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NASA NTRS1997

Evaluation of Two Fractal Methods for Magnetogram Image Analysis

Fractal and multifractal techniques have been applied to various types of solar data to study the fractal properties of sunspots as well as the distribution of photospheric magnetic fields and the role of random motions on the solar surface in this distribution. Other research includes the investigation of changes in the fractal dimension as an indicator for solar flares. Here we evaluate the efficacy of two methods for determining the fractal dimension of an image data set: the Differential Box Counting scheme and a new method, the Jaenisch scheme. To determine the sensitivity of the techniques to changes in image complexity, various types of constructed images are analyzed. In addition, we apply this method to solar magnetogram data from Marshall Space Flight Centers vector magnetograph.

Stark, B.↗

NASA NTRS1992

Assessing deforestation and habitat fragmentation in Uganda using satellite observations and fractal analysis

The MSS, SPOT, and AVHRR imagery of Ugandan forests were analyzed to assess the information content related to deforestation and tropical habitat fragmentation, focusing primarily on the Kibale and Mabira Forests. Analysis of actual and simulated AVHRR imagery showed that it might be possible to monitor major changes in forest extent with the relatively coarse spatial resolution of AVHRR imagery (about 1 km) provided ancillary data were available. The fractal dimension of the forest edges, measured with the Landsat and SPOT imagery, was consistently about 1.7 or 1.8. This high fractal dimension was due to the coplex pattern of clearings, remnant forest stands, and jagged forest edges caused by repeated human encroachment over centuries.

Hlavka, Christine A.↗

NASA NTRS1995

Characterization of microgravity effects on bone structure and strength using fractal analysis

The effect of micro-gravity on the musculoskeletal system has been well studied. Significant changes in bone and muscle have been shown after long term space flight. Similar changes have been demonstrated due to bed rest. Bone demineralization is particularly profound in weight bearing bones. Much of the current techniques to monitor bone condition use bone mass measurements. However, bone mass measurements are not reliable to distinguish Osteoporotic and Normal subjects. It has been shown that the overlap between normals and osteoporosis is found for all of the bone mass measurement technologies: single and dual photon absorptiometry, quantitative computed tomography and direct measurement of bone area/volume on biopsy as well as radiogrammetry. A similar discordance is noted in the fact that it has not been regularly possible to find the expected correlation between severity of osteoporosis and degree of bone loss. Structural parameters such as trabecular connectivity have been proposed as features for assessing bone conditions. In this report, we use fractal analysis to characterize bone structure. We show that the fractal dimension computed with MRI images and X-Ray images of the patella are the same. Preliminary experimental results show that the fractal dimension computed from MRI images of vertebrae of human subjects before bedrest is higher than during bedrest.

Acharya, Raj S.↗

DOE OSTI2025

Effect of Sulfonation Level on the Percolated Morphology and Proton Conductivity of Hydrated Fluorine-Free Copolymers: Experiments and Simulations

Using all-atom molecular dynamics simulations and a variety of experimental methods, we previously reported on a linear polyethylene with pendant phenyl sulfonated groups precisely on every fifth carbon along the backbone. With increasing relative humidity this fluorine-free polymer self-assembled to form nanoscale water channels and exhibited exceptional proton conductivity. Expanding upon those findings, here we explore partially sulfonated random copolymers, referred to as p 5PhSH-Y. Using either acetyl sulfate or sulfuric acid, a wide range of sulfonation levels were prepared ( Y = 34−98%) corresponding to ion-exchange capacities (IEC) of 2.0−4.4 mmol/g. Combining experimental techniques and all-atom molecular dynamics simulations, we study the effect of Y on water uptake, nanoscale morphology, and the proton/water transport properties of p5PhSH- Y . The proton conductivity of p 5PhSH- Y increases with relative humidity and with Y and achieves values in excess of 0.1 S/cm. These high conductivities are attributed to high IEC and welldeveloped nanoscale percolated hydrophilic domains made possible by the flexible backbone. We quantitatively describe the nature of the water channels using the characteristic distance, channel width distribution, the area per sulfonate group at the hydrophilic/ hydrophobic interface, and the fractal dimension. Notably, the channel widths and the areas per sulfonate group are nominally independent of the level of sulfonation, while depending significantly on the level of hydration. The fractal dimension of the water channels correlates strongly with the water diffusion coefficients calculated from the molecular dynamics (MD) simulations. These findings demonstrate that the p 5PhSH- Y hydrocarbon copolymers can be modified to tune properties, particularly proton conductivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Random Knotting in Fractal Ring Polymers

