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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Optimizing conceptual aircraft designs for minimum life cycle cost

A life cycle cost (LCC) module has been added to the FLight Optimization System (FLOPS), allowing the additional optimization variables of life cycle cost, direct operating cost, and acquisition cost. Extensive use of the methodology on short-, medium-, and medium-to-long range aircraft has demonstrated that the system works well. Results from the study show that optimization parameter has a definite effect on the aircraft, and that optimizing an aircraft for minimum LCC results in a different airplane than when optimizing for minimum take-off gross weight (TOGW), fuel burned, direct operation cost (DOC), or acquisition cost. Additionally, the economic assumptions can have a strong impact on the configurations optimized for minimum LCC or DOC. Also, results show that advanced technology can be worthwhile, even if it results in higher manufacturing and operating costs. Examining the number of engines a configuration should have demonstrated a real payoff of including life cycle cost in the conceptual design process: the minimum TOGW of fuel aircraft did not always have the lowest life cycle cost when considering the number of engines.

Johnson, Vicki S.↗
NASA NTRS1992

An interactive system for aircraft design and optimization

A system for aircraft design utilizing a unique analysis architecture, graphical interface, and suite of numerical optimization methods is described in this paper. The non-procedural architecture provides extensibility and efficiency not possible with conventional programming techniques. The interface for analysis and optimization, developed for use with this method, is described and its application to example problems is discussed.

Kroo, Ilan M.↗
NASA NTRS2005

The Systems Engineering Process for Human Support Technology Development

Systems engineering is designing and optimizing systems. This paper reviews the systems engineering process and indicates how it can be applied in the development of advanced human support systems. Systems engineering develops the performance requirements, subsystem specifications, and detailed designs needed to construct a desired system. Systems design is difficult, requiring both art and science and balancing human and technical considerations. The essential systems engineering activity is trading off and compromising between competing objectives such as performance and cost, schedule and risk. Systems engineering is not a complete independent process. It usually supports a system development project. This review emphasizes the NASA project management process as described in NASA Procedural Requirement (NPR) 7120.5B. The process is a top down phased approach that includes the most fundamental activities of systems engineering - requirements definition, systems analysis, and design. NPR 7120.5B also requires projects to perform the engineering analyses needed to ensure that the system will operate correctly with regard to reliability, safety, risk, cost, and human factors. We review the system development project process, the standard systems engineering design methodology, and some of the specialized systems analysis techniques. We will discuss how they could apply to advanced human support systems development. The purpose of advanced systems development is not directly to supply human space flight hardware, but rather to provide superior candidate systems that will be selected for implementation by future missions. The most direct application of systems engineering is in guiding the development of prototype and flight experiment hardware. However, anticipatory systems engineering of possible future flight systems would be useful in identifying the most promising development projects.

Jones, Harry↗
NASA NTRS2004

Subsonic Aircraft With Regression and Neural-Network Approximators Designed

At the NASA Glenn Research Center, NASA Langley Research Center's Flight Optimization System (FLOPS) and the design optimization testbed COMETBOARDS with regression and neural-network-analysis approximators have been coupled to obtain a preliminary aircraft design methodology. For a subsonic aircraft, the optimal design, that is the airframe-engine combination, is obtained by the simulation. The aircraft is powered by two high-bypass-ratio engines with a nominal thrust of about 35,000 lbf. It is to carry 150 passengers at a cruise speed of Mach 0.8 over a range of 3000 n mi and to operate on a 6000-ft runway. The aircraft design utilized a neural network and a regression-approximations-based analysis tool, along with a multioptimizer cascade algorithm that uses sequential linear programming, sequential quadratic programming, the method of feasible directions, and then sequential quadratic programming again. Optimal aircraft weight versus the number of design iterations is shown. The central processing unit (CPU) time to solution is given. It is shown that the regression-method-based analyzer exhibited a smoother convergence pattern than the FLOPS code. The optimum weight obtained by the approximation technique and the FLOPS code differed by 1.3 percent. Prediction by the approximation technique exhibited no error for the aircraft wing area and turbine entry temperature, whereas it was within 2 percent for most other parameters. Cascade strategy was required by FLOPS as well as the approximators. The regression method had a tendency to hug the data points, whereas the neural network exhibited a propensity to follow a mean path. The performance of the neural network and regression methods was considered adequate. It was at about the same level for small, standard, and large models with redundancy ratios (defined as the number of input-output pairs to the number of unknown coefficients) of 14, 28, and 57, respectively. In an SGI octane workstation (Silicon Graphics, Inc., Mountainview, CA), the regression training required a fraction of a CPU second, whereas neural network training was between 1 and 9 min, as given. For a single analysis cycle, the 3-sec CPU time required by the FLOPS code was reduced to milliseconds by the approximators. For design calculations, the time with the FLOPS code was 34 min. It was reduced to 2 sec with the regression method and to 4 min by the neural network technique. The performance of the regression and neural network methods was found to be satisfactory for the analysis and design optimization of the subsonic aircraft.

