Autonomous laboratories are poised to revolutionize research in materials, pharmaceuticals, biology, and other fields. Autonomous experiments combine robotic automation with AI/ML decision making and control. Data streaming — moving data automatically from the instruments where it is collected to storage and compute services —is a core technology for autonomous research because it allows data to be accessed, processed, and acted on in real time. For current (non-autonomous) labs, streaming can vastly improve data throughput, consistency, and reliability.

HEMI Short Course – OpenMSI: Data streaming for autonomous laboratory research

This HEMI short course will introduce students to OpenMSIStream, a new cross-platform tool for streaming and sharing among data-producing and data-consuming devices. Participants will learn how to:

• Install OpenMSIStream on their own computer (Windows, macOS, or Linux)
• Stream actual instrument readings in real time to remote storage
• Access streamed data
• Set up automated processes to analyze and act on the data.

Students will leave the short course with the skills necessary to implement OpenMSIStream to stream and process data in their own labs to create new functionality, enable automated workflows, and participate in development of forward-looking, autonomous research paradigms.

This event is intended for students and postdocs who are interested in autonomous experimental research. Seating is limited. Those interested in participating will be able to sign up for a waitlist once capacity has been reached.

DATE

January 18-19, 2024

LOCATION

Johns Hopkins Homewood campus

REGISTRATION

Follow this link to register

Instructor: Dr. Sankaran Mahadevan (John R. Murray Sr. Professor of Engineering Professor of Civil and Environmental Engineering, Professor of Mechanical Engineering Director, NSF-IGERT Doctoral Program in Reliability and Risk Engineering and Management Co-Director, Laboratory for System Integrity and Reliability Vanderbilt University)

Location: Johns Hopkins University, Homewood Campus, Baltimore, MD

About the course: Model-based simulation is attractive for the performance and reliability analysis of structural and material systems under extreme conditions, since full-scale testing is often unaffordable. However, model-based simulation involves many approximations and assumptions, and thus confidence in the simulation result is an important consideration in risk-informed decision-making. Sources of uncertainty are both aleatory and epistemic, stemming from natural variability, information uncertainty, and modeling approximations at multiple levels. Information uncertainty arises from sparse and imprecise data, measurement and data processing errors, and qualitative information. Model uncertainty arises due to unknown model parameters, model form assumptions, and solution approximation errors. This short course will present recent methods for the quantification of uncertainty from multiple sources, and their aggregation towards the behavior prediction of multi-physics, multi-scale systems. Multiple activities such as calibration, verification and validation are conducted as part of the model development at multiple levels, and methods to integrate the results of these activities will be presented. In a multi-scale modeling environment, the information available is heterogeneous, from multiple sources (models, tests, experts) and in multiple formats. The use of Bayesian networks to integrate heterogeneous information will be presented. An important objective of uncertainty quantification is uncertainty reduction. Different analyses and tests at different levels of fidelity could be performed, offering trade-offs between accuracy and cost; thus resource allocation strategies for different uncertainty quantification activities will be outlined, and their effect on uncertainty reduction will be discussed.

About the instructor:

Professor Sankaran Mahadevan

Professor Sankaran Mahadevan has thirty years of research and teaching experience in reliability and risk methods, uncertainty quantification, model validation, structural health monitoring, and design optimization. His research has been extensively funded by NSF, NASA, FAA, DOE, DOD, DOT, NIST, General Motors, Chrysler, Union Pacific, American Railroad Association, and Sandia, Idaho, Los Alamos and Oak Ridge national laboratories. His research contributions are documented in more than 600 publications, including two textbooks on reliability methods and 250 journal papers. He has directed 40 Ph.D. dissertations and 24 M. S. theses, and has taught many industry short courses on uncertainty and reliability analysis methods. His awards include the NASA Next Generation Design Tools award (NASA), the SAE Distinguished Probabilistic Methods Educator Award, and best paper awards in the MORS Journal and the SDM and IMAC conferences. He is currently managing editor of ASCE-ASME Journal of Risk and Uncertainty (Part B: Mechanical Engineering). Professor Mahadevan obtained his B.S. from Indian Institute of Technology, Kanpur, M.S. from Rensselaer Polytechnic Institute, Troy, NY, and Ph.D. from Georgia Institute of Technology, Atlanta, GA.

Registration:

Description
Progressive damage modeling of composites under low velocity impact and high velocity impact is of interest to many applications including car crash, impact on pressure vessels, perforation and penetration of thin and thick section composites. MAT162 rate dependent progressive composite damage model in LS-DYNA is considered as the state of the art. This short course will include the theory and practice of MAT162 composite damage model with applications to low and intermediate impact velocities, understanding the LS-DYNA programming parameters related to impact-contact, damage evolution, perforation and penetration of thin- and thick-section composites with and without curvature. The following topics will be covered in this one-day short course with illustrative examples. A CD with content of the course will be provided.

