed is the MC-1 engine (formerly FASTRAC) which is simulated with hardware and software in the Marshall Avionics & Software Testbed (MAST) laboratory that currently resides at NASA's Marshall Space Flight Center, building 4476, and is managed by the Avionics Department. A brief plan of action for design, development, implementation, and testing a Phase One effort for QRECS is given, along with expected results. Phase One will focus on development of a Smart Start Engine Module and a Mainstage Engine Module for proper engine start and mainstage engine operations. The overall intent is to demonstrate that by employing soft computing technologies, the quality and reliability of the overall scheme to engine controller development is further improved and vehicle safety is further insured. The final product that this paper proposes is an approach to development of an alternative low cost engine controller that would be capable of performing in unique vision spacecraft vehicles requiring low cost advanced avionics architectures for autonomous operations from engine pre-start to engine shutdown.

Trevino, Luis↗

Application of Lightweight Formal Methods to Software Security

Formal specification and verification of security has proven a challenging task. There is no single method that has proven feasible. Instead, an integrated approach which combines several formal techniques can increase the confidence in the verification of software security properties. Such an approach which species security properties in a library that can be reused by 2 instruments and their methodologies developed for the National Aeronautics and Space Administration (NASA) at the Jet Propulsion Laboratory (JPL) are described herein The Flexible Modeling Framework (FMF) is a model based verijkation instrument that uses Promela and the SPIN model checker. The Property Based Tester (PBT) uses TASPEC and a Text Execution Monitor (TEM). They are used to reduce vulnerabilities and unwanted exposures in software during the development and maintenance life cycles.

security↗

Noninvasive Test Detects Cardiovascular Disease

At NASA's Jet Propulsion Laboratory (JPL), NASA-developed Video Imaging Communication and Retrieval (VICAR) software laid the groundwork for analyzing images of all kinds. A project seeking to use imaging technology for health care diagnosis began when the imaging team considered using the VICAR software to analyze X-ray images of soft tissue. With marginal success using X-rays, the team applied the same methodology to ultrasound imagery, which was already digitally formatted. The new approach proved successful for assessing amounts of plaque build-up and arterial wall thickness, direct predictors of heart disease, and the result was a noninvasive diagnostic system with the ability to accurately predict heart health. Medical Technologies International Inc. (MTI) further developed and then submitted the technology to a vigorous review process at the FDA, which cleared the software for public use. The software, patented under the name Prowin, is being used in MTI's patented ArterioVision, a carotid intima-media thickness (CIMT) test that uses ultrasound image-capturing and analysis software to noninvasively identify the risk for the major cause of heart attack and strokes: atherosclerosis. ArterioVision provides a direct measurement of atherosclerosis by safely and painlessly measuring the thickness of the first two layers of the carotid artery wall using an ultrasound procedure and advanced image-analysis software. The technology is now in use in all 50 states and in many countries throughout the world.

Source record↗

A Methodology for Writing High Quality Requirement Specifications and for Evaluating Existing Ones

Requirements development and management have always been critical in the implementation of software systems-engineers are unable to build what analysts can not define. It is generally accepted that the earlier in the life cycle potential risks are identified the easier it is to eliminate or manage the conditions that introduce that risk. Problems that are not found until testing are approximately 14 times more costly to fix than if the problem was found in the requirement phase. The requirements specification, as the first tangible representation of the capability to be produced, establishes the basis for all of the project's engineering management and assurance functions. If the quality of the requirements specification is poor it can give rise to risks in all areas of the project. Recently, automated tools have become available to support requirements management. The use of these tools not only provides support in the definition and tracing of requirements, but it also opens the door to effective use of metrics in characterizing and assessing the quality of the requirement specifications.

Rosenberg, Linda↗

Risk management and expert system development methodology

A risk-based expert-system development methodology has been developed to provide guidance to managers and technical personnel and to serve as a standard for developing expert systems. Expert-system development differs from conventional software development in that the information needed to prepare system requirements for expert systems is not known at the outset of a project and is obtained by knowledge engineering methods. The paper describes the expert-system life cycle, development methodology, and the approach taken in this methodology to manage and reduce the risks in expert system development. Also examined are the risks of using and of not using a methodology, the studies undertaken to validate the provisions of the expert system development methodology, and the results of these validation studies.

Hull, Larry↗

Maldives Climate: Monitoring Shoreline Changes and Island Loss in Response to Climate Change

Global sea level rise as a result of climate change continues to pose a critical threat to coastal ecosystems and populations. The archipelagic country of the Maldives is of critical concern due to being one of the lowest lying areas in the world. The development of reclaimed land in the Maldives by sand dredging has been a frequent response to both increasing sea levels and population increase. Such disturbance can lead to increased sedimentation off the coast and negatively impact coastal environments. Remote sensing tools such as satellite imagery have proved to be an effective tool in observing coastal changes in response to climate change and development. NASA DEVELOP created a methodology to analyze both water quality and shoreline erosion in the Maldives utilizing satellite imagery. Methods relied on open-source software such as QGIS and Google Earth Engine (GEE) and Satellite Imagery from PlanetScope, Landsat 8 Operational Land Instrument (OLI), Sentinel-2 Multi Spectral Instrument (MSI), and Aqua & Terra Moderate Resolution Imaging Radiospectrometer (MODIS) to analyze the changes in shorelines and assess water quality of select atolls within the Maldives. Findings show less shoreline change in developed parts of the island and more shoreline change in natural parts of the island. Additionally, water quality varies throughout the year and our data did not indicate seasonal trends. The methodology will be replicated to continue to monitor island erosion and water quality with the Maldives and will be applicable to other island and coastal systems.

remote sensing↗