Oct, 2026
ORNL Report
Data and AI Systems FY 2026 Highlights
The Data and AI Systems Section of the Computer Science and Mathematics Division at Oak Ridge National Laboratory conducts research on the data and artificial intelligence foundations of scientific discovery, shortening and automating the path from instrument and simulation to insight at the scale of leadership computing facilities. This report collects 27 project highligh…
Oct, 2026
Journal
Physics-aware adaptive checkpointing with shadow systems for nonlinear PDE simulations
Large-scale simulations of nonlinear partial differential equations (PDEs) that exhibit strongly transient behavior and pattern-forming dynamics produce enormous amounts of data, which, even with modern storage systems, cannot be stored for later curation. Current I/O strategies either write dense time series of snapshots, which is often prohibitive in I/O and storage, or…
Oct, 2026
ORNL Report
From Roadmap to Response: A Community Assessment of Autonomous Science
Autonomous science couples instruments, robots, data systems, and AI agents into workflows that plan and interpret experiments with progressively less human intervention, and a two-year community roadmap published in July 2026 set eighteen milestones for the field. The second Annual Autonomous Workflows Workshop was convened to write such a roadmap and, finding one already…
Oct, 2026
Book Chapter
Probabilistic Forecasting of U.S. County-Level Suicide Mortality Rates (2005–2020): Assessing the Impact of Social Determinants of Health
Understanding the factors that contribute to county-level suicide rates in the U.S. is essential for guiding effective resource allocation and policy interventions. This study introduces a novel approach to incorporating Social Determinants of Health (SDoH) into probabilistic time-series forecasting models to improve predictive accuracy. We applied time-series models to tw…
Sep, 2026
Journal
A block recycled Gmres method with investigations into aspects of solver performance
We propose a block Krylov subspace version of the Gcro-Dr method proposed in [Parks et al.; SISC 2006], which is an iterative method allowing for the efficient minimization of the residual over an augmented Krylov subspace. We offer a clean derivation of our proposed method and discuss methods of selecting recycling subspaces at restart as well as implementation decisions…
Sep, 2026
ORNL Report
Component-Level Analysis of System Degradation, Restoration, and Resilience: Development of a Scalable Grid Interconnection-Point Availability Model
Electric-grid resilience is difficult to quantify because system performance depends on network topology, component reliability, operating configuration, and restoration time. This project produced a scalable component-level framework for estimating resilience at grid interconnection points. The framework converts standard power-system planning models to undirected network…
Sep, 2026
Conference Paper
Profile Generation for GPU Targets
GPU accelerators are ubiquitous, but their ecosystem is far less evolved than the host one. Compiler heuristics are often tuned for CPUs and reused for GPU. Similarly, tooling and more evolved optimization techniques are historically not available on GPU targets. In this work, we address one of these shortcomings and enable profile generation and profile-guided optimizatio…
Aug, 2026
Journal
NeuDiff Agent: a governed AI workflow for single-crystal neutron crystallography
Large-scale facilities increasingly face analysis and reporting latency as a limiting step in scientific throughput, particularly for structural studies that require iterative reduction, integration, refinement and validation. To improve the time to result and analysis efficiency, NeuDiff Agent is introduced as a governed, tool-using AI workflow for TOPAZ at the Spallation…