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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 397 records · Page 22

Orbital Transfer Vehicle (OTV) engine study. Phase A: Extension

An orbital transfer vehicle OTV engine study program was undertaken to provide additional expander and staged combustion cycle data in the design definition of the OTV engine. The proposed program effort optimizes the expander cycle engine concept (consistent with identified OTV engine requirements), investigates the feasibility of kitting the staged combustion cycle engine to provide extended low thrust operation, and conducts in-depth analysis of development risk, crew safety, and reliability for both cycles. Additional tasks to establish the cost of a 10K thrust expander cycle engine and to render support of OTV systems study contractors are reported.

Sobin, A. J.↗

Theoretical performance of a vortex generator type of cloud droplet sampler

One of the goals of the NASA global tropospheric research program is understanding the chemical processes which influence the chemistry of the natural troposphere. An important element of this program is the study of the role of heterogenous chemistry in global tropospheric chemical cycles. Any study of the part which clouds play in the chemistry of tropospheric trace constituents requires a determination of cloud water chemical composition. There exists, therefore, a need for highly efficient collector devices which can obtain unbiased samples of cloud water in sufficient quantities aboard an aircraft platform. A promising concept which could meet the dual requirements of accurate sampling and efficient collection of cloud water droplets in the vortex generator. This concept involves an inertial separator which uses the centrifugal force of a rotating airstream. The separator is built into a commercial device which has been used for many years as a dust separator for air breathing engines. Attention is given to the optimization of the sampler design.

Miller, I. M.↗

Expert System for Automated Design Synthesis

Expert-system computer program EXADS developed to aid users of Automated Design Synthesis (ADS) general-purpose optimization program. EXADS aids engineer in determining best combination based on knowledge of specific problem and expert knowledge stored in knowledge base. Available in two interactive machine versions. IBM PC version (LAR-13687) written in IQ-LISP. DEC VAX version (LAR-13688) written in Franz-LISP.

Rogers, James L., Jr.↗

Shape optimization of tibial prosthesis components

NASA technology and optimal design methodologies originally developed for the optimization of composite structures (engine blades) are adapted and applied to the optimization of orthopaedic knee implants. A method is developed enabling the shape tailoring of the tibial components of a total knee replacement implant for optimal interaction within the environment of the tibia. The shape of the implant components are optimized such that the stresses in the bone are favorably controlled to minimize bone degradation, to improve the mechanical integrity of the implant/interface/bone system, and to prevent failures of the implant components. A pilot tailoring system is developed and the feasibility of the concept is demonstrated and evaluated. The methodology and evolution of the existing aerospace technology from which this pilot optimization code was developed is also presented and discussed. Both symmetric and unsymmetric in-plane loading conditions are investigated. The results of the optimization process indicate a trend toward wider and tapered posts as well as thicker backing trays. Unique component geometries were obtained for the different load cases.

Saravanos, D. A.↗

Thermal/Structural Tailoring of Engine Blades (T/STAEBL) User's manual

The Thermal/Structural Tailoring of Engine Blades (T/STAEBL) system is a computer code that is able to perform numerical optimizations of cooled jet engine turbine blades and vanes. These optimizations seek an airfoil design of minimum operating cost that satisfies realistic design constraints. This report documents the organization of the T/STAEBL computer program, its design and analysis procedure, its optimization procedure, and provides an overview of the input required to run the program, as well as the computer resources required for its effective use. Additionally, usage of the program is demonstrated through a validation test case.

Brown, K. W.↗

ACSYNT inner loop flight control design study

The NASA Ames Research Center developed the Aircraft Synthesis (ACSYNT) computer program to synthesize conceptual future aircraft designs and to evaluate critical performance metrics early in the design process before significant resources are committed and cost decisions made. ACSYNT uses steady-state performance metrics, such as aircraft range, payload, and fuel consumption, and static performance metrics, such as the control authority required for the takeoff rotation and for landing with an engine out, to evaluate conceptual aircraft designs. It can also optimize designs with respect to selected criteria and constraints. Many modern aircraft have stability provided by the flight control system rather than by the airframe. This may allow the aircraft designer to increase combat agility, or decrease trim drag, for increased range and payload. This strategy requires concurrent design of the airframe and the flight control system, making trade-offs of performance and dynamics during the earliest stages of design. ACSYNT presently lacks means to implement flight control system designs but research is being done to add methods for predicting rotational degrees of freedom and control effector performance. A software module to compute and analyze the dynamics of the aircraft and to compute feedback gains and analyze closed loop dynamics is required. The data gained from these analyses can then be fed back to the aircraft design process so that the effects of the flight control system and the airframe on aircraft performance can be included as design metrics. This report presents results of a feasibility study and the initial design work to add an inner loop flight control system (ILFCS) design capability to the stability and control module in ACSYNT. The overall objective is to provide a capability for concurrent design of the aircraft and its flight control system, and enable concept designers to improve performance by exploiting the interrelationships between aircraft and flight control system design parameters.

