Computational Science
Data, Analysis, and Visualization

Data, Analysis, and Visualization

At NREL, scientific data, analysis, and visualization capabilities help advance energy systems integration move energy technologies from fundamental research to real-world application.

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Our world-class visualization experts bring data to life, applying best practices for data management, resolution, and format to ensure a successful translation into visual representations. We explore and implement new interaction and display technologies to support analytical reasoning and decision-making. We research and design novel methods for visually conveying uncertainty and variability in datasets, erroneous or missing data, and data validation. We develop custom software for all stages of the visualization process, including data processing, innovative visualization dashboards, and data pathways to connect to the immersive displays.

Data and Analysis

NREL produces and manages tens of terabytes of data—and millions of related records—through experimentation, simulation, and observation methods. These methods are leading a paradigm shift that academic and industry collaborators leverage to advance their goals.

We use next-generation database clusters and storage systems and transform, translate, and process large-scale data sets to put them into an analysis-ready format. Our advanced analytics approaches ensure the visualizations we design answer the questions we have of the data. Qualitative and quantitative approaches to understand complex scientific data include cutting-edge methods in remote high-performance computing (HPC) visualization, visual mining, and visual exploratory tools.

Human-computer interaction, cognition, and immersive visualization are our research domains that enable researchers to make sense of their data and communicate their results. We empower social computing, learning and education, emergency planning and response, and integrated systems analysis through a variety of multimodal, context-aware interaction techniques.

Our advanced study on computers and algorithmic processes includes their principles, hardware and software designs, applications, and impact on society. We create systems, software, and tools to support the capture, analysis, and management of experimental, observational, and big data sources. Our expertise in this domain includes:

High-throughput and combinatorial experimental data (e.g., photovoltaics, bioenergy, materials)
Time-series data (e.g., observational and meter data management)
Real-time and streaming data (e.g., energy systems hardware-in-the-loop experiments)
Image data (e.g., microscopy and experimental X-ray diffraction and fluorescence)
Statistical modeling and prediction; statistical validation of models and prediction scenarios
Bioinformatics modeling and workflows
Computational approaches to image analysis and computer vision.

Scientific Visualization

Located within the Energy Systems Integration Facility, NREL's Insight Center offers visualization facilities—the Visualization Room and the Collaboration Room—that allow users to walk into and through simulations and examine energy systems from new angles. The Insight Center experience supports knowledge discovery through dynamic interaction and exploration of extremely large, complex, experimental- or simulation-produced data.

Featured Projects

Identifying Next-Generation Materials for Perovskites

Data analysis and visualization nodes on NREL's high-performance computer accelerate model training to identify improved materials for manufacturing perovskites. To investigate a class of redox-active, mixed ionic-electronic conducting metal oxides, HPC-enabled quantum-mechanic calculations model oxygen vacancy in perovskites containing three or more elements. Machine learning-trained and validated models predict oxygen vacancy formation energies in quaternary and quinary perovskites. This depth of material characterization informs strategies to boost solar-to-hydrogen thermal efficiency. DOE's Hydrogen and Fuel Cell Technologies Office funded this project.

2D and 3D Simulations for LED Manufacturing

NREL's high-performance computer is simultaneously tackling a critical manufacturing challenge for thin-film wafers in LEDs and a "grand challenge" computing problem for modeling magnetron plasma discharges at relevant densities in high-powered impulse magnetron sputtering (HiPIMS). HPC-powered simulations in both 2D and 3D are modeling how plasma behaves during the HiPIMS process, helping scientists determine how reactor geometry can be tailored to reliably create thin films with favorable electrical, optical, structural, and chemical properties. On this project, NREL partners with Lawrence Livermore National Laboratory and semiconductor chip manufacturer Applied Materials, with funding from DOE's Advanced Manufacturing Office.