SEARCH · Engineering Papers

Results for “Experiment Optimization”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75

All sources NASA NTRS DOE OSTI

NASA NTRS2017

Dawn Spacecraft Performance at Ceres: Results of Hybrid Control for Ceres Mapping

Dawn is a low-thrust interplanetary spacecraft currently orbiting the dwarf planet Ceres, to better understand the early creation of the solar system. Launched in September 2007, Dawn arrived at Vesta in July 2011. After a 16-month successful science campaign at Vesta, Dawn departed for Ceres, arriving in early 2015. The Dawn spacecraft uses both reaction wheel assemblies (RWA) and a reaction control system (RCS) to provide 3-axis attitude control for the spacecraft. Reaction wheels were designed to be the primary system for attitude control, however two wheels have shown high friction anomalies and have been removed from service. The project has implemented a hybrid control algorithm using two reaction wheels and RCS thrusters. This hybrid control capability enabled Dawn to achieve very high science return, while significantly conserving remaining hydrazine propellant. With only two remaining healthy RWA’s, hybrid control became part of the baseline plan for Ceres science operations. The Dawn team developed specific operational approaches in which sequences were developed with careful consideration of science versus resource trades. Commanding and sequence planning also incorporated contingency planning, in the event that another reaction wheel may fail. Despite the differences in operational approach between Vesta and Ceres, both campaigns achieved very rich scientific data return. This paper highlights Dawn’s recent flight experience with hybrid attitude control during Ceres orbit operations. The discussion includes the approaches utilized by the Dawn team to address unique operational challenges presented by the hybrid approach, and reviews spacecraft performance under hybrid control in low orbit at Ceres. Additionally, methods used to optimize hydrazine use and thereby extend the science campaign will be presented. Finally, a preliminary assessment of an orbit transfer with two reaction wheels, during extended mission operations, is discussed.

Smith, Brett A.↗

NASA NTRSDate not supplied

Leveraging Observing System Simulation Experiments for Satellite Instrument Design: Advancements and Challenges

This abstract highlights NASA's OSSE framework, developed at the Global Modeling and Assimilation Office, which has become a widely adopted tool for evaluating the impact of new observations on weather forecasts. The framework involves simulating realistic observations by introducing errors to mimic real-world scenarios. By utilizing advanced radiative transfer modeling, the accuracy of simulated observations is significantly improved, enhancing the reliability of experimental outcomes. The talk focuses on recent progress and challenges in three key areas. Firstly, it explores the techniques used to simulate synthetic observations, a crucial aspect of OSSE experiments. Secondly, the presentation also discusses the challenges of examining the observation errors that need to be added to the perfect observations to generate realistic simulated observations. Lastly, the assimilation of synthetic observations and their impact on forecast skills is evaluated, providing valuable insights for optimizing current and future observing systems for improving the weather forecasts. By sharing recent advancements and acknowledging challenges, this presentation seeks to inspire researchers to leverage the OSSE framework in weather forecasting. NASA's OSSE techniques hold promise for a better understanding of the atmosphere and the development of more accurate and reliable weather predictions.

Isaac Moradi↗

NASA NTRS2002

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic coefficients to an accuracy of 110% . In our problem, we would like to get an optimized neural network architecture and minimum data set. This has been accomplished within 500 training cycles of a neural network. After removing training pairs (outliers), the GA has produced much better results. The neural network constructed is a feed forward neural network with a back propagation learning mechanism. The main goal has been to free the network design process from constraints of human biases, and to discover better forms of neural network architectures. The automation of the network architecture search by genetic algorithms seems to have been the best way to achieve this goal.

Rajkumar, T.↗

NASA NTRS1972

Resin/graphite fiber composites

High temperature resin matrices suitable for use in advanced graphite fiber composites for jet engine applications were evaluated. A series of planned, sequential screening experiments with resin systems in composite form were performed to reduce the number of candidates to a single A-type polyimide resin that repetitively produced void-free, high strength and modulus composites acceptable for use in the 550 F range for 1000 hours. An optimized processing procedure was established for this system. Extensive mechanical property studies characterized this single system, at room temperature, 500 F, 550 F and 600 F, for various exposure times.

Cavano, P. J.↗

NASA NTRS1972

A design procedure and handling quality criteria for lateral directional flight control systems

A practical design procedure for aircraft augmentation systems is described based on quadratic optimal control technology and handling-quality-oriented cost functionals. The procedure is applied to the design of a lateral-directional control system for the F4C aircraft. The design criteria, design procedure, and final control system are validated with a program of formal pilot evaluation experiments.

