Results for ME

The basic principles of thermodynamics are introduced in this course. Concepts of energy and entropy from elementary considerations of the microscopic nature of matter are discussed. The principles are applied in thermodynamic analyses directed towards understanding the performances of engineering systems. Methods and problems cover socially responsible economic generation and utilization of energy in central power generation plants, solar systems, refrigeration devices, and automobile, jet and gas-turbine engines.

Elements of fluid mechanics as applied to engineering problems. Equations of motion for incompressible flow. Hydrostatics. Control volume laws for mass, momentum, and energy. Bernoulli equation. Differential equations of fluid flow. Euler equations. Dimensional analysis and similarity. Internal flows. Introductory external boundary layer flows. Introductory lift and drag. ENGR14 and ME30 required.

Mechanics of materials and deformation of structural members. Topics include stress and deformation analysis under axial loading, torsion and bending, column buckling and pressure vessels. Introduction to stress transformation and multiaxial loading. Prerequisite: ENGR 14.

Students develop the language and toolset to transform design concepts into tangible models/prototypes that cultivate the emergence of mechanical aptitude. Visual communication tools such as sketching, orthographic projection, and 2D/3D design software are introduced in the context of design and prototyping assignments. Instruction and practice with hand, powered, and digital prototyping tools in the Product Realization Lab support students implementation and iteration of physical project work. Project documentation, reflection, and in-class presentations are opportunities for students to find their design voice and practice sharing it with others. Prerequisite: ME 1 or ME 101 or consent of instructor.

ME103 is designed for sophomores or juniors in mechanical engineering or product design. During the course students will develop a point of view around a product or object of their own design that is meaningful to them in some way. Students will evolve their ideas through a series of prototypes of increasing fidelity ¿ storyboards, sketches, CAD models, rough prototypes, 3D printed models, etc. The final project will be a high-fidelity product or object made with the PRL's manufacturing resources, giving students a sound foundation in fabrication processes, design guidelines, tolerancing, and material choices. The student's body of work will be presented in a large public setting, Meet the Makers, through a professional grade portfolio that shares and reflects on the student's product realization adventure. ME103 assumes familiarity with product realization fundamentals, CAD and 3D printing. Prerequisite for ME103: ME102.

How to design mechanical systems through iterative application of intuition, brainstorming, analysis, computation and prototype testing. Design of custom mechanical components, selection of common machine elements, and selection of electric motors and transmission elements to meet performance, efficiency and reliability goals. Emphasis on high-performance systems. Independent and team-based design projects. Prerequisites: PHYSICS 41; ENGR 14; ME 80; ME 102; ME 103 or 203. Prerequisites strictly enforced. Must have PRL pass. Must attend lecture. Recommended: ENGR 15; CS 106A; ME 128 or ME 318.

Design for Additive Manufacturing (DfAM) combines the fields of Design for Manufacturability (DfM) and Additive Manufacturing (AM). ME127 will introduce the capabilities and limitations of various AM technologies and apply the principles of DfM in order to design models fit for printing. Students will use Computer Aided Design (CAD) software to create and analyze models and then print them using machines and resources in the Product Realization Lab. Topics include: design for rapid prototyping, material selection, post-processing and finishing, CAD simulation, algorithmic modeling, additive tooling and fixtures, and additive manufacturing at scale. Prerequisite: ME102 and ME80, or consent of instructor.

Students will continue to build understanding of Product Realization processes and techniques concentrating on Computer Numerical Control (CNC) machines, materials, tools, and workholding. Students will gain an understanding of CNC in modern manufacturing and alternative methods and tools used in industry. Students will contribute to their professional portfolio by including projects done in class. Limited enrollment. Prerequisite: ME 103 and consent of instructor.

ME129 is designed for Juniors in Mechanical Engineering who have elected the Product Realization concentration. Students will develop professional level knowledge and experience with materials and manufacturing processes. Activities will include lectures, site visits to local manufacturing organizations, and recorded site visits to global manufacturing organizations. Assignments will include essays and discussions based on site visits, materials exploration including hands-on activities in the Product Realization Lab (PRL), and product tear downs supported by PRL resources. The environmental sustainability consequences of materials and transformation process choices will be a unifying thread running throughout the course. Prerequisites: ME102 and ME103.

