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NASA NTRS1999

Cloud 3D Effects Evidenced in Landsat Power Spectra and Autocorrelation Functions

An analysis of nadir reflectivity Fourier spatial power spectra and autocorrelation functions at solar wavelengths and for cloudy conditions has been carried out. The data come from Landsat Thematic Mapper (TM) observations, while Monte Carlo (MC) simulations are used to aid the interpretation of the Landsat results. We show that radiative processes produce consistent signatures on power spectra and autocorrelation functions. The former take a variety of forms not shown or explained in previous observational studies. We demonstrate that the TM spectra can potentially be affected by both radiative "roughening" at intermediate scales (approx. 1 -5 km), being more prevalent at large solar zenith angles, and the already documented radiative "smoothing" at small scales (less than 1 km). These processes are wavelength dependent, as shown by systematic differences between conservative (for cloud droplets) TM band 4 (approx. 0.8 microns) and absorbing band 7 (approx. 2.2 microns): band 7 exhibits more roughening and less smoothing. This is confirmed quantitatively by comparing least-squared fitted power spectral slopes for the two bands. It is also corroborated by a slower decrease with distance of autocorrelation function values for band 4 compared to band 7. The appearance of roughening at large solar zenith angles is a result of side illumination and shadowing and adds an additional complexity to the power spectra. MC spectra are useful in illustrating that scale invariant optical depth fields can produce complex power spectra that take a variety of shapes under different conditions. We show that radiative roughening increases with the decrease of single scattering albedo and with the increase of solar zenith angle (as in the observations). For high Sun there is also a clear shift of the radiative smoothing scale to smaller values as droplet absorption increases. The shape of the power spectrum is sensitive to the magnitude and type of cloud top height variability, with the spectral signatures of decorrelation between reflectance and optical depth at large scales becoming stronger as the magnitude of cloud top variations increase. Finally, the usefulness of power spectral analysis in evaluating the skill of novel optical depth retrieval techniques in removing 3D radiative effects is demonstrated. New techniques using inverse Non-local Independent Pixel Approximation (NIPA) and Normalized Difference of Nadir Reflectivity (NDNR) yield optical depth fields which better match the scale-by-scale variability of the true optical depth field.

Oreopoulos, Lazaros↗
NASA NTRS2000

Modeling Tools for Propulsion Analysis and Computational Fluid Dynamics on the Internet

The existing RocketWeb(TradeMark) Internet Analysis System (httr)://www.iohnsonrockets.com/rocketweb) provides an integrated set of advanced analysis tools that can be securely accessed over the Internet. Since these tools consist of both batch and interactive analysis codes, the system includes convenient methods for creating input files and evaluating the resulting data. The RocketWeb(TradeMark) system also contains many features that permit data sharing which, when further developed, will facilitate real-time, geographically diverse, collaborative engineering within a designated work group. Adding work group management functionality while simultaneously extending and integrating the system's set of design and analysis tools will create a system providing rigorous, controlled design development, reducing design cycle time and cost.

Muss, J. A.↗
NASA NTRS1992

The statistical analysis of circadian phase and amplitude in constant-routine core-temperature data

Accurate estimation of the phases and amplitude of the endogenous circadian pacemaker from constant-routine core-temperature series is crucial for making inferences about the properties of the human biological clock from data collected under this protocol. This paper presents a set of statistical methods based on a harmonic-regression-plus-correlated-noise model for estimating the phases and the amplitude of the endogenous circadian pacemaker from constant-routine core-temperature data. The methods include a Bayesian Monte Carlo procedure for computing the uncertainty in these circadian functions. We illustrate the techniques with a detailed study of a single subject's core-temperature series and describe their relationship to other statistical methods for circadian data analysis. In our laboratory, these methods have been successfully used to analyze more than 300 constant routines and provide a highly reliable means of extracting phase and amplitude information from core-temperature data.

