Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “qualitative methods”

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.

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

At least 1,207 records · Page 67

A Comparison of Void-finding Algorithms Using Crossing Numbers

We study how well void-finding algorithms identify cosmic void regions and whether we can quantitatively and qualitatively compare the voids they find with dynamical information from the underlying matter distribution. Using the ORIGAMI algorithm to determine the number of dimensions along which dark matter particles have undergone shell crossing (crossing number) in N-body simulations from the AbacusSummit simulation suite, we identify dark matter particles that have undergone no shell crossing as belonging to voids. We then find voids in the corresponding halo distribution using two different void-finding algorithms: VoidFinder and V 2 , a ZOBOV-based algorithm. The resulting void catalogs are compared to the distribution of dark matter particles to examine how their crossing numbers depend on void proximity. While both algorithms' voids have a similar distribution of crossing numbers near their centers, we find that beyond 0.25 times the effective void radius, voids found by VoidFinder exhibit a stronger preference for particles with low crossing numbers than those found by V 2 . We examine two possible methods of mitigating this difference in efficacy between the algorithms. While we are able to partially mitigate the ineffectiveness of V 2 by using the distance from the void edge as a measure of centrality, we conclude that VoidFinder more reliably identifies dynamically distinct regions of low crossing number.

79 ASTRONOMY AND ASTROPHYSICS↗

Predictive Modeling to Assess and Address Challenges and Limitations Associated with Clinical Care and Decision Support in Deep Space

Probabilistic risk assessment (PRA) is a method for assessing and integrating the risk of failure in a multivariate system. While it is often applied by engineers designing complex machines, it could also be applied to humans to assess the probability of a health “failure” treating diseases as the multiple “variables” and the human as the “complex machine.” The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) was developed to apply PRA to assess medical risk for exploration spaceflight and inform the design of medical systems for space flight. The NASA engineering community utilizes event-driven and fault tree probabilistic techniques to classify risk in the space flight environment by leveraging the inherent knowledge of complex space flight system design and testing to quantify risk. However, in harmonizing the risk of human space flight, answering the question of “How do we balance astronaut health, performance and resource risks with other engineering risks on exploration space missions?” remains a profoundly challenging and largely qualitative practice. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is one aspect of the Human Research Program’s efforts to represent space fight human health and performance risks quantitatively.

L Mcintyre↗

Portable fiber optic sensor for rare earth elements and other critical metals using photoluminescence methods

Rare earth elements and other metals are vital to a range of technologies that are used in the energy and defense sectors. However, monopolistic market conditions have caused significant concern over the stability of the critical metal supply chain, and this has spurred extensive efforts in many nations to produce these metals domestically, both from conventional sources such as mining and well as from unconventional sources such as coal and its utilization byproducts. Slow and expensive characterization methods pose a significant barrier for both metals prospecting and process monitoring. A promising solution to this challenge is the development of highly sensitive luminescent sensors for metals, which can offer low costs, portability, and sensitivity. Anionic zinc adeninate metal-organic frameworks (BioMOFs) are known to distinguishing and detect part-per-billion levels of terbium, europium, samarium, and dysprosium in water by sensitizing the narrow, element-specific emission bands from these lanthanides. Here, a BioMOF material is immobilized onto a large diameter, solarization-resistant fiber optic tip integrated with a portable, low-cost spectrometer for rare earth element sensing. Immobilizing the sensing material on fiber instead of dispersing the sensing material in solution offers several advantages: it facilitates solvent removal, which enhances luminescent signal from the sensitized lanthanides, and it also allows the BioMOF to be recycled for multiple uses. The sensing system was deployed on a simulated process stream and exhibited qualitative agreement with inductively-coupled plasma mass spectrometry for terbium and europium detection, highlighting the potential for the sensing system to be deployed for real-world applications. By using different sensing materials, the same portable sensor may be deployed to detect other energy relevant metals such as cobalt, providing a cost-effective and sensitive platform for critical metal characterization.