The principles of heat transfer by conduction, convection, and radiation with examples from the engineering of practical devices and systems. Topics include transient and steady conduction, conduction by extended surfaces, boundary layer theory for forced and natural convection, boiling, heat exchangers, and graybody radiative exchange. Prerequisites: ME70, ME30 (formerly listed at ENGR30). Recommended: intermediate calculus, ordinary differential equations.This course was formerly ME131A. Students who have already taken ME131A should not enroll in this course.

This course expands on the introduction to fluid mechanics provided by ME70. Topics include the conservation equations and finite volume approaches to flow quantification; engineering applications of the Navier-Stokes equations for viscous fluid flows; flow instability and transition to turbulence, and basic concepts in turbulent flows, including Reynolds averaging; boundary layers, including the governing equations, the integral method, thermal transport, and boundary layer separation; fundamentals of computational fluid dynamics (CFD); basic ideas of one-dimensional compressible flows.

Exploration of mechanical behaviors of natural and engineered materials. Topics include anisotropic, elastoplastic and viscoelastic behaviors, fatigue and multiaxial failure criteria. Applications to biological materials and materials with natural or induced microstructures (e.g., through additive manufacturing). Prerequisite: ME80 or CEE101A.

Second course of two-quarter capstone sequence. Working in project teams, design and develop an engineering system addressing a real-world problem in theme area of pressing societal need. Learn and utilize industry development process: first quarter focuses on establishing requirements and narrowing to top concept. Second quarter emphasizes implementation and testing. Learn and apply professional communication skills, assess ethics. Students must have completed ME170a; completion of 170b required to earn grade in 170a. Course sequence fulfills ME WIM requirement. Course open to Biomechanics students for Capstone credit. Co- or Prerequisites: ENGR15, ME80, ME104, ME131 (ME only), ME123 (ME only). (Cardinal Course certified by the Haas Center).

Directed study and research for undergraduates on a subject of mutual interest to student and staff member. Student must find faculty sponsor and have approval of adviser.

Student must find faculty honors adviser and apply for admission to the honors program.nn (Staff)

ME203 is intended for any graduate student, from any field of study, who may want the opportunity to design and prototype a physical project of meaning to them. Undergraduate mechanical engineering and product design students should register for ME103. Students are asked to discover a product with meaning to them; develop a point of view which motivates a redesign of that product; manufacture a series of models, multiple candidates, including sketches, product use stories, rapid prototypes, CAD documents, manufacturing test models, and finally a customer ready prototype. Each student will physically create their product using Product Realization Lab resources, and also redesign their product for scaled manufacturing to develop a knowledge of manufacturing processes, design guidelines, materials choices, and the opportunities those processes provide. The student's body of work will be presented in a large public setting, Meet the Makers, through an inspirational portfolio which shares and reflects on their product realization adventure.

Design for Extreme Affordability (fondly called Extreme) is a two-quarter course offered by the d.school through the School of Engineering and the Graduate School of Business. This multidisciplinary project-based experience creates an enabling environment in which students learn to design products and services that will change the lives of the world's poorest citizens. Students work directly with course partners on real world problems, the culmination of which is actual implementation and real impact. Topics include design thinking, product and service design, rapid prototype engineering and testing, business modelling, social entrepreneurship, team dynamics, impact measurement, operations planning and ethics. Possibility to travel overseas during spring break. Previous projects include d.light, Driptech, Earthenable, Embrace, the Lotus Pump, MiracleBrace, Noora Health and Sanku. Periodic design reviews; Final course presentation and expo; industry and adviser interaction. Limited enrollment via application. Must sign up for ME206A and ME206B. See extreme.stanford.edu

Technologies involved in mechatronics (intelligent electro-mechanical systems), and techniques to apply this technology to mecatronic system design. Topics include: electronics (A/D, D/A converters, op-amps, filters, power devices); software program design, event-driven programming; hardware and DC stepper motors, solenoids, and robust sensing. Large, open-ended team project. Prerequisites: ENGR 40, CS 106, or equivalents.

Engineering Design Analytics is for engineering students seeking greater depth in new product development. Students will develop structured methods for addressing questions like: Who are 'customers'? What do customers value? What are leverage points for designing systems? What are robust metrics for assessing system performance and customer satisfaction? What are failure modes? Why are ethics important in engineering projects? Assignments will include readings, case studies, applied activities, and write-ups. In class activities will include lectures, discussions, and working sessions. Prerequisites: ME 103/203 or consent of instructor.