Many ring polymer systems of physical and biological interest exhibit both pronounced topological effects and nontrivial self-similarity, but the relationship between these two phenomena has not yet been clearly established. Here, we use theory and simulation to formulate such a connection by studying a fundamental topological property—the random knotting probability—for ring polymers with varying fractal dimension, d f . Using straightforward scaling arguments, we generalize a classic mathematical result, showing that the probability of a trivial knot decays exponentially with chain size, N, for all fractal dimensions: P 0 (N) ∝ exp(–N/N 0 ). However, no such simple considerations can account for the dependence of the knotting length, N 0 , on d f , necessitating a more involved analytical calculation. This analysis reveals a complicated double-exponential dependence, which is well supported by numerical data. By contrast, functional forms typical of simple scaling theories fail to adequately describe the observations. These findings are equally valid for two-dimensional ring polymer systems, where “knotting” is defined as the intersection of any two segments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2003

Testing Fractal Methods on Observed and Simulated Solar Magnetograms

The term "magnetic complexity" has not been sufficiently quantified. To accomplish this, we must understand the relationship between the observed magnetic field of solar active regions and fractal dimension measurements. Using data from the Marshall Space Flight Center's vector magnetograph ranging from December 1991 to July 2001, we compare the results of several methods of calculating a fractal dimension, e.g., Hurst coefficient, the Higuchi method, power spectrum, and 2-D Wavelet Packet Analysis. In addition, we apply these methods to synthetic data, beginning with representations of very simple dipole regions, ending with regions that are magnetically complex.

Adams, M.↗

NASA NTRS2008

Multiscale Computer Simulation of Failure in Aerogels

Aerogels have been of interest to the aerospace community primarily for their thermal properties, notably their low thermal conductivities. While such gels are typically fragile, recent advances in the application of conformal polymer layers to these gels has made them potentially useful as lightweight structural materials as well. We have previously performed computer simulations of aerogel thermal conductivity and tensile and compressive failure, with results that are in qualitative, and sometimes quantitative, agreement with experiment. However, recent experiments in our laboratory suggest that gels having similar densities may exhibit substantially different properties. In this work, we extend our original diffusion limited cluster aggregation (DLCA) model for gel structure to incorporate additional variation in DLCA simulation parameters, with the aim of producing DLCA clusters of similar densities that nevertheless have different fractal dimension and secondary particle coordination. We perform particle statics simulations of gel strain on these clusters, and consider the effects of differing DLCA simulation conditions, and the resultant differences in fractal dimension and coordination, on gel strain properties.

Good, Brian S.↗

NASA NTRS1991

On representation of fracture profiles by fractional integrals of a Wiener process

An enhancement of the crack diffusion model of brittle fracture is proposed. In the model, certain probabilities are evaluated as averages over the set of all virtual crack paths, and the latter are modeled as realization of a Wiener process. However, commonly observed fracture profiles are smoother. In fact, one can show that their fractal dimension is smaller than the value 3/2 for a Wiener process. Accordingly, it is proposed to represent fracture profiles by graphs of fractional integrals of a Wiener process. This allows one to employ additional fractographic information obtained from fracture profiles, e.g. their fractal dimension, in a predictive formalism, evaluating probabilities of failure.

