ML-Shock-Time-Series-Synthesis
Open-source machine learning tools for GPU-batched synthetic shock time-series generation, GPU-accelerated batched Shock Response Spectrum (SRS) computation, and standardized benchmark datasets.
Watts, Adam↗
Engineering topics
Watts, Adam
Publications and source records attributed to Watts, Adam.
Robust and optimal alignment of high-dimensional data using maximum likelihood estimation through a random sample consensus framework
Abstract Correcting spatial orientations of groups of high-dimensional data sets such that they are all in a consistent coordinate system is often a time-consuming and error-prone process. Automation of this process can be accomplished by using Generalized Procrustes Analysis to estimate the relative orientations among a population of high-dimensional data sets. A least squares Procrustes solution is applied through a maximum likelihood estimation and random sample consensus framework for robustness. The likelihood model is comprised of a mixture distribution where inliers are modeled using t -distribution and outliers from a uniform distribution. Applications will focus on a synthetic data set that emulates triaxial acceleration data and also real shock data from a population of triaxial accelerometers. Outliers represent either non-rigid body responses, environmental noise, and/or sensor and data acquisition issues. The intended application for the methodology is to robustly automate the rotation of populations of experimentally collected triaxial accelerometer data sets to a single global coordinate system.
LOSAC↗
Concepts Rookie Book
This book begins with the basic accelerator knowledge required to understand the latter chapters. This is followed by topics from Fermilab accelerator specifics to general accelerator physics concepts. These chapters are accompanied by descriptions of the instrumentation and utilities required to operate a high-energy physics laboratory. Last, we discuss the role of operators in safety at the lab.
43 PARTICLE ACCELERATORS↗
Toward High-Intensity Ionization Chamber Beam Intensity Monitors in Switchyard
Beam intensity in the Switchyard beamlines is monitored by Secondary Emission Monitors ("SEMs") and Ionization Chambers ("ICs"). While less-expensive and easier to calibrate than SEMs, IC performance has typically degraded at higher beam intensities. This paper describes a proof-of-principle modification to a standard IC and associated electronics to increase the upper dynamic range of the system, showing that it is feasible to use ICs for high-intensity beamlines.
43 PARTICLE ACCELERATORS↗
The Fire and Smoke Model Evaluation Experiment—A Plan for Integrated, Large Fire–Atmosphere Field Campaigns
The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models.
54 ENVIRONMENTAL SCIENCES↗