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Results for “topological data analysis”

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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Ensemble models for circuit topology estimation, fault detection and classification in distribution systems

This paper presents a methodology for simultaneous fault detection, classification, and topology estimation for adaptive protection of distribution systems. The methodology estimates the probability of the occurrence of each one of these events by using a hybrid structure that combines three sub-systems, a convolutional neural network for topology estimation, a fault detection based on predictive residual analysis, and a standard support vector machine with probabilistic output for fault classification. The input to all these sub-systems is the local voltage and current measurements. A convolutional neural network uses these local measurements in the form of sequential data to extract features and estimate the topology conditions. The fault detector is constructed with a Bayesian stage (a multitask Gaussian process) that computes a predictive distribution (assumed to be Gaussian) of the residuals using the input. Since the distribution is known, these residuals can be transformed into a Standard distribution, whose values are then introduced into a one-class support vector machine. The structure allows using a one-class support vector machine without parameter cross-validation, so the fault detector is fully unsupervised. Finally, a support vector machine uses the input to perform the classification of the fault types. All three sub-systems can work in a parallel setup for both performance and computation efficiency. In conclusion, we test all three sub-systems included in the structure on a modified IEEE123 bus system, and we compare and evaluate the results with standard approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1978

Crustal evolution inferred from Apollo magnetic measurements

The topology of lunar remanent fields is investigated by analyzing simultaneous magnetometer and solar wind spectrometer data. The diffusion model proposed by Vanyan (1977) to describe the field-plasma interaction at the lunar surface is extended to describe the interaction with fields characterized by two scale lengths, and the extended model is compared with data from three Apollo landing sites (Apollo 12, 15 and 16) with crustal fields of differing intensity and topology. Local remanent field properties from this analysis are compared with high spatial resolution magnetic maps obtained from the electron reflection experiment. It is concluded that remanent fields over most of the lunar surface are characterized by spatial variations as small as a few kilometers. Large regions (50 to 100 km) of the lunar crust were probably uniformly magnetized early in the evolution of the crust. Smaller scale (5 to 10 km) magnetic sources close to the surface were left by bombardment and subsequent gardening of the upper layers of these magnetized regions. The small scale sized remanent fields of about 100 gammas are measured by surface experiments, whereas the larger scale sized fields of about 0.1 gammas are measured by the orbiting subsatellite experiments.

Dyal, P.↗

DOE OSTI2015

Quantitative analysis of intermolecular interactions in orthorhombic rubrene

Rubrene is one of the most studied organic semiconductors to date due to its high charge carrier mobility which makes it a potentially applicable compound in modern electronic devices. Previous electronic device characterizations and first principles theoretical calculations assigned the semiconducting properties of rubrene to the presence of a large overlap of the extended π-conjugated core between molecules. We present here the electron density distribution in rubrene at 20 K and at 100 K obtained using a combination of high-resolution X-ray and neutron diffraction data. The topology of the electron density and energies of intermolecular interactions are studied quantitatively. Specifically, the presence of C π ...C π interactions between neighbouring tetracene backbones of the rubrene molecules is experimentally confirmed from a topological analysis of the electron density, Non-Covalent Interaction (NCI) analysis and the calculated interaction energy of molecular dimers. A significant contribution to the lattice energy of the crystal is provided by H—H interactions. The electron density features of H—H bonding, and the interaction energy of molecular dimers connected by H—H interaction clearly demonstrate an importance of these weak interactions in the stabilization of the crystal structure. Finally, the quantitative nature of the intermolecular interactions is virtually unchanged between 20 K and 100 K suggesting that any changes in carrier transport at these low temperatures would have a different origin. The obtained experimental results are further supported by theoretical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Exploring the Effects of Node Topology, Connectivity, and Metal Identity on the Binding of Nerve Agents and Their Hydrolysis Products in Metal–Organic Frameworks

