Latent Learning with pyroMind.2020
This paper is for the Proceedings of the IEEE Big Data 2021 Conference (IEEE BigData 2021) published by IEEE Computer Society.
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This paper is for the Proceedings of the IEEE Big Data 2021 Conference (IEEE BigData 2021) published by IEEE Computer Society.
Machine Learning in Oil and Gas 2021 Conference, April 15, 2021
Our society is transitioning fast into the digital age, spurred by development of cheap and new sensing technology, breakthroughs in computing, and development of efficient algorithms for optimization. This transition is also visible in the field of wastewater treatment and is driving new model developments, especially by exploiting the large data sets available with many utilities. Not surprisingly, WRRmod2021 had featured a strong session on ‘data-driven models and digitalization’ focused on this hot topic. At the same time, engineering practice calls for more robust models for performance evaluation and optimization of both conventional facilities and innovative processes. As a result, the WRRmod2021 program also exhibited sessions on modelling of new process units (e.g., aerobic granular sludge), modelling of the nitrogen cycle, and integrated/plant-wide modelling.
This presentation is for the National Association for State Community Services Programs (NASCSP) Annual Conference. The authors provide an overview of several tools and resources, including the Weatherization Assistant, Standard Work Specifications, Installer Badges Toolkit, Grantee Training and Continuous Improvement, and Instructional Systems Design (ISD) Training.
SPIE Photonics West 2021 (Conference), Virtual, March 6-11, 2021
SPIE Photonics West 2021 (Conference), Virtual, March 6-11, 2021
SPIE Photonics West 2021 (Conference), Virtual, March 6-11, 2021
MOLTEN 2021 (Conference), Virtual, February 20-24, 2021
Corrosion 2021 (Conference), Virtual, April 19-30, 2021
Corrosion 2021 (Conference), Virtual, April 19-30, 2021
MOLTEN 2021 (Conference), Virtual, February 20-24, 2021
SciX 2021 Conference, Providence, RI, September 26 - October 1, 2021
We report the High-Luminosity Large Hadron Collider (HL-LHC) will deliver more than ten times the integrated luminosity of the previous runs combined. Meeting its stricter throughput requirements poses new challenges to the Trigger and Data Acquisition (TDAQ) systems of the LHC experiments. Introduced in the framework of the ATLAS experiment’s HL upgrade, the Global Trigger (GT) is a new subsystem which will perform offline-like algorithms on full-granularity calorimeter data. The implementation of the GT’s functionality is firmware-focused and is composed of three layers: multiplexing (or data aggregating), global event processing, and demultiplexing interface to the central trigger processor. Each layer will be composed of several, similar nodes, hosted on replicas of identical hardware, the Global Common Module (GCM), an ATCA front board which is designed to be adopted throughout the entire GT subsystem. This article proceeds from the TWEPP 2021 conference and presents the GCM hardware design, performed in 2020, and focuses on some key results of its extensive testing performed in 2021.
Support from the Department of Energy proved instrumental in supporting the work of Global Council for Science and the Environment (GCSE) on synthetic research, analysis, and community engagement, oriented around the themes and discussions from the GCSE Drawdown 2021 Conference — Research to Action: Science and Solutions for a Planet Under Pressure. These efforts helped inform and enhance the societal relevance of the knowledge that has been generated through the conference and, at the same time, advance the scientific insights acquired through synthesis and scientific translation efforts. The work centered on three main objectives: 1) documentation of findings from the completed GCSE 2021, culminating in the publication of a synthesis report; 2) development and vetting of integrated use cases that illustrate synthesis methods and enable scientific outreach, communications, and translational discussions among universities and the broader research community; and 3) strengthening the scientific basis for energy education research by sharing findings in university-educator fora.
Type I edge-localized modes (ELMs) in the Experimental Advanced Superconducting Tokamak (EAST) were completely suppressed via boron powder injection into the X-point region of an upper-single null configuration over a wide range of operating conditions (2.8 < P aux < 7.5 MW, 3.8 × 10 19 < n e < 6 × 10 19 m -3 , RF-only and RF + NBI heating scenarios, both grad-B drift directions, and even He ion majority plasmas) (Sun et al. in Nucl. Fusion, 2020). A window of edge B concentration for stable long pulse operation was identified: too low and ELMs return, too high and the discharge suffers radiative collapse. The injection of boron powder above the minimum for ELM suppression coincided with the occurrence of an edge harmonic oscillation detected in magnetics (both on the high-field side and low-field side), in AXUV diodes near the upper X-point, divertor Dα emission, and in a range of other diagnostics (Diallo et al. in: Proceedings of 2020 IAEA fusion energy conference, 2021). Furthermore, no harmonic oscillation was observed when ELMs were present, and stored energy was slightly increased at constant density during ELM suppression. Core tungsten emission during ELM suppression either increased or decreased relative to ELMy H-mode, but the W emission was maintained at acceptable levels. The threshold B injection rate was measured for several conditions, and found to increase with heating power. Li powder injection into comparable discharges also resulted in a short phase of ELM suppression, but density and stored energy both decreased due to the strong pumping effect of lithium; no edge harmonic oscillation was observed with Li injection, indicating that the ELM suppression mechanisms differ. The new set of B-seeded, ELM-suppressed discharges exhibited certain characteristics of quiescent H-mode (Burrell et al. in Phys Plasmas 8:2153, 2001), but did not require high shear, counter beams, etc. The wide operating window and compatibility with RF-only discharges paves the way for future experiments targeting long pulse H-mode discharges with complete ELM suppression.
Data bandwidth, timing resolution and resource utilization in readouts of radiation detectors are a constant challenge. Event driven solutions are pushing against well-trenched framed solutions. The idea for an asynchronous readout architecture called EDWARD ( E vent- D riven W ith A ccess and R eset D ecoder) was presented at the TWEPP 2021 conference. Here we show the progress of our work which resulted in two chip prototypes. The first one, named 3FI65P1, is a full device with the analog pixel circuitry suited for full-field fluorescence imaging. It is already manufactured, and preliminary results are presented. Finally, the second chip, named EDWARD65P1, contains digital pulse generators with Poisson-exponential distribution in each pixel for extraction of the performance matrix of the EDWARD architecture alone.
Last year, we refactored the major components of the SpotSDC visualization platform and added a visualization component for fault tolerance boundary. Also, we designed a new analysis framework to understand an application resiliency with a significantly less amount of samples compared to previous approaches. We evaluated the visualization platform and analysis framework for multiple critical HPC computation kernels and collected evidence for the effectiveness of the method developed. We published the findings of our research in the IEEE Transactions on Visualization and Computer Graphics (TVCG), the top journal in visualization. Moreover, we submitted a new paper, "Understanding a Program's Resiliency Through Error Propagation," to the PPOPP 2021 conference.
The objective of this exploratory project is to determine the feasibility of using laser diffraction, structured light 3D scanning, and x-ray diffraction for in-situ assessment and inspection of metal directed energy deposition (DED) that is applied to repair components such as engine parts in remanufacturing. During this project, we have successfully published or submitted at least one journal article for each subtask that we identified. One of our conference paper and presentation has won “best paper award” from Manufacturing & Design Division in the Institute of Industrial and Systems Engineers (IISE) Annual Conference 2021. Through this seed grant, we successfully validated the concepts and proved the three in-situ monitoring techniques work well to predict some defects generation during direct energy deposition. We submitted follow-up proposals to continue work on this topic.