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At least 127 records · Page 7

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NASA NTRS2001

Effect of Under-Resolved Grids on High Order Methods

There has been much discussion on verification and validation processes for establishing the credibility of CFD simulations. Since the early 1990s, many of the aeronautical and mechanical engineering related reference journals mandated that any accepted articles in numerical simulations (without known solutions to compared with) need to perform a minimum of one level of grid refinement and time step reduction. Due to the difficulty in analysis, the effect of under-resolved grids and the nonlinear behavior of available spatial discretizations, are scarcely discussed in the literature. Here, an under-resolved numerical simulation is one where the grid spacing being used is too coarse to resolve the smallest physically relevant scales of the chosen continuum governing equations that are of interest to the numerical modeler. With the advent of new developments in fourth-order or higher spatial schemes, it has become common to regard high order schemes as more accurate, reliable and require less grid points. The danger comes when one tries to perform computations with the coarsest grid possible while still hoping to maintain numerical results sufficiently accurate for complex flows, and especially, data-limited problems. On one hand, high order methods when applies to highly coupled multidimensional complex nonlinear problems might have different stability, convergence and reliability behavior than their well studied low order counterparts, especially for nonlinear schemes such as TVD, MUSCL with limiters, ENO, WENO and discrete Galerkin. On the other hand, high order methods involve more operation counts and systematic grid convergence study can be time consuming and prohibitively expansive. At the same time it is difficult to fully understand or categorize the different nonlinear behavior of finite discretizations, especially at the limits of under-resolution when different types of bifurcation phenomena might occur, depending on the combination of grid spacings, time steps, initial conditions and numerical treatments of boundary conditions.

Yee, H. C.↗

NASA NTRS2002

Dual-Mode Combustion

The Department of Mechanical and Aerospace Engineering at the University of Virginia has conducted an investigation of the mixing and combustion processes in a hydrogen fueled dual-mode scramjet combustor. The experiment essentially consisted of the "direct connect" continuous operation of a Mach 2 rectangular combustor with a single unswept ramp fuel injector. The stagnation enthalpy of the test flow simulated a flight Mach number of 5. Measurements were obtained using conventional wall instrumentation and laser based diagnostics. These diagnostics included, pressure and wall temperature measurements, Fuel Plume Imaging (FPI) and Particle Image Velocimetry (PIV). A schematic of the combustor configuration and a summary of the measurements obtained are presented. The experimental work at UVa was parallel by Computational Fluid Dynamics (CFD) work at NASA Langley. The numerical and experiment results are compared in this document.

Goyne, Christopher P.↗

NASA NTRS2003

Finite Volume Methods: Foundation and Analysis

Finite volume methods are a class of discretization schemes that have proven highly successful in approximating the solution of a wide variety of conservation law systems. They are extensively used in fluid mechanics, porous media flow, meteorology, electromagnetics, models of biological processes, semi-conductor device simulation and many other engineering areas governed by conservative systems that can be written in integral control volume form. This article reviews elements of the foundation and analysis of modern finite volume methods. The primary advantages of these methods are numerical robustness through the obtention of discrete maximum (minimum) principles, applicability on very general unstructured meshes, and the intrinsic local conservation properties of the resulting schemes. Throughout this article, specific attention is given to scalar nonlinear hyperbolic conservation laws and the development of high order accurate schemes for discretizing them. A key tool in the design and analysis of finite volume schemes suitable for non-oscillatory discontinuity capturing is discrete maximum principle analysis. A number of building blocks used in the development of numerical schemes possessing local discrete maximum principles are reviewed in one and several space dimensions, e.g. monotone fluxes, E-fluxes, TVD discretization, non-oscillatory reconstruction, slope limiters, positive coefficient schemes, etc. When available, theoretical results concerning a priori and a posteriori error estimates are given. Further advanced topics are then considered such as high order time integration, discretization of diffusion terms and the extension to systems of nonlinear conservation laws.