Crawford, Scott↗

Simulating Space Capsule Water Landing with Explicit Finite Element Method

A study of using an explicit nonlinear dynamic finite element code for simulating the water landing of a space capsule was performed. The finite element model contains Lagrangian shell elements for the space capsule and Eulerian solid elements for the water and air. An Arbitrary Lagrangian Eulerian (ALE) solver and a penalty coupling method were used for predicting the fluid and structure interaction forces. The space capsule was first assumed to be rigid, so the numerical results could be correlated with closed form solutions. The water and air meshes were continuously refined until the solution was converged. The converged maximum deceleration predicted is bounded by the classical von Karman and Wagner solutions and is considered to be an adequate solution. The refined water and air meshes were then used in the models for simulating the water landing of a capsule model that has a flexible bottom. For small pitch angle cases, the maximum deceleration from the flexible capsule model was found to be significantly greater than the maximum deceleration obtained from the corresponding rigid model. For large pitch angle cases, the difference between the maximum deceleration of the flexible model and that of its corresponding rigid model is smaller. Test data of Apollo space capsules with a flexible heat shield qualitatively support the findings presented in this paper.

Wang, John T.↗

Active and Passive Radiative Transfer Modeling of the Olympic Mountains Experiment

Sensor forward models are an important tool for interpreting remote sensing observations of geophysical phenomena. By implementing a three-dimensional framework, we can simulate and analyze observations from various sensors on disparate platforms. To demonstrate our model framework, we simulate observations from the Olympic Mountains Experiment (OLYMPEX). The use of cloud model simulations allows us to understand sensor response to cloud ice, falling snow, and other processes and features, and the application of model tools to observations allows us to quantify precipitation.MIIST 3D Forward ModelThe Multi-Instrument Inverse Solver Testbed(MIIST) uses the Atmospheric Radiative TransferSimulator (ARTS) for solving the vector radiativetransfer (RT) equation in up to three spatialdimensions within a spherical geometry• Gas absorptiono Line-by-line calculationso Fast transmittance tables• Hydrometeor scattering solverso Discrete ordinateo RT4 (Evans, 1D)o Radar Single Scattering (1D or 3D)o Monte Carlo (3D)Scattering TablesHigh-fidelity hydrometeor scatteringtables are necessary for accurateand consistent forward modeling ofmulti-frequency observations• Requires full Stokes matriceso And absorption vector• Randomly oriented particleso Discrete Dipole Approximationo Characteristic Basis Function Method(coming soon)• Horizontally-oriented plateso Invariant Imbedding T-matrix MethodCloud Resolving SimulationsCloud resolving simulations (e.g.,NU-WRF) supply output consistentwith ARTS needs• Atmospheric Informationo Temperatureo Pressure / heighto Water vapor• Hydrometeor Profileso ARTS architecture ripe for explicit binmicrophysics• Examples use Morrison 2M schemeThe Olympic Mountains Experiment (OLYMPEX)Validation for GPM of mid-latitudefrontal systems approaching nearcoastalmountains from the ocean• Large collection of ground-based andairborne sensorso Radarso Radiometerso In situ• Contemporaneous with RADEXo Two sets of radar at same frequenciesRadiometer Simulation (3 km NUWRF, 20151203, 15:00)2018.12.14 7Simulate 166 GHz polarizationdifference• Corresponds to the presence of aligned icecrystals• Look at trends for both simulations andobservations• Simulations can tolerate lower resolutiono Larger domainSimulations from Observations: OLYMPEXSimulate sensor response usinggeophysical retrievals as input• Single frequency radar retrievals• Multiple scattering enhancementapparent at W band• Spatially dependent phenomenonModeling Application: 1D Retrievals03 December 2015• DC-8 and ER-2 flightso Focus on APR-3 (DC-8)• Citationo Stacked microphysics legso Qualitative comparisonso Range of frozen habitso Presence of supercooledliquid cloudsResults• Retrievals match probeso Good qualitative match• Bands of increasedreflectivity correspond tolarge Dm and highaggregate fraction• Significant amounts ofsupercooled liquid water

Adams, Ian S.↗

The Spacecraft Materials Selector: An Artificial Intelligence System for Preliminary Design Trade Studies, Materials Assessments, and Estimates of Environments Present