Bortins, Richard↗

Design Sensitivity for a Subsonic Aircraft Predicted by Neural Network and Regression Models

A preliminary methodology was obtained for the design optimization of a subsonic aircraft by coupling NASA Langley Research Center s Flight Optimization System (FLOPS) with NASA Glenn Research Center s design optimization testbed (COMETBOARDS with regression and neural network analysis approximators). The aircraft modeled can carry 200 passengers at a cruise speed of Mach 0.85 over a range of 2500 n mi and can operate on standard 6000-ft takeoff and landing runways. The design simulation was extended to evaluate the optimal airframe and engine parameters for the subsonic aircraft to operate on nonstandard runways. Regression and neural network approximators were used to examine aircraft operation on runways ranging in length from 4500 to 7500 ft.

Hopkins, Dale A.↗

Communication Needs Assessment for Distributed Turbine Engine Control

Control system architecture is a major contributor to future propulsion engine performance enhancement and life cycle cost reduction. The control system architecture can be a means to effect net weight reduction in future engine systems, provide a streamlined approach to system design and implementation, and enable new opportunities for performance optimization and increased awareness about system health. The transition from a centralized, point-to-point analog control topology to a modular, networked, distributed system is paramount to extracting these system improvements. However, distributed engine control systems are only possible through the successful design and implementation of a suitable communication system. In a networked system, understanding the data flow between control elements is a fundamental requirement for specifying the communication architecture which, itself, is dependent on the functional capability of electronics in the engine environment. This paper presents an assessment of the communication needs for distributed control using strawman designs and relates how system design decisions relate to overall goals as we progress from the baseline centralized architecture, through partially distributed and fully distributed control systems.

Culley, Dennis E.↗

Computerized optimal control system design for reusable and expendable boost vehicles.

An optimization technique has been developed which combines the practical features of hybrid simulation of the dynamic system under study with the systematic approach of modern control theory where a mathematically formulated design criterion is optimized by functional minimization. Standard hybrid computer optimization methods using high-speed repetitive simulations and gradient minimization schemes have been extended to obtain time-varying optimal gain schedules and reduce the sensitivity of the optimized system to parameter and disturbance uncertainties. In this approach the performance index is expressed in meaningful engineering terms that reflect the interactions among all major disciplines, structures, control/actuation system design, aerodynamics and performance. The basic optimization technique is developed and its application to current aerospace control problems including the space shuttle is presented in detail. In the discussion of the application, the controllers resulting from the technique are compared with controllers developed by conventional methods. The paper concludes with a review of the advantages and disadvantages of the technique and plans for future applications.

Connor, C. L.↗

High Pressure Transcritical Combustion (HPTC Combustion)

Combustion is the predominant source of the energy in the US and worldwide, and an overwhelming majority in the transportation sector, particularly liquid hydrocarbons (i.e., gasoline, diesel and jet fuel). Engine manufacturers move to higher operating pressures, above and beyond the critical pressures of the fuel, in order to optimize performance, maximize efficiency and reduce pollutant formation. The design of the next generation of engines, however, are limited by a lack of fundamental understanding of the thermo-physical properties, fluid behavior and chemical kinetics at these high pressures. Terrestrial laboratory studies are hampered by the ubiquitous buoyant flow that renders fundamental experiments difficult and/or impossible to interpret. Studying high pressure transcritical phenomena in microgravity allows researchers to investigate the fundamental aspects of phase change, chemical kinetics and property evaluation in a simplified geometry without the complicating influence of a buoyancy-induced flow.

Combustion↗

Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft

The neural network and regression methods of NASA Glenn Research Center s COMETBOARDS design optimization testbed were used to generate approximate analysis and design models for a subsonic aircraft operating at Mach 0.85 cruise speed. The analytical model is defined by nine design variables: wing aspect ratio, engine thrust, wing area, sweep angle, chord-thickness ratio, turbine temperature, pressure ratio, bypass ratio, fan pressure; and eight response parameters: weight, landing velocity, takeoff and landing field lengths, approach thrust, overall efficiency, and compressor pressure and temperature. The variables were adjusted to optimally balance the engines to the airframe. The solution strategy included a sensitivity model and the soft analysis model. Researchers generated the sensitivity model by training the approximators to predict an optimum design. The trained neural network predicted all response variables, within 5-percent error. This was reduced to 1 percent by the regression method. The soft analysis model was developed to replace aircraft analysis as the reanalyzer in design optimization. Soft models have been generated for a neural network method, a regression method, and a hybrid method obtained by combining the approximators. The performance of the models is graphed for aircraft weight versus thrust as well as for wing area and turbine temperature. The regression method followed the analytical solution with little error. The neural network exhibited 5-percent maximum error over all parameters. Performance of the hybrid method was intermediate in comparison to the individual approximators. Error in the response variable is smaller than that shown in the figure because of a distortion scale factor. The overall performance of the approximators was considered to be satisfactory because aircraft analysis with NASA Langley Research Center s FLOPS (Flight Optimization System) code is a synthesis of diverse disciplines: weight estimation, aerodynamic analysis, engine cycle analysis, propulsion data interpolation, mission performance, airfield length for landing and takeoff, noise footprint, and others.