Patnaik, Surya N.↗
NASA NTRS2012

Strategies for Stabilizing Nitrogenous Compounds in ECLSS Wastewater: Top-Down System Design and Unit Operation Selection with Focus on Bio-Regenerative Processes for Short and Long Term Scenarios

Water recycling and eventual nutrient recovery is crucial for surviving in or past low earth orbit. New approaches and syste.m architecture considerations need to be addressed to meet current and future system requirements. This paper proposes a flexible system architecture that breaks down pretreatment , steps into discrete areas where multiple unit operations can be considered. An overview focusing on the urea and ammonia conversion steps allows an analysis on each process's strengths and weaknesses and synergy with upstream and downstream processing. Process technologies to be covered include chemical pretreatment, biological urea hydrolysis, chemical urea hydrolysis, combined nitrification-denitrification, nitrate nitrification, anammox denitrification, and regenerative ammonia absorption through struvite formation. Biological processes are considered mainly for their ability to both maximize water recovery and to produce nutrients for future plant systems. Unit operations can be considered for traditional equivalent system mass requirements in the near term or what they can provide downstream in the form of usable chemicals or nutrients for the long term closed-loop ecological control and life support system. Optimally this would allow a system to meet the former but to support the latter without major modification.

Lunn, Griffin M.↗
NASA NTRS2015

Space Synthetic Biology Project

Synthetic biology is an effort to make genetic engineering more useful by standardizing sections of genetic code. By standardizing genetic components, biological engineering will become much more similar to traditional fields of engineering, in which well-defined components and subsystems are readily available in markets. Specifications of the behavior of those components and subsystems can be used to model a system which incorporates them. Then, the behavior of the novel system can be simulated and optimized. Finally, the components and subsystems can be purchased and assembled to create the optimized system, which most often will exhibit behavior similar to that indicated by the model. The Space Synthetic Biology project began in 2012 as a multi-Center effort. The purpose of this project was to harness Synthetic Biology principals to enable NASA's missions. A central target for application was to Environmental Control & Life Support (ECLS). Engineers from NASA Marshall Space Flight Center's (MSFC's) ECLS Systems Development Branch (ES62) were brought into the project to contribute expertise in operational ECLS systems. Project lead scientists chose to pursue the development of bioelectrochemical technologies to spacecraft life support. Therefore, the ECLS element of the project became essentially an effort to develop a bioelectrochemical ECLS subsystem. Bioelectrochemical systems exploit the ability of many microorganisms to drive their metabolisms by direct or indirect utilization of electrical potential gradients. Whereas many microorganisms are capable of deriving the energy required for the processes of interest (such as carbon dioxide (CO2) fixation) from sunlight, it is believed that subsystems utilizing electrotrophs will exhibit smaller mass, volume, and power requirements than those that derive their energy from sunlight. In the first 2 years of the project, MSFC personnel conducted modeling, simulation, and conceptual design efforts to assist the project in selecting the best approaches to the application of bioelectrochemical technologies to ECLS. Figure 1 shows results of simulation of charge transport in an experimental system. Figure 2 shows one of five conceptual designs for ECLS subsystems based on bioelectrochemical reactors. Also during the first 2 years, some work was undertaken to gather fundamental data (conductivities, overpotentials) relevant to the modeling efforts.