Institutions need ways to retain valuable information even as experienced individuals leave an organization. Modern electronic systems have enough capacity to retain large quantities of information that can mitigate the loss of experience. Performance information for long-term space applications is relatively scarce and specific information (typically held by a few individuals within a single project) is often rather narrowly distributed. Spacecraft operate under severe conditions and the consequences of hardware and/or system failures, in terms of cost, loss of information, and time required to replace the loss, are extreme. These risk factors place a premium on appropriate choice of materials and components for space applications. An expert system is a very cost-effective method for sharing valuable and scarce information about spacecraft performance. Boeing has an artificial intelligence software package, called the Boeing Expert System Tool (BEST), to construct and operate knowledge bases to selectively recall and distribute information about specific subjects. A specific knowledge base to evaluate the on-orbit performance of selected materials on spacecraft has been developed under contract to the NASA SEE program. The performance capabilities of the Spacecraft Materials Selector (SMS) knowledge base are described. The knowledge base is a backward-chaining, rule-based system. The user answers a sequence of questions, and the expert system provides estimates of optical and mechanical performance of selected materials under specific environmental conditions. The initial operating capability of the system will include data for Kapton, silverized Teflon, selected paints, silicone-based materials, and certain metals. For situations where a mission profile (launch date, orbital parameters, mission duration, spacecraft orientation) is not precisely defined, the knowledge base still attempts to provide qualitative observations about materials performance and likely exposures. Prior to the NASA contract, a knowledge base, the Spacecraft Environments Assistant (SEA,) was initially developed by Boeing to estimate the environmental factors important for a specific spacecraft mission profile. The NASA SEE program has funded specific enhancements to the capability of this knowledge base. The SEA qualitatively identifies over 25 environmental factors that may influence the performance of a spacecraft during its operational lifetime. For cases where sufficiently detailed answers are provided to questions asked by the knowledge base, atomic oxygen fluence levels, proton and/or electron fluence and dose levels, and solar exposure hours are calculated. The SMS knowledge base incorporates the previously developed SEA knowledge base. A case history for previous flight experiment will be shown as an example, and capabilities and limitations of the system will be discussed.

Pippin, H. G.↗

Slosh-Induced Ullage Collapse Validation by Computational Fluid Dynamics and Application to In-space Propellant Dynamics

Ullage collapse predictions made using Computational Fluid Dynamics (CFD) were validated then made for an in-space cryogenic propellant unsettling application. Ullage collapse is the decrease in propellant tank pressure due to cooling of the ullage gas, which can be significant for cryogenic propulsion systems. Vehicles may be developed that are robust to temperature and pressure changes caused by heat leaks, e.g., propellant tanks with high maximum operation pressures, technologies yielding active thermal conditioning, and systems with ample pressurant for conditioning. These methods are robust because additional mass, cost, and complexity are used to address cryogenic fluid management (CFM). As vehicles are optimized for increased payload capacity, tracking of events such as ullage collapse and self-pressurization in tanks will become increasingly important for propellant inventory calculations. Some ullage collapse events can be studied through ground experimentation, but propellant unsettling in and around in-space coast mission phases must be studied in the absence of an acceleration field. Computational Fluid Dynamics is a powerful tool to address this need, enabling prediction of complex physics prior to flight. Validation of the chosen CFD tool and modeling methodology was done using data from a previously conducted subscale slosh-induced ullage collapse ground test performed in part by the Japan Aerospace Exploration Agency (JAXA). A small tank was partially filled with liquid nitrogen and pressurized with gaseous nitrogen at various temperatures. The tank was oscillated laterally to induce high amplitude slosh dynamics resulting in wave breakup. Successful qualitative validation of slosh wave dynamics and quantitative validation of ullage collapse promoted confidence in extending ullage collapse predictions to a flight application. Mechanisms of ullage collapse caused by main engine cutoff while in-space were identified. Both slosh dynamics leading to engine shutdown and body dynamics following shutdown were shown to contribute to propellant unsettling and ullage collapse.