Barth, Timothy↗

NASA NTRS2011

Qualification of Electrical Ground Support Equipment for New Space Programs

With the Space Shuttle program coming to an end, the National Aeronautics and Space Administration (NASA) is moving to a new space flight program that will allow expeditions beyond low earth orbit. The space vehicles required to comply with these missions will be carrying heavy payloads. This implies that the Earth departure stage capabilities must be of higher magnitudes, given the current propulsion technology. The engineering design of the new flight hardware comes with some structural, thermal, propulsion and other subsystems' challenges. Meanwhile, the necessary ground support equipment (GSE) used to test, validate, verify and process the flight hardware must withstand the new program specifications. This paper intends to provide the qualification considerations during implementation of new electrical GSE for space programs. A team of engineers was formed to embark on this task, and facilitate the logistics process and ensure that the electrical, mechanical and fluids subsystems conduct the proper level of testing. Ultimately, each subsystem must certify that each piece of ground support equipment used in the field is capable of withstanding the strenuous vibration, acoustics, environmental, thermal and Electromagnetic Interference (EMf) levels experienced during pre-launch, launch and post-launch activities. The benefits of capturing and sharing these findings will provide technical, cost savings and schedule impacts infon11ation to both the technical and management community. Keywords: Qualification; Testing; Ground Support Equipment; Electromagnetic Interference Testing; Vibration Testing; Acoustic Testing; Power Spectral Density.

SotoToro, Felix A.↗

NASA NTRS2015

Reliability and Probabilistic Risk Assessment - How They Play Together

Since the Space Shuttle Challenger accident in 1986, NASA has extensively used probabilistic analysis methods to assess, understand, and communicate the risk of space launch vehicles. Probabilistic Risk Assessment (PRA), used in the nuclear industry, is one of the probabilistic analysis methods NASA utilizes to assess Loss of Mission (LOM) and Loss of Crew (LOC) risk for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability distributions to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: 1) what can go wrong that would lead to loss or degraded performance (i.e., scenarios involving undesired consequences of interest), 2) how likely is it (probabilities), and 3) what is the severity of the degradation (consequences). Since the Challenger accident, PRA has been used in supporting decisions regarding safety upgrades for launch vehicles. Another area that was given a lot of emphasis at NASA after the Challenger accident is reliability engineering. Reliability engineering has been a critical design function at NASA since the early Apollo days. However, after the Challenger accident, quantitative reliability analysis and reliability predictions were given more scrutiny because of their importance in understanding failure mechanism and quantifying the probability of failure, which are key elements in resolving technical issues, performing design trades, and implementing design improvements. Although PRA and reliability are both probabilistic in nature and, in some cases, use the same tools, they are two different activities. Specifically, reliability engineering is a broad design discipline that deals with loss of function and helps understand failure mechanism and improve component and system design. PRA is a system scenario based risk assessment process intended to assess the risk scenarios that could lead to a major/top undesirable system event, and to identify those scenarios that are high-risk drivers. PRA output is critical to support risk informed decisions concerning system design. This paper describes the PRA process and the reliability engineering discipline in detail. It discusses their differences and similarities and how they work together as complementary analyses to support the design and risk assessment processes. Lessons learned, applications, and case studies in both areas are also discussed in the paper to demonstrate and explain these differences and similarities.

Safie, Fayssal↗

NASA NTRS2011

SSC Engineering Analysis

A package for the automation of the Engineering Analysis (EA) process at the Stennis Space Center has been customized. It provides the ability to assign and track analysis tasks electronically, and electronically route a task for approval. It now provides a mechanism to keep these analyses under configuration management. It also allows the analysis to be stored and linked to the engineering data that is needed to perform the analysis (drawings, etc.). PTC s (Parametric Technology Corp o ration) Windchill product was customized to allow the EA to be created, routed, and maintained under configuration management. Using Infoengine Tasks, JSP (JavaServer Pages), Javascript, a user interface was created within the Windchill product that allows users to create EAs. Not only does this interface allow users to create and track EAs, but it plugs directly into the out-ofthe- box ability to associate these analyses with other relevant engineering data such as drawings. Also, using the Windchill workflow tool, the Design and Data Management System (DDMS) team created an electronic routing process based on the manual/informal approval process. The team also added the ability for users to notify and track notifications to individuals about the EA. Prior to the Engineering Analysis creation, there was no electronic way of creating and tracking these analyses. There was also a feature that was added that would allow users to track/log e-mail notifications of the EA.

Ryan, Harry↗

NASA NTRSDate not supplied

CMC Research at NASA Glenn in 2021: Recent Progress and Plans

As part of NASA’s Aeronautics research, Glenn Research Center has developed SiC/SiC Ceramic Matrix Composites for 2700°F turbine engine applications in the next generation of ultra-efficient aircraft. In this presentation, the development and characterization of constituents and fabrication processes that enabled this advancement will be reviewed, and the resulting improvements in CMC mechanical properties and durability will be summarized. Progress toward the development and experimental validation of analytical models predicting the effects of engine operating conditions on the durability of Ceramic Matrix Composites with Environmental Barrier Coatings will be summarized. Results from current collaborative research with industry, universities and other government agencies will be reviewed. Research plans for 2021 and opportunities for future collaborations with NASA will also be summarized.