Lecture/lab. Second in team design project series on programmable electromechanical systems design. Topics: More microcontroller hardware subsystems: timer systems, PWM, interrupts; analog circuits, operational amplifiers, comparators, signal conditioning, interfacing to sensors, actuator characteristics and interfacing, noise, and power supplies. Lab fee. Limited enrollment. Prerequisite: 218A or passing the smart product design fundamentals proficiency examination.

Fundamentals of physics-based modeling and deep learning; deep neural networks, recurrent neural networks, constitutive artificial neural networks; Bayesian methods; training, testing, and validation; prediction and uncertainty quantification; soft materials and living matter; discovering models, parameters, and experiments to best explain soft matter systems. Prerequisite: ME80.

Mechanical cues play a critical role in development, normal functioning of cells and tissues, and various diseases. This course will cover what is known about cellular mechanotransduction, or the processes by which living cells sense and respond to physical cues such as physiological forces or mechanical properties of the tissue microenvironment. Experimental techniques and current areas of active investigation will be highlighted. This class is for graduate students only.

Linear-elastic and elastic-plastic fracture mechanics from a materials science perspective, emphasizing microstructure and the micromechanisms of fracture. Plane strain fracture toughness and resistance curve behavior. Mechanisms of failure associated with cohesion and adhesion in bulk materials, composites, and thin film structures. Fracture mechanics approaches to toughening and subcritical crack-growth processes, with examples and applications involving cyclic fatigue and environmentally assisted subcritical crack growth. Prerequisite: 151/251, 198/208, or equivalent. SCPD offering.

Students design and fabricate a highly refined chair. The process is informed and supported by historical reference, anthropometrics, form studies, user testing, material investigations, and workshops in wood steam-bending, plywood forming, metal tube bending, TIG & MIG welding, upholstery & sewing. Prerequisite: ME103/203 or consent of instructor. May be repeated for credit.

The time of robotics/AI is upon us. Within the next 10 to 20 years, many jobs will be replaced by robots/AI (artificial intelligence). This seminar features guest lecturers from industry and academia discussing the current state of the field of robotics/AI, preparing students for the rise of robotics/AI, and redesigning and reinventing education to adapt to the new era.

We investigate Learning and Making environments that enable participants to learn technical concepts through designing and prototyping at low cost. The course consists of lectures, invited guest talks and a final project. Students interact with guest speakers who have developed novel learning environments and deployed them in mainstream education settings as well as in extreme conditions such as remote rural locations. Students work in teams to complete a course project using design methodology to develop a learning environment solution.

Experimental techniques to study human and animal movement including motion capture systems, EMG, force plates, medical imaging, and animation. The mechanical properties of muscle and tendon, and quantitative analysis of musculoskeletal geometry. Projects and demonstrations emphasize applications of mechanics in sports, orthopedics, and rehabilitation.

Introduction to the mechanical analysis of tissues (biomechanics), and how mechanical cues play a role in regulating tissue development, adaptation, regeneration, and aging (mechanobiology). Topics include tissue viscoelasticity, cardiovascular biomechanics, blood rheology, interstitial flow, bone mechanics, muscle contraction and mechanics, and mechanobiology of the musculoskeletal system. Undergraduates should have taken ME70 and ME80, or equivalent courses.

This course introduces computational modeling methods for cardiovascular blood flow and physiology. Topics in this course include analytical and computational methods for solutions of flow in deformable vessels, one-dimensional equations of blood flow, cardiovascular anatomy, lumped parameter models, vascular trees, scaling laws, biomechanics of the circulatory system, and 3D patient specific modeling with finite elements; course will provide an overview of the diagnosis and treatment of adult and congenital cardiovascular diseases and review recent research in the literature in a journal club format. Students will use SimVascular software to do clinically-oriented projects in patient specific blood flow simulations. Pre-requisites: CME102, ME133 and CME192.

Introduction to the mechanical behaviors of biological tissues in health and disease. Overview of experimental approaches to evaluating tissue properties and mathematical constitutive models. Elastic behaviors of hard tissues, nonlinear elastic and viscoelastic models for soft tissues.

A course focusing on creating small scale objects in precious metals, with equal attention given to design and the process of investment casting in the Product Realization Lab.

For master's students. Educational opportunities in high technology research and development labs in industry. Students engage in internship work and integrate that work into their academic program. Following internship work, students complete a research report outlining work activity, problems investigated, key results, and follow-up projects they expect to perform. Meets the requirements for curricular practical training for students on F-1 visas. Student is responsible for arranging own internship/employment and faculty sponsorship. Register under faculty sponsor's section number. All paperwork must be completed by student and faculty sponsor, as the Student Services Office does not sponsor CPT. Students are allowed only two quarters of CPT per degree program. Course may be repeated twice.