J M Brodnick↗

Natural frequency of uniform and optimized tetrahedral truss platforms

Qualitative and quantitative estimates for the fundamental frequency of uniform and optimized tetrahedral truss platforms are determined. A semiempirical equation is developed for the frequency of free-free uniform trusses as a function of member material properties, truss dimensions, and parasitic (nonstructural) mass fraction Mp/Mt. Optimized trusses with frequencies approximately two times those of uniform trusses are determined by varying the cross-sectional areas of member groups. Trusses with 3 to 8 rings, no parasitic mass, and member areas up to 25 times the minimum area are optimized. Frequencies computed for ranges of both Mp/Mt and the ratio of maximum area to minimum area are normalized to the frequency of a uniform truss with no parasitic mass. The normalized frequency increases with the number of rings, and both frequency and the ratio of maximum area to minimum area decrease with increasing Mp/Mt. Frequency improvements that are achievable with a limited number of member areas are estimated for a 3-ring truss by using Taguchi methods. Joint stiffness knockdown effects are also considered. Comparison of optimized and baseline uniform truss frequencies indicates that tailoring can significantly increase structural frequency; maximum gains occur for trusses with low values of Mp/Mt. This study examines frequency trends for ranges of structural parameters and may be used as a preliminary design guide.

Wu, K. Chauncey↗

Multifractal characterizations of nonstationarity and intermittency in geophysical fields: Observed, retrieved, or simulated

Geophysical data rarely show any smoothness at any scale, and this often makes comparison with theoretical model output difficult. However, highly fluctuating signals and fractal structures are typical of open dissipative systems with nonlinear dynamics, the focus of most geophysical research. High levels of variability are excited over a large range of scales by the combined actions of external forcing and internal instability. At very small scales we expect geophysical fields to be smooth, but these are rarely resolved with available instrumentation or simulation tools; nondifferentiable and even discontinuous models are therefore in order. We need methods of statistically analyzing geophysical data, whether measured in situ, remotely sensed or even generated by a computer model, that are adapted to these characteristics. An important preliminary task is to define statistically stationary features in generally nonstationary signals. We first discuss a simple criterion for stationarity in finite data streams that exhibit power law energy spectra and then, guided by developments in turbulence studies, we advocate the use of two ways of analyzing the scale dependence of statistical information: singular measures and qth order structure functions. In nonstationary situations, the approach based on singular measures seeks power law behavior in integrals over all possible scales of a nonnegative stationary field derived from the data, leading to a characterization of the intermittency in this (gradient-related) field. In contrast, the approach based on structure functions uses the signal itself, seeking power laws for the statistical moments of absolute increments over arbitrarily large scales, leading to a characterization of the prevailing nonstationarity in both quantitative and qualitative terms. We explain graphically, step by step, both multifractal statistics which are largely complementary to each other. The geometrical manifestations of nonstationarity and intermittency, 'roughness' and 'sparseness', respectively, are illustrated and the associated analytical (differentiability and continuity) properties are discussed. As an example, the two techniques are applied to a series of recent measurements of liquid water distributions inside marine stratocumulus decks; these are found to be multifractal over scales ranging from approximately 60 m to approximately 60 km. Finally, we define the 'mean multifractal plane' and show it to be a simple yet comprehensive tool with many applications including data intercomparison, (dynamical or stochastic) model and retrieval validations.

Davis, Anthony↗

A Quantitative Risk-Benefit Analysis of Prophylactic Surgery Prior to Extended-Duration Spaceflight

INTRODUCTION: Among otherwise healthy astronauts undertaking deep space missions, the risks for acute appendicitis (AA) and cholecystitis (AC) are not zero. If these conditions were to occur during spaceflight they may require surgery for definitive care. The proposed study quantifies and compares the risks of developing de novo AA and AC in-flight to the surgical risks of prophylactic laparoscopic appendectomy (LA) and cholecystectomy (LC) using NASA's Integrated Medical Model (IMM). METHODS: The IMM is a Monte Carlo simulation that forecasts medical events during spaceflight missions and estimates the impact of these medical events on crew health. In this study, four Design Reference Missions (DRMs) were created to assess the probability of an astronaut developing in-flight small-bowel obstruction (SBO) following prophylactic 1) LA, 2) LC, 3) LA and LC, or 4) neither surgery (SR# S-20160407-351). Model inputs were drawn from a large, population-based 2011 Swedish study that examined the incidence and risks of post-operative SBO over a 5-year follow-up period. The study group included 1,152 patients who underwent LA, and 16,371 who underwent LC. RESULTS: Preliminary results indicate that prophylactic LA may yield higher mission risks than the control DRM. Complete analyses are pending and will be subsequently available. DISCUSSION: The risk versus benefits of prophylactic surgery in astronauts to decrease the probability of acute surgical events during spaceflight has only been qualitatively examined in prior studies. Within the assumptions and limitations of the IMM, this work provides the first quantitative guidance that has previously been lacking to this important question for future deep space exploration missions.

