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At least 109 records · Page 6

TPSAS-NF1676L-33626-DND

NASA is conducting a series of computational experiments to quantify atmospheric effects on low noise sonic booms. In the current study, simulated cruise nearfield pressure data from NASA?s X-59 Quiet Supersonic Technology aircraft was propagated from the aircraft to the ground at four cardinal headings through five years of realistic atmospheric profiles at 30 locations across the eastern USA. Statistical design of experiments was used to select the locations where primary sonic thump carpet widths (CW) and metric levels at the ground were computed. Atmospheric profiles were taken from the Climate Forecast System Reanalysis database, which contains reanalyzed atmospheric profiles four times daily. Decision tree analyses were performed to determine relative importance of predictors for CW and metric levels. Predictors included were latitude, longitude, date, time of day, season, climate, aircraft heading, and ground elevation. Results of this study indicate the propagation resolution needed to adequately characterize the distributions of CW and ground metric data, i.e., necessary separation distance between propagation locations and total number of atmospheres through which to propagate. This resolution will be used for a follow-on study of simulated X-59 carpets across the entire US mainland.

Will Doebler↗

Advances in Integrally Formed Metallic Structures

NASA Langley Research Center (LaRC) is applying flow forming technology to aerospace aluminum alloys for the manufacture of integrally stiffened cylinders that meet aircraft fuselage or launch vehicle specifications. High-strength 2xxx series alloys, in various temper/product form conditions, are being compared with medium-strength, very formable AA 6061 as the benchmark. Screening of candidate materials traditionally relies on empirical forming trials, but more recently on metrics derived from constant nominal strain rate tensile testing. In this work, the established hierarchy of formability metrics is adopted as the baseline; tensile area reduction, work hardening exponent, and modulus of resilience. The suite of metrics can be expanded based on phenomenological and mechanistic considerations of plastic flow instabilities to incorporate anisotropy ratio, rate of work hardening, and dynamic strain aging effects. Separate research thrusts at LaRC are aimed at formulating a protocol for scalable production of fully formed, defect-free components: 1) quantifying the extended set of formability metrics from constant and jump strain rate tensile tests with digital image correlation (DIC); 2) using statistically designed experiments on a vertical spin/flow forming facility (WF VUD-600®) to isolate the effect of convenient process variables, such as axial feed rate and thickness reduction; and 3) predicting the effect of feed ratio (roller translation relative to mandrel rotation speeds) on material response via process modeling using the DEFORM® simulation software. Current results will be discussed in terms of correlating intrinsic material properties with the bulk workability characteristics to successfully fabricate cylinders with complex cross-sections.

Aluminum↗

Statistical support for the ATL program

Statistical experimental designs are presented for various numbers of organisms and agar solutions pertinent to the experiment, ""colony growth in zero gravity''. Missions lasting 7 and 30 days are considered. For the designs listed, the statistical analysis of the observations obtained on the space shuttle are outlined.

Hinkelmann, K.↗

Multispectral data acquisition and classification - Statistical models for system design

In this paper we relate the statistical processes that are involved in multispectral data acquisition and classification to a simple radiometric model of the earth surface and atmosphere. If generalized, these formulations could provide an analytical link between the steadily improving models of our environment and the performance characteristics of rapidly advancing device technology. This link is needed to bring system analysis tools to the task of optimizing remote sensing and (real-time) signal processing systems as a function of target and atmospheric properties, remote sensor spectral bands and system topology (e.g., image-plane processing), radiometric sensitivity and calibration accuracy, compensation for imaging conditions (e.g., atmospheric effects), and classification rates and errors.

