Results for “experimental learning” — Page 11

NASA NTRS2003

Wind-US Flow Calculations for the M2129 S-Duct Using Structured and Unstructured Grids

Computational Fluid Dynamics (CFD) flow solutions for the M2129 diffusing S-duct with and without vane effectors were computed by the Wind-US flow solver. Both structured and unstructured 3-D grids were used. Without vane effectors, the duct exhibited massive flow separation in both experiment and CFD. With vane effectors installed, the flow remained attached and aerodynamic losses were reduced. Total pressure recovery and distortion near the duct outlet were computed from the solutions and compared favorably to experimental values. These calculations are part of a validation effort for the Wind-US code. They also provide an example case to aid engineers in learning to use the Wind-US software.

Mohler, Stanley R., Jr.↗

NASA NTRS1997

AB Initio Study of the Structure and Spectroscopic Properties of Halogenated Thioperoxy Radicals

Thioperoxy (XSO or XOS) radicals exist in a variety of chemical environments, and they have as a consequence drawn some interest. HSO, an important species in the chemistry of the troposphere, has been examined both experimentally. The halogenated (X = F, Cl or Br) peroxy species and isovalent thioperoxy species have been studied less, but they too are potentially interesting because oxidized sulfur species and halogen sources are present in the atmosphere. Learning the fate of XSO and XOS radicals is important to understanding the atmospheric oxidation chemistry of sulfur compounds. Of these, FSO and ClSO are particularly interesting because they have been directly detected spectroscopically. Recent studies in our laboratory on the photochemistry of thionyl halides (X2SO; where X = F or Cl) have suggested new ways to generate XSO species. The laser-induced photodissociation of thionyl fluoride, F2SO, at 193 nm and thionyl chloride, ClSO, at 248 nm is characterized by a radical mechanism, X2SO -> XSO + X. The structure of FSO has been characterized experimentally by Endo et cd. employing microwave spectroscopy. Using the unrestricted Hartree-Fock (UHF) self-consistent field (SCF) method, Sakai and Morokuma computed the electronic structure of the ground (sup 2)A" and the first excited (sup 2)A' states of FSO. Electron correlation was not taken into account in their study. In a laser photodissociation experiment, Huber et al. identified ClSO mass spectromctrically. ClSO has also been detected in low temperature matrices by EPR and in the gas phase by far IR laser magnetic resonance. Although the structure of FSO is known in detail, the only study, experimental or theoretical, of CISO has been an ab initio HFSCF study by Hinchliffe. Electron correlation corrections were also excluded from this study. In order to better understand the isomerization and dissociation dynamics of the radical species, we have performed ab initio correlated studies of the potential energy surfaces (PES) of ClSO and its isomer ClOS at the QCISD(T)/6-31 G* level of theory. For FSO and FOS, more extensive QCISD/6-31 1G(2df) calculations have been possible, and the results are summarized here.

Munoz, Luis A.↗

NASA NTRS2005

The Different Wavelengths of Radio Science

Radio Science covers many different avenues. This summer I attempted to work in each of the different avenues to learn the full range of subjects covered by Radio Science. I began my summer by traveling to Greece for the 3rd International Planetary Probe Workshop (IPPW-3). I went as a co-author of the Doppler Wind Experiment (DWE) team paper. My first job when I returned from Greece was to update the Radio Science activities webpage. I then used Fast Fourier Transforms (FFT) to find radio signals in recorded Radio Science experimental data and determine frequencies and powers. I read about and ran Fortran code being used to determine wind measurements on Huygens. I formatted and revised the abstracts and data lengths for the DVD data sets. By performing these tasks, I also learned the Unix operating system as well as a small amount of shell programming.

Malecha, Jessica L.↗

NASA NTRS2017

Lessons Learned from Applying Design Thinking in a NASA Rapid Design Study in Aeronautics