NASA Discipline Regulatory Physiology↗
NASA NTRS2009

Updating the Finite Element Model of the Aerostructures Test Wing using Ground Vibration Test Data

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the Aerostructures Test Wing (ATW), which was designed and tested at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center (DFRC) (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Lung, Shun-fat↗
NASA NTRS2009

Updating the Finite Element Model of the Aerostructures Test Wing Using Ground Vibration Test Data

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the aerostructures test wing (ATW), which was designed and tested at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Lung, Shun-Fat↗
DOE OSTI2020

Future projections and uncertainty assessment of precipitation extremes in the Korean peninsula from the CMIP5 ensemble

Abstract Projections of changes in extreme climate are sometimes predicted by multimodel ensemble methods that combine forecasts from individual simulation models using weighted averaging. One method to assign weight to each model is the Bayesian model averaging (BMA) in which posterior probability is used. For the cases of extreme climate, the generalized extreme value distribution (GEVD) is typically used. We applied the approach of GEV‐embedded BMA to a series of 35 years of the annual maximum daily precipitation data (both historical data and data gathered from simulation experiments for future periods) over the Korean peninsula as simulated by the models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Simulation data under two Representative Concentration Pathway (RCP) scenarios, namely RCP4.5 and RCP8.5, were used. Observed data and 17 CMIP5 models for 12 gird cells in Korea have been examined to predict future changes in precipitation extremes. A simple regional frequency analysis of pooling observations from three stations in each cell was employed to reduce the estimation variance and local fluctuations. A bias correction technique using the regression‐type transfer function was applied to these simulation data. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1971–2005), were estimated for two future periods, namely Period 1 (2021–2050) and Period 2 (2066–2095). From these analyses, relative increase observed in the spatially averaged 20‐year (50‐year) return level was approximately 23% (16%) and 45% (36%) in the RCP4.5 and RCP8.5 experiments, respectively, by the end of the 21st century. We concluded that extreme rainfalls will likely occur two times and four times more frequently in the RCP4.5 and RCP8.5 scenarios, respectively, as compared to in the reference years by the end of the 21st century.

Lee, Youngsaeng↗
NASA NTRS1994

Analysis of small-scale microwave background radiation anisotropy in the presence of foreground contamination

Many of the current round of experiments searching for anisotropies in the microwave background radiation (MBR) are confronting the problem of how to disentangle the cosmic signal from contamination due to Galactic and intergalactic foreground sources. Here we show how commonly used likelihood function techniques can be generalized to account for foreground. Specifically we set some restrictions on the spectrum of foreground contamination but allow the amplitude to vary arbitrarily. The likelihood function thus generalized gives reasonable limits on the MBR anisotropy which, in some cases, are not much less restrictive than what one would get from more detailed modeling of the foreground. Furthermore, the likelihood function is exactly the same as one would obtain by simply projecting out foreground contamination and looking at the reduced data set. We apply this generalized analysis to the recent medium-angle data sets of ACME-HEMT (Gaier et al. 1992; Schuster et al. 1993) and MAX (Meinhold et al. 1993; Gunderson et al. 1993). The resulting analysis constrains the one free parameter in the standard cold dark matter theory to be Q(sub rms-ps) = 18(sub -5 sup +8) microKelvin. This best fit value, although in striking agreement with the normalization from Cosmic Background Explorer (COBE), is not a very good fit, with an overall chi-squared/degrees of freedom = 208/168. We also argue against three commonly used methods of dealing with foreground: (1) ignoring it completely; (2) subtracting off a best-fit foreground and treating the residuals as if uncontaminated; and (3) culling data which appears to be contaminated by foreground.

