Build a Supercomputer
Students will build a supercomputer! Well, almost. Supercomputers typically use thousands of processors running in parallel to solve problems in science, finance, and other areas. They will build a smaller supercomputer to gain insight and understanding in how supercomputers are organized and then how to program them. Students will build a Beowulf cluster using ordinary computers. Students will then write a parallel program, compile the program, and execute that program on the cluster. Areas that will be covered during this project are:
- Computing basics
- Computer networking
- Linux operating system
- Computer programming
Project review and summary
Students will be required to answer the research question: "In what year would the supercomputer we build be considered the world's fastest supercomputer?" Students will be given classroom-style lectures in addition to hands-on assignment to enforce topics discussed.
Joint Institute for Computational Sciences
Mentor: Robert Whitten
Facilitator: Jerry Sherrod
Assistants: James Howard,
Students: Kelsey Anderson,
Holden Le Dinh,
Consequence Management Plan and Visualization
The Departments of Homeland Security, Defense, and Energy are actively involved in counter-terrorism, focusing on detecting and preventing catastrophic events as well as planning to manage the consequences should such an event occur. In this project, ARC/ORNL Summer Institute student participants will develop a consequence management plan for an event at a major U.S. city. Students will choose a city and a chemical, biological, radiological, or nuclear event. Model results for the event will be provided, and the students will create a Keyhole Markup Language (KML) file for display with Google Earth. The Consequence Management (CM) Plan KML file will include information about the event and predicted results, evacuation routes, references to available hospitals and emergency response resources, etc.
ORNL Division: Computational Sciences and Engineering
Mentor: Ronald W. Lee and James Black
Students: Hannah Alley,
Design of Novel Polymeric Materials Using Computer Simulation
In everyday life, we encounter systems that consist of huge numbers of molecules. For example, 1 gm of water (H20) contains 3.3x1022 molecules. These molecules interact with each other in a very complex fashion. These interactions help assemble smaller molecules to larger assemblies. Everything around us is possible for the natural self-assembly of these molecules.
For larger molecules (usually also known as polymers or macromolecules) the interactions are so complex that one cannot possibly understand the basics of their motions and stability of the materials. The macromolecules often self-assemble to form natural materials like protein, DNA and also commercial materials like rubber etc. We can get knowledge by mimicking nature and produce different kinds of materials artificially for applications in our daily life. For example, tires, plastics, and medicines are artificially made materials which we use in our daily life. To design these materials, expensive experimental techniques are used. These experiments, however, may not produce results always and lack the basic understanding of physics.
With the help of computers, we can predict materials that can be easily produced and also understand the basic physics behind it. It is well known that the particles follow Newtonian mechanics at a classical level, i.e., they follow F=ma, where ʽFʼ is the force on each particle, ʽmʼ is the mass and ʽaʼ is the acceleration, which is related to the position coordinate of a particle. Therefore, if we know the force acting on a particle at a given time, we can predict, by using basic physics (Newtonʼs equation of motion), what is going to happen in a future time. The process is even more complicated for macromolecules because of bonds, intra-molecular interactions. For this, we feed the computer with the ʽvirtualʼ macromolecules and instruct the computer to find out the final product following Newtonian mechanics. Hence, the designing of novel polymeric materials on a computer can be achieved.
In this project we will try to understand how molecules interacts using computer simulation. What are the forces that bind them together? Why do they self-assemble in a particular form? What is the temperature and density range that should be used to achieve the best material design? Our goal in this project is to engage the students in a thought process where they can understand how research can be conducted, so that they can contribute to the scientific discovery in their future studies.
ORNL Division: Computer Science and Mathematics
Mentors: Monojoy Goswami and Bobby Sumpter
Students: Leila Cappellano-Sarver,
Measuring Moisture Content in Isolated Lignin
Lignin is a coproduct of paper mills and biorefineries. Those are useful for carbon precursor and polymer synthesis. Unless it is purified extensively, lignin retains some inorganic impurities and moisture. In this work the students will measure moisture content in lignin by gravimetric measurement and compare it with data from thermal analysis. An oven dried lignin sample will be kept under ambient conditions to measure the moisture regain.
