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At least 1,081 records · Page 60

Tool path influence on electric pulse aided deformation during incremental sheet metal forming

Titanium and its alloys are difficult to form at room temperature due to their high flow stress. Super plastic deformation of Ti alloys involves low strain rate forming at very high temperatures which need special tooling which can withstand high temperatures. It was observed that when high current density electric pulse is applied during deformation it reduces the flow stress through electron-dislocation interaction. This phenomenon is known as electro-plasticity. In the present work, importance of tool configuration to enhance the formability without much resistive heating is demonstrated for Incremental Sheet Metal Forming (ISMF). Tool configuration is selected to minimize the current carrying zone in DC pulse aided incremental forming to enhance the formability due to electro plasticity and the same is demonstrated by forming two pyramid shaped components of 30° and 45° wall angles using a Titanium alloy sheet of 0.6 mm thickness. Load measurement indicated that a critical current density is essential for the electro-plasticity to be effective and the same is realized with the load and temperature measurements.

36 MATERIALS SCIENCE↗

Nearside-farside, local angular momentum and resummation theories: Useful tools for understanding the dynamics of complex-mode reactions

A valuable tool for understanding the dynamics of direct reactions is Nearside-Farside (NF) scattering theory. It makes a decomposition of the (resummed) partial wave series for the scattering amplitude, both for the differential cross section (DCS) and the Local Angular Momentum (LAM). This paper makes the first combined application of these techniques to complex-mode reactions. We ask if NF theory is a useful tool for their identification, in particular, can it distinguish complex-mode from direct-mode reactions? We also ask whether NF theory can identify NF interference oscillations in the full DCSs of complex-mode reactions. Our investigation exploits the fact that accurate quantum scattering matrix elements have recently become available for complex-mode reactions. We first apply NF theory to two simple models for the scattering amplitude of a complex-mode reaction: One involves a single Legendre polynomial; the other involves a single Legendre function of the first kind, whose form is suggested by complex angular momentum theory. We then study, at fixed translational energies, four state-to-state complex-mode reactions. They are: S({sup 1}D) + HD → SH + D, S({sup 1}D) + DH → SD + H, N({sup 2}D) +H{sub 2} → NH + H, and H{sup +} + D{sub 2} → HD + D{sup +}. We compare the NF results for the DCSs and LAMs with those for a state-to-state direct reaction, namely, F + H{sub 2} → FH + H. We demonstrate that NF theory is a valuable tool for identifying and analyzing the dynamics of complex-mode reactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

S&T converging trends in dealing with disaster: A review on AI tools

Science and Technology (S&T) has been able to help mankind to solve or minimize problems when arise. Different methodologies, techniques and tools were developed or used for specific cases by researchers, engineers, scientists throughout the world, and numerous papers and articles have been written by them. Nine selected cases such as flash flood, earthquakes, workplace accident, fault in aircraft industry, seismic vulnerability, disaster mitigation and management, and early fault detection in nuclear industry have been studied. This paper looked at those cases, and their results showed nearly 60% uses artificial intelligence (AI) as a tool. This paper also did some review that will help young researchers in deciding the types of AI tools to be selected; thus proving the future trends in S&T.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Charge breeders: Development of diagnostic tools to probe the underlying physics