Dodelson, Scott↗
NASA NTRS2003

Extended Statistical Short-Range Guidance for Peak Wind Speed Analyses at the Shuttle Landing Facility: Phase II Results

This report describes the results from Phase II of the AMU's Short-Range Statistical Forecasting task for peak winds at the Shuttle Landing Facility (SLF). The peak wind speeds are an important forecast element for the Space Shuttle and Expendable Launch Vehicle programs. The 45th Weather Squadron and the Spaceflight Meteorology Group indicate that peak winds are challenging to forecast. The Applied Meteorology Unit was tasked to develop tools that aid in short-range forecasts of peak winds at tower sites of operational interest. A seven year record of wind tower data was used in the analysis. Hourly and directional climatologies by tower and month were developed to determine the seasonal behavior of the average and peak winds. Probability density functions (PDF) of peak wind speed were calculated to determine the distribution of peak speed with average speed. These provide forecasters with a means of determining the probability of meeting or exceeding a certain peak wind given an observed or forecast average speed. A PC-based Graphical User Interface (GUI) tool was created to display the data quickly.

Lambert, Winifred C.↗
NASA NTRS2011

Lightning Observations and Tropical Cyclogenesis in the Atlantic and East Pacific

It has been hypothesized that deep, intense convective-scale "hot" towers may aid the process of tropical cyclogenesis and intensification through dynamic and thermodynamic feedbacks on the larger meso-to-synoptic scale circulation. In this study, we make use of NCEP Reanalysis data and Tropical Rainfall Measurement Mission (TRMM) lightning imaging sensor (LIS), precipitation radar (PR), and microwave imager (TMI) data to investigate the role that widespread and/or intense lightning-producing convection (i.e., "electrically-hot towers") present in African easterly waves (AEWs) may play in tropical cyclogenesis over the Atlantic, Caribbean, and East Pacific regions. NCEP Reanalysis 700 hPa meridional winds for the months of June to November for the years 2001-2009 were analyzed for the domain of 5degN-20degN and 130degW-20degE in order to partition individual AEWs into northerly, southerly, trough, and ridge phases. Subsequently, information from National Hurricane Center (NHC) storm reports was used to divide the waves into developing and non-developing waves. In addition, information from the NHC reports was used to further divide the developing waves into those waves that spawned storms that only developed to tropical storm strength and those that spawned storms that reached hurricane strength. The developing waves were also divided by the region in which they developed. To assess the evolution of convection associated with the AEWs as they propagated across our analysis domain, the full 130degW-20degE domain was divided into five longitude bands, and waves were analyzed for each band. To help determine the gross nature of the smaller convective scale, composites were created of all developing and non-developing waves as a function of AEW wave phase over the full analysis domain and each longitude band by compositing TRMM PR, TMI, LIS, and IR brightness temperature data extracted from the NASA global-merged infrared brightness temperature dataset. Finally, similar composites were created using various NCEP variables to assess the nature of the larger scale environment and circulation.

Leppert, Kenneth D., II↗
NASA NTRS2006

Trade Studies of Space Launch Architectures using Modular Probabilistic Risk Analysis

A top-down risk assessment in the early phases of space exploration architecture development can provide understanding and intuition of the potential risks associated with new designs and technologies. In this approach, risk analysts draw from their past experience and the heritage of similar existing systems as a source for reliability data. This top-down approach captures the complex interactions of the risk driving parts of the integrated system without requiring detailed knowledge of the parts themselves, which is often unavailable in the early design stages. Traditional probabilistic risk analysis (PRA) technologies, however, suffer several drawbacks that limit their timely application to complex technology development programs. The most restrictive of these is a dependence on static planning scenarios, expressed through fault and event trees. Fault trees incorporating comprehensive mission scenarios are routinely constructed for complex space systems, and several commercial software products are available for evaluating fault statistics. These static representations cannot capture the dynamic behavior of system failures without substantial modification of the initial tree. Consequently, the development of dynamic models using fault tree analysis has been an active area of research in recent years. This paper discusses the implementation and demonstration of dynamic, modular scenario modeling for integration of subsystem fault evaluation modules using the Space Architecture Failure Evaluation (SAFE) tool. SAFE is a C++ code that was originally developed to support NASA s Space Launch Initiative. It provides a flexible framework for system architecture definition and trade studies. SAFE supports extensible modeling of dynamic, time-dependent risk drivers of the system and functions at the level of fidelity for which design and failure data exists. The approach is scalable, allowing inclusion of additional information as detailed data becomes available. The tool performs a Monte Carlo analysis to provide statistical estimates. Example results of an architecture system reliability study are summarized for an exploration system concept using heritage data from liquid-fueled expendable Saturn V/Apollo launch vehicles.

