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Institute for the Design of Advanced Energy Systems

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The Institute for the Design of Advanced Energy Systems (IDAES) was formed in 2016 to develop new advanced Process Systems Engineering (PSE) capabilities to improve the efficiency and reliability of the existing fleet of coal-fired power plants while accelerating the development of a broad range of advanced fossil energy systems. Website: idaes.org

Ensuring the Integrity of Exascale Scientific Data

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This project, "Toward a Hardware/Software Co-Design Framework for Ensuring the Integrity of Exascale Scientific Data", takes a broad look at several aspects of security and scientific integrity issues in HPC systems. This project is supported by the US Department of Energy’s Office of Science’s Advanced Scientific Computing Research (ASCR) program.

AmeriFlux

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AmeriFlux is a network of PI-managed sites measuring ecosystem CO2, water, and energy fluxes in North, Central and South America. AmeriFlux observations have been instrumental in defining the relationships between environmental drivers and responses of whole ecosystems, which can be spatialized using machine learning methods like neural networks or genetic algorithms informed by remote sensing products.

Collaboration Shines in Materials Project Success

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The Materials Project aims to take the guesswork out of finding the best material for a job—be it a new battery electrode or a lightweight spacecraft body—by making the characteristics of every inorganic compound available to any interested scientist. IDF contributes to the design and deployment of the Materials Project infrastructure. » Read More

The Integrated Data Frameworks (IDF) group works in a wide variety of scientific domains, building tools and models to allow scientists to move from the “raw” data generated by simulations, experiments, and observations, to a combined quality-controlled view of the data that they can easily manipulate to gain scientific insight. Often this process will involve extensive work on “cleaning” and transforming data in custom data pipelines, and often there will also be a strong user interface component to either the pipelines or the final data products.

Overall, our approach is distinguished by a strong focus on usability and user research, early and often in the software design process. We have learned that designing the best systems can only occur when we have the best understanding of the constraints, needs, and culture of the scientists who will use it. The IDF group works closely with the Usable Software Systems group on research and development of user-centered solutions.

Research

IDAES

The Institute for the Design of Advanced Energy Systems (IDAES) project is developing next generation computational tools for Process Systems Engineering (PSE) of advanced energy systems to enable their rapid design and optimization. The IDAES…

Inferring Computing Activity Using Physical Sensors

This project involves using power data for monitoring use of computing systems, including supercomputers and large computing centers. By using power data, as opposed to data provided by the computing environment itself, the technology collects the…

AmeriFlux

AmeriFlux datasets provide the crucial linkage between organisms, ecosystems, and process-scale studies at climate-relevant scales of landscapes, regions, and continents, which can be incorporated into biogeochemical and climate models. When viewed…

The Materials Project

The Materials Project is a high-throughput framework developed by MIT and LBNL and subsequently extended by collaborators at the Lawrence Berkeley Laboratory and National Energy Research Scientific Computing (NERSC). This Center, funded by the DOE…

Carbon Capture Simulation Initiative

The CCSI Toolset will accelerate the development and deployment cycle for bringing new Carbon Capture and Storage (CCS) technologies to market. Integrated Data Frameworks (and other Data Science & Technology Department) personnel are leading the…

Integrated Multi Scale Machine Learning for the Power Grid

The goal of this project is to create advanced, distributed data analytics capability to provide visibility and controllability to distribution grid operators. This project is supported by the U.S. Department of Energy’s Grid Modernization…

NetSage - an open privacy-aware network measurement, analysis, and visualization service

NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to address the needs of today’s international networks. Modern science is increasingly data-driven and collaborative in nature, producing petabytes…

Cybersecurity for Energy Delivery Systems Research and Development

The Berkeley Lab Data Science and Technology Department is an active participant in a number of projects in the arena of cybersecurity for energy delivery systems.  Recently, this work has been funded largely via DOE's Cybersecurity for Energy…

Power Grid Threat Detection and Response with Data Analytics

The goal of this project is to develop technologies and methodologies to protect the nation's power grid from advanced cyber and all-hazard threats. This will be done through the collection of disparate data and the use of advanced analytics to…

Toward a Hardware/Software Co-Design Framework for Ensuring the Integrity of Exascale Scientific Data

Scientific data today is at risk due to how it is collected, stored, and analyzed in highly disparate computing systems. How can we make claims about the integrity of data as it traverses open, international networks and via instruments and systems…

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