Apr 26, 2019 - Quantifying human exposure to everyday particulate matter: A study on emissions from 3D printers

indoor air quality particulate matter emissions 3D printing additive manufacturing

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Marina Vance

10:10 am
322 Fryklund Hall

Abstract

The field of indoor air quality continually grows to accommodate novel pollutant sources as they are developed. Office equipment such as laser printers and photocopiers are known to emit volatile and particulate air pollutants, especially ultrafine aerosols. With the recent development and popularization of 3D printers, studies are needed to understand their potential emissions to indoor environments. 3D printing (also referred to as additive manufacturing or rapid prototyping) is a bottom-up process of creating a three-dimensional object layer by layer. As low-cost 3D printers are continually developed, personal-use units have become more popular in everyday indoor environments such as homes, offices, and schools. As shown in by studies published in recent years, heating and extrusion of polymeric materials generates ultrafine aerosols.

This talk will focus on an investigation of aerosols emissions from the operation of a 3D printer in a chamber study and also under real-use conditions. Specific objectives of this study were (1) to measure the time- and size-resolved emissions of ultrafine aerosols from the operation of a FDM 3D printer in a chamber study, (2) to gain insight into the chemistry of these aerosols through electron microscopy coupled with energy dispersive X-ray spectroscopy and Raman spectroscopy, and also (3) to perform comparative aerosol concentration measurements under real-use conditions in a variety of indoor environments.

Bio

Dr. Marina Vance is an Assistant Professor in Mechanical Engineering and Environmental Engineering at the University of Colorado Boulder. Her research is focused on applying engineering tools to better understand and minimize human exposure to novel environmental contaminants, especially nanoparticles or ultrafine aerosols, from everyday activities and the use of consumer products.

Lecture archive

Apr 19, 2019 - Billion-degree of freedom Computational Dynamics: from granular flows to 3D printing and on to river fording simulation

numerical analysis computational dynamics multi-physics 3D printing

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Dan Negrut

10:10 am
322 Fryklund Hall

Abstract

This talk will focus on how a Lagrangian perspective on dynamics is used to capture the time evolution of complex systems, e.g., granular flows, fluid-solid interaction problems, etc. In this context, the aspects that turn out to be more challenging are tied to the handling of friction, contact, geometry, large deformations and numerical solution scaling. The talk will highlight modeling and numerical solution techniques developed to address several of these challenges. Our solution methodology contributions have been implemented in an open-source simulation platform called Chrono, which is available on GitHub and used by hundreds of individuals to analyze large multi-physics dynamics problems. The talk will touch on several applications tied to granular dynamics, 3D printing and additive manufacturing, robotics, and ground vehicle mobility.

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Fluid-solid interaction simulation of a vehicle engaged in a fording maneuver. This scenario has been simulated both using an SPH-based solution of the Navier-Stokes equations of motion, and using a many-body dynamics approach in which the fluid dynamics was modeled using a collection of 1.4 million interacting rigid spheres. Collection of chain-mail sheets of material as they are dropped in a 3D printing volume for a reverse engineering analysis used to figure out where each link of the yet-to-be-printed fabric lies.

Bio

Dan Negrut received his Mechanical Engineering Ph.D. in 1998 from the University of Iowa. He leads the Simulation-Based Engineering Lab at UW-Madison. The lab’s projects focus on high performance computing, computational dynamics, terramechanics, robotics, autonomous vehicles, and fluid-solid interaction problems. Dr. Negrut received in 2009 a National Science Foundation Career Award. Since 2010 he is an NVIDIA CUDA Fellow.

Lecture archive

Apr 12, 2019 - Estimating competitive rowing kinematic metrics: An undergraduate sports biomechanics research project

rowing kinematics biomechanics sports

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Jason Moore

10:10 am
322 Fryklund Hall

Abstract

Competitive rowing highly values boat position and velocity data for real-time feedback during training, racing and post-training analysis. The ubiquity of smartphones with embedded position (GPS) and motion (accelerometer) sensors motivates their possible use in these tasks. In this project, we investigate the use of two real-time digital filters to achieve highly accurate but reasonably priced measures of boat speed and distance traveled. Both filters combine acceleration and location data to estimate boat distance and speed; the first using a complementary frequency response-based filter technique, the second with a Kalman filter formalism that includes adaptive, real-time estimates of effective accelerometer bias. The estimates of distance and speed from both filters were validated and compared with accurate reference data from a 10 Hz differential GPS system with better than 1 cm precision, in experiments using two subjects (an experienced club-level rower and an elite rower) in two different boats on a 300 m course. Relative to single channel (smartphone GPS only) measures of distance and speed, the complementary filter improved the accuracy and precision of boat speed, boat distance traveled, and distance per stroke by 44%, 42%, and 73%, respectively, while the Kalman filter improved the accuracy and precision of boat speed and distance per stroke by 51% and 72%, respectively. Both filters demonstrate promise as general purpose methods to substantially improve estimates of important rowing performance metrics.

Bio

Jason K. Moore is an assistant teaching professor in the Mechanical and Aerospace Engineering Department at the University of California, Davis. He leads the Laboratorium of Marvelous Mechanical Motum and teaches courses in dynamics and mechanical design. He completed postdoctoral research on the control of lower limb exoskeletons in Ton van den Bogert’s Human Motion and Control Laboratory at Cleveland State University in 2015. He received both his PhD ‘12 and MSc ‘07 under Mont Hubbard and Ron Hess on the research topic “Human Control of a Bicycle”. He is a 2008 Fulbright Scholar to the Netherlands where he worked in Arend Schwab’s Bicycle Dynamics Laboratory at Delft University of Technology. His 2004 Mechanical Engineering BSc is from Old Dominion University. He is currently active in the scientific Python computing, open science, biomechanics, vehicle dynamics, and open educational resources communities.

Lecture archive