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At least 343 records · Page 19

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

Koshak, William↗

Slides for LDRD review presentation of 18A12-131FP, "Cyber-Secure Physical Layer Security in Millimeter Wave Communications"

Objective Enhance cyber security, protection, and assurance of advanced mmWave wireless communications in the presence of unauthorized devices and intruders with novel capabilities within the physical layer. Significance Wireless communications using millimeter waves (mmWave) in the GigaHertz (GHz) band is a key new technology that will play a major role in the 5th Generation (5G) wireless networks. Cyber-physical solutions for other frequency bands are not directly applicable to mmWave technologies. We propose to validate the hypotheses that: 1) communications can be better protected from eavesdropping and cyber intrusion with security features built within the mmWave physical layer, 2) User authentication can be conducted in a non-intrusive manner and with high probability of success by the use of physical channel variations of mmWaves which get scattered by a human body.

99 GENERAL AND MISCELLANEOUS↗

The BBC network radio time and frequency standard and its role in the provision of the Greenwich time signal

The British Broadcasting Corporation (BBC) has broadcast the Greenwich Time Signal (GTS) on its networks since 1924. Up to February 1990 this signal was generated by the Royal Greenwich Observatory (RGO) in England. The BBC was informed that the RGO was moving its location to Cambridge and might not be able to continue to provide the Greenwich Time Service. The BBC in its role of a public service broadcaster believed that a long tradition of providing a time signal to its listeners should be upheld, and as such decided to seek alternative methods of provision. In parallel with this activity, an in-house requirement arose to re-engineer time switch equipment and provide new facilities for digital audio projects. As both requirements have a common engineering core, a decision was taken to design and procure a Time and Frequency Standard that could generate the Greenwich Time Signal to the same specification adhered to by the RGO, and provide additional time and frequency facilities. The concept of time and time/frequency dissemination as used in a broadcast network is discussed, as well as the details of an engineering solution to the requirements of BBC Network Radio.

Mcilroy, Jim J.↗

At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms

The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.

Janich, Karl W.↗

Access Control of Web- and Java-Based Applications

Cybersecurity has become a great concern as threats of service interruption, unauthorized access, stealing and altering of information, and spreading of viruses have become more prevalent and serious. Application layer access control of applications is a critical component in the overall security solution that also includes encryption, firewalls, virtual private networks, antivirus, and intrusion detection. An access control solution, based on an open-source access manager augmented with custom software components, was developed to provide protection to both Web-based and Javabased client and server applications. The DISA Security Service (DISA-SS) provides common access control capabilities for AMMOS software applications through a set of application programming interfaces (APIs) and network- accessible security services for authentication, single sign-on, authorization checking, and authorization policy management. The OpenAM access management technology designed for Web applications can be extended to meet the needs of Java thick clients and stand alone servers that are commonly used in the JPL AMMOS environment. The DISA-SS reusable components have greatly reduced the effort for each AMMOS subsystem to develop its own access control strategy. The novelty of this work is that it leverages an open-source access management product that was designed for Webbased applications to provide access control for Java thick clients and Java standalone servers. Thick clients and standalone servers are still commonly used in businesses and government, especially for applications that require rich graphical user interfaces and high-performance visualization that cannot be met by thin clients running on Web browsers

Tso, Kam S.↗

Physics-constrained machine learning for electrodynamics without gauge ambiguity based on Fourier transformed Maxwell’s equations

We utilize a Fourier transformation-based representation of Maxwell’s equations to develop physics-constrained neural networks for electrodynamics without gauge ambiguity, which we label the Fourier–Helmholtz–Maxwell neural operator method. In this approach, both of Gauss’s laws and Faraday’s law are built in as hard constraints, as well as the longitudinal component of Ampère–Maxwell in Fourier space, assuming the continuity equation. An encoder–decoder network acts as a solution operator for the transverse components of the Fourier transformed vector potential, $\hat{A}_⟂(k,t)$, whose two degrees of freedom are used to predict the electromagnetic fields. This method was tested on two electron beam simulations. Among the models investigated, it was found that a U-Net architecture exhibited the best performance as it trained quicker, was more accurate and generalized better than the other architectures examined. We demonstrate that our approach is useful for solving Maxwell’s equations for the electromagnetic fields generated by intense relativistic charged particle beams and that it generalizes well to unseen test data, while being orders of magnitude quicker than conventional simulations. We show that the model can be re-trained to make highly accurate predictions in as few as 20 epochs on a previously unseen data set.

97 MATHEMATICS AND COMPUTING↗

High speed all-optical networks

An inherent problem of conventional point-to-point WAN architectures is that they cannot translate optical transmission bandwidth into comparable user available throughput due to the limiting electronic processing speed of the switching nodes. This report presents the first solution to WDM based WAN networks that overcomes this limitation. The proposed Lightnet architecture takes into account the idiosyncrasies of WDM switching/transmission leading to an efficient and pragmatic solution. The Lightnet architecture trades the ample WDM bandwidth for a reduction in the number of processing stages and a simplification of each switching stage, leading to drastically increased effective network throughputs.

