Computer aided design and manufacturing of composite propfan blades for a cruise missile wind tunnel model

One of the propulsion concepts being investigated for future cruise missiles is advanced unducted propfans. To support the evaluation of this technology applied to the cruise missile, a joint DOD and NASA test project was conducted to design and then test the characteristics of the propfans on a 0.55-scale, cruise missile model in a NASA wind tunnel. The configuration selected for study is a counterrotating rearward swept propfan. The forward blade row, having six blades, rotates in a counterclockwise direction, and the aft blade row, having six blades, rotates in a clockwise direction, as viewed from aft of the test model. Figures show the overall cruise missile and propfan blade configurations. The objective of this test was to evaluate propfan performance and suitability as a viable propulsion option for next generation of cruise missiles. This paper details the concurrent computer aided design, engineering, and manufacturing of the carbon fiber/epoxy propfan blades as the NASA Lewis Research Center

The NASA-IGES geometry data exchange standard

Described here are the data exchange efforts and plans supported by the NASA Steering Committee for Surface Modeling and Grid Generation. Current methods for geometry data exchange between computer aided design (CAD) systems and NASA computational fluid dynamics (CFD) analysis systems are tedious and induce errors. A Geometry Data Exchange Standard is proposed, utilizing a subset of an existing national standard titled Initial Graphic Exchange Standard (IGES). Future plans for data exchange standardization include all aspects of CFD data. Software systems to utilize this NASA-IGES Geometry Data Exchange Specification are under development

Results of an Advanced Fan Stage Operating Over a Wide Range of Speed and Bypass Ratio

NASA s Fundamental Aeronautics Program is investigating turbine-based combined cycle (TBCC) propulsion systems for access to space because it provides the potential for aircraft-like, space-launch operations that may significantly reduce launch costs and improve safety. To this end, National Aeronautics and Space Administration (NASA) and General Electric (GE) teamed to design a Mach 4 variable cycle turbofan/ramjet engine for access to space. To enable the wide operating range of a Mach 4+ variable cycle turbofan ramjet required the development of a unique fan stage design capable of multi-point operation to accommodate variations in bypass ratio (10 ), fan speed (7 ), inlet mass flow (3.5 ), inlet pressure (8 ), and inlet temperature (3 ). In this paper, NASA has set out to characterize a TBCC engine fan stage aerodynamic performance and stability limits over a wide operating range including power-on and hypersonic-unique "windmill" operation. Herein, we will present the fan stage design, and the experimental test results of the fan stage operating from 15 to 100 percent corrected design speed. Whereas, in the companion paper, we will provide an assessment of NASA s APNASA code s ability to predict the fan stage performance and operability over a wide range of speed and bypass ratio

NASA geometry data exchange specification for computational fluid dynamics (NASA IGES)

This document specifies a subset of an existing product data exchange specification that is widely used in industry and government. The existing document is called the Initial Graphics Exchange Specification. This document, a subset of IGES, is intended for engineers analyzing product performance using tools such as computational fluid dynamics (CFD) software. This document specifies how to define mathematically and exchange the geometric model of an object. The geometry is represented utilizing nonuniform rational B-splines (NURBS) curves and surfaces. Only surface models are represented; no solid model representation is included. This specification does not include most of the other types of product information available in IGES (e.g., no material properties or surface finish properties) and does not provide all the specific file format details of IGES. The data exchange protocol specified in this document is fully conforming to the American National Standard (ANSI) IGES 5.2

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture

Testing and Performance Verification of a High Bypass Ratio Turbofan Rotor in an Internal Flow Component Test Facility

A 1/5 scale model rotor representative of a current technology, high bypass ratio, turbofan engine was installed and tested in the W8 single-stage, high-speed, compressor test facility at NASA Glenn Research Center (GRC). The same fan rotor was tested previously in the GRC 9x15 Low Speed Wind Tunnel as a fan module consisting of the rotor and outlet guide vanes mounted in a flight-like nacelle. The W8 test verified that the aerodynamic performance and detailed flow field of the rotor as installed in W8 were representative of the wind tunnel fan module installation. Modifications to W8 were necessary to ensure that this internal flow facility would have a flow field at the test package that is representative of flow conditions in the wind tunnel installation. Inlet flow conditioning was designed and installed in W8 to lower the fan face turbulence intensity to less than 1.0 percent in order to better match the wind tunnel operating environment. Also, inlet bleed was added to thin the casing boundary layer to be more representative of a flight nacelle boundary layer. On the 100 percent speed operating line the fan pressure rise and mass flow rate agreed with the wind tunnel data to within 1 percent. Detailed hot film surveys of the inlet flow, inlet boundary layer and fan exit flow were compared to results from the wind tunnel. The effect of inlet casing boundary layer thickness on fan performance was quantified. Challenges and lessons learned from testing this high flow, low static pressure rise fan in an internal flow facility are discussed

Neural Networks Used to Compare Designed and Measured Time-Average Patterns

Electronic time-average holograms are convenient for comparing the measured vibration modes of fan blades with those calculated by finite-element models. At the NASA Lewis Research Center, neural networks recently were trained to perform what had been a simple visual comparison of the predictions of the design models with the measurements. Finite-element models were used to train neural networks to recognize damage and strain information encoded in subtle changes in the time-average patterns of cantilevers. But the design-grade finite element models were unable to train the neural networks to detect damage in complex blade shapes. The design-model-generated patterns simply did not agree well enough with the measured patterns. Instead, hybrid-training records, with measured time-average patterns as the input and model-generated strain information as the output, were used to effect successful training

The challenge of enterprise/innovation: a case study of a modern university

In the prevailing economic and political climate for Higher Education a greater emphasis has been placed on diversifying the funding base. The present study was undertaken between 2012 and 2014 and addressed the implementation of an approach to the transformation of one academic school in a medium-sized modern university in Wales to a more engaged enterprise culture. A multimethod investigation included a bi-lingual (English and Welsh) online survey of academic staff and yielded a 71% response rate (n = 45). The findings informed a series of in-depth interviews (n = 24) with a representative sample of those involved in enterprise work (support staff, managers, senior managers), and those who were not. The results provided the platform for the ‘S4E model’ for effective engagement with enterprise: (1) Strategic significance for Enterprise, (2) Support for Enterprise, (3) Synergy for Enterprise, and (4) Success for Enterprise. The outcomes of the research and the recommendations from it have potential to inform practice in other academic schools within the university and, in a wider context, within other Schools of Education regionally, nationally and internationally. Its original empirical exploration of enterprise within education studies is a significant contribution to that body of knowledge

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts