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At least 199 records · Page 11

The negative effect of hypokinesia involving injury and preventive measures

The optimum length of bed rest for athletes suffering from broken bones is considered. Negative effects of hypokinesia induced by bed rest include general weakness and deconditioning of the muscles as well as sleeplessness, headaches, muscle pain, constipation, unstable pulse and arterial pressure, and changes in reflexes. This is considered to be the result of a vegetative dysfunction induced by the decreased flow of nerve impulses and a decrease in interoceptive and exteroceptive signals. The briefest possible period of bed rest, followed by an increase in motor activity, the prescription of a large quantity of LFK, and an active program of physical therapy are recommended. The symptomology associated with hypokinesia disappears after one month of free motor activity.

Izakson, K. A.↗

An approach for relating the results of quantitative nondestructive evaluation to intrinsic properties of high-performance materials

One of the most difficult problems the manufacturing community has faced during recent years has been to accurately assess the physical state of anisotropic high-performance materials by nondestructive means. In order to advance the design of ultrasonic nondestructive testing systems, a more fundamental understanding of how ultrasonic waves travel and interact within the anisotropic material is needed. The relationship between the ultrasonic and engineering parameters needs to be explored to understand their mutual dependence. One common denominator is provided by the elastic constants. The preparation of specific graphite/epoxy samples to be used in the experimental investigation of the anisotropic properties (through the measurement of the elastic stiffness constants) is discussed. Accurate measurements of these constants will depend upon knowledge of refraction effects as well as the direction of group velocity propagation. The continuing effort for the development of improved visualization techniques for physical parameters is discussed. Group velocity images are presented and discussed. In order to fully understand the relationship between the ultrasonic and the common engineering parameters, the physical interpretation of the linear elastic coefficients (the quantities that relate applied stresses to resulting strains) are discussed. This discussion builds a more intuitional understanding of how the ultrasonic parameters are related to the traditional engineering parameters.

Miller, James G.↗

Spectral diagnostics from X-ray to radio wavelengths

A spectral diagnostic is defined as an observable spectral quantity that can be used to measure a physical parameter characterizing the observed plasma. The first step in establishing a spectral line is to determine whether the upper state of the transition is excited primarily by collisions (typically by electrons), by a radiative process, or by recombination (either direct or cascade). The ultraviolet portion of the spectrum is emphasized as it is well studied, the background photospheric continuum is weak for cool stars, and the spectrum consists of an interesting mix of lines formed by all three mechanisms.

Linsky, Jeffrey L.↗

Theory of Fiber Optical Bragg Grating: Revisited

The reflected signature of an optical fiber Bragg grating is analyzed using the transfer function method. This approach is capable to cast all relevant quantities into proper places and provides a better physical understanding. The relationship between reflected signal, number of periods, index of refraction, and reflected wave phase is elucidated. The condition for which the maximum reflectivity is achieved is fully examined. We also have derived an expression to predict the reflectivity minima accurately when the reflected wave is detuned. Furthermore, using the segmented potential approach, this model can handle arbitrary index of refraction profiles and compare the strength of optical reflectivity of different profiles. The condition of a non-uniform grating is also addressed.

Tai, H.↗

The M-dwarf Ultraviolet Spectroscopic Sample. I. Determining Stellar Parameters for Field Stars

Accurate stellar properties are essential for precise stellar astrophysics and exoplanetary science. In the M-dwarf regime, much effort has gone into defining empirical relations that can use readily accessible observables to assess physical stellar properties. Often, these relations for the quantity of interest are cast as a nonlinear function of available data; in Bayesian modeling, however, the reverse is needed. In this article, we introduce a new Bayesian framework to self-consistently and simultaneously apply multiple empirical calibrations to fully characterize the mass, luminosity, radius, and effective temperature of a field age M-dwarf. This framework includes a new M-dwarf mass–radius relation with a scatter of 3.1% at fixed mass. We further introduce the M-dwarf Ultraviolet Spectroscopic Sample (MUSS), and apply our methodology to provide consistent stellar parameters for these nearby low-mass stars, selected as having available spectroscopic data in the ultraviolet. These targets are of interest largely as either exoplanet hosts or benchmarks in multiwavelength stellar activity. We use the field MUSS stars to define a low-mass main sequence in the solar neighborhood through Gaussian Process (GP) regression. These results enable us to empirically measure a feature in the GP derivative at M ⊙ that indicates where the MUSS transitions from fully to partly convective interiors.