Kunin, B.↗

NASA NTRS1992

Fractal analysis of Venus topography in Tinatin Planitia and Ovda Regio

A one-dimensional fractal analysis is applied to Magellan altimetry data for two 20 x 20 deg equatorial regions on Venus. For the Ovda Regio, highlands the power spectra of the altimetry data correlate well with power law (fractal) statistics over the full range of wavelengths considered 36-703 km; the mean fractal dimension is D(Ovda) = 1.64. For the Tinatin Planitia lowlands, the power spectra consistently show a rollover at long wavelengths, (greater than 200 km), the long-wavelength topography in this region either never developed or has subsequently relaxed. The mean of the best fit fractal dimension for Tinatin is D(Tinatin) = 1.41. The measure of roughness (RA) correlates well with variations in relief, especially at short wavelengths (about 50 km). The quantitative analysis of Venus topography can be applied on a global scale. The one-dimensional method can be extended to two-dimensional space, yielding two-dimensional maps of regional D and RA, allowing a more complete use of regional two-dimensional altimetry data.

Kucinskas, Algis B.↗

NASA NTRS1988

Fractal distributions of stress and strength and variations of b-value

A two-dimensional planar fault zone on which the difference between stress and strength follows a fractal distribution is simulated to study the variation of the frequency-magnitude b-value under different distributions of heterogeneities and ambient stress levels. It is suggested that earthquakes occur in regions where this difference exceeds a specified value and that the size of these regions is a measure of the magnitude of the associated earthquake. A systematic variation in b-value is observed. It is found that the b-value has a positive correlation with the fractal dimension of the distribution and is inversely related to the ambient stress level. Observational data are compared with the simulation, showing that the observed b-value variation before and during earthquake sequences is a result of changes in both the ambient stress level and in the fractal dimension of the stress-strength distribution.

Huang, J.↗

DOE OSTI2021

Thermal Experiments for Fractured Rock Characterization: Theoretical Analysis and Inverse Modeling

Abstract Field‐scale properties of fractured rocks play a crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion technique to infer two such parameters, fracture density and fractal dimension, from cross‐borehole thermal experiments data. It is based on a particle‐based heat‐transfer model, whose evaluation is accelerated with a deep neural network (DNN) surrogate that is integrated into a grid search. The DNN is trained on a small number of the heat‐transfer model runs and predicts the cumulative density function of the thermal field. The latter is used to compute fine posterior distributions of the (to be estimated) parameters. Our synthetic experiments reveal that fracture density is well constrained by data, while fractal dimension is harder to determine. Adding nonuniform prior information related to the DFN connectivity improves the inference of this parameter.

Zhou, Zitong↗

DOE OSTI2026

Evaluating the role of green infrastructure features in post-disaster recovery – Case Study of Beaumont, Texas after tropical storm imelda

While green infrastructure (GI) can provide multiple environmental benefits, its role in post-disaster economic and social recovery remains relatively underexplored. This article investigates whether different characteristics of GI, such as size, shape, connectivity, and amenities, affect the resilience of local businesses following Tropical Storm Imelda in Beaumont, Texas. The study utilizes SafeGraph mobility data to analyze foot traffic patterns to local businesses before, during, and after the disaster. FRAGSTATS indices measure GI characteristics (e.g., area, shape index, fractal dimension, proximity) while park features such as sports facilities, playgrounds, water features, and accessibility are cataloged through manual observation. Ordinary Least Squares regression models assess the relationship between park characteristics and post-recovery business performance, controlling for demographic variables including income, race, and poverty levels. Results indicate that certain GI attributes significantly enhance business recovery. Points of interest within walking distance (0.5 miles) of parks demonstrated better post-recovery status compared to those beyond this range. Specifically, parks with larger areas (p < 0.01) and more complex shapes measured by fractal dimension index (p < 0.01) had the strongest positive impact on surrounding businesses' recovery. Interestingly, playgrounds showed a negative correlation with recovery (p < 0.05), likely due to flood damage rendering them unusable during the immediate recovery period. Social vulnerability factors, including higher poverty rates and minority populations, negatively affected recovery outcomes despite park proximity.

Economic resilience↗

NASA NTRS1985

Fractal structure of the interplanetary magnetic field

Under some conditions, time series of the interplanetary magnetic field strength and components have the properties of fractal curves. Magnetic field measurements made near 8.5 AU by Voyager 2 from June 5 to August 24, 1981 were self-similar over time scales from approximately 20 sec to approximately 3 x 100,000 sec, and the fractal dimension of the time series of the strength and components of the magnetic field was D = 5/3, corresponding to a power spectrum P(f) approximately f sup -5/3. Since the Kolmogorov spectrum for homogeneous, isotropic, stationary turbulence is also f sup -5/3, the Voyager 2 measurements are consistent with the observation of an inertial range of turbulence extending over approximately four decades in frequency. Interaction regions probably contributed most of the power in this interval. As an example, one interaction region is discussed in which the magnetic field had a fractal dimension D = 5/3.