ORNL Division: Materials Science and Technology
Mentors: Amit K. Naskar
Students: Ebony Rush,
Robotic Systems and Engineering Development
Robots are used in the industry to protect humans from hazardous environments or when the work involves highly repetitive and precision tasks. The objectives of this project are to (1) expose students to robotic projects underway at ORNL and (2) provide hands-on experience in designing, constructing and programming a small robot. The students will work in two groups on similar problems at the Remote Systems Group of ORNL's Fusion and Materials for Nuclear Systems Division. The focus of this project is to develop the mechanical and programming skills that are needed to design, build and operate a robot. The student will build a robot that can navigate an obstacle course using various sensors (light, ultrasonic and/or touch). The students will learn which sensors are best suited for which purposes and what logic is appropriate for controlling the robot's trajectory. Students will be using the Lynxmotion Tri-Track Robot and AL5A Robotic Arm for building and testing.
ORNL Division: Fusion and Materials for Nuclear Systems
Mentors: Venugopal Varma, Adam Carroll and Adam Aaron
Facilitators: Carl Mallette and Ken Swayne
Students: Mickayla Bachar,
Seeing from Space
> Technologies that can allow us to see and understand events on Earth from space can have a wide array of applications ranging from disaster management to business analytics. Remote sensing technology is on its path of rapid advancement since the early days where kites, balloons, and messenger pigeons were used to image the Earth. The emerging field encompasses a wide range of disciplines including computer science, geography, mathematics, and statistics. For the past fifty years considerable progress has been made in interpreting the 3D world around us through the images captured from space. The progress in the field has been measured by the advancements made in theories, models, and applications.
ORNL Division: Computational Science and Engineering Division
Mentors: Anil Cheriyadat, Harini Sridharan
Students: Nathan Bowman,
Using Computers to Design Therapeutic Drugs and
Statistics to Determine Their Efficacy
Computers are as much a part of day-to-day scientific research as they are in our personal lives. With the emergence of functional computational tools in every major branch of science and engineering, it is of critical importance to appreciate the role they play in a scientist’s life. The conceptual design, modeling and stress-testing of cars, airplanes and ships currently occurs almost entirely on a computer and well before the first prototype is ever made. In a similar fashion, drugs for new diseases and/or better drugs for existing diseases are increasingly found by scanning databases of billions of compounds and testing their efficacy on the malfunctioning protein(s) involved in diseases. This scanning, visualization and testing of drugs involves computational tools. In this context, we will see how computational visualization tools can be used to study the structure of proteins and drug compounds and help verify if a drug compound is a suitable target for a particular protein. We will also discuss the emergence of a biology-based video game where the general public (including high school students!) can help find the structures of proteins involved in diseases. Determination of protein structures allows scientists to develop drugs that target the proteins.
In the second week, we will see how data from various sources like scientific experiments, baseball games, stock markets, and polling are processed in a meaningful way that allows us to make decisions like which drug among a pool of candidates works best, which player should you pick for your fantasy baseball team, which stocks should you invest in, which way is the election going to swing, and how will any particular announcement be received by the public? Statistics is the science of collecting and analyzing data and forms the backbone of any data-driven decision making process. We will look at how different types of data can be analyzed and look beyond the routine calculations of mean, median and mode of data. We will also use an extremely powerful open-source statistical analysis and graphical representation software called R to analyze example data sets and arrive at pertinent decisions.
ORNL Division: Biosciences
Mentors: Edward Uberbacher, Pavan K. GhattyVenkataKrishna
Students: Dessen Bolton, Amberleigh Dixon,
Cosmic Explosions and Fundamental Neutron Physics
Stellar Explosions are the most violent events in the cosmos and simultaneously serve to create and disperse the elements of life. In this two-component project, a group of ARC/ORNL Summer Institute Teacher participants will (a) learn about how stars explode and how we simulate them on computers using the latest information from accelerator laboratories, and (b) learn how researchers use fundamental physics at ORNL’s 1.4 billion dollar Spallation Neutron Source (SNS).