Chlamtac, Imrich↗

Deep space network energy program

If the Deep Space Network is to exist in a cost effective and reliable manner in the next decade, the problems presented by international energy cost increases and energy availability must be addressed. The Deep Space Network Energy Program was established to implement solutions compatible with the ongoing development of the total network.

Friesema, S. E.↗

Delay/Disruption Tolerant Networking

Communicating from Earth to any spacecraft is a complex challenge, largely due to the extreme distances involved. When data are transmitted and received across thousands and even millions of miles, the delay and potential for disruption or data loss is significant. Delay/Disruption Tolerant Networking (DTN) is NASA’s solution to reliable internet working for space missions.

delay tolerant networking↗

End-to-End Data Movement Using MPI-IO Over Routed Terabots Infrastructures

Scientific discovery is nowadays driven by large-scale simulations running on massively parallel high-performance computing (HPC) systems. These applications each generate a large amount of data, which then needs to be post-processed for example for data mining or visualization. Unfortunately, the computing platform used for post processing might be different from the one on which the data is initially generated, introducing the challenge of moving large amount of data between computing platforms. This is especially challenging when these two platforms are geographically separated since the data needs to be moved between computing facilities. This is even more critical when scientists tightly couple their domain specific applications with a post processing application. The paper presents a solution for the data transfer between MPI applications using a dedicated wide area network (WAN) terabit infrastructure. The proposed solution is based on parallel access to data files and the Message Passing Interface (MPI) over the Common Communication Infrastructure (CCI) for the data transfer over a routed infrastructure. In the context of this research, the Energy Sciences Network (ESnet) of the U.S. Department of Energy (DOE) is targeted for the transfer of data between DOE national laboratories.

Vallee, Geoffroy R↗

Structural Analysis and Electrochemical Properties of Bimetallic Palladium-Platinum Aerogels Prepared by a Two-Step Gelation Process

Multimetallic aerogels have emerged as promising unsupported and high-surface-area metal materials for different applications in heterogeneous catalysis and electrochemistry, which are fabricated using a gelation process characterized by the controlled aggregation of metallic nanoparticles to form a macroscopic network structure in aqueous solution. However, the achievement of the structural homogeneity of the multimetallic aerogels in terms of the diameter of the nanochains and the chemical composition at the nano- and the macro-scale is still a great challenge. In this paper, we investigated two Pd-Pt aerogels prepared by the two-step gelation method. The structural homogeneity and chemical distribution of both metals inside the aerogels were analyzed by using high-resolution (scanning) transmission microscopy, energy-dispersive X-ray spectroscopy, extended X-ray absorption fine structure spectroscopy and cyclic voltammetry. The Pd-Pt aerogels show the presence of Pd/Pt-rich domains inside the long-range framework. It is evident that the initial monometallic features dominate over alloying during the gelation process. Although the same synthetic approach for Pd-Pt aerogels with different atomic ratios was used, we observed that the sizes of these monometallic domains varied strongly between the Pd-rich and Pt-rich aerogels. The presence of such metal clusters influenced the electrochemical robustness of the Pd-Pt aerogels dramatically. Further, electrochemical durability investigations revealed that the aerogels with a high content of Pd are less stable because of the gradual dissolution of the less noble metal particularly inside the Pd-rich domains. A chemical and structural homogeneity might improve the lifetime of the Pd-Pt aerogels under electrochemical conditions. In this work, we provide a better understanding of the structure and chemical distribution of the bimetallic aerogel framework prepared by the two-step gelation process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Refueling infrastructure planning in intercity networks considering route choice and travel time delay for mixed fleet of electric and conventional vehicles

The range anxiety has been a major factor that affects the market acceptance of electric vehicles. Even with the recent development of battery technologies, a lack of charging stations and range anxiety are still significant concerns, specifically for intercity trips. This calls for more investments in building charging stations and advancing battery technologies to increase the market share of electric vehicles and improve sustainability. This study suggests a configuration for plug-in electric vehicle charging infrastructure to support long-distance intercity trips of electric vehicles at the network level. A model is proposed to minimize the total system cost including infrastructure investment (building charging stations/spots) and travel time delays (charging time, waiting time in the queue, and detour time to access charging stations). This study fills existing gaps in the literature by capturing realistic patterns of travel demand and considering flow-dependent charging delays at charging stations. Furthermore, the proposed model, which is formulated as a mixed-integer program with nonlinear constraints, solves the optimization problem at the network level. At the network level, impacts of charging station locations on the traffic assignment problem with a mixed fleet of electric and conventional vehicles need to be considered. To this end, a traffic assignment module is integrated with a simulated annealing algorithm. The numerical experiments show a satisfactory application of the model for a full-scale case study (intercity network in Michigan). The solution quality and efficiency of the proposed solution algorithm are evaluated against those of an enumeration approach for a small case study. The results suggest that even for the current market share and charging stations’ setting, a significant investment is needed to support intercity trips without range anxiety issues and with acceptable delays. Additionally, through sensitivity analyses, the required infrastructure and battery investments to support intercity trips with acceptable delays are established for hypothetical increased market shares and battery size in the future.