Huck, F. O.↗

Launch Vehicle Design and Requirements Verification Using Statistical Methods

- This presentation applies statistics to launch vehicle design, but the methods may be used for other engineering applications - Vehicle Models: What do we know when? How to separate parameters for making Monte Carlo runs - Known when assembling the vehicle but not during design - Known prior to committing to flight - Unknown at lift off - How do we correctly model the vehicle during the design phases? - Number of Monte Carlo samples - Requirements success - Design parameter values

Monte Carlo↗

Implementation of Probabilistic Design Methodology at Tennessee State University

Engineering Design is one of the most important areas in engineering education. Deterministic Design Methodology (DDM) is the only design method that is taught in most engineering schools. This method does not give a direct account of uncertainties in design parameters. Hence, it is impossible to quantify the uncertainties in the response and the actual safety margin remains unknown. The desire for a design methodology tha can identify the primitive (random) variables that affect the structural behavior has led to a growing interest on Probabilistic Design Methodology (PDM). This method is gaining more recognition in industries than in educational institutions. Some of the reasons for the limited use of the PDM at the moment are that many are unaware of its potentials, and most of the software developed for PDM are very recent. The central goal of the PDM project at Tennessee State University is to introduce engineering students to the method. The students participating in the project learn about PDM and the computer codes that are available to the design engineer. The software being used of this project is NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) developed under NASA probabilistic structural analysis program. NESSUS has three different modules which make it a very comprehensive computer code for PDM. A research in technology transfer through course offering in PDM is in effect a Tennessee State University. The aim is to familiarize students with the problem of uncertainties in engineering design. Included in the paper are some projects on PDM carried out by some students and faculty. The areas this method is being applied at the moment include, Design of Gears (spur and worm); Design of Shafts; Design of Statistically Indeterminate Frame Structures; Design of Helical Springs; and Design of Shock Absorbers. Some of the current results of these projects are presented.

Onwubiko, Chinyere↗

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Tomberlin, T. J.↗

A two-component rain model for the prediction of attenuation statistics

A two-component rain model has been developed for calculating attenuation statistics. In contrast to most other attenuation prediction models, the two-component model calculates the occurrence probability for volume cells or debris attenuation events. The model performed significantly better than the International Radio Consultative Committee model when used for predictions on earth-satellite paths. It is expected that the model will have applications in modeling the joint statistics required for space diversity system design, the statistics of interference due to rain scatter at attenuating frequencies, and the duration statistics for attenuation events.

Crane, R. K.↗

Maximizing Macromolecule Crystal Size for Neutron Diffraction Experiments

A challenge in neutron diffraction experiments is growing large (greater than 1 cu mm) macromolecule crystals. In taking up this challenge we have used statistical experiment design techniques to quickly identify crystallization conditions under which the largest crystals grow. These techniques provide the maximum information for minimal experimental effort, allowing optimal screening of crystallization variables in a simple experimental matrix, using the minimum amount of sample. Analysis of the results quickly tells the investigator what conditions are the most important for the crystallization. These can then be used to maximize the crystallization results in terms of reducing crystal numbers and providing large crystals of suitable habit. We have used these techniques to grow large crystals of Glucose isomerase. Glucose isomerase is an industrial enzyme used extensively in the food industry for the conversion of glucose to fructose. The aim of this study is the elucidation of the enzymatic mechanism at the molecular level. The accurate determination of hydrogen positions, which is critical for this, is a requirement that neutron diffraction is uniquely suited for. Preliminary neutron diffraction experiments with these crystals conducted at the Institute Laue-Langevin (Grenoble, France) reveal diffraction to beyond 2.5 angstrom. Macromolecular crystal growth is a process involving many parameters, and statistical experimental design is naturally suited to this field. These techniques are sample independent and provide an experimental strategy to maximize crystal volume and habit for neutron diffraction studies.

Judge, R. A.↗

Estimation Model of Spacecraft Parameters and Cost Based on a Statistical Analysis of COMPASS Designs

The Collaborative Modeling for Parametric Assessment of Space Systems (COMPASS) team at Glenn Research Center has performed integrated system analysis of conceptual spacecraft mission designs since 2006 using a multidisciplinary concurrent engineering process. The set of completed designs was archived in a database, to allow for the study of relationships between design parameters. Although COMPASS uses a parametric spacecraft costing model, this research investigated the possibility of using a top-down approach to rapidly estimate the overall vehicle costs. This paper presents the relationships between significant design variables, including breakdowns of dry mass, wet mass, and cost. It also develops a model for a broad estimate of these parameters through basic mission characteristics, including the target location distance, the payload mass, the duration, the delta-v requirement, and the type of mission, propulsion, and electrical power. Finally, this paper examines the accuracy of this model in regards to past COMPASS designs, with an assessment of outlying spacecraft, and compares the results to historical data of completed NASA missions.