For Ph.D. students. Educational opportunities in high technology research and development labs in industry. Students engage in internship work and integrate that work into their academic program. Following internship work, students complete a research report outlining work activity, problems investigated, key results, and follow-up projects they expect to perform. Meets the requirements for curricular practical training for students on F-1 visas. Student is responsible for arranging own internship/employment and faculty sponsorship. Register under faculty sponsor's section number. All paperwork must be completed by student and faculty sponsor, as the student services office does not sponsor CPT. Students are allowed only two quarters of CPT per degree program. Course may be repeated twice.

Geometric interpretation of partial differential equation (PDE) characteristics; solution of first order PDEs and classification of second-order PDEs; self-similarity; separation of variables as applied to parabolic, hyperbolic, and elliptic PDEs; special functions; eigenfunction expansions; the method of characteristics. If time permits, Fourier integrals and transforms, Laplace transforms. Prerequisite: CME 200/ME 300A, equivalent, or consent of instructor.

This course provides a holistic overview over the field of vehicle automation. The course starts with the history of vehicle automation and then introduces key terminology and taxonomy. Guest lecturers present the legal and policy aspects of vehicle automation both on the federal and state level. Then, the state of the art in vehicle automation is provided. This includes sensor and actuator technology as well as the driver assistance technology in cars today. Finally, the technology currently being developed for future highly and fully automated vehicles is described, including a high-level introduction of the software and algorithms used as well as HMI and system aspects. Students are asking to work in groups on a current topic related to vehicle automation and present their findings in the final two classes in a short presentation.

ME310BC is a two-quarter continuation of ME310 and typically requires ME310A as a prerequisite. In ME310B the focus is on detailed design and prototyping of novel components and systems, often re-framing the problem and identifying new user populations in light of new information. ME310C focuses on making the design credible from an engineering and business perspective. Teams perform user testing and explore pre-production manufacturing techniques to create their final prototypes. They present their solutions at the EXPE (http://expe.stanford.edu) and produce a report that documents not only the final solutions but also the alternatives considered. Final reports are archived in the Stanford Engineering Libraries: ME310 Project Based Engineering, Digital Collection.

This class focuses on individuals and their psychological wellbeing. The class delves into how students perceive themselves and their work, and how they might use design thinking to lead a more creative and committed life. As a participant you read parts of a different book each week and then engage in exercises designed to unlock learnings. In addition, there are two self-selected term projects dealing with eliminating a problem from your life and doing something you have never done before. Apply the first day during class. Attendance at the first session is mandatory.

Design course focusing on an integrated suite of computer tools: rapid prototyping, solid modeling, computer-aided machining, and computer numerical control manufacturing. Students choose, design, and manufacture individual products, emphasizing individual design process and computer design tools. Structured lab experiences build a basic CAD/CAM/CNC proficiency. Limited enrollment. Prerequisite: ME103 or equivalent and consent of instructor. ME 203 or consent of instructor.

Robotics foundations in modeling, design, planning, and control. Class covers relevant results from geometry, kinematics, statics, dynamics, motion planning, and control, providing the basic methodologies and tools in robotics research and applications. Concepts and models are illustrated through physical robot platforms, interactive robot simulations, and video segments relevant to historical research developments or to emerging application areas in the field. Recommended: matrix algebra.

Design course focusing on the process of injection molding as a prototyping and manufacturing tool. Coursework will include creating and evaluating initial design concepts, detailed part design, mold design, mold manufacturing, molding parts, and testing and evaluating the results. Students will work primarily on individually selected projects, using each project as a tool to continue developing and exercising individual design process. Lectures and field trips will provide students with context for their work in the Stanford Product Realization Lab. Prerequisite: ME318 or consent of instructors.

This course focuses on how robots can be effective teammates with other robots and human partners. Concepts and tools will be reviewed for characterizing task objectives, robot perception and control, teammate behavioral modeling, inter-agent communication, and team consensus. We will consider the application of these tools to robot collaborators, wearable robotics, and the latest applications in the relevant literature. This will be a project-based graduate course, with the implementation of algorithms in either python or C++.

