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At least 937 records · Page 52

Composite Flywheels Assessed Analytically by NDE and FEA

As an alternative to expensive and short-lived lead-acid batteries, composite flywheels are being developed to provide an uninterruptible power supply for advanced aerospace and industrial applications. Flywheels can help prevent irregularities in voltage caused by power spikes, sags, surges, burnout, and blackouts. Other applications include load-leveling systems for wind and solar power facilities, where energy output fluctuates with weather. Advanced composite materials are being considered for these components because they are significantly lighter than typical metallic alloys and have high specific strength and stiffness. However, much more research is needed before these materials can be fully utilized, because there is insufficient data concerning their fatigue characteristics and nonlinear behavior, especially at elevated temperatures. Moreover, these advanced types of structural composites pose greater challenges for nondestructive evaluation (NDE) techniques than are encountered with typical monolithic engineering metals. This is particularly true for ceramic polymer and metal matrix composites, where structural properties are tailored during the processing stages. Current efforts involving the NDE group at the NASA Glenn Research Center at Lewis Field are focused on evaluating many important structural components, including the flywheel system. Glenn's in-house analytical and experimental capabilities are being applied to analyze data produced by computed tomography (CT) scans to help assess the damage and defects of high-temperature structural composite materials. Finite element analysis (FEA) has been used extensively to model the effects of static and dynamic loading on aerospace propulsion components. This technique allows the use of complicated loading schemes by breaking the complex part geometry into many smaller, geometrically simple elements.

Abdul-Aziz, Ali↗

Uncertainty Modeling for Robustness Analysis of Control Upset Prevention and Recovery Systems

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. Such systems (developed for failure detection, identification, and reconfiguration, as well as upset recovery) need to be evaluated over broad regions of the flight envelope and under extreme flight conditions, and should include various sources of uncertainty. However, formulation of linear fractional transformation (LFT) models for representing system uncertainty can be very difficult for complex parameter-dependent systems. This paper describes a preliminary LFT modeling software tool which uses a matrix-based computational approach that can be directly applied to parametric uncertainty problems involving multivariate matrix polynomial dependencies. Several examples are presented (including an F-16 at an extreme flight condition, a missile model, and a generic example with numerous crossproduct terms), and comparisons are given with other LFT modeling tools that are currently available. The LFT modeling method and preliminary software tool presented in this paper are shown to compare favorably with these methods.

Belcastro, Christine M.↗

The Application of Infrared Thermographic Inspection Techniques to the Space Shuttle Thermal Protection System

The Nondestructive Evaluation Sciences Branch at NASA s Langley Research Center has been actively involved in the development of thermographic inspection techniques for more than 15 years. Since the Space Shuttle Columbia accident, NASA has focused on the improvement of advanced NDE techniques for the Reinforced Carbon-Carbon (RCC) panels that comprise the orbiter s wing leading edge. Various nondestructive inspection techniques have been used in the examination of the RCC, but thermography has emerged as an effective inspection alternative to more traditional methods. Thermography is a non-contact inspection method as compared to ultrasonic techniques which typically require the use of a coupling medium between the transducer and material. Like radiographic techniques, thermography can be used to inspect large areas, but has the advantage of minimal safety concerns and the ability for single-sided measurements. Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. A typical implementation of PCA is when the eigenvectors are generated from the data set being analyzed. Although it is a powerful tool for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from the RCC materials. Details of a one-dimensional analytic model and a two-dimensional finite-element model will be presented. An overview of the PCA process as well as a quantitative signal-to-noise comparison of the results of performing both embodiments of PCA on thermographic data from various RCC specimens will be shown. Finally, a number of different applications of this technology to various RCC components will be presented.

Cramer, K. E.↗

The Application of Principal Component Analysis Using Fixed Eigenvectors to the Infrared Thermographic Inspection of the Space Shuttle Thermal Protection System