Hopkins, Dale A.↗

Uncovering Hazards Using a Multi-Objective Optimization to Explore the Faulty State-Space

Considering resilience when designing complex engineered systems is crucial to ensure the system is safe under unexpected hazardous scenarios. Traditional risk-based approaches, such as Failure Modes and Effects Analysis (FMEA) are useful for designing the system to mitigate hazardous scenarios that can be identified by the designer, but often require experience or prior knowledge of system failures to generate. More recently, researchers have developed simulation tools that enable the designer to model large sets of hazardous scenarios (driven by both internal faults and external factors) through simulation. While these tools enable a wider scope of fault modes to be evaluated (e.g., by injecting combined set of fault modes or injecting modes at different times), the resulting assessments (like FMEA) still require knowledge of the specific modes to be evaluated. However, failure to analyze a wide variety of fault scenarios can lead to an incomplete picture of the system resilience, especially to "surprise events'' which may be difficult for the designer to identify and predict beforehand. To overcome this challenge, previous work developed a fault sampling approach for resilience simulations which would procedurally-generate a wide variety of potential faults by systematically perturbing the health states of the system. While the resulting fault modes generated covered a much larger space hazards than would be otherwise considered (and identified many unique failure trajectories which would not have otherwise been identified), it also significantly increased the computational cost of the analysis and resulted in the simulation and analysis of a large set of essentially duplicate scenarios. Additionally, as the number of dimensions in the faulty state-space increases, the full elaboration of possible modes becomes computationally infeasible, justifying the use of a more targeted search. To resolve this limitation, this work proposes the use of a multiobjective optimization algorithm to search the health state space for potential fault modes that are both (1) hazardous and (2) unique. To solve this type of problem, this work proposes the use of a cooperative co-evolutionary algorithm. To demonstrate this approach, it will be applied to a model of an autonomous rover which uses line markings to navigate, focusing on potential hazards in the drive system which could cause the rover to crash. To determine the merit of the approach, it will further be compared with the previously-presented range elaboration approach and a random mode generation approach on the basis of computational efficiency and found modes.

Resilience↗

Liquid Crystal Orientation and Shape Optimization for the Active Response of Liquid Crystal Elastomers

Liquid crystal elastomers (LCEs) are responsive materials that can undergo large reversible deformations upon exposure to external stimuli, such as electrical and thermal fields. Controlling the alignment of their liquid crystals mesogens to achieve desired shape changes unlocks a new design paradigm that is unavailable when using traditional materials. While experimental measurements can provide valuable insights into their behavior, computational analysis is essential to exploit their full potential. Accurate simulation is not, however, the end goal; rather, it is the means to achieve their optimal design. Such design optimization problems are best solved with algorithms that require gradients, i.e., sensitivities, of the cost and constraint functions with respect to the design parameters, to efficiently traverse the design space. In this work, a nonlinear LCE model and adjoint sensitivity analysis are implemented in a scalable and flexible finite element-based open source framework and integrated into a gradient-based design optimization tool. To display the versatility of the computational framework, LCE design problems that optimize both the material, i.e., liquid crystal orientation, and structural shape to reach a target actuated shapes or maximize energy absorption are solved. Multiple parameterizations, customized to address fabrication limitations, are investigated in both 2D and 3D. The case studies are followed by a discussion on the simulation and design optimization hurdles, as well as potential avenues for improving the robustness of similar computational frameworks for applications of interest.

42 ENGINEERING↗

Flutter optimization in fighter aircraft design

The efficient design of aircraft structure involves a series of compromises among various engineering disciplines. These compromises are necessary to ensure the best overall design. To effectively reconcile the various technical constraints requires a number of design iterations, with the accompanying long elapsed time. Automated procedures can reduce the elapsed time, improve productivity and hold the promise of optimum designs which may be missed by batch processing. Several examples are given of optimization applications including aeroelastic constraints. Particular attention is given to the success or failure of each example and the lessons learned. The specific applications are shown. The final two applications were made recently.