Newton, Euler, D'Alembert (road-map) methods and computational tools for 3D kinematic, force, and motion analysis of multibody systems. Power, work, and energy. Computational solutions of nonlinear algebraic and differential equations governing the static and dynamic behavior of multibody systems.

Fundamental concepts and techniques of primal finite element methods. Method of weighted residuals, Galerkin's method and variational equations. Linear eliptic boundary value problems in one, two and three space dimensions; applications in structural, solid and fluid mechanics and heat transfer. Properties of standard element families and numerically integrated elements. Implementation of the finite element method using Matlab, assembly of equations, and element routines. Lagrange multiplier and penalty methods for treatment of constraints. The mathematical theory of finite elements.

Linear and kernel support vector machines, deep learning, deep neural networks, generative adversarial networks, physics-based machine learning, forward and reverse mode automatic differentiation, optimization algorithms for machine learning, TensorFlow, PyTorch.

Guest speakers present research related to plasma science and engineering, ranging from fundamental plasma physics to industrial applications of plasma.

Laminar viscous fluid flow. Governing equations, boundary conditions, and constitutive laws. Exact solutions for parallel flows. Creeping flow limit, lubrication theory, and boundary layer theory including free-shear layers and approximate methods of solution; boundary layer separation. Introduction to stability theory and transition to turbulence, and turbulent boundary layers. Prerequisite: 351A.

The spectroscopy of gases and laser-based diagnostic techniques for measurements of species concentrations, temperature, density, and other flow field properties. Topics: electronic, vibrational, and rotational transitions; spectral lineshapes and broadening mechanisms; absorption, fluorescence, Rayleigh and Raman scattering methods; collisional quenching. Prerequisite: 362A or equivalent.

An introduction to the science and applications of laser-plasma interactions. The first part of the course will discuss the fundamental concepts and analytic, computational, and experimental tools for understanding the linear and nonlinear propagation of light in plasma, including dispersion relations, ionization and absorption mechanisms, stimulated scattering and light-driven waves, and relativistic optics. The second part of the course will use these tools to understand a variety of existing and under-development applications of laser-plasma interactions and high-power beams, including EUV lithography, laser diagnostics, directed energy, laser-wakefield accelerators, laboratory astrophysics, and inertial confinement fusion.Previous coursework in plasma physics, optics, or electromagnetism, or discussion with the instructor, is recommended.

In this two-quarter course series ( BIOE 374A/B, MED 272A/B, ME 368A/B, OIT 384/5), multidisciplinary student teams identify real-world unmet healthcare needs, invent new health technologies to address them, and plan for their implementation into patient care. During the first quarter (winter), students select and characterize an important unmet healthcare problem, validate it through primary interviews and secondary research, and then brainstorm and screen initial technology-based solutions. In the second quarter (spring), teams select a lead solution and move it toward the market through prototyping, technical re-risking, strategies to address healthcare-specific requirements (regulation, reimbursement), and business planning. Final presentations in winter and spring are made to a panel of prominent health technology experts and/or investors. Class sessions include faculty-led instruction and case studies, coaching sessions by industry specialists, expert guest lecturers, and interactive team meetings. Enrollment is by application only, and students are required to participate in both quarters of the course. Visit http://biodesign.stanford.edu/programs/stanford-courses/biodesign-innovation.html to access the application, examples of past projects, and student testimonials. More information about Stanford Biodesign, which has led to the creation of 50 venture-backed healthcare companies and has helped hundreds of student launch health technology careers, can be found at http://biodesign.stanford.edu/.

Development of quantitative device models for complex energy systems, including fuel cells, reformers, combustion engines, and electrolyzers, using thermodynamic and transport analysis. Student groups work on energy systems to develop conceptual understanding, and high-level, quantitative and refined models. Advanced topics in thermodynamics and special topics associated with devices under study. Prerequisite: 370A.

Heat of reaction, adiabatic flame temperature, and chemical composition of products of combustion; kinetics of combustion and pollutant formation reactions; conservation equations for multi-component reacting flows; propagation of laminar premixed flames and detonations. Prerequisite: 362A or 370A, or consent of instructor.

Individual storytelling action and reflective observations gives the course an evolving framework of evaluative methods, from engineering design; socio cognitive psychology; and art that are formed and reformed by collaborative development within the class. Stories attached to an idea, a discovery or starting up something new, are considered through iterative narrative work, storytelling as rapid prototyping and small group challenges. This course will use qualitative and quantitative methods for story engagement, assessment, and class determined research projects with practice exercises, artifacts, short papers and presentations. Graduate and Co-Term students from all programs welcome. Class size limited to 21.