cost modeling↗

Statistical Considerations for the Design and Execution of NASA's Community Noise Surveys

The World Health Organization defines community noise as noise emitted from all sources apart from noise at an industrial workplace. Example sources include neighborhood and construction noise, noise from road and rail, and air traffic noise. In particular, overland supersonic flights have been banned in the United States since the 1970s based on data accumulated during the 1960s; the degree of reported annoyance from the resulting sonic booms was a key factor leading to the prohibition. In subsequent years, scientific and engineering understanding has led to the potential to produce low amplitude sonic booms, or ‘sonic thumps’, during supersonic flight through aircraft design choices. Aircraft manufacturers have expressed renewed interest in producing supersonic commercial aircraft, but without appropriate changes to regulation, only overseas routes can be traveled supersonically. The National Aeronautics and Space Administration (NASA) will be flying the X-59 demonstrator aircraft in a series of community tests to begin in the 2024 fiscal year. In this presentation we provide some historical context for the current prohibitions on supersonic commercial flight. Using data collected during earlier NASA risk reduction tests, we demonstrate how generalized linear mixed models can be used to inform the functional dose-response response curve. Finally, we discuss some of the challenges in designing the future community studies and generalizing them to a nationally-representative dose-response curve. The study effort will be of national and international importance as the data and models prepared during the community tests will be provided to the International Civil Aviation Organization (ICAO) in order to help noise regulators determine if supersonic flight will be permitted over land once again and at what demonstrable noise levels.

Nathan B Cruze↗

Using experimental design modules for process characterization in manufacturing/materials processes laboratories

Modules dealing with statistical experimental design (SED), process modeling and improvement, and response surface methods have been developed and tested in two laboratory courses. One course was a manufacturing processes course in Mechanical Engineering and the other course was a materials processing course in Materials Science and Engineering. Each module is used as an 'experiment' in the course with the intent that subsequent course experiments will use SED methods for analysis and interpretation of data. Evaluation of the modules' effectiveness has been done by both survey questionnaires and inclusion of the module methodology in course examination questions. Results of the evaluation have been very positive. Those evaluation results and details of the modules' content and implementation are presented. The modules represent an important component for updating laboratory instruction and to provide training in quality for improved engineering practice.

Ankenman, Bruce↗

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Dubovik, O↗

Advanced Vibration Analysis Tools and New Strategies for Robust Design of Turbine Engine Rotors

The adverse effects of small, random structural irregularities among the blades, called mistuning, can result in blade forced-response amplitudes and stresses that are much larger than those predicted for a perfectly tuned rotor. Manufacturing tolerances, deviations in material properties, or nonuniform operational wear causes mistuning; therefore, mistuning is unavoidable. Furthermore, even a small mistuning can have a dramatic effect on the vibratory behavior of a rotor because it can lead to spatial localization of the vibration energy (see the following photographs). As a result, certain blades may experience forced response amplitudes and stresses that are substantially larger than those predicted by an analysis of the nominal (tuned) design. Unfortunately, these random uncertainties in blade properties, and the immense computational effort involved in obtaining statistically reliable design data, combine to make this aspect of rotor design cumbersome.

Min, James B.↗

Advanced Vibration Analysis Tools and New Strategies for Robust Design of Turbine Engine Rotors

The adverse effects of small, random structural irregularities among the blades, called mistuning, can result in blade forced-response amplitudes and stresses that are much larger than those predicted for a perfectly tuned rotor. Manufacturing tolerances, deviations in material properties, or nonuniform operational wear causes mistuning; therefore, mistuning is unavoidable. Furthermore, even a small mistuning can have a dramatic effect on the vibratory behavior of a rotor because it can lead to spatial localization of the vibration energy (see the following photographs). As a result, certain blades may experience forced response amplitudes and stresses that are substantially larger than those predicted by an analysis of the nominal (tuned) design. Unfortunately, these random uncertainties in blade properties, and the immense computational effort involved in obtaining statistically reliable design data, combine to make this aspect of rotor design cumbersome.

Min, James B.↗