The Nondestructive Evaluation Sciences Branch at NASA s Langley Research Center has been actively involved in the development of thermographic inspection techniques for more than 15 years. Since the Space Shuttle Columbia accident, NASA has focused on the improvement of advanced NDE techniques for the Reinforced Carbon-Carbon (RCC) panels that comprise the orbiter s wing leading edge. Various nondestructive inspection techniques have been used in the examination of the RCC, but thermography has emerged as an effective inspection alternative to more traditional methods. Thermography is a non-contact inspection method as compared to ultrasonic techniques which typically require the use of a coupling medium between the transducer and material. Like radiographic techniques, thermography can be used to inspect large areas, but has the advantage of minimal safety concerns and the ability for single-sided measurements. Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. A typical implementation of PCA is when the eigenvectors are generated from the data set being analyzed. Although it is a powerful tool for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the good material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued when a fixed set of eigenvectors is used to process the thermal data from the RCC materials. These eigen vectors can be generated either from an analytic model of the thermal response of the material under examination, or from a large cross section of experimental data. This paper will provide the details of the analytic model; an overview of the PCA process; as well as a quantitative signal-to-noise comparison of the results of performing both embodiments of PCA on thermographic data from various RCC specimens. Details of a system that has been developed to allow insitu inspection of a majority of shuttle RCC components will be presented along with the acceptance test results for this system. Additionally, the results of applying this technology to the Space Shuttle Discovery after its return from flight will be presented.

Cramer, K. Elliott↗

A Framework for Parallel Unstructured Grid Generation for Complex Aerodynamic Simulations

A framework for parallel unstructured grid generation targeting both shared memory multi-processors and distributed memory architectures is presented. The two fundamental building-blocks of the framework consist of: (1) the Advancing-Partition (AP) method used for domain decomposition and (2) the Advancing Front (AF) method used for mesh generation. Starting from the surface mesh of the computational domain, the AP method is applied recursively to generate a set of sub-domains. Next, the sub-domains are meshed in parallel using the AF method. The recursive nature of domain decomposition naturally maps to a divide-and-conquer algorithm which exhibits inherent parallelism. For the parallel implementation, the Master/Worker pattern is employed to dynamically balance the varying workloads of each task on the set of available CPUs. Performance results by this approach are presented and discussed in detail as well as future work and improvements.

Zagaris, George↗

Mutual Coupling of Internal Transmit/Receive Pair in Launch Vehicle Fairing Model Using WIPL-D

Evaluating the fairing Radio Frequency (RF) Environment within the launch vehicle payload fairing cavity due to internal transmitters is an issue for the spacecraft and launch vehicle industry. This paper provides an effective approach for launch vehicle fairing evaluation of power reception and field distribution due to internal transmitters. A commercial electromagnetic computational tool, WIPL-D is applied in this study for test data comparison.

Trout, Dawn H.↗

Remote Sensing and Information Technology for Large Farms

A method of applying remote sensing (RS) and information-management technology to help large farms produce at maximum efficiency is undergoing development. The novelty of the method does not lie in the concept of precision agriculture, which involves variation of seeding, of application of chemicals, and of irrigation according to the spatially and temporally local variations in the growth stages and health of crops and in the chemical and physical conditions of soils. The novelty also does not lie in the use of RS data registered with other data in a geographic information system (GIS) to guide the use of precise agricultural techniques. Instead, the novelty lies in a systematic approach to overcoming obstacles that, heretofore, have impeded the timely distribution of reliable, relevant, and sufficient GIS data to support day-to-day, acre-to-acre decisions concerning the application of precise agricultural techniques to increase production and decrease cost. The development and promotion of the method are inspired in part by a vision of equipping farm machinery to accept GIS (including RS) data and using the data for automated or semi-automated implementation of precise agricultural techniques. Primary examples of relevant GIS data include information on plant stress, soil moisture, and effects of applied chemicals, all derived by automated computational analysis of measurements taken by one or more airborne spectroradiometers. Proper management and timeliness of the large amount of GIS information are of paramount concern in agriculture. Information on stresses and changes in crops is especially perishable and important to farmers. The need for timeliness and management of information is satisfied by use of computing hardware and software capable of (1) rapid geo-rectification and other processing of RS data, (2) packaging the output data in the form of GIS plots, and (3) making the data available to farmers and other subscribers by Internet password access. It is a goal of this development program to make RS data available no later than the data after an aerial survey. In addition, data from prior surveys are kept in the data base. Farmers can, for example, use current and prior data to analyze changes.

Williams, John E.↗

Computer Modeling of Direct Metal Laser Sintering

A computational approach to modeling direct metal laser sintering (DMLS) additive manufacturing process is presented. The primary application of the model is for determining the temperature history of parts fabricated using DMLS to evaluate residual stresses found in finished pieces and to assess manufacturing process strategies to reduce part slumping. The model utilizes MSC SINDA as a heat transfer solver with imbedded FORTRAN computer code to direct laser motion, apply laser heating as a boundary condition, and simulate the addition of metal powder layers during part fabrication. Model results are compared to available data collected during in situ DMLS part manufacture.

