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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Optimization of engines for a commercial Mach 0.98 transport using advanced turbine cooling methods

A study was made of an advanced technology airplane using supercritical aerodynamics. Cruise Mach number was 0.98 at 40,000 feet altitude with a payload of 60,000 pounds and a range of 3000 nautical miles. Separate-flow turbofans were examined parametrically to determine the effect of sea-level-static design turbine-inlet-temperature and noise on takeoff gross weight (TOGW) assuming full-film turbine cooling. The optimum turbine inlet temperature was 2650 F. Two-stage-fan engines, with cruise fan pressure ratio of 2.25, achieved a noise goal of 103.5 EPNdB with todays noise technology while one-stage-fan engines, achieved a noise goal of 98 EPNdB. The take-off gross weight penalty to use the one-stage fan was 6.2 percent.

Kraft, G. A.↗
NASA NTRS1972

Optimization of engines for a commercial Mach 0.85 transport using advanced turbine cooling methods

A parametric study was made of a group of separate-flow-turbofan engines for use in advanced technology airplanes designed for a cruise Mach number of 0.85 at 40,000 feet. The three-engined airplanes were sized to carry 200 passengers 3000 nautical miles. Supercritical aerodynamics were assumed. Film-cooled turbines were used and sea-level-static turbine-rotor-inlet temperature was always 2600 F. The optimum cycle depends on the noise goal assumed. Without a noise goal the best fan pressure ratio (FPR) is about 1.90. At noise goals of FAR 36, -10 EPNdb, and -20 EPNdb, the best FPR's are 1.85, 1.76, and 1.70, respectively, at cruise. The take-off FPR's are progressively less than the cruise value as the noise goal approaches -20 EPNdb. The penalties in take-off gross weight incurred were 8.5, 19, and 64 percent at goals of FAR 36, -10 EPNdb, and -20 EPNdb, respectively.

Kraft, G. A.↗
NASA NTRS1989

Approximate simulation model for analysis and optimization in engineering system design

Computational support of the engineering design process routinely requires mathematical models of behavior to inform designers of the system response to external stimuli. However, designers also need to know the effect of the changes in design variable values on the system behavior. For large engineering systems, the conventional way of evaluating these effects by repetitive simulation of behavior for perturbed variables is impractical because of excessive cost and inadequate accuracy. An alternative is described based on recently developed system sensitivity analysis that is combined with extrapolation to form a model of design. This design model is complementary to the model of behavior and capable of direct simulation of the effects of design variable changes.

Sobieszczanski-Sobieski, Jaroslaw↗
NASA NTRS2000

Cascade Optimization for Aircraft Engines With Regression and Neural Network Analysis - Approximators

The NASA Engine Performance Program (NEPP) can configure and analyze almost any type of gas turbine engine that can be generated through the interconnection of a set of standard physical components. In addition, the code can optimize engine performance by changing adjustable variables under a set of constraints. However, for engine cycle problems at certain operating points, the NEPP code can encounter difficulties: nonconvergence in the currently implemented Powell's optimization algorithm and deficiencies in the Newton-Raphson solver during engine balancing. A project was undertaken to correct these deficiencies. Nonconvergence was avoided through a cascade optimization strategy, and deficiencies associated with engine balancing were eliminated through neural network and linear regression methods. An approximation-interspersed cascade strategy was used to optimize the engine's operation over its flight envelope. Replacement of Powell's algorithm by the cascade strategy improved the optimization segment of the NEPP code. The performance of the linear regression and neural network methods as alternative engine analyzers was found to be satisfactory. This report considers two examples-a supersonic mixed-flow turbofan engine and a subsonic waverotor-topped engine-to illustrate the results, and it discusses insights gained from the improved version of the NEPP code.

Patnaik, Surya N.↗
NASA NTRS1992

Mathematical Model For Engineering Analysis And Optimization

Computational support for engineering design process reveals behavior of designed system in response to external stimuli; and finds out how behavior modified by changing physical attributes of system. System-sensitivity analysis combined with extrapolation forms model of design complementary to model of behavior, capable of direct simulation of effects of changes in design variables. Algorithms developed for this method applicable to design of large engineering systems, especially those consisting of several subsystems involving many disciplines.

Sobieski, Jaroslaw↗
NASA NTRS1985

Finite element engine blade structural optimization

The Structural Tailoring of Engine Blades (STAEBL) computer program was developed to perform engine fan blade numerical optimizations. These blade optimizations seek a minimum weight or cost design that satisfies realistic blade design constraints, by tuning one to twenty design variables. The STAEBL system has been generalized to include both fan and compressor blade numerical optimizations. The system analyses have been significantly improved through the inclusion of an efficient plate finite element analysis for blade stress and frequency determinations. Additionally, a finite element based approximate severe foreign object damage (FOD) analysis has been included. The new FOD analysis gives very accurate estimates of the full nonlinear bird ingestion solution. Optimizations of fan and compressor blades have been performed using the system, showing significant cost and weight reductions, while comparing very favorably with refined design validation procedures.