Burlaga, L. F.↗

NASA NTRS1986

Fractal structure of the interplanetary magnetic field

Burlaga, L. F.↗

NASA NTRS2007

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.↗

NASA NTRS1989

A fractal approach to probabilistic seismic hazard assessment

The definition of a fractal distribution is that the number of objects (events) N with a characteristic size greater than r satisfies the relation N proportional to r exp - D is the fractal dimension. The applicability of a fractal relation implies that the underlying physical process is scale-invariant over the range of applicability of the relation. The empirical frequency-magnitude relation for earthquakes defining a b-value is a fractal relation with D = 2b. Accepting the fractal distribution, the level of regional seismicity can be related to the rate of regional strain and the magnitude of the largest characteristic earthquake. High levels of seismic activity indicate either a large regional strain or a low-magnitude maximum characteristic earthquake (or both). If the regional seismicity has a weak time dependence, the approach can be used to make probabilistic seismic hazard assessments.

Turcotte, D. L.↗

DOE OSTI2021

Water transport properties of virtual fractal porous media: Implications for the unsaturated transport properties of cement-based materials

Cement-based materials are more and more recognized as fractal materials. From a practical point of view, fractality means that the pore size distribution can be described using fractal scaling law (i.e. power functions). Here, the simplest scaling law making use of a single fractal dimension was used to generate simple and virtual fractal porous media (based on bundles of parallel cylindrical pores). The capillary curve and permeability (relative and intrinsic) of the virtual porous media were then estimated through theoretical and numerical approaches. The results show that: (1) although bereft of any physical basis, van Genuchten equation bears some fractal information; (2) although highly flexible, van Genuchten equation fails to perfectly fit the capillary curves and can thus generate error in inverse analysis (for intrinsic permeability evaluation) and (3) there seems to be a relation between the intrinsic permeability and van Genuchten pressure parameter.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Size distribution of dust grains: A problem of self-similarity

Distribution functions describing the results of natural processes frequently show the shape of power laws, e.g., mass functions of stars and molecular clouds, velocity spectrum of turbulence, size distributions of asteroids, micrometeorites and also interstellar dust grains. It is an open question whether this behavior is a result simply coming about by the chosen mathematical representation of the observational data or reflects a deep-seated principle of nature. The authors suppose the latter being the case. Using a dust model consisting of silicate and graphite grains Mathis et al. (1977) showed that the interstellar extinction curve can be represented by taking a grain radii distribution of power law type n(a) varies as a(exp -p) with 3.3 less than or equal to p less than or equal to 3.6 (example 1) as a basis. A different approach to understanding power laws like that in example 1 becomes possible by the theory of self-similar processes (scale invariance). The beta model of turbulence (Frisch et al., 1978) leads in an elementary way to the concept of the self-similarity dimension D, a special case of Mandelbrot's (1977) fractal dimension. In the frame of this beta model, it is supposed that on each stage of a cascade the system decays to N clumps and that only the portion beta N remains active further on. An important feature of this model is that the active eddies become less and less space-filling. In the following, the authors assume that grain-grain collisions are such a scale-invarient process and that the remaining grains are the inactive (frozen) clumps of the cascade. In this way, a size distribution n(a) da varies as a(exp -(D+1))da (example 2) results. It seems to be highly probable that the power law character of the size distribution of interstellar dust grains is the result of a self-similarity process. We can, however, not exclude that the process leading to the interstellar grain size distribution is not fragmentation at all. It could be, e.g., diffusion-limited growth discussed by Sander (1986), who applied the theory of fractal geometry to the classification of non-equilibrium growth processes. He received D=2.4 for diffusion-limited aggregation in 3d-space.

Henning, TH.↗