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The design practices for the gas turbine are traced throughout history with particular emphasis on the calculational or analytical methods. Three principal components of the gas turbine engine will be considered: namely, the compressor, the combustor and the turbine.
The design practices for the gas turbine are traced throughout history with particular emphasis on the calculational or analytical methods. Three principal components of the gas turbine engine will be considered: namely, the compressor, the combustor and the turbine.
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Probabilistic Structural Analysis (PSA) is now commonly used for predicting the distribution of time/cycles to failure of turbine blades and other engine components. These distributions are typically based on fatigue/fracture and creep failure modes of these components. Additionally, reliability analysis is used for taking test data related to particular failure modes and calculating failure rate distributions of electronic and electromechanical components. How can these individual failure time distributions of structural, electronic and electromechanical component failure modes be effectively combined into a top level model for overall system evaluation of component upgrades, changes in maintenance intervals, or line replaceable unit (LRU) redesign? This paper shows an example of how various probabilistic failure predictions for turbine engine components can be evaluated and combined to show their effect on overall engine performance. A generic model of a turbofan engine was modeled using various Probabilistic Risk Assessment (PRA) tools (Quantitative Risk Assessment Software (QRAS) etc.). Hypothetical PSA results for a number of structural components along with mitigation factors that would restrict the failure mode from propagating to a Loss of Mission (LOM) failure were used in the models. The output of this program includes an overall failure distribution for LOM of the system. The rank and contribution to the overall Mission Success (MS) is also given for each failure mode and each subsystem. This application methodology demonstrates the effectiveness of PRA for assessing the performance of large turbine engines. Additionally, the effects of system changes and upgrades, the application of different maintenance intervals, inclusion of new sensor detection of faults and other upgrades were evaluated in determining overall turbine engine reliability.
The present invention blocks and/or attenuates the upstream travel of acoustic disturbances or sound waves from a flight vehicle or components of a flight vehicle traveling at subsonic speed using a local injection of a high molecular weight gas. Additional benefit may also be obtained by lowering the temperature of the gas. Preferably, the invention has a means of distributing the high molecular weight gas from the nose, wing, component, or other structure of the flight vehicle into the upstream or surrounding air flow. Two techniques for distribution are direct gas injection and sublimation of the high molecular weight solid material from the vehicle surface. The high molecular weight and low temperature of the gas significantly decreases the local speed of sound such that a localized region of supersonic flow and possibly shock waves are formed, preventing the upstream travel of sound waves from the flight vehicle.
Results are presented from the optimization process of a winged-cone configuration SSTO launch vehicle that employs a rocket-based ejector/ramjet/scramjet/rocket operational mode variable-cycle engine. The Taguchi multidisciplinary parametric-design method was used to evaluate the effects of simultaneously changing a total of eight design variables, rather than changing them one at a time as in conventional tradeoff studies. A combination of design variables was in this way identified which yields very attractive vehicle dry and gross weights.
This investigation summarizes a comparative study of two high-speed engine performance assessment techniques based on energy (available work) and thrust-potential (thrust availability). Simple flow-fields utilizing Rayleigh heat addition and one-dimensional flow with friction are used to demonstrate the fundamental inability of conventional energy techniques to predict engine component performance, aid in component design, or accurately assess flow losses. The use of the thrust-based method on these same examples demonstrates its ability to yield useful information in all these categories. Energy and thrust are related and discussed from the stand-point of their fundamental thermodynamic and fluid dynamic definitions in order to explain the differences in information obtained using the two methods. The conventional definition of energy is shown to include work which is inherently unavailable to an aerospace Brayton engine. An engine-based energy is then developed which accurately accounts for this inherently unavailable work; performance parameters based on this quantity are then shown to yield design and loss information equivalent to the thrust-based method.
The purpose of this work-in-progress is to present a semi-empirical analysis method developed to predict the buckling and crippling loads of carbon/epoxy fabric blade stiffened panels in compression. This is a hand analysis method comprised of well known, accepted techniques, logical engineering judgements, and experimental data that results in conservative solutions. In order to verify this method, a stiffened panel was fabricated and tested. Both the best and analysis results are presented.
As computing technology continues to improve, simulating unsteady aerodynamic environments on launch vehicle geometries becomes more viable. For NASA’s Space Launch System, the flowfield is characterized by large regions of unsteady turbulent wall-bounded flow. Simulating these unsteady wall-bounded environments is of interest to the SLS Aerodynamics team. Wall-modeled LES methods are currently the best approach for simulating these environments in engineering applications. Less-expensive computationally than fully-resolved methods while maintaining many of the benefits in simulating unsteady environments. Before applying these methods blindly to large geometries, best practices can first be applied and understood on smaller canonical problems.
An improved method of model-based diagnosis of a complex engineering system is embodied in an algorithm that involves considerably less computation than do prior such algorithms. This method and algorithm are based largely on developments reported in several NASA Tech Briefs articles: The Complexity of the Diagnosis Problem (NPO-30315), Vol. 26, No. 4 (April 2002), page 20; Fast Algorithms for Model-Based Diagnosis (NPO-30582), Vol. 29, No. 3 (March 2005), page 69; Two Methods of Efficient Solution of the Hitting-Set Problem (NPO-30584), Vol. 29, No. 3 (March 2005), page 73; and Efficient Model-Based Diagnosis Engine (NPO-40544), on the following page. Some background information from the cited articles is prerequisite to a meaningful summary of the innovative aspects of the present method and algorithm. In model-based diagnosis, the function of each component and the relationships among all the components of the engineering system to be diagnosed are represented as a logical system denoted the system description (SD). Hence, the expected normal behavior of the engineering system is the set of logical consequences of the SD. Faulty components lead to inconsistencies between the observed behaviors of the system and the SD. Diagnosis the task of finding faulty components is reduced to finding those components, the abnormalities of which could explain all the inconsistencies. The solution of the diagnosis problem should be a minimal diagnosis, which is a minimal set of faulty components. The calculation of a minimal diagnosis is inherently a hard problem, the solution of which requires amounts of computation time and memory that increase exponentially with the number of components of the engineering system. Among the developments to reduce the computational burden, as reported in the cited articles, is the mapping of the diagnosis problem onto the integer-programming (IP) problem. This mapping makes it possible to utilize a variety of algorithms developed previously for IP to solve the diagnosis problem. In the IP approach, the diagnosis problem can be formulated as a linear integer optimization problem, which can be solved by use of well-developed integer-programming algorithms. This concludes the background information.
