Arctic Master Works Webinar Series
As part of an effort to foster scientific collaboration among Arctic nations, the Master Works webinar series highlights the impact of advanced computing in health sciences, energy, and environmental research.
This webinar series brings together scientists from the United States, Iceland, and the Nordic countries to discuss compelling scientific challenges of common interest being addressed through advanced computing and to explore opportunities for collaboration. These Master Works events feature two 30-minute presentations followed by a 30-minute panel session, for a total of 90 minutes each.
Webinar Series Organizing Committee
- Morris Riedel, associate professor, University of Iceland
- David Martin, Industry Partnerships and Outreach manager, Argonne National Laboratory
- Henning Úlfarsson, assistant professor, Reykjavik University
- Steve Hammond, senior research advisor, National Renewable Energy Laboratory
Upcoming Arctic Master Works Webinars
June 10, 2021
9 a.m. MDT, 10 a.m. CDT, 15 GMT
The ongoing global coronavirus pandemic, first identified in December 2019, continues to have significant widespread social and economic impacts, including disruptions to education systems, workplaces, and supply chains. This webinar and panel session, which is part of the Arctic Master Works Webinar Series, features three experts in the field who will discuss advances in modeling, testing, therapies, and COVID-19 transmission. Learn more and register for the Health Sciences webinar.
Anna Sigridur Islind
Argonne National Laboratory
The Arctic is warming at a rate of almost twice the global average. This is contributing to rising sea levels, changes in precipitation patterns, increasing severe weather events, and significant changes in sea ice extent. This webinar and panel session features two expert speakers who will discuss the state of sea ice modeling and atmospheric modeling as well as challenges for the future. Learn more about the upcoming Environmental webinar.
Los Alamos National Laboratory
Iceland Meteorological Office
Dec. 9, 2020
Digitalization for the Future Weather-Driven Low-Carbon Energy System
Henrik Madsen – Professor and Head of Section, Department of Applied Mathematics and Computer Science, Technical University of Denmark
Today energy systems are operated and planned such that the production follows the demand. However, a future low-carbon society calls for systems where demand follows the weather-driven energy production. This highlights a need for a disruption of the whole spectrum of methods ranging energy systems operation to planning. Most importantly we need methods for enabling energy flexibility at all levels of the society; examples being buildings, supermarkets, wastewater treatment plants, districts, and cities. Madsen describes a framework called the Smart-Energy Operating-System for controlling the electricity load in integrated energy systems using big data analytics, artificial intelligence, edge/fog/cloud computing and Internet of things solutions. The framework can also provide ancillary services (like congestion management, voltage, and frequency control) for systems with a large penetration of wind and solar power.
Understanding the Challenges with Integrating Very High Levels of Wind and Solar in Electric Power Systems
Ben Kroposki – Director of the Power Systems Engineering Center, NREL, and Institute of Electrical and Electronics Engineers Fellow
Around the world, electric utilities are setting 100% clean energy goals of which renewable technologies will be a major player. Variable renewable energy like wind and solar photovoltaics differs from conventional generation in that they use power electronic converters instead of synchronous generators to connect to electric power grids. At high levels, there are several technical challenges that must be addressed to ensure reliable and economic operations. Kroposki discusses the challenges and solutions to operating power system with high levels of variable renewables and how power electronic interfaces can be used to solve some of these challenges.
Oct. 28, 2020
Towards Automatic Analysis of Sleep To Improve Health
Jacky Mallet – Assistant Professor, Computer Science, Reykjavik University
Applying artificial intelligence and machine learning to multisensor inputs offers the possibility of significantly improving detection and analysis of increasingly common conditions such as sleep apnea that can cause major health issues over time if left untreated. One of the most important indicators of potential sleep apnea is pathological snoring. Mallet reviews some of the challenges of working in this area and the progress we have made with audio analysis of snoring and other signals as a basis for detecting apneic events.
Overview of High Performance Computing and Artificial Intelligence Computing For COVID-19 in the United States
Rick Stevens – Argonne National Laboratory's Associate Laboratory Director for Computing, Environment, and Life Sciences
Stevens describes some of the ongoing work in the United States applying high performance computing and artificial intelligence to COVID-19 related research. He also discusses the COVID-19 high performance computing consortium that joins U.S. supercomputing centers, computing and technology vendors, and federal agencies to provide high performance computing cycles to the SARS- CoV-2/COVID-19 research community and to streamline access to resources via a single proposal mechanism. Additionally, Stevens discusses the collaboration amongst U.S. Department of Energy laboratories formed to apply advanced computing to the problem of developing molecular therapeutics for COVID-19.