Mathias, Donovan L.↗
NASA NTRS1980

A variational technique for smoothing flight-test and accident data

The problem of determining aircraft motions along a trajectory is solved using a variational algorithm that generates unmeasured states and forcing functions, and estimates instrument bias and scale-factor errors. The problem is formulated as a nonlinear fixed-interval smoothing problem, and is solved as a sequence of linear two-point boundary value problems, using a sweep method. The algorithm has been implemented for use in flight-test and accident analysis. Aircraft motions are assumed to be governed by a six-degree-of-freedom kinematic model; forcing functions consist of body accelerations and winds, and the measurement model includes aerodynamic and radar data. Examples of the determination of aircraft motions from typical flight-test and accident data are presented.

Bach, R. E., Jr.↗
NASA NTRS1982

A Variational Technique for Smoothing Flight-Test and Accident Data

The problem of determining aircraft motions along a trajectory is solved using a variational algorithm that generates unmeasured states and forcing functions, and estimates instrument bias and scale-factor errors. The problem is formulated as a nonlinear fixed-interval smoothing problem, and is solved as a sequence or linear two-point boundary value problems, using a sweep method. The algorithm has been implemented for use in flight-test and accident analysis. Aircraft motions are assumed to be governed by a six-degree-of-freedom kinematic model; forcing functions consist of body accelerations and winds, and the measurement model includes aerodynamic and radar data. Examples of the determination of aircraft motions from typical flight-test and accident data are presented.

Bach, Ralph E. , Jr.↗
NASA NTRS1997

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

Potter, C. S.↗
DOE OSTI2022

Unraveling the Wrinkle in Time-Variable Sources with Lunes and Synthetic Seismic Data

In this report, we describe how to estimate the time-variable components of the seismic moment tensor and compare these estimates to the more conventional analysis that incorporates an assumption of the source time function (STF) across all components of the seismic moment tensor. The advantage of our method is that we are able to independently estimate the time-evolution of each component of the seismic moment tensor, which may help to resolve the complex source phenomena associated with buried explosions. By performing an eigen decomposition of the time-evolving seismic moment tensor components, we are able to plot the seismic mechanism as a trajectory on a lune diagram. This technique enables interpretation of the seismic mechanism as a function of time, as opposed to the more conventional analysis which assumes that the seismic mechanism is time invariant. Finally, we describe the differences between the seismic moment and the seismic moment rate STFs, how to implement each one in inversion schemes, and the relative strengths/weaknesses of each. Our key take-away is that we are able to distinguish nearly-overlapping sources with highly different mechanisms, such as an explosion immediately following an earthquake, by estimating moment rate from seismic data through a STF-invariant inversion for the full time-variable moment tensor.

58 GEOSCIENCES↗
NASA NTRS1976

Geologic mapping using LANDSAT data

The feasibility of automated classification for lithologic mapping with LANDSAT digital data was evaluated using three classification algorithms. The two supervised algorithms analyzed, a linear discriminant analysis algorithm and a hybrid algorithm which incorporated the Parallelepiped algorithm and the Bayesian maximum likelihood function, were comparable in terms of accuracy; however, classification was only 50 per cent accurate. The linear discriminant analysis algorithm was three times as efficient as the hybrid approach. The unsupervised classification technique, which incorporated the CLUS algorithm, delineated the major lithologic boundaries and, in general, correctly classified the most prominent geologic units. The unsupervised algorithm was not as efficient nor as accurate as the supervised algorithms. Analysis of spectral data for the lithologic units in the 0.4 to 2.5 microns region indicated that a greater separability of the spectral signatures could be obtained using wavelength bands outside the region sensed by LANDSAT.