Directed study for graduate engineering students on subjects of mutual interest to student and staff member. May be used to prepare for experimental research during a later quarter under 392. Faculty sponsor required.

Graduate engineering students undertake experimental investigation under guidance of staff member. Previous work under 391 may be required to provide background for experimental program. Faculty sponsor required.

Directed research experience for MS students in mechanical engineering who are pursuing the Distinction in Research (DiR). The student is responsible for securing a faculty research advisor and will register under that advisor's section number. Students must provide confirmation of faculty research advisor's agreement to supervise DiR, at which time they will receive a permission code from ME Student Services allowing them to enroll. Course may be repeated for credit.

Required of Ph.D. candidates in solid mechanics. Guest speakers present research topics related to mechanics theory, computational methods, and applications in science and engineering. May be repeated for credit.

Directed research experience for first-year Mechanical Engineering Ph.D. students with faculty sponsors. The student is responsible for arranging the faculty sponsor and registering under the faculty sponsor's section number. Course may be repeated up to four times in the first year. A different faculty sponsor must be selected each time.

Investigation of some engineering problems. Required of Engineer degree candidates

This course is not a standard teaching of asymptotic methods as thought in the applied math programs. Nor does it involve such elaborate algebra and analytical derivations. Instead, the class relies on students' numerical programming skills and introduces improvements on numerical methods using standard asymptotic and scaling ideas. The main objective of the course is to bring physical insight into numerical programming. The majority of the problems to be explored involve one- and two-dimensional transient partial differential equations inspired by thermal-fluid and transport engineering applications. Topics include: 1-Review of numerical discretization and numerical stability, 2-Implicit versus explicit methods, 3-Introduction to regular and singular perturbation problems, 4-Method of matched asymptotic expansions, 5-Stationary thin interfaces: boundary layers, Debye layers, 6-Moving thin interfaces: shocks, phase-interfaces, 7-Reaction-diffusion problems, 8-Directional equilibrium and lubrication theory.

Statistical analysis of turbulent flow data. Modal representations. Goals for low - order models, observability and controllability. Data-driven techniques: proper orthogonal decomposition (POD)/principal component analysis (PCA), spectral POD, dynamic mode decomposition, linear stochastic estimation, and their extensions. Disambiguating linear and nonlinear effects, sparse identification of nonlinear dynamics (SINDy), Koopman analysis, etc. Equation-driven models: eigenanalysis, pseudospectra, resolvent analysis. Connections between data-driven and equation-driven modeling approaches. Low-order models for turbulent flows. Prerequisites: Familiarity with turbulent flows (ME 361), or consent of the instructor.

Transport phenomena on small-length scales appropriate to applications in microfluidics, complex fluids, and biology. The basic equations of mass, momentum, and energy, derived for incompressible fluids and simplified to the slow-flow limit. Topics: solution techniques utilizing expansions of harmonic and Green's functions; singularity solutions; flows involving rigid particles and fluid droplets; applications to suspensions; lubrication theory for flows in confined geometries; slender body theory; and capillarity and wetting. Prerequisites: CHEMENG 120A, CHEMENG 120B, CHEMENG 300, or equivalents.

Uncertainty is an unavoidable component of engineering practice and decision making. Representing a lack of knowledge, uncertainty stymies our attempts to draw scientific conclusions, and to confidently design engineering solutions. Failing to account for uncertainty can lead to false discoveries, while inaccurate assessment of uncertainties can lead to overbuilt engineering designs. Overcoming these issues requires identifying, quantifying, and managing uncertainties through a combination of technical skills and an appropriate mindset. This class will introduce modern techniques for quantifying and propagating uncertainty and current challenges. Emphasis will be on applying techniques in genuine applications, through assignments, case studies, and student-defined projects. Prerequisite: Basic probability and statistics at the level of CME 106 or equivalent.

Ph.D. students may enroll for up to 3 units while working as a TA or CA. May be repeated for credit.

In this interactive seminar course, students will learn active learning and inclusive teaching strategies as well as receive support for serving as a CA/TA in an engineering context. Intended for current and future CAs/TAs in Mechanical Engineering or related departments, the course will also feature a workshop on collecting feedback, a panel with former TAs, and teaching techniques tailored to different class environments.Mechanical Engineering Teaching Assistance Training