Stein, G.↗

NASA NTRS1986

Elevated temperature strengthening of a melt spun austenitic steel by TiB2

Mechanical properties of an iron-based alloy containing (by wt pct) 33Ni, 2Al, 6Ti, and 2B (resulting in an alloy containing 10 vol pct TiB2) were evaluated by hardness and tensile testing. The alloy was cast as a ribbon using a dual 'free-jet' variation of Jech et al. (1984) method of chill-block melt-spinning against a copper wheel; to simulate thermal cycles the alloy ribbon would experience during compaction into shapes, various segments of the ribbon were annealed under a vacuum at temperatures ranging from 500 to 1150 C. The results show that maximum strengths at 650 and 760 C were developed in ribbons annealed at 1100 C; in these ribbons an optimal combination of grain coarsening with minimum TiB2 particle growth was observed. However, the elevated-temperature strength of the TiB2-strengthened alloy under optimal annealing conditions was poorer than that of conventional iron-based superalloys strengthened by gamma-prime precipitates.

Michal, G. M.↗

NASA NTRS1989

Design and control of a multi-fingered robot hand provided with tactile feedback

The design, construction, control and application of a three fingered robot hand with nine degrees of freedom and built-in multi-component force sensors is described. The adopted gripper kinematics are justified and optimized with respect to grasping and manipulation flexibility. The hand was constructed with miniature motor drive systems imbedded into the fingers. The control is hierarchically structured and is implemented on a simple PC-AT computer. The hand's dexterity and intelligence are demonstrated with some experiments.

Vanbrussel, H.↗

NASA NTRS1993

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Hong, Steven W.↗

NASA NTRS1993

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives, resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Hong, Steven W.↗

NASA NTRS1994

A proven approach for more effective software development and maintenance

Modern space flight mission operations and associated ground data systems are increasingly dependent upon reliable, quality software. Critical functions such as command load preparation, health and status monitoring, communications link scheduling and conflict resolution, and transparent gateway protocol conversion are routinely performed by software. Given budget constraints and the ever increasing capabilities of processor technology, the next generation of control centers and data systems will be even more dependent upon software across all aspects of performance. A key challenge now is to implement improved engineering, management, and assurance processes for the development and maintenance of that software; processes that cost less, yield higher quality products, and that self-correct for continual improvement evolution. The NASA Goddard Space Flight Center has a unique experience base that can be readily tapped to help solve the software challenge. Over the past eighteen years, the Software Engineering Laboratory within the code 500 Flight Dynamics Division has evolved a software development and maintenance methodology that accommodates the unique characteristics of an organization while optimizing and continually improving the organization's software capabilities. This methodology relies upon measurement, analysis, and feedback much analogous to that of control loop systems. It is an approach with a time-tested track record proven through repeated applications across a broad range of operational software development and maintenance projects. This paper describes the software improvement methodology employed by the Software Engineering Laboratory, and how it has been exploited within the Flight Dynamics Division with GSFC Code 500. Examples of specific improvement in the software itself and its processes are presented to illustrate the effectiveness of the methodology. Finally, the initial findings are given when this methodology was applied across the mission operations and ground data systems software domains throughout Code 500.

Pajerski, Rose↗

NASA NTRS1994

Status of diffused junction p+n InP solar cells for space applications

Recently, we have succeeded in fabricating diffused junction p(sup +)n(Cd,S) InP solar cells with measured AMO, 25 C open circuit voltage (V(sub OC)) of 887.6 mV, which, to the best of our knowledge, is higher than previously reported V(sub OC) values for any InP homojunction solar cells. The experiment-based projected achievable efficiency of these cells using LEC grown substrates is 21.3 percent. The maximum AMO, 25 C internal losses due to date on bare cells is, however, only 13.2 percent. This is because of large external and internal losses due to non-optimized front grid design, antireflection (AR) coating and emitter thickness. This paper summarizes recent advances in the technology of fabrication of p(sup +)n InP diffused structures and solar cells, resulted from a study undertaken in an effort to increase the cell efficiency. The topics discussed in this paper include advances in: (1) the formation on thin p(sup +) InP:Cd emitter layers, (2) electroplated front contacts, (3) surface passivation and (4) the design of a new native oxide/Al2O3/MgF2 tree layer AR coating using a chemically-grown P-rich passivating oxide as a first layer. Based on the high radiation resistance and the excellent post-irradiation annealing and recovery demonstrated in the early tests done to date, as well as the projected high efficiency and low-cost high-volume fabricability, these cells show a very good potential for space photovoltaic applications.