Charge breeders were developed more than 20 years ago in the context of radioactive ion beam (RIB) production. The main goal is to boost the charge state of a singly charged RIB to a higher value matching the A/Q of a post-accelerator. In that way, the RIB produced at some tens of keV can efficiently be accelerated to energies in a range of few MeV/u up to several tens of MeV/u, which is of interest for nuclear structure and nuclear astrophysics experiments. Two families of charge breeders have been developed: one based on Electron Cyclotron Resonance Ion Sources (ECRISs) suitable for Continuous Wave (CW) operation and another built around Electron Beam Ion Sources (EBISs) used for pulsed post-accelerators. For many years, experimental studies have been carried out to enhance the charge breeding process and improve the extracted beam quality, i.e., purity, intensity, emittance, and time structure. The evolution of the charge breeders is also closely related to the emergence of new facilities delivering even more exotic beams. Diagnostic tools, such as Faraday cups, beam profile monitors, and emittance scanners, are mandatory to tune the machines and evaluate their performances. However, to go beyond that, a better understanding of plasma physics (in ECRIS) and electron-ion interactions (in EBIS), as well as the 1+ beam characteristics, for instance, energy spread transverse emittance, is needed. Therefore, simulation codes modeling the physics phenomena in both type of charge breeders were developed to support the understanding of experimental outputs and to gain insights into non-observable parameters. Nevertheless, more sophisticated diagnostic tools are required to improve the charge breeding performance and to extend the potential applications toward new RIB facilities. This Review will present the two kinds of charge breeders and their technical evolutions. It will review the diagnostic tools and simulation codes employed for operation and evaluation of the internal physics processes.

47 OTHER INSTRUMENTATION↗

Flexible visualization of a 3rd party Intrusion Prevention (Security) tool: A use case with the ELK stack

A difficult aspect of cyber security is the ability to achieve automated real time intrusion prevention across various sets of systems. To this extent, several companies are offering comprehensive solutions that leverage an "accuracy of scale" and moving much of the intelligence and detection on the Cloud, relying on an ever-growing set of data and analytics to increase decision accuracy. Often, they provide tools to visualize the decision workflows in attack prevention (as well as tune the algorithm) but those solutions are not always practical as companies see the problem as "global" that is, from a unified Cyber-security standpoint. However, a key to a successful Cyber-security program is transparency and trust: from an experimental team viewpoint, this specifically means having the ability to immediately see what and from where, who has been blocked and being able to inform the community in case of a revoked access without the need for filing a "ticket" (that may eventually be answered) – in other words, rapid response to their user-base is essential but solutions targeting "sub-groups" in an organization are not often available. We have come up with a versatile solution leveraging the ELK stack (Elasticsearch, Logstash, & Kibana) and an IPS (Intrusion Prevention System) based WAF (Web Application Firewall) from Signal Sciences. Signal Science allows the streaming of detailed logs in a Logstash format suitable for custom solutions for visualization. By combining these two tools, we have strengthened our security posture and enabled individual experiments to monitor their own traffic. Specifically, the IPS WAF provides unique data such as country of origin, protocol, response code, source IP, and paths accessed. In this contribution, we will show how we engineered a visualization solution so experiment groups could access a dashboard with predefined graphs but also, where they can create individual customizable dashboards used to display blocked traffic and troubleshoot latency issues. We will discuss the details and procedures for developing and configuring these tools and how it benefits cyber security postures across our scientific based environment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The 'last mile' of data handling: Fermilab's IFDH tools

IFDH (Intensity Frontier Data Handling), is a suite of tools for data movement tasks for Fermilab experiments and is an important part of the FIFE[2] (Fabric for Intensity Frontier [1] Experiments) initiative described at this conference. IFDH encompasses moving input data from caches or storage elements to compute nodes (the 'last mile' of data movement) and moving output data potentially to those caches as part of the journey back to the user. IFDH also involves throttling and locking to ensure that large numbers of jobs do not cause data movement bottlenecks. IFDH is realized as an easy to use layer that users call in their job scripts (e.g. 'ifdh cp'), hiding the low level data movement tools. One advantage of this layer is that the underlying low level tools can be selected or changed without the need for the user to alter their scripts. Logging and performance monitoring can also be added easily. This system will be presented in detail as well as its impact on the ease of data handling at Fermilab experiments.

