| | 01 | TBA | | TBA | Widder | Default - none. | 30 | 16 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | TBA | | TBA | Shao | Default - none. | 0 | 1 | 0 | | |
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| Description: | The summer edition of CSE 131 is identical in content to the material covered during a fall or spring semester. An important difference is that this course can easily be taken remotely: the lecture material has been captured and professionally produced to create short segments interleaved with simple exercises to reinforce the concepts that are presented. During fall and spring, students work collaboratively in lab and studio sessions, proctored by a TA. In this summer offering, students will collaborate with each other and TAs using an online video chat room. Quizzes given during the summer session will prepare students for the final exam to be administered on the Danforth Campus on 9/3/19 from 6:00-8:00 p.m.
This course has been named by students as one of the top-5 not-to-be-missed courses. Approximately 800 students are taking this course per year, and its popularity continues to increase steadily. If you have questions please contact Ron Cytron (cytron@wustl.edu).
An introduction to software concepts and implementation, emphasizing problem solving through abstraction and decomposition. Introduces processes and algorithms, procedural abstraction, data abstraction, encapsulation, and object-oriented programming. Recursion, iteration, and simple data structures are covered. Concepts and skills are mastered through programming projects, many of which employ graphics to enhance conceptual understanding. Java, an object-oriented programming language, is the vehicle of exploration.
Prerequisites: Comfort with algebra and geometry at the high school level is assumed. Patience, good planning, and organization will promote success. This course assumes no prior experience with programming.
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| | 01 | TBA | | TBA | Shook | See Department | 0 | 39 | 0 | | | | |
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| | 01 | M-W-F-- | 9:30A-12:00P | TBA | Buhler, Cole, Siever | See Instructor | 60 | 31 | 0 | | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | M-W---- | 3:00P-5:30P | TBA | Sproull | See Instructor | 50 | 43 | 0 | | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | -T-RF-- | 10:00A-12:30P | TBA | Shidal | See Instructor | 25 | 18 | 0 | | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | TBA | | TBA | Guerin | Default - none. | 0 | 0 | 0 | | | | |
| 50 | TBA | | TBA | Kamilov | Default - none. | 0 | 0 | 0 | | |
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| | 01 | TBA | | TBA | Shook | See Instructor | 0 | 32 | 0 | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
| Waits Not Allowed |
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| | 01 | -T-R--- | 3:00P-5:30P | TBA | Sproull | See Department | 35 | 21 | 0 | | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | The summer edition of CSE 131 is identical in content to the material covered during a fall or spring semester. An important difference is that this course can easily be taken remotely: the lecture material has been captured and professionally produced to create short segments interleaved with simple exercises to reinforce the concepts that are presented. During fall and spring, students work collaboratively in lab and studio sessions, proctored by a TA. In this summer offering, students will collaborate with each other and TAs using an online video chat room. Quizzes given during the summer session will prepare students for the final exam to be administered on the Danforth Campus on 9/3/19 from 6:00-8:00 p.m.
This course has been named by students as one of the top-5 not-to-be-missed courses. Approximately 800 students are taking this course per year, and its popularity continues to increase steadily. If you have questions please contact Ron Cytron (cytron@wustl.edu).
An introduction to software concepts and implementation, emphasizing problem solving through abstraction and decomposition. Introduces processes and algorithms, procedural abstraction, data abstraction, encapsulation, and object-oriented programming. Recursion, iteration, and simple data structures are covered. Concepts and skills are mastered through programming projects, many of which employ graphics to enhance conceptual understanding. Java, an object-oriented programming language, is the vehicle of exploration.
Prerequisites: Comfort with algebra and geometry at the high school level is assumed. Patience, good planning, and organization will promote success. This course assumes no prior experience with programming.
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| | 01 | TBA | | TBA | Shook | See Department | 0 | 39 | 0 | | | | |
|
| | 01 | M-W-F-- | 9:30A-12:00P | TBA | Buhler, Cole, Siever | See Instructor | 60 | 31 | 0 | | | | |
|
| | 01 | M-W---- | 3:00P-5:30P | TBA | Sproull | See Instructor | 50 | 43 | 0 | | | | |
|
| | 01 | -T-RF-- | 10:00A-12:30P | TBA | Shidal | See Instructor | 25 | 18 | 0 | | | | |
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| | 01 | -T-RF-- | 2:00P-4:30P | TBA | Shidal | No Final | 25 | 13 | 0 | | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 02 | TBA | | TBA | Kamilov | Default - none. | 0 | 0 | 0 | | | |
| 29 | TBA | | TBA | Zhang | Default - none. | 0 | 0 | 0 | | |
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| | 05 | TBA | | TBA | Ehrhard | No Final | 0 | 1 | 0 | | |
| 33 | TBA | | TBA | Thimsen | No Final | 0 | 0 | 0 | | |
| 35 | TBA | | TBA | Singamaneni | No Final | 0 | 0 | 0 | | |
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| Description: | Engineers have great potential for innovation, but creating value from our ideas is not an entirely intuitive enterprise. This course is designed to help engineering students prepare for entrepreneurial success. The course walks through three critical phases of a startup company: Creative, Critical, and Crusader Phases. Students will master financial calculations, work in teams to create and assess the commercial viability of their business idea, prepare a financial forecast and prepare a short business plan.