Siegal, B. S.↗
DOE OSTI2022

Anomalies in the topology of the temperature fluctuations in the cosmic microwave background: An analysis of the NPIPE and FFP10 data releases

We present a topological analysis of the temperature fluctuation maps from the Planck 2020 Data Release 4 NPIPE dataset and the Planck 2018 Data Release 3 FFP10 dataset. We performed a multiscale analysis in terms of the homology characteristics of the maps, invoking relative homology to account for the analysis in the presence of masks. We performed our analysis for a range of smoothing scales spanning sub- and super-horizon scales corresponding to a full width at half maximum (FWHM) of 5',10',20',40',80',160',320', and 640', and employed simulations based on the standard model for comparison, which assumes the initial fluctuation field to be an isotropic and homogeneous Gaussian random field. Examining the behavior of topological components, represented by the 0D homology group, we find the observations to be approximately 2σ or less deviant from the simulations for all resolutions and scales for the NPIPE dataset. For the FFP10 dataset, we detect a 2.96σ deviation between the observations and simulations at N = 128, FWHM = 80'. For the topological loops, represented by the first homology group, the simulations and observations are consistent within 2σ for most resolutions and scales for both the datasets. However, for the NPIPE dataset, we observe a high deviation between the observation and simulations in the number of loops at FWHM = 320', but at a low dimensionless threshold ν = –2.5. Under a Gaussian assumption, this would amount to a deviation of ~4σ. However, the distribution in this bin is manifestly non-Gaussian and does not obey Poisson statistics either. In the absence of a true theoretical understanding, we simply note that the significance is higher than what may be resolved by 600 simulations, yielding an empirical p-value of at most 0.0016. Specifically in this case, our tests indicate that the numbers arise from a statistically stable regime, despite being based on small numbers. For the FFP10 dataset, the differences are not as strong as for the NPIPE dataset, indicating a 2.77σ deviation at this resolution and threshold. The Euler characteristic, which is the alternating sum of the ranks of relative homology groups, reflects the deviations in the components and loops. To assess the significance of combined levels for a given scale, we employed the empirical and theoretical versions of the χ 2 test as well as the nonparametric Tukey depth test. Although all statistics exhibit a stable distribution, we favor the empirical version of the χ 2 test in the final interpretation, as it indicates the most conservative differences. For the NPIPE dataset, we find that the components and loops differ at more than 95%, but agree within the 99% confidence level with respect to the base model at N = 32, FWHM = 320'. The Euler characteristic at this resolution displays a per mil deviation. In contrast, the FFP10 dataset shows that the observations are consistent with the base model within the 95% confidence level, at this and smaller scales. This is consistent with the observations of the Planck analysis pipeline via Minkowski functionals. For the largest smoothing scale, N = 16, FWHM = 640', both datasets exhibit an anomalous behavior of the loops, where FFP10 data exhibit a deviation that is larger by an order of magnitude than that of the NPIPE dataset. In contrast, the values for the topological components and the Euler characteristic agree between observations and model to within a confidence level of 99%. However, for the largest scales, the statistics are based on low numbers and may have to be regarded with caution. Even though both datasets exhibit mild to significant discrepancies, they also exhibit contrasting behaviors at various instances. Therefore, we do not find it feasible to convincingly accept or reject the null hypothesis. Disregarding the large-scale anomalies that persist at similar scales in WMAP and Planck, observations of the cosmic microwave background are largely consistent with the standard cosmological model within 2σ.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Electrically-Active Convection and Tropical Cyclogenesis in the Atlantic and East Pacific