Faur, Mircea↗

NASA NTRS2002

Equilibrium Kinetics Studies and Crystallization Aboard the International Space Station (ISS) Using the Protein Crystallization Apparatus for Microgravity (PCAM)

Protein Crystallization Apparatus in Microgravity (PCAM) trays have been used in Shuttle missions to crystallize proteins in a microgravity environment. The crystallization experiments are 'sitting drops' similar to that in Cryschem trays, but the reservoir solution is soaked in a wick. From early 2001, crystallization experiments are conducted on the International Space Station using mission durations of months rather than two weeks on previous shuttle missions. Experiments were set up in April 2001 on Flight 6A to characterize the time crystallization experiments will take to reach equilibrium in a microgravity environment using salts, polyethylene glycols and an organic solvent as precipitants. The experiments were set up to gather data for a series of days of activation with different droplet volumes and precipitants. The experimental set up on ISS and results of this study will be presented. These results will help future users of PCAM to choose precipitants to optimize crystallization conditions for their target macromolecules for a particular mission with known mission duration. Changes in crystal morphology and size between the ground and space grown crystals of a protein and a protein -DNA complex flown on the same mission will also be presented.

Achari, Aniruddha↗

NASA NTRS2004

Putting Priors in Mixture Density Mercer Kernels

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

Srivastava, Ashok N.↗

NASA NTRS1997

Reduced gravitropism in hypocotyls of starch-deficient mutants of Arabidopsis

Gravitropism was examined in dark- and light-grown hypocotyls of wild-type (WT), two reduced starch mutants (ACG 20 and ACG 27), and a starchless mutant (ACG 21) of Arabidopsis. In addition, the starch content of these four strains was studied with light and electron microscopy. Based on time course of curvature and orientation studies, the graviresponse in hypocotyls is proportional to the amount of starch in a genotype. Furthermore, starch mutations seem to primarily affect gravitropism rather than differential growth since both phototropic curvature and growth rates among the four genotypes are approximately equal. Our results suggest that gravity perception may require a greater plastid mass in hypocotyls compared to roots. The kinetics of gravitropic curvature also was compared following reorientation at 45 degrees, 90 degrees, and 135 degrees. As has been reported for other plant species, the optimal angle of reorientation is 135 degrees for WT Arabidopsis and the two reduced starch mutants, but the magnitude of curvature of the starchless mutant appears to be independent of the initial angle of displacement. Taken together, the results of the present study and our previous experiments with roots of the same four genotypes [Kiss et al. (1996) Physiol. Plant. 97: 237] support a plastid-based hypothesis for gravity perception in plants.

Non-NASA Center↗

NASA NTRS2005

Hybrid Power Management Program Evaluated Ultracapacitors for the Next Generation Launch Transportation Project

The NASA Glenn Research Center initiated baseline testing of ultracapacitors to obtain empirical data in determining the feasibility of using ultracapacitors for the Next Generation Launch Transportation (NGLT) Project. There are large transient loads associated with NGLT that require a very large primary energy source or an energy storage system. The primary power source used for this test was a proton-exchange-membrane (PEM) fuel cell. The energy storage system can consist of batteries, flywheels, or ultracapacitors. Ultracapacitors were used for these tests. NASA Glenn has a wealth of experience in ultracapacitor technology through the Hybrid Power Management (HPM) Program, which the Avionics, Power and Communications Branch of Glenn s Engineering Development Division initiated for the Technology Transfer and Partnership Office. HPM is the innovative integration of diverse, state-ofthe- art power devices in optimal configurations for space and terrestrial applications. The appropriate application and control of the various advanced power devices (such as ultracapacitors and fuel cells) significantly improves overall system performance and efficiency. HPM has extremely wide potential. Applications include power generation, transportation systems, biotechnology systems, and space power systems. HPM has the potential to significantly alleviate global energy concerns, improve the environment, and stimulate the economy.

Eichenberg, Dennis J.↗

NASA NTRS2005

An Ensemble Approach to Building Mercer Kernels with Prior Information

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

Srivastava, Ashok N.↗

NASA NTRS2005

Managing Space Radiation Risks On Lunar and Mars Missions: Risk Assessment and Mitigation

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Cucinotta, F. A.↗

NASA NTRS2005

Managing Space Radiation Risks on Lunar and Mars Missions: Risk Assessment and Mitigation

Cucinotta, F. A.↗