Ceramic Matrix Composites↗

NASA NTRS2011

Lunar Wormbot: Design and Development of a Ground Base Robotic Tunneling Worm for Operation in Harsh Environments

From 1969 to 1972, the National Aeronautics and Space Administration (NASA) sent Apollo missions to the moon to conduct various exploration experiment. A few of the missions were directed to the study and sampling of moon soil, otherwise known as lunar regolith. The extent of the sample acquisition was limited due to the astronauts' limited ability to penetrate the moon's surface to a depth greater than three meters. However. the samples obtained were sufficient enough to provide key information pertaining to lunar regolith material properties that would further assist in future exploration endeavors. Analysis of the collected samples showed that the properties of lunar regolith may lead to knowledge of processed materials that will be beneficial for future human exploration or colonization. However, almost 40 years after the last Apollo mission, limited infonnation is known about regions underneath the moon's surface. Future lunar missions will require hardware that possesses the ability to burrow to greater depths in order to collect samples for subsequent analysis. During the summer of 2010, a team (Dr. Jessica Gaskin, Michael Kuhlman. Blaze Sanders, and Lafe Zabowski) from the NASA Robotics Academy at Marshall Space Flight Center (MSFC) was given the task of designing a robot to function as a soil collection and analysis device. Working with the National Space Science and Technology Center (NSSTC), the team was able to propose an initial design, build a prototype, and test the various subsystems of the prototype to be known as the "Lunar Wormbot" (LW). The NASA/NSSTC team then transferred the project to a University of Alabama in Huntsville (UAH) Mechanical and Aerospace Engineering (MAE) senior design class for further development. The UAH team was to utilize the NASA Systems Engineering Engine Design Process in the continuance of the Lunar Wormbot project. This process was implemented in order to coordinate the efforts of the team and guide the design of the project to ensure a high quality product that met requirements within the academic year timeframe. When the transition from the NASA NSSTC team to the UAH team occurred in August 2010, the scope and requirements were provided to the UAH team. The main objective for the UAH team was to design and fabricate a robotic burrowing prototype using peristaltic or earthworm-like motion with the purpose of collecting soil samples. The team was tasked with the design of a sub-system of the LW called the locomotive, or active, segment. Through the design process, the team extensively reviewed the requirements and functions to be performed of the LW, which led to the proposal of a final design. The present paper provides the details of the development of the design up to and including the Critical Design Review (CDR) of the Lunar Wormbot. This document briefly describes thc overall system and its function but primarily focuses on the design and implementation of the locomotive segment. Content presented includes: general design and system functionality, technical drawings, system analysis, manufacturing methods, and general project costs.

Boyles, Charles↗

NASA NTRS1972

Cost reduction by integration of the assurance technologies.

It is shown how the cost of applying assurance disciplines to the development of complex systems can be reduced by integrating the mechanics of system engineering and system management into a 'Development Risk Control System'. The essential features of the integration process are examined. A 'Development Risk Management Model' is described, and the use of the model to integrate and thereby reduce the cost of other assurance disciplines is discussed and illustrated.

Ball, L. W.↗

NASA NTRS1989

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

Gupta, U. K.↗

NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗

NASA NTRS2014

NASA Engineering and Safety Center Technical Bulletin No. 14-03: COPV Mechanical Model Validation

Global and local deformation measurements should be incorporated into the composite overwrapped pressure vessel (COPV) design and analysis process to allow correlation of these measurements with finite element analysis (FEA) models. This correlation improves understanding of liner, liner/overwrap interface, and composite deformation response in COPVs. The improved accuracy reduces error in subsequent analyses, such as fracture, fatigue, and stress rupture that are critical for COPV qualification.

Composite Overwrap Pressure Vehicle↗

NASA NTRS1992

Influence of engineered interfaces on residual stresses and mechanical response in metal matrix composites

Because of the inherent coefficient of thermal expansion (CTE) mismatch between fiber and matrix within metal and intermetallic matrix composite systems, high residual stresses can develop under various thermal loading conditions. These conditions include cooling from processing temperature to room temperature as well as subsequent thermal cycling. As a result of these stresses, within certain composite systems, radial, circumferential, and/or longitudinal cracks have been observed to form at the fiber matrix interface region. A number of potential solutions for reducing this thermally induced residual stress field have been proposed recently. Examples of some potential solutions are high CTE fibers, fiber preheating, thermal anneal treatments, and an engineered interface. Here the focus is on designing an interface (by using a compensating/compliant layer concept) to reduce or eliminate the thermal residual stress field and, therefore, the initiation and propagation of cracks developed during thermal loading. Furthermore, the impact of the engineered interface on the composite's mechanical response when subjected to isothermal mechanical load histories is examined.