Brown, K. W.↗
NASA NTRS2006

A COTS-Based Attitude Dependent Contact Scheduling System

The mission architecture of the Gamma-ray Large Area Space Telescope (GLAST) requires a sophisticated ground system component for scheduling the downlink of science data. Contacts between the ````````````````` satellite and the Tracking and Data Relay Satellite System (TDRSS) are restricted by the limited field-of-view of the science data downlink antenna. In addition, contacts must be scheduled when permitted by the satellite s complex and non-repeating attitude profile. Complicating the matter further, the long lead-time required to schedule TDRSS services, combined with the short duration of the downlink contact opportunities, mandates accurate GLAST orbit and attitude modeling. These circumstances require the development of a scheduling system that is capable of predictively and accurately modeling not only the orbital position of GLAST but also its attitude. This paper details the methods used in the design of a Commercial Off The Shelf (COTS)-based attitude-dependent. TDRSS contact Scheduling system that meets the unique scheduling requirements of the GLAST mission, and it suggests a COTS-based scheduling approach to support future missions. The scheduling system applies filtering and smoothing algorithms to telemetered GPS data to produce high-accuracy predictive GLAST orbit ephemerides. Next, bus pointing commands from the GLAST Science Support Center are used to model the complexities of the two dynamic science gathering attitude modes. Attitude-dependent view periods are then generated between GLAST and each of the supporting TDRSs. Numerous scheduling constraints are then applied to account for various mission specific resource limitations. Next, an optimization engine is used to produce an optimized TDRSS contact schedule request which is sent to TDRSS scheduling for confirmation. Lastly, the confirmed TDRSS contact schedule is rectified with an updated ephemeris and adjusted bus pointing commands to produce a final science downlink contact schedule.

DeGumbia, Jonathan D.↗
NASA NTRS1977

Optimal controls for an advanced turbofan engine

Linear optimal control theory is applied to the control synthesis of a high bypass ratio, variable pitch, turbofan engine. The basic control philosophy is to use only a low order dynamic model of the plant coupled with the concept of integral-output states so as to maintain control simplicity yet guarantee integral control of thrust, turbine temperature and other important engine outputs. Linear simulation results indicate that the control system developed provides rapid control of small thrust perturbations and quickly eliminates the effect of unmodelled thrust and temperature disturbances. Large thrust accelerations are obtained in about one half second while the control maintains negligible overshoot in temperature and stall margins.

Slater, G. L.↗
NASA NTRS1986

Configuration evaluation and criteria plan. Volume 1: System trades study and design methodology plan (preliminary). Space Transportation Main Engine (STME) configuration study

The System Trades Study and Design Methodology Plan is used to conduct trade studies to define the combination of Space Shuttle Main Engine features that will optimize candidate engine configurations. This is accomplished by using vehicle sensitivities and engine parametric data to establish engine chamber pressure and area ratio design points for candidate engine configurations. Engineering analyses are to be conducted to refine and optimize the candidate configurations at their design points. The optimized engine data and characteristics are then evaluated and compared against other candidates being considered. The Evaluation Criteria Plan is then used to compare and rank the optimized engine configurations on the basis of cost.

Bair, E. K.↗
NASA NTRS1980

Orbit transfer vehicle advanced expander cycle engine point design study. Volume 2: Study results

The design characteristics of the baseline engine configuration of the advanced expander cycle engine are described. Several aspects of engine optimization are considered which directly impact the design of the baseline thrust chamber. Four major areas of the power cycle optimization are emphasized: main turbine arrangement; cycle engine source; high pressure pump design; and boost pump drive.

Diem, H. G.↗
NASA NTRS1992

System controls challenges of hypersonic combined-cycle engine powered vehicles

Hypersonic aircraft with air-breathing engines have been described as the most complex and challenging air/space vehicle designs ever attempted. This is particularly true for aircraft designed to accelerate to orbital velocities. The propulsion system for the National Aerospace Plane will be an active factor in maintaining the aircraft on course. Typically addressed are the difficulties with the aerodynamic vehicle design and development, materials limitations and propulsion performance. The propulsion control system requires equal materials limitations and propulsion performance. The propulsion control system requires equal concern. Far more important than merely a subset of propulsion performance, the propulsion control system resides at the crossroads of trajectory optimization, engine static performance, and vehicle-engine configuration optimization. To date, solutions at these crossroads are multidisciplinary and generally lag behind the broader performance issues. Just how daunting these demands will be is suggested. A somewhat simplified treatment of the behavioral characteristics of hypersonic aircraft and the issues associated with their air-breathing propulsion control system design are presented.

Morrison, Russell H.↗
NASA NTRS1986

A general-purpose optimization program for engineering design

A new general-purpose optimization program for engineering design is described. ADS (Automated Design Synthesis) is a FORTRAN program for nonlinear constrained (or unconstrained) function minimization. The optimization process is segmented into three levels: Strategy, Optimizer, and One-dimensional search. At each level, several options are available so that a total of nearly 100 possible combinations can be created. An example of available combinations is the Augmented Lagrange Multiplier method, using the BFGS variable metric unconstrained minimization together with polynomial interpolation for the one-dimensional search.

Vanderplaats, G. N.↗