Recent studies have shown that metal–organic frameworks (MOFs) built from hexanuclear M(IV) oxide cluster nodes are effective catalysts for nerve agent hydrolysis, where the properties of the active sites on the nodes can strongly influence the reaction energetics. The connectivity and metal identity of these M6 nodes can be easily tuned, offering extensive opportunities for computational screening to predict promising new materials. Thus, we used density functional theory (DFT) to examine the effects of node topology, connectivity, and metal identity on the binding energies of multiple nerve agents and their corresponding hydrolysis products. By computing an optimization metric based on the relative binding strengths of key hydrolysis reaction species (water, agent, and bidentate-bound products), we predicted optimal M6 nodes for hydrolyzing specific nerve agent and simulant molecules, where our results are in qualitative agreement with observed experimental trends. This analysis highlighted the notion that no single metal or node topology is optimal for all possible organophosphates, suggesting that MOFs should be selected based on the agent of interest. Using the large amount of data generated from our DFT calculations, we then derived quantitative structure–activity relationship (QSAR) models to help explain the complex trends observed in the binding energies. Through linear regression, we identified the most important descriptors for describing the binding of nerve agents and their hydrolysis products to M6 nodes. These results suggested that both molecular and node properties, including both structural and chemical features, collectively contribute to the binding energetics. By performing a thorough statistical analysis, we showed that our QSAR models are capable of making quantitatively accurate binding energy predictions for nerve agents and their hydrolysis products in a wide variety of M(IV)-MOFs. In conclusion, the insights gained herein can be used to guide future experiments for the synthesis of MOFs with enhanced catalytic activity for organophosphate hydrolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Deletions of chromosomal regulatory boundaries are associated with congenital disease

Background: Recent data from genome-wide chromosome conformation capture analysis indicate that the human genome is divided into conserved megabase-sized self-interacting regions called topological domains. These topological domains form the regulatory backbone of the genome and are separated by regulatory boundary elements or barriers. Copy-number variations can potentially alter the topological domain architecture by deleting or duplicating the barriers and thereby allowing enhancers from neighboring domains to ectopically activate genes causing misexpression and disease, a mutational mechanism that has recently been termed enhancer adoption. Results: We use the Human Phenotype Ontology database to relate the phenotypes of 922 deletion cases recorded in the DECIPHER database to monogenic diseases associated with genes in or adjacent to the deletions. We identify combinations of tissue-specific enhancers and genes adjacent to the deletion and associated with phenotypes in the corresponding tissue, whereby the phenotype matched that observed in the deletion. We compare this computationally with a gene-dosage pathomechanism that attempts to explain the deletion phenotype based on haploinsufficiency of genes located within the deletions. Up to 11.8% of the deletions could be best explained by enhancer adoption or a combination of enhancer adoption and gene-dosage effects. Conclusions: Our results suggest that enhancer adoption caused by deletions of regulatory boundaries may contribute to a substantial minority of copy-number variation phenotypes and should thus be taken into account in their medical interpretation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Nanocalorimetric evidence for nematic superconductivity in the doped topological insulator Sr 0.1 Bi 2 Se 3

Spontaneous rotational-symmetry breaking in the superconducting state of doped ${\mathrm{Bi}}_{2}{\mathrm{Se}}_{3}$ has attracted significant attention as an indicator for topological superconductivity. High-resolution calorimetry of the single-crystal ${\mathrm{Sr}}_{0.1}{\mathrm{Bi}}_{2}{\mathrm{Se}}_{3}$ provides unequivocal evidence of a twofold rotational symmetry in the superconducting gap by a bulk thermodynamic probe, a fingerprint of nematic superconductivity. The extremely small specific heat anomaly resolved with our high-sensitivity technique is consistent with the material's low carrier concentration proving bulk superconductivity. The large basal-plane anisotropy of ${H}_{c2}$ (${\mathrm{{\Gamma}}}_{\mathrm{exp}}=3.5$) is attributed to a nematic phase of a two-component topological gap structure $\mathbf{{\eta}}=({{\eta}}_{1},{{\eta}}_{2})$ and caused by a symmetry-breaking energy term ${\delta}(|{{\eta}}_{1}{|}^{2}{-}|{{\eta}}_{2}{|}^{2}){T}_{c}$. A quantitative analysis of our data excludes more conventional sources of this twofold anisotropy and provides an estimate for the symmetry-breaking strength ${\delta}{\approx}0.1$, a value that points to an onset transition of the second order parameter component below 2 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1989

Detecting and diagnosing SSME faults using an autoassociative neural network topology