In late 2015, NASA's Aeronautics Research Mission Directorate (ARMD) funded an experiment in rapid design and rapid teaming to explore new approaches to solving challenging design problems in aeronautics in an effort to cultivate and foster innovation. This report summarizes several lessons learned from the rapid design portion of the study. This effort entailed learning and applying design thinking, a human-centered design approach, to complete the conceptual design for an open-ended design challenge within six months. The design challenge focused on creating a capability to advance experimental testing of autonomous aeronautics systems, an area of great interest to NASA, the US government as a whole, and an entire ecosystem of users and developers around the globe. A team of nine civil servant researchers from three of NASA's aeronautics field centers with backgrounds in several disciplines was assembled and rapidly trained in design thinking under the guidance of the innovation and design firm IDEO. The design thinking process, while used extensively outside the aerospace industry, is less common and even counter to many practices within the aerospace industry. In this report, several contrasts between common aerospace research and development practices and design thinking are discussed, drawing upon the lessons learned from the NASA rapid design study. The lessons discussed included working towards a design solution without a set of detailed design requirements, which may not be practical or even feasible for management to ascertain for complex, challenging problems. This approach allowed for the possibility of redesigning the original problem statement to better meet the needs of the users. Another lesson learned was to approach problems holistically from the perspective of the needs of individuals that may be affected by advances in topic area instead of purely from a technological feasibility viewpoint. The interdisciplinary nature of the design team also provided valuable experience by allowing team members from different technological backgrounds to work side-by-side instead of dividing into smaller teams, as is frequently done in traditional multidisciplinary design. The team also learned how to work with qualitative data obtained primarily through the 70-plus interviews that were conducted over the course of this project, which was a sharp contrast to using quantitative data with regards to identifying, capturing, analyzing, storing, and recalling the data. When identifying potential interviewees who may have useful contributions to the design subject area, the team found great value in talking to non-traditional users and potential beneficiaries of autonomous aeronautics systems whose impact on the aeronautics autonomy ecosystem is growing swiftly. Finally, the team benefitted from using "sacrificial prototyping," which is a method of rapidly prototyping draft concepts and ideas with the intent of enabling potential users to provide significant feedback early in the design process. This contrasts the more common approach of using expensive prototypes that focus on demonstrating technical feasibility. The unique design approach and lessons learned by the team throughout this process culminated in a final design concept that was quite different than what the team originally assumed would be the design concept initially. A summary of the more usercentered final design concept is also provided.

McGowan, Anna-Maria↗

NASA NTRS1988

Facilities for microgravity combustion research

Combustion science and applications have benefited in unforeseen ways from experimental research performed in the low-gravity environment. The capability to control for the first time the influence of gravitational buoyancy has provided some insight into soot formation in droplet combustion, the nature of flammability limits in premixed gases, and the relationship between normal-gravity and low-gravity material flammability that may influence how materials are best selected for routine use in habitable spacecraft. The opportunity to learn about these complex phenomena is derived from the control of the ambient body-force field and, perhaps as importantly, the simplified boundary conditions that can be established in well designed low-gravity combustion experiments. A description of the test facilities and typical experimental apparatus are provided; and conceptual plans for a Space Station Freedom capability, the Modular Combustion Facility, are described.

Sacksteder, Kurt R.↗

NASA NTRS2019

Modern Modal Testing: A Cautionary Tale

Over the past 50 years, great advances have been achieved in both analytical modal analysis (i.e. finite element models and analysis) and experimental modal analysis (i.e. modal testing) in aerospace and other fields. With the advent of more powerful computers, higher performance instrumentation and data acquisition systems, and powerful linear modal extraction tools, analysts and test engineers have a breadth and depth of technical resources only dreamed of by our predecessors. However, some observed recent trends indicate that hard lessons learned are being forgotten or ignored, and possibly fundamental concepts are not being understood. These trends have the potential of leading to the degradation of the quality of and confidence in both analytical and test results. These trends are a making of our own doing, and directly related to having ever more powerful computers, programmatic budgetary pressures to limit analysis and testing, and technical capital loss due to the retirement of the senior component of a bimodal workforce. This paper endeavors to highlight some of the most important lessons learned, common pitfalls to hopefully avoid, and potential steps that may be taken to help reverse this trend.

bimodal workforce↗

NASA NTRS2006

On-Orbit Testing of Materials and Processes

The Pore Formation and Mobility Investigation (PFMI) and the In-Space Soldering Investigation (ISSI) were conducted aboard the International Space Station (ISS) with the intent of promoting our understanding of materials processing in a low-gravity environment. The numerous experiments were conducted by telescience with the results evaluated by real time video and subsequently returned tapes and samples. In addition to discussing the experimental results and analysis the presentation will include an account of the ISS facilities (Microgravity Science Glovebox and Maintenance Work Area) used as well as some lessons-learned comments.

Grugel, R. N.↗

NASA NTRS2011

Imbalanced Learning for Functional State Assessment

This paper presents results of several imbalanced learning techniques applied to operator functional state assessment where the data is highly imbalanced, i.e., some function states (majority classes) have much more training samples than other states (minority classes). Conventional machine learning techniques usually tend to classify all data samples into majority classes and perform poorly for minority classes. In this study, we implemented five imbalanced learning techniques, including random undersampling, random over-sampling, synthetic minority over-sampling technique (SMOTE), borderline-SMOTE and adaptive synthetic sampling (ADASYN) to solve this problem. Experimental results on a benchmark driving lest dataset show thai accuracies for minority classes could be improved dramatically with a cost of slight performance degradations for majority classes,