Triplett, W. E.↗

Computer Simulation For Multilevel Optimization Of Design

New simulator for multilevel optimization of complex hierarchical systems reduces cost of analysis in experimentation with multilevel design-optimization algorithms. Computer program mimics qualitative behavior and data couplings that occur among subsystems of complex engineering system, such as car, aircraft, or building. Eliminates engineering analyses in subsystems by replacing them with judiciously-chosen analytical functions. Serves as tool for development of strategy for multilevel optimization of design.

Padula, Sharon L.↗

A Requirements-Driven Optimization Method for Acoustic Treatment Design

Acoustic treatment designers are able to attenuate specific noise sources inside turbofan engines. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But, characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. The subject of this paper is an analytic method that derives the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground. Software is developed and used to test and validate the method on a simple, notional source. With experience gained from minimizing noise of the simple source, the software is tested against a realistic hardwall fan source.

aircraft noise↗

Engineering Overview of a Multidisciplinary HSCT Design Framework Using Medium-Fidelity Analysis Codes

An objective of the HPCC Program at NASA Langley has been to promote the use of advanced computing techniques to more rapidly solve the problem of multidisciplinary optimization of a supersonic transport configuration. As a result, a software system has been designed and is being implemented to integrate a set of existing discipline analysis codes, some of them CPU-intensive, into a distributed computational framework for the design of a High Speed Civil Transport (HSCT) configuration. The proposed paper will describe the engineering aspects of integrating these analysis codes and additional interface codes into an automated design system. The objective of the design problem is to optimize the aircraft weight for given mission conditions, range, and payload requirements, subject to aerodynamic, structural, and performance constraints. The design variables include both thicknesses of structural elements and geometric parameters that define the external aircraft shape. An optimization model has been adopted that uses the multidisciplinary analysis results and the derivatives of the solution with respect to the design variables to formulate a linearized model that provides input to the CONMIN optimization code, which outputs new values for the design variables. The analysis process begins by deriving the updated geometries and grids from the baseline geometries and grids using the new values for the design variables. This free-form deformation approach provides internal FEM (finite element method) grids that are consistent with aerodynamic surface grids. The next step involves using the derived FEM and section properties in a weights process to calculate detailed weights and the center of gravity location for specified flight conditions. The weights process computes the as-built weight, weight distribution, and weight sensitivities for given aircraft configurations at various mass cases. Currently, two mass cases are considered: cruise and gross take-off weight (GTOW). Weights information is obtained from correlations of data from three sources: 1) as-built initial structural and non-structural weights from an existing database, 2) theoretical FEM structural weights and sensitivities from Genesis, and 3) empirical as-built weight increments, non-structural weights, and weight sensitivities from FLOPS. For the aeroelastic analysis, a variable-fidelity aerodynamic analysis has been adopted. This approach uses infrequent CPU-intensive non-linear CFD to calculate a non-linear correction relative to a linear aero calculation for the same aerodynamic surface at an angle of attack that results in the same configuration lift. For efficiency, this nonlinear correction is applied after each subsequent linear aero solution during the iterations between the aerodynamic and structural analyses. Convergence is achieved when the vehicle shape being used for the aerodynamic calculations is consistent with the structural deformations caused by the aerodynamic loads. To make the structural analyses more efficient, a linearized structural deformation model has been adopted, in which a single stiffness matrix can be used to solve for the deformations under all the load conditions. Using the converged aerodynamic loads, a final set of structural analyses are performed to determine the stress distributions and the buckling conditions for constraint calculation. Performance constraints are obtained by running FLOPS using drag polars that are computed using results from non-linear corrections to the linear aero code plus several codes to provide drag increments due to skin friction, wave drag, and other miscellaneous drag contributions. The status of the integration effort will be presented in the proposed paper, and results will be provided that illustrate the degree of accuracy in the linearizations that have been employed.

Weston, R. P.↗

Design and Optimization of Low-thrust Orbit Transfers Using Q-law and Evolutionary Algorithms

Future space missions will depend more on low-thrust propulsion (such as ion engines) thanks to its high specific impulse. Yet, the design of low-thrust trajectories is complex and challenging. Third-body perturbations often dominate the thrust, and a significant change to the orbit requires a long duration of thrust. In order to guide the early design phases, we have developed an efficient and efficacious method to obtain approximate propellant and flight-time requirements (i.e., the Pareto front) for orbit transfers. A search for the Pareto-optimal trajectories is done in two levels: optimal thrust angles and locations are determined by Q-law, while the Q-law is optimized with two evolutionary algorithms: a genetic algorithm and a simulated-annealing-related algorithm. The examples considered are several types of orbit transfers around the Earth and the asteroid Vesta.

low-thrust orbit transfer↗