Lyon, Adam L.↗

Calibration and validation of a spar-type floating offshore wind turbine model using the FAST dynamic simulation tool

In this study, high-quality computer simulations are required when designing floating wind turbines because of the complex dynamic responses that are inherent with a high number of degrees of freedom and variable metocean conditions. In 2007, the FAST wind turbine simulation tool, developed and maintained by the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL), was expanded to include capabilities that are suitable for modeling floating offshore wind turbines. In an effort to validate FAST and other offshore wind energy modeling tools, DOE funded the DeepCwind project that tested three prototype floating wind turbines at 1/50 th scale in a wave basin, including a semisubmersible, a tension-leg platform, and a spar buoy. This paper describes the use of the results of the spar wave basin tests to calibrate and validate the FAST offshore floating simulation tool, and presents some initial results of simulated dynamic responses of the spar to several combinations of wind and sea states. Wave basin tests with the spar attached to a scale model of the NREL 5-megawatt reference wind turbine were performed at the Maritime Research Institute Netherlands under the DeepCwind project. This project included free-decay tests, tests with steady or turbulent wind and still water (both periodic and irregular waves with no wind), and combined wind/wave tests. The resulting data from the 1/50th model was scaled using Froude scaling to full size and used to calibrate and validate a full-size simulated model in FAST. Results of the model calibration and validation include successes, subtleties, and limitations of both wave basin testing and FAST modeling capabilities.

17 WIND ENERGY↗

Open access to high-level data and analysis tools in the CMS experiment at the LHC

The CMS experiment, in recognition of its commitment to data preservation and open access as well as to education and outreach, has made its first public release of high-level data under the CC0 waiver: up to half of the proton-proton collision data (by volume) at 7 TeV from 2010 in CMS Analysis Object Data format. CMS has prepared, in collaboration with CERN and the other LHC experiments, an open-data web portal based on Invenio. The portal provides access to CMS public data as well as to analysis tools and documentation for the public. The tools include an event display and histogram application that run in the browser. In addition a virtual machine containing a CMS software environment along with XRootD access to the data is available. Within the virtual machine the public can analyse CMS data, example code is provided. As a result, we describe the accompanying tools and documentation and discuss the first experiences of data use.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data

Abstract Summary Here we introduce Lipid Mini-On, an open-source tool that performs lipid enrichment analyses and visualizations of lipidomics data. Lipid Mini-On uses a text-mining process to bin individual lipid names into multiple lipid ontology groups based on the classification (e.g. LipidMaps) and other characteristics, such as chain length. Lipid Mini-On provides users with the capability to conduct enrichment analysis of the lipid ontology terms using a Shiny app with options of five statistical approaches. Lipid classes can be added to customize the user’s database and remain updated as new lipid classes are discovered. Visualization of results is available for all classification options (e.g. lipid subclass and individual fatty acid chains). Results are also visualized through an editable network of relationships between the individual lipids and their associated lipid ontology terms. The utility of the tool is demonstrated using biological (e.g. human lung endothelial cells) and environmental (e.g. peat soil) samples. Availability and implementation Rodin (R package: https://github.com/PNNL-Comp-Mass-Spec/Rodin), Lipid Mini-On Shiny app (https://github.com/PNNL-Comp-Mass-Spec/LipidMiniOn) and Lipid Mini-On online tool (https://omicstools.pnnl.gov/shiny/lipid-mini-on/). Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

RAG-3D: A search tool for RNA 3D substructures

In this study, to address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive High Throughput One‐Pot Analysis of Glycoproteins through Tool for Rapid Analysis of Glycopeptide by Permethylation (TRAP) Method.