J. Sebastian Pineda↗

On the Integration of Loudness Over Time for the Prediction of Single-Event Annoyance

Loudness is the quality of human perception that is most related to acoustic intensity and energy, however there is no agreed-upon way of integrating loudness over time for the prediction of noise-induced annoyance. Most noise metrics used today for aircraft certification and regulation employ the “Equal-Energy Hypothesis” (EEH) and sum the acoustical energy of one or more noise events over time to create a single metric value that represents the entire exposure. Using the EEH creates a natural tradeoff between the peak energy and the duration of a single noise event, the “hypothesis” being that this tradeoff optimally predicts annoyance in a wide variety of situations. This work proposes a strategy for integrating a loudness-like time series which is flexible in two ways: First, it includes a parameter b ∈ [0,1]. When b = 0, the metric will return the peak of the time series. At b = .5, the metric will behave in accordance with the EEH. At b = 1, the metric will penalize the duration of the sound more than the EEH would. Second, transformations are given so that the strategy can be computed from, or generate quantities in units analogous to, decibels (or phon), physical units (acoustic pressure/power), or perceptually-scaled units (sone). This approach is demonstrated on a dataset of annoyance responses to single events of UAV and road vehicle noise that is fit with an augmented linear regression. Analyses based on this integration of A-weighted level and the output of the “Zwicker” loudness model yield similar results: that subjects may have been slightly more sensitive to the durations of the events than the EEH would suppose, but that the EEH cannot be disproven using these data. The time-integrated metrics outperform both time-averaged and centile-based metrics.

Psychoacoustics↗

On the Integration of Loudness Over Time for the Prediction of Single-Event Annoyance

Loudness is the quality of human perception that is most related to acoustic intensity and energy, however there is no agreed-upon way of integrating loudness over time for the prediction of noise-induced annoyance. Most noise metrics used today for aircraft certification and regulation employ the “Equal-Energy Hypothesis” (EEH) and sum the acoustical energy of one or more noise events over time to create a single metric value that represents the entire exposure. Using the EEH creates a natural tradeoff between the peak energy and the duration of a single noise event, the “hypothesis” being that this tradeoff optimally predicts annoyance in a wide variety of situations. This work proposes a strategy for integrating a loudness-like time series which is flexible in two ways: First, it includes a parameter b ∈ [0,1]. When b = 0, the metric will return the peak of the time series. At b = .5, the metric will behave in accordance with the EEH. At b = 1, the metric will penalize the duration of the sound more than the EEH would. Second, transformations are given so that the strategy can be computed from, or generate quantities in units analogous to, decibels (or phon), physical units (acoustic pressure/power), or perceptually-scaled units (sone). This approach is demonstrated on a dataset of annoyance responses to single events of UAV and road vehicle noise that is fit with an augmented linear regression. Analyses based on this integration of A-weighted level and the output of the “Zwicker” loudness model yield similar results: that subjects may have been slightly more sensitive to the durations of the events than the EEH would suppose, but that the EEH cannot be disproven using these data. The time-integrated metrics outperform both time-averaged and centile-based metrics.

Psychoacoustics↗

Experimental and Theoretical Study of Propeller Spinner/Shank Interference

A fundamental experimental and theoretical investigation into the aerodynamic interference associated with propeller spinner and shank regions was conducted. The research program involved a theoretical assessment of solutions previously proposed, followed by a systematic experimental study to supplement the existing data base. As a result, a refined computational procedure was established for prediction of interference effects in terms of interference drag and resolved into propeller thrust and torque components. These quantities were examined with attention to engineering parameters such as two spinner finess ratios, three blade shank forms, and two/three/four/six/eight blades. Consideration of the physics of the phenomena aided in the logical deduction of two individual interference quantities (cascade effects and spinner/shank juncture interference). These interference effects were semi-empirically modeled using existing theories and placed into a compatible form with an existing propeller performance scheme which provided the basis for examples of application.

Cornell, C. C.↗

Hydrophobicity of Cryogenic Fluids for Fuel Transfer in Space Applicaitons

Introduction Hydrophobicity is the tendency of a fluid to repel another material or fluid. Hydrophobiciy can be measured through the wetting angle of the fluid on the surface of the other material. The greater the wetting angle, the more hydrophobic the surface is against the fluid. Hydrophobicity properties can be caused by one of two means, either through physical properties or chemical properties [\citenum{NARBUTT2020121}]. Physical hydrophobicity due to the surface of a solid creating surface roughness/patterning, minimizing the contact area between the fluid and the surface. This can be observed throughout nature, such as the surface of lotus leaves or butterfly wings. This physical property can be induced on a variety of surfaces, namely through laser etching, allowing a surface to be finely lineated to imitate these natural surfaces while controlling quantity, depth, and patterns of the etching on the surface [\citenum{10.1063/1.4905616}]. Physical hydrophobicity is therefore dependent on several variables, including the surface that the fluid is on and properties of the fluid itself, such as density and surface tension, both of which are dependent on temperature and/or pressure. Chemical hydrophobicity [\citenum{MadeiraHydrophobocicicici}] is due to the inherent chemical properties of the materials being used. This is most commonly due to the molecular structures changing the polarity of the materials. Depending on a nonpolar material will repel a polar material, proving to be hydrophobic, conversely if the polarity of the materials is the same (polar – polar, nonpolar – nonpolar), they will attract each other. Cryogenics refers to the behavior of materials at very low temperatures (<\ang{-100} C) [\citenum{ZOHURI20181}]. In space applications many things are inherently cryogenic, therefore this is an important field. There has been little research in how hydrophobicity changes at cryogenic temperatures. Cryogenic fluids are commonly used as fuels for spacecraft, therefore, integrating a hydrophobic surface can increase the transfer rate of the fuel. To test this, several experiments were set up to determine the hydrophobic properties of cryogenic fluids, including nitrogen (LN2), argon (LAr), oxygen (LOx), hydrogen (LH2), and methane (CH4), at cryogenic temperatures. Etched Wafer Testing A silicon wafer cut from a crystal of silicon [100] was used to model the potential hydrophobicity of various cryogenic fluids. Silicon [100] references to the crystallographic orientation of the silicon crystals in the wafer. These wafers were then laser etched to create a surface that is more likely to be hydrophobic. To test the hydrophobicity of the wafers at cryogenic temperatures, the temperatures of the wafers must be reduced to the same temperature as the cryogenic fluid being used to prevent rapid boil-off. To achieve this a double-walled vacuum insulated glass chamber was utilized. The chamber is open, with a double-walled glass that can be placed in a vacuum to remove condensation from the outside to allow easier viewing of the experiment. Furthermore, the silicon wafer's temperature must be lowered to the temperature of LN2, as well as maintain the temperature throughout the experiment. To achieve this a piece of 6061 aluminum was used, creating a stand-off for the wafer and it would allow for the insulation of the temperature of the wafers. The container was then filled with LN2 and once the LN2 stabilized the vaporization and the levels of LN2 dropped under the height of the wafer, the wafer was then allowed to air dry. Once the wafer was dry from the LN2, drops of LN2 were placed on the surface of the wafer for observation. During the first trial, the LN2 that was dropped on the surface displayed nonhydrophobic behaviors, spreading out along the surface, with a minimal wetting angle (too small to be measured). This process was repeated for liquid argon. Further testing with other cryogenic liquids will require different testing apparatuses due to being more volatile. Furthermore, several papers [\citenum{voltvolt7}] have suggested that running a voltage can induce a hydrophobic effect throughout a surface, further testing will include a voltage (constant and oscillating) to determine if voltage influences inducing hydrophobicity at cryogenic temperatures. Chemical Testing Coating the interior walls of the fuel tanks and fuel lines can successfully create a hydrophobic surface. The inherent problem is finding a material that can be used to coat the surface, furthermore, at these temperatures, the coating will remain solid, which could pose issues in maintaining the hydrophobic properties. To test this water (polar) is hydrophobic against oils and fats (nonpolar), therefore the same experiment as the etched wafer testing was conducted to determine if the hydrophobic properties will persist as the nonpolar material remains solid and the polar material remains a fluid. The water remained hydrophobic, allowing testing can expand to the cryogenic fluids. However, another hurdle is faced in finding a chemically opposite material to the cryogenic fluids being tested. As many of the cryogenic fluids being tested are diatomic, they are inherently nonpolar, therefore, the material used for the hydrophobic coating must be polar. Polar greases and lubricants are difficult to come by, however, lithium stearate, appears to be a potential candidate for creating a coated hydrophobic surface for cryogenic fluids at cryogenic temperatures.

Cryogenics↗

Mixed boundary value problems in mechanics

Certain boundary value problems were studied over a domain D which may contain the point at infinity and may be multiply connected. Contours forming the boundary are assumed to consist of piecewise smooth arcs. Mixed boundary value problems are those with points of flux singularity on the boundary; these are points on the surface, either side of which at least one of the differential operator has different behavior. The physical system was considered to be described by two quantities, the potential and the flux type quantities. Some of the examples that were illustrated included problems in potential theory and elasticity.

Erdogan, F.↗

Stability of water on the Galilean satellites

The selective loss of water from Io under currently prevailing physical conditions was studied to determine whether a large quantity of water can be lost from the satellite over the lifetime of the solar system. Loss processes considered include: thermal escape, photolysis, sputtering, and gas-phase charged particle interactions.

Pilcher, C. B.↗

Finite element analysis of time-independent superconductivity

The development of electromagnetic (EM) finite elements based upon a generalized four-potential variational principle is presented. The use of the four-potential variational principle allows for downstream coupling of EM fields with the thermal, mechanical, and quantum effects exhibited by superconducting materials. The use of variational methods to model an EM system allows for a greater range of applications than just the superconducting problem. The four-potential variational principle can be used to solve a broader range of EM problems than any of the currently available formulations. It also reduces the number of independent variables from six to four while easily dealing with conductor/insulator interfaces. This methodology was applied to a range of EM field problems. Results from all these problems predict EM quantities exceptionally well and are consistent with the expected physical behavior.

Schuler, James J.↗

Facility design consideration for continuous mix production of class 1.3 propellant

In November of 1989, NASA awarded the Advanced Solid Rocket Motor (ASRM) contract to Lockheed Missiles and Space Company (LMSC) for production of advanced solid rocket motors using the continuous mix process. Aerojet ASRM division (AAD) was selected as the facility operator and RUST International Corporation provided the engineering, procurement, and construction management services. The continuous mix process mandates that the mix and cast facilities be 'close-coupled' along with the premix facilities, creating unique and challenging requirements for the facility designer. The classical approach to handling energetic materials-division into manageable quantities, segregation, and isolation-was not available due to these process requirements and quantities involved. This paper provides a description of the physical facilities, the continuous mix process, and discusses the monitoring and detection techniques used to mitigate hazards and prevent an incident.

Williamson, K. L.↗

Leaf Area Influence on Surface Layer in a Deciduous Forest: Site Description - Part I

A study over a deciduous forest located in middle Massachusetts (USA) has been performed to examine the role of leaves in the forest-atmosphere interaction. Due to the seasonal presence of leaves, a deciduous forest is a 'good laboratory' to study this interaction. In this first part, a description of a 30 m micrometeorological tower as well a qualitative description of some meteorological parameters are presented. The presence of leaves affects the forest in several ways. There is a decrease of upward PAR (Photosynthetically Active Radiation) due to absorption of visible light in the canopy. Water vapor concentration increases, and the CO2 concentration decreases in the surface layer as the canopy starts to be foliated. The physical presence of the leaves is felt in other quantities such as the global albedo and the subcanopy environment.

Sakai, Ricardo K.↗

Application of Machine Learning Techniques to Aviation Operations: Promises and Challenges

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. This paper reviews the current-state-of-the art in applying MLT to aviation operations, its promises and challenges. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This paper compares the methodology used in and issues to be addressed in applying either model-driven or data-driven methods. Some aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for data-driven methods. The application of MLT to aviation operations falls into three categories: (a) based on the lack of a physics-based model, MLT is the favored approach, (b) marginal difference between regression methods using physics-based models and MLT and (c) better results using a blend of physics-based methods combined with MLT. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗

Observations on the Application of Machine Learning Techniques to Aviation Operations

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues are illustrated by a detailed example and summary of current research in the area. The application of MLT to aviation operations falls into two categories: (a) based on the lack of a physics-based model, MLT is the favored approach and (b) marginal difference between regression methods using physics-based models and MLT. Further research is needed in the selection of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗

Application of Machine Learning Techniques to Aviation Operations: A Case Study

There is an increasing interest in applying methods based on Machine Learning Techniques (MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues are illustrated by a detailed example and summary of current research in the area. The application of MLT to aviation operations falls into two categories 58; (a) based on the lack of a physics-based model, MLT is the favored approach and (b) marginal difference between regression methods using physics-based models and MLT. Further research is needed in the selection of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗

Application of Machine Learning Techniques to Aviation Operations: NASA Case Studies

There is an increasing interest in applying methods based on Machine Learning Techniques(MLT) to problems in aviation operations. The current interest is based on developments in Cloud Computing, the availability of open software and the success of MLT in automation, consumer behavior and finance involving large database. Historically aviation operations have been analyzed using physics-based models and provide information for making operational decisions. This talk describes issues to be addressed in applying either model-driven or data-driven methods. Aviation operations involving many decision makers, multiple objectives, poor or unavailable physics-based models and a rich historical database are prime candidates for analysis using data-driven methods. The issues relating to data, feature selection and validation of the models are illustrated by examining case studies of the application of MLT to problems in air traffic management at NASA. Further research is needed in the application of MLT to critical aviation operations. As always, the best approach depends on the task, the physical understanding of the problem and the quality and quantity of the available data.

Sridhar, Banavar↗