Carroll, Danielle↗

Use of machine learning to analyze chemistry card sort tasks

Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student’s organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student’s strategy. Here in this work, we propose new machine learning strategies that leverage a potentially richer source of student thinking: free-form written language justifications associated with student sorts. Using data from a university chemistry card sort task, we use vectorized representations of language and unsupervised learning techniques to generate qualitatively interpretable clusters, which can provide unique insight in how students organize their knowledge. We compared these to machine learning analysis of the students’ sorts themselves. Machine learning-generated clusters revealed different organizational strategies than those built into the task; for example, sorts by difficulty or even discipline. There were also many more categories generated by machine learning for what we would identify as more novice-like sorts and justifications than originally built into the task, suggesting students’ organizational strategies converge when they become more expert-like. Finally, we learned that categories generated by machine learning for students’ justifications did not always match the categories for their sorts, and these cases highlight the need for future research on students’ organizational strategies, both manually and aided by machine learning. In sum, the use of machine learning to analyze results from a card sort task has helped us gain a more nuanced understanding of students’ expertise, and demonstrates a promising tool to add to existing analytic methods for card sorts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of Realistic, Cyclic Atmospheric Cycles on the Pitting Corrosion of Austenitic Stainless Steels

Pitting corrosion was evaluated on stainless steels 304H, 304, and 316L the surfaces of which had ASTM seawater printed on them as a function of surface roughness after exposure to an exemplar realistic atmospheric diurnal cycle for up to one year. Methods to evaluate pitting damage included optical imaging, scanning electron microscopy imaging, profilometry analysis, and polarization scans. The developed cyclic exposure environment did not significantly influence pitting morphology nor depth in comparison to prior static exposure environments. Cross-hatching was observed in a majority of pits for all material compositions with the roughest surface finish (#4 finish) and in all surface finishes for the 304H composition. Evidence is provided that cross-hatched pit morphologies are caused by slip bands produced during the grinding process for the #4 finish or by material processing. Additionally, micro-cracking was observed in pits formed on samples with the #4 surface finish and was greatly reduced or absent for pits formed on samples with smooth surface finishes. This suggests that both a low RH leading to an MgCl 2 -dominated environment and a rough surface containing significant residual stress are necessary for micro-cracking. Finally, the use of various characterization techniques and cross sectioning was employed to both qualitatively and quantitatively assess pitting damage across all SS compositions and surface finishes.

36 MATERIALS SCIENCE↗

Investigation of Sooting in Microgravity Droplet Combustion: Fuel-Dependent Effects