Glycoproteins plays key roles in various cellular functions such as protein folding, protein targeting, receptor function, cell–cell recognition, protein stability, signaling, and other cellular functions. Currently a comprehensive and universal tool for the automated analysis of glycopeptides through their tandem mass spectrometry and data processing is a tedious process. We recently developed a method, Tool for Rapid Analysis of glycopeptide by Permethylation (TRAP), that simplifies glycoprotein analysis by integrating glycan sequencing and glycopeptide analysis in a single experiment. We employed this approach for the detailed analysis of glycosidic linkages, composition, glycan sequencing, glycosylation site mapping and sequencing of peptide moiety of glycopeptides of glycoproteins from both prokaryotes and eukaryotes. Here we are presenting an easy to use, robust, suitable for large as well as small sample sets and also cost‐effective glycoprotein analysis tool through TRAP approach. A permethylation protocol which can be automated and suitable for reliable permethylation of glycopeptides from the protease digest of glycoproteins was developed. Initial studies on glycopeptides from a model glycoprotein bovine RNAse B indicates that improved sensitivity and throughput of permethylation reactions can be achieved in conducting the reaction in microscale. This approach would enable convenient, rapid, and reliable high‐throughput screening of protein glycosylation and can be employed as a cost‐effective kit for glycosylated biomarker discoveries. In order to improvise the comprehensive glycosylation analysis and throughput, we have also developed an LC‐MS/MS platform for the analysis of glycopeptides processed through TRAP. We have conducted the analysis of standard glycoproteins such as bovine RNase B, human transferrin, and bovine fetuin and our preliminary results indicate that TRAP hyphened with LC‐MS/MS enables characterization of isomers of each glycoform at each glycosylation sites of complex glycoprotein mixtures. Support or Funding Information This research was supported by the National Institutes of Health (NIH) funded research, Grant R21GM122633; resource for biomedical glycomics, Grant P41GM103490; instrument grant, Grant S10OD018530; and U.S. Department of Energy grant, Grant DE‐SC0015662, to the Complex Carbohydrate Research Center. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Shajahan, Asif↗

Tools for probing new physics with newly discovered gamma-ray targets

Here, we present a computational tool, TweedleDEE, for empirically modeling diffuse gamma-ray background emission in a 1° region of the sky, using publicly available gamma-ray data off-axis from the region of interest. This background model allows a user to perform a purely data-driven search for anomalous localized sources of gamma-ray emission, including new physics. A major application of this tool would be in searching for dark matter annihilation in newly discovered astrophysical targets. For this purpose, we derive a scaling relation for determining velocity-dependent 𝐽-factors using only the stellar parameters, which can be broadly applied to obtain dark matter constraints from new targets. As an application of these tools, we use TweedleDEE and MADHATv2 to perform the first search for dark matter annihilation in the newly discovered Leo VI dwarf spheroidal galaxy, and present model constraints for a variety of choices of the annihilation channel and velocity dependence of the cross section.

dark matter↗

XUV-driven plasma switch for THz: new spatio-temporal overlap tool for XUV–THz pump–probe experiments at FELs

A simple and robust tool for spatio-temporal overlap of THz and XUV pulses in in-vacuum pump–probe experiments is presented. The technique exploits ultrafast changes of the optical properties in semiconductors (i.e. silicon) driven by ultrashort XUV pulses that are probed by THz pulses. This work demonstrates that this tool can be used for a large range of XUV fluences that are significantly lower than when probing by visible and near-infrared pulses. This tool is mainly targeted at emerging X-ray free-electron laser facilities, but can be utilized also at table-top high-harmonics sources.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Hybrid Dynamic/Steady-State Tool With Protection Simulation for Cascading-Outage Analysis of Extreme Events in Power Systems

The bulk electric power grid is subject to vulnerabilities from component outages, which in certain combinations (extreme events) might lead to cascading outages. Some of these outages can be severe enough to trigger brownouts and blackouts. Much is known about mitigating the first few failures near the beginning of a cascade, but there are few established methods and tools for directly analyzing the risks of cascading component outages over a longer time scale. Current power system tools have limited ability to perform detailed and accurate cascading-outage analysis, which could be computationally intensive. The Dynamic Contingency Analysis Tool (DCAT) enables power system planning engineers to more realistically assess the consequences of extreme contingencies and potential cascading events across their systems and interconnections. DCAT has several unique features: (i) detailed hybrid dynamic and steady-state analysis of power systems to mimic real-world cascading outages, (ii) detailed modeling of protection systems embedded in the dynamic simulation, (iii) simulation of corrective action after transients, (iv) simulation of islanding , and (v) high-performance computing capability to simulate a large number of contingencies in a reasonable time. DCAT outputs will help find technically sound solutions to reduce the risk of cascading outages. This paper provides details of DCAT methodology and shows its capabilities with extreme events on real-world cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Virtual Trajectories for I–24 MOTION: Data and Tools