An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

Ali, M.↗

DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

data-driven forecasting↗

DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources: Preprint

contingencies↗

DOE OSTI2014

A three-dimensional view of the thermal structure in a super-penumbral canopy

We investigate the three-dimensional (3D) thermal topology in a super-penumbral canopy of an active region (AR). We derive temperature stratifications in the AR by an inversion of the Ca II IR line at 854.2 nm, assuming local thermal equilibrium. We find that about half of the radially oriented fibrils in the super-penumbral canopy form short, low-lying (h < 1 Mm) loops in the 3D temperature cube. These closed loops connect from bright grains in or close to the penumbra to the photosphere a few Mms away from the sunspot. The other half of the fibrils monotonically rise with distance from the sunspot. Many of the fibrils show a central dark core and two lateral brightenings in line-core intensity images. The corresponding velocity image shows fibrils that are as wide as the fibrils seen in intensity without a lateral substructure. Additionally, we study a feature from a different class of structures without prominent mass flows. Its 3D topology is formed by two parallel, closed loops that connect patches of opposite polarity. We present evidence that the inverse Evershed flow into the sunspot in the lower chromosphere is the consequence of siphon flows along short loops that connect photospheric foot points. The dark-cored structure of the chromospheric fibrils cannot have a convective origin because of their location above regular granulation. The dark core most likely results from an opacity difference between the central axis and the lateral edges caused by the significant flow speed along the fibrils.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2002

CAPRI: Using a Geometric Foundation for Computational Analysis and Design

CAPRI (Computational Analysis Programming Interface) is a software development tool intended to make computerized design, simulation and analysis faster and more efficient. The computational steps traditionally taken for most engineering analysis (Computational Fluid Dynamics (CFD), structural analysis, etc.) are: Surface Generation, usually by employing a Computer Aided Design (CAD) system; Grid Generation, preparing the volume for the simulation; Flow Solver, producing the results at the specified operational point; Post-processing Visualization, interactively attempting to understand the results. It should be noted that the structures problem is more tractable than CFD; there are fewer mesh topologies used and the grids are not as fine (this problem space does not have the length scaling issues of fluids). For CFD, these steps have worked well in the past for simple steady-state simulations at the expense of much user interaction. The data was transmitted between phases via files. In most cases, the output from a CAD system could go IGES files. The output from Grid Generators and Solvers do not really have standards though there are a couple of file formats that can be used for a subset of the gridding (i.e. PLOT3D) data formats and the upcoming CGNS). The user would have to patch up the data or translate from one format to another to move to the next step. Sometimes this could take days. Instead of the serial approach to analysis, CAPRI takes a geometry centric approach. CAPRI is a software building tool-kit that refers to two ideas: (1) A simplified, object-oriented, hierarchical view of a solid part integrating both geometry and topology definitions, and (2) programming access to this part or assembly and any attached data. The connection to the geometry is made through an Application Programming Interface (API) and not a file system.

Haimes, Robert↗

DOE OSTI2016

Data and programs in support of network analysis of genes and their association with diseases

The network-based approaches that were employed in order to depict the relationships between human genetic diseases and their associated genes are described. Towards this direction, monopartite disease-disease and gene-gene networks were constructed from bipartite gene-disease association networks. The latter were created by collecting and integrating data from three diverse resources, each one with different content, covering from rare monogenic disorders to common complex diseases. Moreover, topological and clustering graph analyses were performed. The methodology and the programs presented in this article are related to the research article entitled “Network analysis of genes and their association with diseases”.

Disease-disease networks↗

DOE OSTI2019

Resilience Analysis of DC Microgrids under Denial of Service Threats

This paper develops a resilience analysis framework to study the fault ride-through capability of direct current (DC) microgrids in unknown denial of service (DoS) cyber incidents. DoS can be a frequent threat to DC microgrids with advanced controllers that hinge on active information exchanges: it can paralyze data communications and cause control ineptness or even system instability. Furthermore, we show that temporal DoS incidents render the DC microgrid cyber-physical topology and parameters time-varying and cause them to jump between faulty conditions. As existing DC microgrid stability analysis results are primarily developed from time-invariant systems, they might not be valid for the DoS interrupted systems. In this paper, we seek to study whether a DC microgrid is resilient against time-varying unknown DoS incidents. The problem is formulated as a stability analysis problem for a system with randomly switching dynamics. Scalable conditions are developed to provide provable resilience guarantees. In addition, we exploit the special structure of the conditions to yield quantified resilience measure by convex optimization techniques. As a result, the measure can be used for the evaluation of the resilience of different DC microgrid design against DoS incidents. We demonstrate the effectiveness of the proposed work using simulation case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Distribution System Secondary Circuit Parameter Estimation for Model Calibration