Kumagai and coworkers first performed microgravity droplet combustion experiments [Kumagai, 1957]. The primary goal of these early experiments were to validate simple 'd(sup 2)-law models [Spalding, 1954, Godsave, 1954] Inherent in the 'd(sup 2) -law' formulation and in the scope of the experimental observation is the neglect of sooting behavior. In fact, the influence of sooting has not received much attention until more recent works [Choi et al., 1990; Jackson et al., 1991; Jackson and Avedisian, 1994; Choi and Lee, 1996; Jackson and Avedisian, 1996; Lee et al., 1998]:. Choi and Lee measured soot volume fraction for microgravity droplet flames using full-field light extinction and subsequent tomographic inversion [Choi and Lee, 1996]. In this investigation, soot concentrations were measured for heptane droplets and it was reported that soot concentrations were considerably higher in microgravity compared to the normal gravity flame. It was reasoned that the absence of buoyancy and the effects of thermophoresis resulted in the higher soot concentrations. Lee et al. [1998] performed soot measurement experiments by varying the initial droplet diameter and found marked influence of sooting on the droplet burning behavior. There is growing sentiment that sooting in droplet combustion must no longer be neglected and that "perhaps one of the most important outstanding contributions of (micro)g droplet combustion is the observation that in the absence of asymmetrical forced and natural convection, a soot shell is formed between the droplet surface and the flame, exerting an influence on the droplet combustion response far greater than previously recognized." [Law and Faeth, 1994]. One of the methods that we are exploring to control the degree of sooting in microgravity is to use different fuels. The effect of fuel structure on sooting propensity has been investigated for over-ventilated concentric coflowing buoyant diffusion flames. (Glassman, 1996]. In these investigations, the fuel flowrate was increased until smoke was observed to escape from the "luminous visible flame" [Glassman, 1996]. A total of 29 fuels were used in order to characterize relative sooting propensity. The sooting propensity of a particular fuel was assessed by comparing the flowrates for soot emission from the tip of the flame. It was reported that the sooting tendency for diffusion flames increased for fuels with higher rates of pyrolysis. Randolph and Law [1986 and not 1994] also examined the effect of fuel structure on droplet sooting behavior. In their experiments the droplets were separated from the bulk gas stream and quenched with nitrogen prior to gravimetric measurements. A variety of fuels were studied, namely aromatics, phenyl-alkanes and alkanes. The results were in qualitative agreement with the work of Glassman [1986]. Vander Wal et al. [1994] performed relative soot concentration measurements using laser-induced incandescence for heptane and decane fuel droplets burning under normal-gravity conditions. It was found that soot volume fractions for decane was more than a factor of two larger than that for heptane. Although the normal-gravity investigations have provided some important insights regarding the influence of fuel structure on the sooting behavior of droplet flames, results cannot be easily extrapolated for microgravity studies since increased residence times and thermophoretic effects must be considered in greater detail. Several studies have compared sooting behavior of different fuel droplets burning under microgravity conditions [Card and Choi, 1990; Jackson et al., 1991; Jackson and Avedisian, 1994], however, detailed quantitative results were not provided. In all of these previous studies, the degree of sooting was only visually assessed from an incandescent backlighted image of the soot containing region. Such techniques can provide misleading results regarding sooting behavior [Choi, 1996].

Manzello, Samuel L.↗

Exploring Ligand-to-Metal Charge-Transfer States in the Photo-Ferrioxalate System Using Excited-State Specific Optimization

The photo-ferrioxalate system (PFS), [Fe(III)(C 2 O 4 )] 3– , more than an exact chemical actinometer, has been extensively applied in wastewater and environment treatment. Despite many experimental efforts to improve clarity, important aspects of the mechanism of ferrioxalate photolysis are still under debate. In this paper, we employ the recently developed WΓ-CASSCF to investigate the ligand-to-metal charge-transfer states that are key to ferrioxalate photolysis. This investigation provides a qualitative picture of these states and key potential energy surface features related to the photolysis. Furthermore, our theoretical results are consistent with the prompt charge-transfer picture seen in recent experiments and clarify some features that are not visible in experiments. Two ligand-to-metal charge-transfer states contribute to the photolysis of ferrioxalate, and the avoided crossing barrier between them is low compared with the initial photoexcitation energy. Our data also clarify that one Fe–O bond cleaves first, followed by the C–C bond and the other Fe–O bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding, quantifying, and controlling the molecular ordering of semiconducting polymers: from novices to experts and amorphous to perfect crystals