It has been hypothesized that deep, intense convective-scale hot towers may aid the process of tropical cyclogenesis and intensification through dynamic and thermodynamic feedbacks on the larger meso-to-synoptic scale circulation. In this study, we make use of NCEP Reanalysis data and Tropical Rainfall Measurement Mission (TRMM) lightning imaging sensor (LIS), precipitation radar (PR), and microwave imager (TMI) data to investigate the role that widespread and/or intense lightning-producing convection (i.e., electrically-hot towers) present in African easterly waves (AEWs) may play in tropical cyclogenesis over the Atlantic, Caribbean, and East Pacific regions. NCEP Reanalysis 700 hPa meridional winds for the months of June to November for the years 2001-2009 were analyzed for the domain of 5 deg. N-20 deg. N and 130 deg. W-20 deg. E in order to partition individual AEWs into northerly, southerly, trough, and ridge phases. Subsequently, information from National Hurricane Center (NHC) storm reports was used to divide the waves into developing and non-developing waves. In addition, information from the NHC reports was used to further divide the developing waves into those waves that spawned storms that only developed to tropical storm strength and those that spawned storms that reached hurricane strength. The developing waves were also divided by the region in which they developed. To assess the evolution of convection associated with the AEWs as they propagated across our analysis domain, the full 130 deg. W-20 deg. E domain was divided into five longitude bands, and waves were analyzed for each band. To help determine the gross nature of the smaller convective scale, composites were created of all developing and non-developing waves as a function of AEW wave phase over the full analysis domain and each longitude band by compositing TRMM PR, TMI, LIS, and IR brightness temperature data extracted from the NASA global-merged infrared brightness temperature dataset. Finally, similar composites were created using various NCEP variables to assess the nature of the larger scale environment and circulation. Results suggest a clear distinction between developing and non-developing waves as developing waves near their region of development in terms of the intensity of convection (indicated by lightning flash rate), coverage of cold cloudiness (indicated by the percentage of a 2.5 deg. by 2.5 deg. box covered by IR brightness temperatures less than 240 deg. K and 210 deg. K), and large-scale variables, such as midlevel moisture and upper-level upward motion. For example, waves that developed in the East Pacific longitude band (i.e., 130 deg. W 95 deg. W) were observed in that band to have a flash rate of 56.4 flashes per day, a coverage by brightness temperatures less than 240 deg. K equal to 15.9%, a coverage by brightness temperatures less than 210 deg. K equal to 2.2%, a 700-hPa specific humidity anomaly of 0.4 g per kilogram, and a 300-hPa omega value of -0.04 Pascals per second in the trough phase compared to the non-developing wave trough values of 22.1 flashes per day, a coverage by brightness temperatures less than 240 deg. K equal to 8.1%, a coverage by brightness temperatures less than 210 deg. K equal to 0.9%, a 700-hPa specific humidity anomaly of -0.3 g per kilogram, and a 300-hPa omega value of -0.01 Pascals per second. Further analysis is being conducted to determine if the aforementioned behavior is observed for developing waves farther from their region of development and to determine any significant differences between waves that spawned storms that reached tropical storm strength and those that spawned storms that reached hurricane strength.

Leppert, Kenneth D., II↗
DOE OSTI2021

Critical Role of the Interfacial Layer in Associating Polymers with Microphase Separation

Polymers with dynamic (transient) bonds, often called associating polymers, have been attracting significant attention in recent years due to their unique viscoelastic properties, self-healing ability, and recyclability. Nevertheless, understanding the mechanisms and the factors controlling their macroscopic properties remains limited due to the higher complexity introduced by the dynamic bonds. Here in this study, small-angle X-ray scattering (SAXS), broadband dielectric spectroscopy (BDS), and rheology were applied to unravel the structure and dynamics of telechelic associating polymers with different molecular weights. SAXS measurements revealed phase separation of the functional end groups with an average cluster size of ~2–3 nm and the distance between clusters controlled by the chain length. Borrowing the interfacial layer model analysis of BDS data from the polymer nanocomposite field, we demonstrated the presence of an interfacial polymer layer with a thickness of ~0.7–0.9 nm surrounding these clusters. Rheological measurements showed quantitatively that the presence of the interfacial layer significantly alters the viscoelastic behavior of these materials, indicating the crucial role of the interfacial layer in defining the macroscopic mechanical properties of the studied telechelic materials. The presented results emphasize that phase separation of the functional groups in associating polymers leads to very significant changes of the viscoelastic properties, opening a promising avenue in the design of novel functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