In Part (a), they will get a detailed description of stellar explosions and instructions on how to run explosion simulations. They will then run a series of simulations in a research project to help determine which thermonuclear reactions have the largest impact on our predications of element creation in these explosions. They will also be given information on how to use these simulations in a variety of classroom activities in the future.
In Part (b), they will learn about the SNS facility at ORNL and the fundamental physics studies that are enabled by measurements with neutrons. They will obtain hands-on experience with the NPDGamma experiment that is getting ready for measurements in Fall 2013. They will also participate in R&D activities for our other SNS-based experiments, including testing electronics and neutron detectors.
ORNL Division: Physics
Mentors: Michael Smith, Seppo Penttila
Teachers: Susan Aycock,
Nanoparticles – Production, Characterization and Uses
This research project will be conducted in ORNL’s Chemical Sciences Division (CSD) and is designed to allow participants to better understand processes required to conduct a research project on nanoparticles. The teachers will research a nanotechnology project and be trained on processes and safety procedures used for nanoparticles research. They will then work with a research scientist to prepare samples of nanoparticles, evaluate analytical data characterizing the nanoparticles, and draw conclusions from the data they collect. The teachers also will learn potential applications of some of the nanoparticles being produced and investigated at ORNL. During the two-week program, the teachers will meet other researchers within the Laboratory community and learn about projects related to nanoparticles that are currently being researched at ORNL.
ORNL Division: Chemical Sciences
Mentor: M. Parans Paranthaman
Facilitator: James R. Davis
Teachers: Christy Fitzwater,
Janice St. Pierre, Allena Wiese
Residual Stress Determination in 3-D Printed Nickel Super Alloys
Electron-beam melting (EBM) is a type of 3-D printing in the additive manufacturing industry that demonstrates the ability to fabricate complex metal parts that are very difficult to fabricate with more traditional methods. It involves an imported computer-generated model that instructs the machine to melt precursor metal powder in successive layers of specified geometries. This method is very fast and the recycled powder can be re-used in later builds. Despite these advantages, the effect that the parameters of the melting process have on the microstructure and residual stress are not well understood. Nickel-alloys fabricated via EBM are amongst some of the metals are currently being studied. They are typically used for their corrosion resistance, high strength and high-temperature applications. It is imperative that the mechanical properties and microstructures are well characterized for EBM produced parts so that industry needs can be met.
In this project, X-ray diffraction will be performed on nickel alloy EBM fabricated parts. The data collected will then be used in a computer programs to determine the residual stress. The results will help provide a better understanding of the characterization of EBM fabricated materials.
ORNL Division: Materials Science and Technology
Mentors: Tom Watkins, Lindsay Kolbus
Facilitator: Burl Cavin
Teachers: Sherry Baucom,
Understanding Energy Efficiency in Buildings Using Computer Simulation
This research project is designed to allow participants gain exposure to sustainable building design and an understanding of the impacts of weather, building design and materials, systems, and operation on building energy use. The teacher will research energy efficiency strategies in residential buildings located in different climates through computer modeling of building energy use using a software – MulTEA (Multifamily Tool for Energy Audit). MulTEA is an online software for the analysis of energy retrofits in existing multifamily buildings, being developed by Oak Ridge National Laboratory in collaboration with Lawrence Berkeley National Laboratory. The teacher will be performing building energy simulations using MulTEA’s user interface and evaluate energy savings from a wide range of energy efficient building technologies, such as thermal insulation, air sealing, energy-efficient windows, high-performance systems, and high-efficiency lighting and appliances.
ORNL Division: Energy and Transportation Sciences
Mentor: Mini Malhotra
Teachers: Annette Mezzadonna,