Howard, David↗
NASA NTRS2012

Apparatus and methods for manipulation and optimization of biological systems

The invention provides systems and methods for manipulating, e.g., optimizing and controlling, biological systems, e.g., for eliciting a more desired biological response of biological sample, such as a tissue, organ, and/or a cell. In one aspect, systems and methods of the invention operate by efficiently searching through a large parametric space of stimuli and system parameters to manipulate, control, and optimize the response of biological samples sustained in the system, e.g., a bioreactor. In alternative aspects, systems include a device for sustaining cells or tissue samples, one or more actuators for stimulating the samples via biochemical, electromagnetic, thermal, mechanical, and/or optical stimulation, one or more sensors for measuring a biological response signal of the samples resulting from the stimulation of the sample. In one aspect, the systems and methods of the invention use at least one optimization algorithm to modify the actuator's control inputs for stimulation, responsive to the sensor's output of response signals. The compositions and methods of the invention can be used, e.g., to for systems optimization of any biological manufacturing or experimental system, e.g., bioreactors for proteins, e.g., therapeutic proteins, polypeptides or peptides for vaccines, and the like, small molecules (e.g., antibiotics), polysaccharides, lipids, and the like. Another use of the apparatus and methods includes combination drug therapy, e.g. optimal drug cocktail, directed cell proliferations and differentiations, e.g. in tissue engineering, e.g. neural progenitor cells differentiation, and discovery of key parameters in complex biological systems.

Ho, Chih-Ming↗
NASA NTRS2014

Space Evaporator Absorber Radiator (SEAR) for Thermal Storage on Manned Spacecraft

Future manned exploration spacecraft will need to operate in challenging thermal environments. State-of the- art technology for active thermal control relies on sublimating water ice and venting the vapor overboard in very hot environments. This approach can lead to large loss of water and a significant mass penalty for the spacecraft. This paper describes an innovative thermal control system that uses a Space Evaporator Absorber Radiator (SEAR) to control spacecraft temperatures in highly variable environments without venting water. SEAR uses heat pumping and energy storage by LiCl/water absorption to enable effective cooling during hot periods and regeneration during cool periods. The LiCl absorber technology has the potential to absorb over 800 kJ per kg of system mass, compared to phase change heat sink systems that typically achieve approx. 50 kJ/kg. The optimal system is based on a trade-off between the mass of water saved and extra power needed to regenerate the LiCl absorber. This paper describes analysis models and the predicted performance and optimize the size of the SEAR system, estimated size and mass of key components, and power requirements for regeneration. We also present a concept design for an ISS test package to demonstrate operation of a subscale system in zero gravity.

Izenson, Michael G.↗
NASA NTRS1973

On optimal modeling of systems.

A procedure for modeling a linear system by an optimal finite-dimensional approximation is developed on the basis of Sard's (1967) generalized spline. Error bounds are given, and the application of the procedure is illustrated by two presented examples. The procedure may be employed, not only in the modeling of conventional lumped-parameter and distributed-parameter continuous dynamical systems, but also in mathematical operations such as those involved in pattern recognition and picture enhancement problems.

De Figueiredo, R. J. P.↗
NASA NTRS1973

A summary report on system effectiveness and optimization study

Report treats optimization and effectiveness separately. Report illustrates example of dynamic programming solution to system optimization. Computer algorithm has been developed to solve effectiveness problem and is included in report.

Williamson, O. L.↗
NASA NTRS1984

Aircraft configuration optimization including optimized flight profiles

The Flight Optimization System (FLOPS) is an aircraft configuration optimization program developed for use in conceptual design of new aircraft and in the assessment of the impact of advanced technology. The modular makeup of the program is illustrated. It contains modules for preliminary weights estimation, preliminary aerodynamics, detailed mission performance, takeoff and landing, and execution control. An optimization module is used to drive the overall design and in defining optimized profiles in the mission performance. Propulsion data, usually received from engine manufacturers, are used in both the mission performance and the takeoff and landing analyses. Although executed as a single in-core program, the modules are stored separately so that the user may select the appropriate modules (e.g., fighter weights versus transport weights) or leave out modules that are not needed.

Mccullers, L. A.↗