42 ENGINEERING↗

On the need for the light elements primary process (LEPP)

Extant chemical evolution models underestimate the galactic production of Sr, Y, and Zr as well as the solar system abundances of s-only isotopes with 90 < A < 130. To solve this problem, an additional (unknown) process has been invoked, the so-called light element primary process (LEPP). In this paper we investigate possible alternative solutions. Based on Full Network Stellar evolutionary calculations, we investigate the effects on the solar system s-only distribution induced by the inclusion of some commonly ignored physical processes (e.g., rotation) or by the variation of the treatment of convective overshoot, mass loss, and the efficiency of nuclear processes. Our main findings are (1) at the epoch of the formation of the solar system, our reference model produces supersolar abundances for the whole s-only distribution, even in the range 90 < A < 130, (2) within errors, the s-only distribution relative to {sup 150}Sm is flat, (3) the s-process contribution of the less massive AGB stars (M < 1.5 M {sub ⊙}) as well as of the more massive ones (M > 4.0 M {sub ⊙}) are negligible, (4) the inclusion of rotation implies a downward shift of the whole distribution with a higher efficiency for the heavy s-only isotopes, leading to a flatter s-only distribution, (5) different prescriptions on convection or mass loss produce nearly rigid shifts of the whole distribution. In summary, a variation of the standard paradigm of AGB nucleosynthesis would allow reconciliation of model predictions with solar system s-only abundances. Nonetheless, the LEPP cannot be definitely ruled out because of the uncertainties still affecting stellar and galactic chemical evolution models.

79 ASTRONOMY AND ASTROPHYSICS↗

Efficient Data-Driven Geologic Feature Characterization from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm

Conventional seismic techniques for detecting the subsurface geologic features are challenged by limited data coverage, computational inefficiency and subjective human factors. We developed a novel data-driven geological feature characterization approach based on pre-stack seismic measurements. Our characterization method employs an efficient and accurate machine learning method to extract useful subsurface geologic features automatically. Specifically, we use kernel ridge regression to account for the nonlinear relationship between seismic data and geological features. We moreover employ kernel tricks to avoid the explicit nonlinear mapping and infinite dimension of feature space. Yet, the conventional kernel ridge regression can be computationally prohibitive because of the large volume of seismic measurements. We employ a data reduction technique in combination with the conventional kernel ridge regression method to improve the computational efficiency and reduce memory usage. In particular, we utilize a randomized numerical linear algebra technique, named Nyström method, to effectively reduce the dimensionality of the feature space without compromising the information content required for accurate characterization. We provide thorough computational cost analysis to show the efficiency of our new geological feature characterization methods. We validate the performance of our method in characterizing geologic fault zones because faults play an important role in various subsurface applications. Our numerical examples demonstrate that our new characterization method significantly improves the computational efficiency while maintaining comparable accuracy. Interestingly, we demonstrate that our approach yields a speedup ratio on the order of ~102 to ~103 in a multicore computational environment.

58 GEOSCIENCES↗

Incremental Threshold Scheme Enabled IoT Group Key Management

Cyber landscape evolves rapidly. Internet of Things (IoT) and Edge Computing (EC) have rapidly become an integral part of the modern computing infrastructure. It is expected that there will be more than 50 billion active and connected IoT devices by 2025 [1]. Pervasive IoT/EC creates unprecedented opportunities bridging the gap between previously segregated cyber and physical spaces. However, this progress also brings along new security challenges. IoT devices typically have limited computation, communication, and storage resources. This leads to security architecture designs such as using symmetric keys for group communication. While secure and efficient in stable network settings, symmetric key solutions are ill-adapted for IoT's highly dynamic device mobility behavior and frequent group membership turnover. Whenever IoT members leave a group, the known symmetric keys cannot be made forgotten, posing a serious vulnerability. This leads to frequent re-groupings that require expensive re-authentication, key regeneration, and key redistribution in order to maintain IoT/EC security. We present a novel symmetric key management framework that integrate an Incremental Threshold Scheme (ITS) cryptographical function into communication protocol's key rotation mechanism to allow for secure and efficient symmetric key communication group member node revocation. This ITS-enabled key management framework alleviates the need of frequent and expensive re-grouping and re-keying needed by today's large and dynamic IoT/EC operations. We further applied this ITS-enabled key management framework to a distributed IoT/EC-integrated publish and subscribe framework for applicability validation.

Li, Mingyan↗