Topics Covered in this Short Course:

Introduction to LS-DYNA
Writing a structured LS-DYNA keyword input deck from scratch for a unit single element (USE) under tension, compression, and shear

Introduction to Continuum Mechanics and Composite Mechanics
Concepts of large deformation finite strain theory
Deformation gradient
Cauchy-Green strain tensors
Piola-Kirchhoff and Cauchy stress
Stiffness matrix for orthotropic and anisotropic composite materials

Composite Material Models in LS-DYNA for Shell and Solid Elements

Theory and Practice in MAT162 Progressive Composite Damage Model
Unit Single Element analysis

Low Velocity Impact (LVI) and Compression after Impact (CAV) Applications
For Shell and Solid Elements

Perforation Mechanics of Thin-Composites with MAT162 and Solid Elements

Penetration Mechanics of Thick-Composites
Depth of Penetration Experiments
Ballistic Impact Experiments

Application of MAT162 in Engineering and Research Problems
Impact on Composite Cylinders and Spheres with and without Internal Pressure and/or Blast Pressure
Penetration and Perforation of Sandwich Composites
Normal and Oblique Impact
Multi-Hit Ballistics
Meso-Mechanical Modeling of Woven and 3D Composites

Click here to register. Registration closes on January 15, 2015. 

Dynamic Behavior of Soft Materials and Biological Tissues

Instructor: Dr. Wayne Chen, Professor of Aeronautics, Astronautics, and Materials Engineering at Purdue University

Location: Johns Hopkins University, Homewood Campus, Baltimore, MD

About the course:

This course presents an overview of the experimental methods to obtain the dynamic mechanical responses of soft materials and biological tissues. The main tool, Kolsky bar, also known as split Hopkinson pressure bar (SHPB), will be discussed in details in terms of its design, operation, and modifications. Examples are given illustrating the applications of this method in the dynamic characterization of polymers, foams, soft geo-materials, composites, fibers, and biological tissues. The main topics of the course are listed below.

• Kolsky Bar Fundamentals: The mechanics of one-dimensional elastic waves; principle of Kolsky bar; Kolsky bar history and its modern versions.
• Operations of Kolsky Bar: Design, instrumentation, and typical operation of a Kolsky bar; Challenges in Kolsky bar characterization of soft materials; remedies to obtain valid experimental results.
• Pulse Shaping: The necessity of control over loading pulse profiles; the methods for pulse shaping; quantitative analysis of pulse shaping.
• Dynamic Compression Experiments: Design of compression experiments to characterize soft materials; typical experiments on soft materials and results; new challenges when the specimen is extra soft.
• Dynamic Tension Experiments: Tension Kolsky bar design for soft specimens, specimen gripping methods, typical tensile experimental results, dynamic behavior of fibers.
• Experiments under Multiaxial Loading: Dynamic tri-axial experimental set-ups and their operations; proportional and non-proportional loading; high-rate experiments on pressure-sensitive materials.
• Environmental Temperature Control: Computer-controlled dynamic experiments on specimens at low and high temperatures.
• Integration of Synchrotron X-ray with Kolsky Bar: Real-time damage visualization methods to assess damage process in opaque specimens loaded by a Kolsky bar.

WHO SHOULD ATTEND?

This course is information rich for graduate students, researchers and engineers who intended to conduct or evaluate experimental studies on dynamic response of soft materials and biological tissues. The course is also useful for modelers who are interested in learning the details of the dynamic experiments for either input or validation information.

About the instructor:

Professor Wayne Chen co-authored the book “Split Hopkinson (Kolsky) Bar: Design, Testing and Applications” published by Springer in 2011. He received his Ph.D. degree (1995) in Aeronautics from California Institute of Technology and is currently a Professor of Aeronautics, Astronautics, and Materials Engineering at Purdue University, West Lafayette, Indiana. His research interests are in the development of innovative dynamic experimental techniques and the characterization of the dynamic behavior of challenging materials. The precision dynamic experimental methods developed in his laboratory have been transferred to numerous government, university, and industrial laboratories. He is a Fellow of the American Society of Mechanical Engineers, a Fellow of the Society of Experimental Mechanics, and an Associate Fellow of the American Institute of Aeronautics and Astronautics. He serves on the Editorial Advisory Board of the International Journal of Impact Engineering, serves as an Associate Editor of the Journal of Applied Mechanics, and as a member of the United States National Committee on Theoretical and Applied Mechanics.

Registration: Click here to register for this event. Cost is $500 or student registrants and $950 for professional registrants.

Travel and Accommodations:

For those traveling by air, we recommend flying in to BWI Thurgood Marshall Airport in Baltimore.
Shuttle, taxi and rental car options are readily available at BWI for a reasonable price.
For those traveling by train, Baltimore’s Penn Station is a 10 minute drive from campus.
The Inn at the Colonnade is located within walking distance of Homewood Campus.

Cancellation Policy:

HEMI reserves the right to cancel a course up to 2 weeks before the scheduled presentation date. Please contact the HEMI office ([email protected]) to confirm that the course is happening before making non-refundable travel arrangements.

Information for course attendees:

If you are traveling by car, visitor parking is available in the South Garage. If you are using a GPS system for directions, the best address to use in 3101 Wyman Park Drive. We will have parking vouchers available when you arrive.

Malone Hall is the newest building on campus as is noted by number 45 on the Johns Hopkins campus map. Click HERE to view.