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Benchmarking Current and Emerging Approaches to Infrasound Signal Classification

Albert, Sarah; Linville, Lisa

Low frequency sound ≤ 20 Hz, known as infrasound, is generated by a variety of natural and anthropogenic sources. Following an event, infrasonic waves travel through a dynamic atmosphere that can change on the order of minutes. This makes infrasound event classification a difficult problem as waveforms from the same source type can look drastically different. Event classification usually requires ground truth information from seismic or other methods. This is time consuming, inefficient, and does not allow for a classification if the event locates somewhere other than a known source, the location accuracy is poor, or ground truth from seismic data is lacking. Here we compare the performance of the state of the art for infrasound event classification, support vector machine (SVM), to the performance of a convolutional neural network (CNN), a method that has been proven in tangential fields such as seismology. For a 1-class catalog consisting of only volcanic activity and earthquake events, the 4-fold average SVM classification accuracy is 75%, while it is 74% when using a CNN. Classification accuracies from the 4-class catalog consisting of the most common infrasound events detected at the global scale are 55% and 56% for the SVM and CNN architectures, respectively. These results demonstrate that using a CNN does not increase performance for infrasound event classification. This suggests that SVM should be the preferred classification method as it is a simpler and more trustworthy architecture and can be tied to the physical properties of the waveforms. The SVM and CNN algorithms described in this paper are not yet generalizable to other infrasound event catalogs. We anticipate this study to be a starting point for the development of large and comprehensive, systematically labeled, infrasound event catalogs as such catalogs will be necessary to provide an increase in the value of deep learning on event classification.

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TYPE SAND Report YEAR 2019
DOIOSTI

Energy Storage Policy Summaries for the Global Energy Storage Database

Mcnamara, Joseph W.

This report includes energy storage policy analysis from six states: Arizona, California, Massachusetts, Nevada, New Mexico, and New York. These summaries offer prototypes for summaries that will subsequently be prepared for all 50 states (and territories). There is presently a shortage of comprehensive energy storage policy analysis that public utility regulators can call upon to inform policymaking in their own jurisdictions. The state policy summaries that will be offered publicly on the Global Energy Storage Database (GESDB) will include analysis on the executive directives, legislation, regulations pertaining to energy storage that have been adopted by an individual state, along with perspective on the remaining policy issues pertaining to storage that a state will be likely to address in the future. It is anticipated that public utility regulators in particular will find the database to be a useful resource in benchmarking policy approaches critical to the continued development of an energy storage marketplace in the U.S., including policy approaches specific to storage and renewables procurement targets, interconnection standards, valuation of energy storage, rate reform and tariff design specific to energy storage, consideration of multiple uses for storage at the distribution level, and potential revisions to existing state net metering programs to accommodate an expected growth of energy storage technologies.

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TYPE SAND Report YEAR 2019
DOIOSTI

Guralp Affinity Evaluation for SNL Infrasound Testbed

Slad, George W.

Sandia National Laboratories has tested and evaluated a new digitizer, the Affinity, manufactured by Guralp Systems. This digitizer is used to record sensor output for seismic and infrasound monitoring applications. The purpose of the digitizer evaluation was to measure the performance characteristics in such areas as sensitivity, self-noise, dynamic range, system noise, relative transfer function, analog bandwidth, harmonic distortion, common mode, cross talk, timing tag accuracy and timing drift. The Affinity provides eight, rather the typical six, channels of 24 bit high sample rate digitization. Moreover, it also provides 16 single-ended, 24 bit resolution, low sample rate auxiliary channels. The Affinity digitizer is undergoing these tests prior to installation in the FACT site infrasound test bed.

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TYPE SAND Report YEAR 2019
DOIOSTI

Novel Applications of Scanning Ultrafast Electron Microscopy (SUEM)

Nakakura, Craig Y.; Celio, Kimberlee C.

The Scanning Ultrafast Electron Microscope (SUEM) was used to image a wide array samples using a variety of standard and non-standard operating conditions on a custom system built in Org. 8942. The ability of this technique to produce high-quality images was assessed during this one year LDRD. To obtain details about the devices imaged, as well as the experimental details, please refer to the classified report from the project manager, Rich Dondero, or the NSP IA lead, Kristina Czuchlewski.

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TYPE SAND Report YEAR 2019
DOIOSTI

Resilient Computing with Dynamical Systems

Rothganger, Fredrick R.; Cardwell, Suma G.

We reformulate fundamental numerical problems to run on novel hardware inspired by the brain. Such "neuromorphie hardware consumes less energy per computation, promising a means to augment next-generation exascale computers. However, their programming model is radically different from floating-point machines, with fewer guarantees about precision and communication. The approach is to pass each given problem through a sequence of transformations (algorithmic "reductions") which change it from conventional form into a dynamical system, then ultimately into a spiking neural network. Results for the eigenvalue problem are presented, showing that the dynamical system formulation is feasible.

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TYPE SAND Report YEAR 2019
DOIOSTI

Compatible Particle Discretizations (Final LDRD Report)

Bochev, Pavel B.; Bosler, Peter A.; Kuberry, Paul; Perego, Mauro; Peterson, Kara J.; Trask, Nathaniel A.

This report summarizes the work performed under a three year LDRD project aiming to develop mathematical and software foundations for compatible meshfree and particle discretizations. We review major technical accomplishments and project metrics such as publications, conference and colloquia presentations and organization of special sessions and minisimposia. The report concludes with a brief summary of ongoing projects and collaborations that utilize the products of this work.

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TYPE SAND Report YEAR 2019
DOIOSTI

Site Preparation Integration and Operation of Mini-Sierra ART System

Davis, Kevin; Gauntt, Nathan E.

ATS platforms are some of the largest, most complex, and most expensive computer systems installed in the United States at just a few major national laboratories. This milestone describes our recent efforts to procure, install, and test a machine called Vortex at Sandia National Laboratories that is compatible with the larger ATS platform Sierra at LLNL. In this milestone, we have 1) configured and procured a machine with similar hardware characteristics as Sierra ATS, 2) installed the machine, verified its physical hardware, and measured its baseline performance, and 3) demonstrated the machine’s compatibility with Sierra ATS, and capacity for useful development and testing of Sandia computer codes (such as SPARC), including uses such as nightly regression testing workloads.

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TYPE SAND Report YEAR 2019
DOIOSTI
Results 21101–21200 of 99,299
Results 21101–21200 of 99,299