Li, Feng↗

NASA NTRS2014

Advanced Clothing Studies

All human space missions require significant logistical mass and volume that add an unprecedented burden on longduration missions beyond low-Earth orbit. For these missions with limited cleaning resources, a new wardrobe must be developed to reduce this logistical burden by reducing clothing mass and extending clothing wear. The present studies have been undertaken, for the first time, to measure length of wear and to assess the acceptance of such extended wear. Garments in these studies are commercially available exercise T-shirts and shorts, routine-wear T-shirts, and longsleeved pullover shirts. Fabric composition (cotton, polyester, light-weight, superfine Merino wool, modacrylic, cotton/rayon, polyester/Cocona, modacrylic/Xstatic, modacrylic/rayon, modacrylic/lyocell/aramid), construction (open knit, tight knit, open weave, tight weave), and finishing treatment (none, quaternary ammonium salt) are the independent variables. Eleven studies are reported here: five studies of exercise T-shirts, three of exercise shorts, two of routine wear Tshirts, and one of shirts used as sleep-wear. All studies are conducted in a climate-controlled environment, similar to a space vehicle's. For exercise clothing, study participants wear the garments during aerobic exercise. For routine wear clothing, study participants wear the T-shirts daily in an office or laboratory. Daily questionnaires collected data on ordinal preferences of nine sensory elements and on reason for retiring a used garment. Study 1 compares knitted cotton, polyester, and Merino exercise T-shirts (61 participants), study 2, knitted polyester, modacrylic, and polyester/Cocona exercise T-shirts (40 participants), study 3, cotton and polyester exercise shorts, knitted and woven (70 participants), all three using factorial experimental designs with and without a finishing treatment, conducted at the Johnson Space Center, sharing study participants. Study 4 compares knitted polyester and ZQ Merino exercise T-shirts, study 5, knitted ZQ Merino and modacrylic routine-wear T-shirts, with study 6 using only knitted polyester exercise shorts. No finishing treatment is used. Studies 4 and 5 use cross-over experimental designs, and all three studies were conducted aboard the ISS with six crew. Studies 4 and 6 were repeated on the ground with the same participants to learn if perception was affected microgravity. Study 7 is a longer-term, single-blind panel study of knitted routine-wear undershirts with at least 12 participants to assess tolerance to Merino by comparing it with a cotton/rayon blends, using a cross-over design, eliminating carryover effects with wash-out periods between shirts.

Orndoff, Evelyne↗

NASA NTRSDate not supplied

High-Fidelity Simulations of HyMETS Arc-Jet Flows for PICA-N Modeling

Arc-jet testing is a fundamental tool in the screening of thermal protection systems under atmospheric entry conditions. In this work, high-fidelity computational fluid dynamics simulations coupled with machine learning methods for the Hypersonic Materials Environmental Test System arc-jet facility have been carried out. This effort improves the MEDLI-2 data reconstruction fidelity by understanding the impact of the NuSil coating over the PICA thermocouple plugs. Thermochemical non-equilibrium models are employed to simulate the flows inside the arc-jet nozzle and chamber and machine learning techniques are used to calibrate the arc-jet inflow conditions. The material response is simulated with the recession and in-depth numerical results compared to experimental measurements.

STMD↗

NASA NTRS1986

Design concepts for bioreactors in space

Microbial food sources are becoming viable and more efficient alternatives to conventional food sources especially in the context of Closed Ecological Life Support Systems (CELSS) in space habitats. Since bioreactor designs for terrestrial operation will not readily apply to conditions of microgravity, there is an urgent need to learn about the differences. These differences cannot be easily estimated due to the complex nature of the mass transport and mixing mechanisms in fermenters. Therefore, a systematic and expeditious experimental program must be undertaken to obtain the engineering data necessary to lay down the foundations of designing bioreactors for microgravity. Two bioreactor design concepts presented represent two dissimilar approaches to grappling with the absence of gravity in space habitats and deserve to be tested for adoption as important components of the life support function aboard spacecrafts, space stations and other extra-terrestrial habitats.

Seshan, P. K.↗

NASA NTRS2000

Intelligence Applied to Air Vehicles

The exponential growth in information technology has provided the potential for air vehicle capabilities that were previously unavailable to mission and vehicle designers. The increasing capabilities of computer hardware and software, including new developments such as neural networks, provide a new balance of work between humans and machines. This paper will describe several NASA projects, and review results and conclusions from ground and flight investigations where vehicle intelligence was developed and applied to aeronautical and space systems. In the first example, flight results from a neural network flight control demonstration will be reviewed. Using, a highly-modified F-15 aircraft, a NASA/Dryden experimental flight test program has demonstrated how the neural network software can correctly identify and respond to changes in aircraft stability and control characteristics. Using its on-line learning capability, the neural net software would identify that something in the vehicle has changed, then reconfigure the flight control computer system to adapt to those changes. The results of the Remote Agent software project will be presented. This capability will reduce the cost of future spacecraft operations as computers become "thinking" partners along with humans. In addition, the paper will describe the objectives and plans for the autonomous airplane program and the autonomous rotorcraft project. Technologies will also be developed.