Molecular packing and texture of semiconducting polymers are often critical to the performance of devices using these materials. Although frameworks exist to quantify the ordering, interpretations are often just qualitative, resulting in imprecise use of terminology. Here, we reemphasize the significance of quantifying molecular ordering in terms of degree of crystallinity (volume fractions that are ordered) and quality of ordering and their relation to the size scale of an ordered region. We are motivated in part by our own imprecise and inconsistent use of terminology in the past, as well as the need to have a primer or tutorial reference to teach new group members. We strive to develop and use consistent terminology with regards to crystallinity, semicrystallinity, paracrystallinity, and related characteristics. To account for vastly different quality of ordering along different directions, we classify paracrystals into 2D and 3D paracrystals and use paracrystallite to describe the spatial extent of molecular ordering in 1–10 nm. We show that a deeper understanding of molecular ordering can be achieved by combining grazing-incidence wide-angle X-ray scattering and differential scanning calorimetry, even though not all aspects of these measurements are consistent, and some classification appears to be method dependent. We classify a broad range of representative polymers under common processing conditions into five categories based on the quantitative analysis of the paracrystalline disorder parameter (g) and thermal transitions. A small database is presented for 13 representative conjugated and insulating polymers ranging from amorphous to semi-paracrystalline. Lastly, we outline the challenges to rationally design more perfect polymer crystals and propose a new molecular design approach that envisions conceptual molecular grafting that is akin to strained and unstrained hetero-epitaxy in classic (compound) semiconductors thin film growth.

36 MATERIALS SCIENCE↗

The spatial variation of the infrared-to-radio ratio in spiral galaxies

We have produced two-dimensional maps of the intensity ratio, Q(sub 60), of 60 micron infrared to 20 cm radio continuum emission, for a set of 25 nearby galaxies, mostly spirals. The ratio maps were obtained from infrared images made using IRAS data with the maximum correlation method, and radio images made using VLA data. Before taking the ratio, the radio images were processed so as to have the same resolution properties as the infrared images; the final spatial resolution in all cases is approximately 1 min, corresponding to 1 - 2 kpc for most galaxies. This resolution represents a significant improvement over previous studies. Our new high-resolution maps confirm the slow decrease of Q(sub 60) with increasing radial distance from the nucleus, but show additional structure which is probably associated with separate sites of active star formation in the spiral arms. The maps show Q(sub 60) to be more closely related to infrared surface brightness than to the radial distance r in the galaxy disk. We note also that the Q(sub 60) gradients are absent (or at least reduced) for the edge-on galaxies, a property which can be attributed to the dilution of contrast due to the averaging of the additional structure along the line of sight. The results are all in qualitative agreement with the suggestion that the radio image represents a smeared version of the infrared image, as would be expected on the basis of current models in which the infrared-radio correlation is driven by the formation of massive stars, and the intensity distribution of radio emission is smeared as a result of the propagation of energetic electrons accelerated during the supernova phase.

Marsh, K. A.↗

Bayesian model-data comparison incorporating theoretical uncertainties

Accurate comparisons between theoretical models and experimental data are critical for scientific progress. However, inferred physical model parameters can vary significantly with the chosen physics model, highlighting the importance of properly accounting for theoretical uncertainties. In this Letter, we present a Bayesian framework that explicitly quantifies these uncertainties by statistically modeling theory errors, guided by qualitative knowledge of a theory’s varying reliability across the input domain. We demonstrate the effectiveness of this approach using two systems: a simple ball drop experiment and multi-stage heavy-ion simulations. In both cases incorporating model discrepancy leads to improved parameter estimates, with systematic improvements observed as additional experimental observables are integrated.

Bayesian methods↗

Calcaneal loading during walking and running

PURPOSE: This study of the foot uses experimentally measured kinematic and kinetic data with a numerical model to evaluate in vivo calcaneal stresses during walking and running. METHODS: External ground reaction forces (GRF) and kinematic data were measured during walking and running using cineradiography and force plate measurements. A contact-coupled finite element model of the foot was developed to assess the forces acting on the calcaneus during gait. RESULTS: We found that the calculated force-time profiles of the joint contact, ligament, and Achilles tendon forces varied with the time-history curve of the moment about the ankle joint. The model predicted peak talocalcaneal and calcaneocuboid joint loads of 5.4 and 4.2 body weights (BW) during walking and 11.1 and 7.9 BW during running. The maximum predicted Achilles tendon forces were 3.9 and 7.7 BW for walking and running. CONCLUSIONS: Large magnitude forces and calcaneal stresses are generated late in the stance phase, with maximum loads occurring at approximately 70% of the stance phase during walking and at approximately 60% of the stance phase during running, for the gait velocities analyzed. The trajectories of the principal stresses, during both walking and running, corresponded to each other and qualitatively to the calcaneal trabecular architecture.

NASA Center ARC↗