This paper introduces a toolbox for generating virtual trajectories, which we call VT-tools v1.0, to address challenges in analyzing large but imperfect trajectory datasets. VT-tools v1.0 is able to generate virtual trajectories from large raw datasets that are typically challenging to process due to their size. We also provide a set of these virtual trajectories resulting from I–24 MOTION INCEPTION v1.0 data and demonstrate the practical utility of these trajectories in as-sessing speed variability and travel times across different lanes within the INCEPTION dataset. The virtual trajectory toolbox opens future research on traffic waves and their impact on energy. The VT-tools v1.0 Python implementation and sample data are publicly available at https://i24motion.org.

42 ENGINEERING↗

Effective Tooling for Linked Data Publishing in Scientific Research

Challenges that make it difficult to find, share, and combine published data, such as data heterogeneity and resource discovery, have led to increased adoption of semantic data standards and data publishing technologies. To make data more accessible, interconnected and discoverable, some domains are being encouraged to publish their data as Linked Data. Consequently, this trend greatly increases the amount of data that semantic web tools are required to process, store, and interconnect. In attempting to process and manipulate large data sets, tools–ranging from simple text editors to modern triplestores– eventually breakdown upon reaching undefined thresholds. This paper offers a systematic approach that data publishers can use to categorize suitable tools to meet their data publishing needs. We present a real-world use case, the Resource Discovery for Extreme Scale Collaboration (RDESC), which features a scientific dataset(maximum size of 1.4 billion triples) used to evaluate a toolbox for data publishing in climate research. This paper also introduces a semantic data publishing software suite developed for the RDESC project.

Purohit, Sumit↗

Real-Time Inertia Estimation Tool Implementation Based on Probing Signals

As renewable energy penetration increases and the traditional generators retire in power grids, system inertia decreases and exhibits significant daily fluctuations. Furthermore, fast frequency responses (FFRs) provided by the inverter-based resources (IBRs) begin to playa very critical role and bring new challenges to real-time system inertia monitoring due to the difficulties of quantifying its artificial inertia contribution. Thus, necessitating an accurate real-time inertia estimation tool will not only benefit the secure power grid operations, but also provide insights on assessing the artificial inertia contribution from the IBRs. This paper presents a probing-based real-time inertia estimation tool that has been validated through a power-hardware-in-the-Ioop (PHIL) test system using identical hardware battery energy storage system (BESS) and control in an actual power grid. Preliminary results indicate high estimation accuracy of the developed tool and pave the way for the field test and deployment.

inverter-based resources↗

PATHA: Performance Analysis Tool for HPC Applications

Large science projects rely on complex workflows to analyze terabytes or petabytes of data. These jobs are often running over thousands of CPU cores and simultaneously performing data accesses, data movements, and computation. It is difficult to identify bottlenecks or to debug the performance issues in these large workflows. In order to address these challenges, we have developed Performance Analysis Tool for HPC Applications (PATHA) using the state-of-art open source big data processing tools. Our framework can ingest system logs to extract key performance measures, and apply the most sophisticated statistical tools and data mining methods on the performance data. Furthermore, it utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of PATHA, we conduct a case study on the workflows from an astronomy project known as the Palomar Transient Factory (PTF). This study processed 1.6 TB of system logs collected on the NERSC supercomputer Edison. Using PATHA, we were able to identify performance bottlenecks, which reside in three tasks of PTF workflow with the dependency on the density of celestial objects.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