To analyze and coordinate the operation of distribution systems with rapidly increasing amounts of PV, more accurate distribution system models are required, especially for the distribution system secondary (low-voltage) circuits down to the point of common coupling for distributed PV. There is a growing need for automated procedures to calibrate the distribution system secondary circuit models that are typically either not modeled at all or are modeled with a lower level of detail than the better modeled medium-voltage systems. This report presents an accurate, flexible, and computationally efficient method to use measurement data to estimate secondary circuit series impedance parameters in existing utility feeder models. The parameter estimation method assumes well-modeled primary circuit models, known secondary circuit topologies, and AMI active power, and reactive power measurements at all the loads in the secondary circuit. The method also requires AMI voltage measurement at most of the loads in the secondary circuit but can handle loads that do not have voltage measurements. No existing secondary circuit model information is needed, except for topology. The method is based on the well-known linearized voltage drop approximation and linear regression. The performance of the method is demonstrated on a three-phase test circuit with ten different secondary circuit topologies and on the Georgia Tech campus distribution system with AMI data. The developed method can be utilized to improve existing utility feeder models for more accurate analysis and operation with ubiquitous distributed PV interconnected on the low-voltage circuits.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1997

Global MHD Simulation of Mesoscale Structures at the Magnetospheric Boundary

We have continued our modeling of the solar wind/magnetosphere interaction for steady solar Wind conditions by carrying out a series of 3 D global magneto-hydrodynamics (MHD) simulations using a set of predetermined solar wind parameters as input to the code. With the results from the simulations that we ran last year for two other dipole tilts (0 and 35 deg), we have 36 data sets to study the dynamics of mesoscale structures at the magnetospheric boundary. We have started the analysis of these runs to investigate geometrical properties and the topology of the magnetic and electric fields for the different solar wind regimes and orientations considered. Preliminary results indicate that merging sites are consistent with patterns proposed for antiparallel merging at the dayside magnetopause. Another goal of this investigation is to establish the displacement of the cusp region as a function of the solar wind dynamic pressure, IMF direction and magnetic field dipole tilt. One of the difficulties of that study is to locate precisely the cusp in the simulation results. We have used several case studies to establish a series of criteria in to permit a routine identification of that location. We need now to process the rest of the simulation results using these criteria to obtain statistical results.

Berchem, Jean↗

NASA NTRS2013

Coarse-Grain Bandwidth Estimation Techniques for Large-Scale Space Network

In this paper, we describe a top-down analysis and simulation approach to size the bandwidths of a store-andforward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. We use these techniques to estimate the wide area network (WAN) bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network.

Cheung, Kar-Ming↗

NASA NTRS2009

Magnetopause Reconnection Impact Parameters from Multiple Spacecraft Magnetic Field Measurements

We present a novel technique that exploits multiple spacecraft data to determine the impact parameters of the most general form of magnetic reconnection at the magnetopause. The method consists of a superposed epoch of multiple spacecraft magnetometer measurements that yields the instantaneous magnetic spatial gradients near a magnetopause reconnection site. The gradients establish the instantaneous positions of the spacecraft relative to the reconnection site. The analysis is well suited to evaluating the spatial scales of singular field line reconnection, which is characterized by a two-dimensional x-type topology adjacent and perpendicular to a reconnecting singular field line. Application of the method to Cluster data known to lie in the vicinity of a northward IMF reconnection site establishes a field topology consistent with singular field line reconnection and a normal magnetic field component of 20 nT. The corresponding current structure consists of a 130 km sheet possibly embedding a thinner. bifurcated sheet.

Wendel, Deirdre E.↗

DOE OSTI2013

A Posteriori Ontology Engineering for Data-Driven Science

Science—and biology in particular—has a rich tradition in categorical knowledge management. This continues today in the generation and use of formal ontologies. Unfortunately, the link between hard data and ontological content is predominately qualitative, not quantitative. The usual approach is to construct ontologies of qualitative concepts, and then annotate the data to the ontologies. This process has seen great value, yet it is laborious, and the success to which ontologies are managing and organizing the full information content of the data is uncertain. An alternative approach is the converse: use the data itself to quantitatively drive ontology creation. Under this model, one generates ontologies at the time they are needed, allowing them to change as more data influences both their topology and their concept space. We outline a combined approach to achieve this, taking advantage of two technologies, the mathematical approach of Formal Concept Analysis (FCA) and the semantic web technologies of the Web Ontology Language (OWL).

Gessler, Damian Dg↗