Rosen, Robert↗

NASA NTRS1995

Earth-space links and fade-duration statistics

In recent years, fade-duration statistics have been the subject of several experimental investigations. A good knowledge of the fade-duration distribution is important for the assessment of a satellite communication system's channel dynamics: What is a typical link outage duration? How often do link outages exceeding a given duration occur? Unfortunately there is yet no model that can universally answer the above questions. The available field measurements mainly come from temperate climatic zones and only from a few sites. Furthermore, the available statistics are also limited in the choice of frequency and path elevation angle. Yet, much can be learned from the available information. For example, we now know that the fade-duration distribution is approximately lognormal. Under certain conditions, we can even determine the median and other percentiles of the distribution. This paper reviews the available data obtained by several experimenters in different parts of the world. Areas of emphasis are mobile and fixed satellite links. Fades in mobile links are due to roadside-tree shadowing, whereas fades in fixed links are due to rain attenuation.

Davarian, Faramaz↗

NASA NTRS1996

Earth-Space Links and Fade-Duration Statistics

In recent years, fade-duration statistics have been the subject of several experimental investigations. A good knowledge of the fade-duration distribution is important for the assessment of a satellite communication system's channel dynamics: What is a typical link outage duration? How often do link outages exceeding a given duration occur? Unfortunately there is yet no model that can universally answer the above questions. The available field measurements mainly come from temperate climatic zones and only from a few sites. Furthermore, the available statistics are also limited in the choice of frequency and path elevation angle. Yet, much can be learned from the available information. For example, we now know that the fade-duration distribution is approximately lognormal. Under certain conditions, we can even determine the median and other percentiles of the distribution. This paper reviews the available data obtained by several experimenters in different parts of the world. Areas of emphasis are mobile and fixed satellite links. Fades in mobile links are due to roadside-tree shadowing, whereas fades in fixed links are due to rain attenuation.

Davarian, Faramaz↗

NASA NTRS1995

Emergence of Relations and the Essence of Learning: A Review of Sidman's Equivalence Relations and Behavior: A Research Story

Sidman addresses two very important questions in Equivalence Relations and Behavior: A Research Story: What are the bases of behavioral competence? And how do units of learning become related? The book recounts the story of how an understanding of emergent relations and competencies was achieved through studies in his teaching-research program with mentally retarded subjects. Although children normally accrue vast networks of relations between stimuli and events, those with mental retardation typically do not. Consequently, by learning how to establish those networks, Sidman and his students contribute richly both to the cultivation of competencies by their subjects and, more generally, to an understanding of real-world human behavior. The basic equivalence paradigm affords the subject feedback and reinforcement for very specific choices during training, but the test is not for those choices! Rather, tests for equivalence look for new choices, ones seemingly quite foreign to the training regimen. The tests for equivalence relations entail presentations of stimuli that were the options for conditional choice during reinforced training. In tests of equivalence, correct choices are novel; hence, they have never been reinforced during training. The study of equivalence relations can encourage the emergence of new perspectives that are more symbiotic than competitive. In full acknowledgment of the important role and contributions made by those who identify themselves as experimental analysts of behavior, it is timely that rapprochements be worked toward, as indeed they are, to meld that perspective with others of our time. Both our research methods and our expectations about the nature of the learning process and the abilities of our subjects can delimit what they might learn and what we, in turn, learn about their learning. The text will be of great value for instruction at the upper-division and graduate levels. Its impact will be substantial, for it defines an important advance in our efforts to understand the richness of behavior in both humans and nonhuman animals. Although not presented to that end, the book might also serve to bridge communications with other groups of animal researchers whose interests lie more in a comparative or ethological framework.

Rumbaugh, Duane M.↗

NASA NTRSDate not supplied

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗

NASA NTRSDate not supplied

Hybrid Approaches to Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Systems Health Management↗

NASA NTRS2001

National Transonic Facility Wall Pressure Calibration Using Modern Design of Experiments (Invited)

The Modern Design of Experiments (MDOE) has been applied to wind tunnel testing at NASA Langley Research Center for several years. At Langley, MDOE has proven to be a useful and robust approach to aerodynamic testing that yields significant reductions in the cost and duration of experiments while still providing for the highest quality research results. This paper extends its application to include empty tunnel wall pressure calibrations. These calibrations are performed in support of wall interference corrections. This paper will present the experimental objectives, and the theoretical design process. To validate the tunnel-empty-calibration experiment design, preliminary response surface models calculated from previously acquired data are also presented. Finally, lessons learned and future wall interference applications of MDOE are discussed.

Underwood, Pamela J.↗