As part of the NASA Aviation Safety Program, a unique model-based diagnostics method that employs neural networks and genetic algorithms for aircraft engine performance diagnostics has been developed and demonstrated at the NASA Glenn Research Center against a nonlinear gas turbine engine model. Neural networks are applied to estimate the internal health condition of the engine, and genetic algorithms are used for sensor fault detection, isolation, and quantification. This hybrid architecture combines the excellent nonlinear estimation capabilities of neural networks with the capability to rank the likelihood of various faults given a specific sensor suite signature. The method requires a significantly smaller data training set than a neural network approach alone does, and it performs the combined engine health monitoring objectives of performance diagnostics and sensor fault detection and isolation in the presence of nominal and degraded engine health conditions.
The Fan Noise Module of ANOPP is used to predict the broadband noise and pure tones for axial flow compressors or fans. The module, based on the method developed by M. F. Heidmann, uses empirical functions to predict fan noise spectra as a function of frequency and polar directivity. Previous studies have determined the need to modify the module to better correlate measurements of fan noise from engines in the 3000- to 6000-pound thrust class. Additional measurements made by AlliedSignal have confirmed the need to revise the ANOPP fan noise method for smaller engines. This report describes the revisions to the fan noise method which have been verified with measured data from three separate AlliedSignal fan engines. Comparisons of the revised prediction show a significant improvement in overall and spectral noise predictions.
Blockage predicted for all components including inducers, impellers and diffusers. Pump performance predicted by semiempirical method shows excellent agreement with test results in Space Shuttle main-engine highpressure fuel turbopump. Comparisons of pump efficiency show equally good agreement of calculated values with experimental ones. Method improves current estimation methods based solely on subjective engineering judgment.
In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.
The utilization of local resources for the construction and operation of a lunar base can significantly reduce the cost of transporting materials and supplies from Earth. The feasibility of processing lunar regolith to form construction materials and structural components is investigated. A preliminary review of potential processing methods such as sintering, hot-pressing, liquification, and cast basalt techniques, was completed. The processing method proposed is a variation on the cast basalt technique. It involves liquification of the regolith at 1200-1300 C, casting the liquid into a form, and controlled cooling. While the process temperature is higher than that for sintering or hot-pressing (1000-1100 C), this method is expected to yield a true engineering material with low variability in properties, high strength, and the potential to form large structural components. A scenario for this processing method was integrated with a design for a representative lunar base structure and potential construction techniques. The lunar shelter design is for a modular, segmented, pressurized, hemispherical dome which could serve as habitation and laboratory space. Based on this design, estimates of requirements for power, processing equipment, and construction equipment were made. This proposed combination of material processing method, structural design, and support requirements will help to establish the feasibility of lunar base construction using indigenous materials. Future work will refine the steps of the processing method. Specific areas where more information is needed are: furnace characteristics in vacuum; heat transfer during liquification; viscosity, pouring and forming behavior of molten regolith; design of high temperature forms; heat transfer during cooling; recrystallization of basalt; and refinement of estimates of elastic moduli, compressive and tensile strength, thermal expansion coefficient, thermal conductivity, and heat capacity. The preliminary design of the lunar shelter showed us that joining is a critical technology needed for building a structure from large segments. The problem of joining is important to the design of any structure that is not completely prefabricated. It is especially important when the structure is subjected to tensile loading by an internal pressure. For a lunar shelter constructed from large segments the joints between these large segments must be strong, and they must permit automated construction. With a cast basalt building material which is brittle, there is the additional problem of connecting the joint with the material and avoiding stress concentration that would cause failure. Thus, a well-defined project which we intend to pursue during this coming year is the design of joints for cast basalt structural elements.
Data obtained from an extensive investigation of the cooling characteristics of four multicylinder, liquid-cooled engines have been analyzed and a correlation of both the cylinder-head temperatures and the coolant heat rejections with the primary engine and coolant variables was obtained. The method of correlation was previously developed by the NACA from an analysis of the cooling processes involved in a liquid-cooled-engine cylinder and is based on the theory of nonboiling, forced-convection heat transfer. The data correlated included engine power outputs from 275 to 1860 brake horsepower; coolant flows from 50 to 320 gallons per minute; coolants varying in composition from 100 percent water to 97 percent ethylene glycol and 3 percent water; and ranges of engine speed, manifold pressure, carburetor-air temperature, fuel-air ratio, exhaust-gas pressure, ignition timing, and coolant temperature. The effect on engine cooling of scale formation on the coolant passages of the engine and of boiling of the coolant under various operating conditions is also discussed.
There are no author-identified significant results in this report. Review of ERTS-1 imagery indicates that it contains information of great value in coastal engineering studies. A brief introduction is given to the methods by which imagery is generated, and examples of its application to coastal engineering. Specific applications discussed include study of the movement of coastal and nearshore sediment-laden water masses and information for planning and construction in remote areas of the world.