Cross, Matthew↗

Assessing Fan Flutter Stability in the Presence of Inlet Distortion Using One-way and Two-way Coupled Methods

Concerns regarding noise, propulsive efficiency, and fuel burn are inspiring aircraft designs wherein the propulsive turbomachines are partially (or fully) embedded within the airframe; such designs present serious concerns with regard to aerodynamic and aeromechanic performance of the compression system in response to inlet distortion. Previously, a preliminary design of a forward-swept high-speed fan exhibited flutter concerns in cleaninlet flows, and the present author then studied this fan further in the presence of off-design distorted in-flows. Continuing this research, a three-dimensional, unsteady, Navier-Stokes computational fluid dynamics code is again applied to analyze and corroborate fan performance with clean inlet flow and now with a simplified, sinusoidal distortion of total pressure at the aerodynamic interface plane. This code, already validated in its application to assess aerodynamic damping of vibrating blades at various flow conditions using a one-way coupled energy-exchange approach, is modified to include a two-way coupled time-marching aeroelastic simulation capability. The two coupling methods are compared in their evaluation of flutter stability in the presence of distorted in-flows.

aeroelasticity↗

Assessing Fan Flutter Stability in Presence of Inlet Distortion Using One-Way and Two-Way Coupled Methods

Concerns regarding noise, propulsive efficiency, and fuel burn are inspiring aircraft designs wherein the propulsive turbomachines are partially (or fully) embedded within the airframe; such designs present serious concerns with regard to aerodynamic and aeromechanic performance of the compression system in response to inlet distortion. Previously, a preliminary design of a forward-swept high-speed fan exhibited flutter concerns in clean-inlet flows, and the present author then studied this fan further in the presence of off-design distorted in-flows. Continuing this research, a three-dimensional, unsteady, Navier-Stokes computational fluid dynamics code is again applied to analyze and corroborate fan performance with clean inlet flow and now with a simplified, sinusoidal distortion of total pressure at the aerodynamic interface plane. This code, already validated in its application to assess aerodynamic damping of vibrating blades at various flow conditions using a one-way coupled energy-exchange approach, is modified to include a two-way coupled timemarching aeroelastic simulation capability. The two coupling methods are compared in their evaluation of flutter stability in the presence of distorted in-flows.

fluid-structure interaction↗

Principal Component Analysis of Thermographic Data

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. While a reliable technique for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from composite materials. This method has been applied for characterization of flaws.

Winfree, William P.↗

Structured Overlapping Grid Simulations of Contra-rotating Open Rotor Noise

Computational simulations using structured overlapping grids with the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are presented for predicting tonal noise generated by a contra-rotating open rotor (CROR) propulsion system. A coupled Computational Fluid Dynamics (CFD) and Computational AeroAcoustics (CAA) numerical approach is applied. Three-dimensional time-accurate hybrid Reynolds Averaged Navier-Stokes/Large Eddy Simulation (RANS/LES) CFD simulations are performed in the inertial frame, including dynamic moving grids, using a higher-order accurate finite difference discretization on structured overlapping grids. A higher-order accurate free-stream preserving metric discretization with discrete enforcement of the Geometric Conservation Law (GCL) on moving curvilinear grids is used to create an accurate, efficient, and stable numerical scheme. The aeroacoustic analysis is based on a permeable surface Ffowcs Williams-Hawkings (FW-H) approach, evaluated in the frequency domain. A time-step sensitivity study was performed using only the forward row of blades to determine an adequate time-step. The numerical approach is validated against existing wind tunnel measurements.

Grid↗

A Numerical Investigation of Parachute Deployment in Supersonic Flow

A validated computational fluid-structure interaction method applied to supersonic parachute inflation is extended to consider a unique, parallel self-contact algorithm, porosity interface conditions on the canopy, improved flow field sampling procedures for obtaining quality loading on the parachute canopy, adaptive mesh refinement, and improved treatment of thin geometries in an immersed boundary framework. These extensions are discussed in detail and demonstrated individually on test problems. Finally, the developments are brought together for demonstration on a sub-scale MSL parachute geometry.

Boustani, Jonathan↗

Estimation With Range Dependent Sensor Model

This paper focuses on the improvement of target tracking accuracy taking into account the sensor’s reading degradation as the relative range increases. The approach is based on the assumption that range measurement error depends on the actual range. Specifically, we model the measurement error as a proportional to the actual range term plus a zero-mean, Gaussian distributed, and uncorrelated process. We present two approaches to tracking a target with constant velocity model. The first approach uses Extended Kalman Filter (EKF) framework to estimate target's states and the unknown proportionality coefficient with linearization on the observation model on the predicted states at each time step. The second one uses a measurement conversion method to estimate the target's scaled by the unknown constant term states, which is shown to be unbiased. This conversion results in linear state and observation models, hence the standard Kalman filter can be applied. The actual target state is computed by application of back scaling with the estimate of unknown scale factor. We evaluate the approaches in desktop simulations.

Target tracking↗

Assessing Effects of Climate and Technology Uncertainties in Large Natural Resource Allocation Problems

The productivity of the world's natural resources is critically dependent on a variety of highly uncertain factors, which obscure individual investors and governments that seek to make long-term, sometimes irreversible, investments in their exploration and utilization. These dynamic considerations are poorly represented in disaggregated resource models, as incorporating uncertainty into large-dimensional problems presents a challenging computational task. In this paper, we apply the SCEQ algorithm (Cai and Judd, 2023) to solve a large-scale dynamic stochastic global land resource use problem with stochastic crop yields due to adverse climate impacts and limits on further technological progress. For the same model parameters and bounded shocks, the range of land conversion is considerably smaller for the dynamic stochastic model than for deterministic scenario analysis.

numerical methods↗

A Survey of Applications and Research in Integrated Design Systems Technology

The initial part of the study was begun with a combination of literature searches, World Wide Web searches, and contacts with individuals and companies who were known to members of our team to have an interest in topics that seemed to be related to our study. There is a long list of such topics, such as concurrent engineering, design for manufacture, life-cycle engineering, systems engineering, systems integration, systems design, design systems, integrated product and process approaches, enterprise integration, integrated product realization, and similar terms. These all capture, at least in part, the flavor of what we describe here as integrated design systems. An inhibiting factor in this inquiry was the absence of agreed terminology for the study of integrated design systems. It is common for the term to be applied to what are essentially augmented Computer-Aided Design (CAD) systems, which are integrated only to the extent that agreements have been reached to attach proprietary extensions to proprietary CAD programs. It is also common for some to use the term integrated design systems to mean a system that applies only, or mainly, to the design phase of a product life cycle. It is likewise common for many of the terms listed earlier to be used as synonyms for integrated design systems. We tried to avoid this ambiguity by adopting the definition of integrated design systems that is implied in the introductory notes that we provided to our contacts, cited earlier. We thus arrived at this definition: Integrated Design Systems refers to the integration of the different tools and processes that comprise the engineering, of complex systems. It takes a broad view of the engineering of systems, to include consideration of the entire product realization process and the product life cycle. An important aspect of integrated design systems is the extent to which they integrate existing, "islands of automation" into a comprehensive design and product realization environment. As the study progressed, we relied increasingly upon a networking approach to lead us to new information. The departure point for such searches often was a government-sponsored project or a company initiative. The advantage of this approach was that short conversations with knowledgeable persons would usually cut through confusion over differences of terminology, thereby somewhat reducing the search space of the study. Even so, it was not until late in our eight-month inquiry that we began to see signs of convergence of the search, in the sense that a number of the latest inquiries began to turn up references to earlier contacts. As suggested above, this convergence often occurred with respect to particular government or company projects.

Source record↗

Sequential Testing Algorithms for Multiple Fault Diagnosis

In this paper, we consider the problem of constructing optimal and near-optimal test sequencing algorithms for multiple fault diagnosis. The computational complexity of solving the optimal multiple-fault isolation problem is super-exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and AND/OR graph search, we present several test sequencing algorithms for the multiple fault isolation problem. These algorithms provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a diagnostic directed graph (digraph), instead of a diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. The algorithms developed herein have been successfully applied to several real-world systems. Computational results indicate that the size of a multiple fault strategy is strictly related to the structure of the system.

Shakeri, Mojdeh↗

Building a Transdisciplinary, Exascale-Capable Workforce for Geospace Science

Key Points: ●First-principles, self-consistent geospace modeling will require at least exascale-level computing capabilities; however, the technical skills necessary to develop such simulation codes are not taught as part of Heliophysics training/PhD programs. ●Developing exascale Heliophysics codes will require transdisciplinary collaborations between physicists, computer scientists, software engineers, data scientists, and applied mathematics. Such teams must be persistent and formed around specific skills, not specific problems. ●We must have stable, positive long-term career outcomes for Heliophysics scientific developers in order to retain knowledge of and promote future innovation in scientific algorithm development and advanced computing techniques. One such way to do this is by funding long-term scientific programming groups, akin to Heliophysics DRIVE Centers. ●We must have a balance between promoting innovation via funding short-term closed-source development and allowing the open-source community to benefit from and build on the newest scientific modeling techniques.

C Bard↗