Arnold, Steven M.↗

NASA NTRS2001

Challenges Facing Design and Analysis Tools

The design and analysis of future aerospace systems will strongly rely on advanced engineering analysis tools used in combination with risk mitigation procedures. The implications of such a trend place increased demands on these tools to assess off-nominal conditions, residual strength, damage propagation, and extreme loading conditions in order to understand and quantify these effects as they affect mission success. Advances in computer hardware such as CPU processing speed, memory, secondary storage, and visualization provide significant resources for the engineer to exploit in engineering design. The challenges facing design and analysis tools fall into three primary areas. The first area involves mechanics needs such as constitutive modeling, contact and penetration simulation, crack growth prediction, damage initiation and progression prediction, transient dynamics and deployment simulations, and solution algorithms. The second area involves computational needs such as fast, robust solvers, adaptivity for model and solution strategies, control processes for concurrent, distributed computing for uncertainty assessments, and immersive technology. Traditional finite element codes still require fast direct solvers which when coupled to current CPU power enables new insight as a result of high-fidelity modeling. The third area involves decision making by the analyst. This area involves the integration and interrogation of vast amounts of information - some global in character while local details are critical and often drive the design. The proposed presentation will describe and illustrate these areas using composite structures, energy-absorbing structures, and inflatable space structures. While certain engineering approximations within the finite element model may be adequate for global response prediction, they generally are inadequate in a design setting or when local response prediction is critical. Pitfalls to be avoided and trends for emerging analysis tools will be described.

Knight, Norman F., Jr.↗

NASA NTRS2018

CMC Research at NASA Glenn in 2018: Recent Progress and Plans

As part of NASA's Aeronautics research, Glenn Research Center has developed SiC/SiC Ceramic Matrix Composites for 2700 °F turbine engine applications in the next generation of ultra-efficient aircraft. In this presentation, the development of fiber and matrix constituents and fabrication processes that enabled this advancement will be reviewed, and characterization of the resulting improvements in CMC mechanical properties and durability will be summarized. Progress toward the development and validation of models predicting the effects of the engine environment on durability of Ceramic Matrix Composites and Environmental Barrier Coatings will be summarized. Results from current collaborative research with industry and other government agencies will be reviewed. Research plans for 2018 and opportunities for future collaborations with NASA will also be summarized.

Ceramic Matrix Composites↗

NASA NTRS2018

CMC Research at NASA Glenn in 2018: Recent Progress and Plans

Ceramic Matrix Composites↗

NASA NTRS2018

CMC Research at NASA Glenn in 2018: Recent Progress and Plans

As part of NASA's Aeronautics research, Glenn Research Center has developed SiC/SiC Ceramic Matrix Composites for 2700Â°F turbine engine applications in the next generation of ultra-efficient aircraft. In this presentation, the development of fiber and matrix constituents and fabrication processes that enabled this advancement will be reviewed, and characterization of the resulting improvements in CMC mechanical properties and durability will be summarized. Progress toward the development and validation of models predicting the effects of the engine environment on durability of Ceramic Matrix Composites and Environmental Barrier Coatings will be summarized. Results from current collaborative research with industry and other government agencies will be reviewed. Research plans for 2018 and opportunities for future collaborations with NASA will also be summarized.

composites↗

NASA NTRS2019

CMC Research at NASA Glenn in 2019: Recent Progress and Plans

As part of NASA's Aeronautics research, Glenn Research Center has developed SiC/SiC Ceramic Matrix Composites (CMC) for 2700 degrees Fahrenheit turbine engine applications in the next generation of ultra-efficient aircraft. In this presentation, the development of fiber and matrix constituents and fabrication processes that enabled this advancement will be reviewed, and characterization of the resulting improvements in CMC mechanical properties and durability will be summarized. Progress toward the development and validation of models predicting the effects of the engine environment on durability of Ceramic Matrix Composites and Environmental Barrier Coatings will be summarized. Results from current collaborative research with industry and other government agencies will be reviewed. Research plans for 2019 and opportunities for future collaborations with NASA will also be summarized.

Composites↗