Topics: Entrepreneur's Primer, Recognizing Opportunity, Defining Opportunity, Developing Your Business Concept, Creating Your Team, Creating Your Company, Financial Accounting, Business Plans and
Presentations.
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| | 01 | M-W---- | 6:00P-7:15P | TBA | Reardon | See Instructor | 40 | 11 | 0 | | | |
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| | 02 | TBA | | TBA | Bai | Default - none. | 0 | 0 | 0 | | | |
| 03 | TBA | | TBA | Axelbaum | Default - none. | 0 | 0 | 0 | | | |
| 04 | TBA | | TBA | Biswas | Default - none. | 0 | 0 | 0 | | | |
| 05 | TBA | | TBA | Ehrhard | Default - none. | 0 | 0 | 0 | | | |
| 06 | TBA | | TBA | Dudukovic | Default - none. | 0 | 0 | 0 | | | |
| 07 | TBA | | TBA | Giammar | Default - none. | 0 | 0 | 0 | | | |
| 08 | TBA | | TBA | Gleaves | Default - none. | 0 | 0 | 0 | | | |
| 10 | TBA | | TBA | Pakrasi | Default - none. | 0 | 0 | 0 | | | |
| 11 | TBA | | TBA | Ramachandran | Default - none. | 0 | 0 | 0 | | | |
| 12 | TBA | | TBA | Jun | Default - none. | 0 | 0 | 0 | | | |
| 14 | TBA | | TBA | Turner | Default - none. | 0 | 0 | 0 | | | |
| 15 | TBA | | TBA | Sadtler | Default - none. | 0 | 0 | 0 | | |
| 16 | TBA | | TBA | Ravi | Default - none. | 0 | 0 | 0 | | | |
| 17 | TBA | | TBA | Yablonsky | Default - none. | 0 | 0 | 0 | | | |
| 18 | TBA | | TBA | Nissing | Default - none. | 0 | 0 | 0 | | | |
| 19 | TBA | | TBA | Lipeles | Default - none. | 0 | 0 | 0 | | | |
| 20 | TBA | | TBA | Lo | Default - none. | 0 | 0 | 0 | | | |
| 21 | TBA | | TBA | Brennan | Default - none. | 0 | 0 | 0 | | | |
| 22 | TBA | | TBA | Tang | Default - none. | 0 | 0 | 0 | | | |
| 23 | TBA | | TBA | Kumfer | Default - none. | 0 | 0 | 0 | | |
| 24 | TBA | | TBA | Ramani, Vijay | Default - none. | 0 | 0 | 0 | | |
| 26 | TBA | | TBA | Fortner | Default - none. | 0 | 0 | 0 | | | |
| 27 | TBA | | TBA | Williams | Default - none. | 0 | 0 | 0 | | | |
| 28 | TBA | | TBA | Bose | Default - none. | 0 | 0 | 0 | | |
| 29 | TBA | | TBA | Foston | Default - none. | 0 | 1 | 0 | | | |
| 30 | TBA | | TBA | Moon | Default - none. | 0 | 0 | 0 | | | |
| 31 | TBA | | TBA | Zhang | Default - none. | 0 | 0 | 0 | | | |
| 32 | TBA | | TBA | Chakrabarty | Default - none. | 0 | 0 | 0 | | | |
| 33 | TBA | | TBA | Thimsen | Default - none. | 0 | 0 | 0 | | | |
| 34 | TBA | | TBA | Michels | Default - none. | 0 | 0 | 0 | | |
| 35 | TBA | | TBA | Ling | Default - none. | 0 | 0 | 0 | | |
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| Description: | An introduction to the theory and practice of engineering project management, with an emphasis on projects related to environmental protection and occupational health and safety. Topics include: project definition and justification; project evaluation and selection; financial analysis and cost estimation; project planning, including scheduling, resourcing, and budgeting; project oversight, auditing, and reporting; and effective project closure. Students will be introduced to commonly used project management tools and systems, such as work breakdown structures, network diagrams, Gantt charts, and project management software. Topics will also include project management in different organizational structures and philosophies; creating effective project teams; and managing projects in international settings. Prereqs: Enrolled in M Eng Program; Senior or Higher Standing. |
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| | 01 | -T-R--- | 4:00P-6:30P | TBA | Moore | See Instructor | 40 | 31 | 0 | | | |
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| | 29 | TBA | | TBA | Foston | Default - none. | 0 | 1 | 0 | | | |
| 32 | TBA | | TBA | Chakrabarty | Default - none. | 0 | 1 | 0 | | | |
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| | 03 | TBA | | TBA | Axelbaum | Default - none. | 0 | 0 | 0 | | |
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| | 01 | TBA | | TBA | Kruessel | No Final | 0 | 0 | 0 | | | |
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| | 01 | TBA | | TBA | Kruessel | No Final | 0 | 9 | 0 | | | |
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| | 01 | TBA | | TBA | Kruessel | No Final | 0 | 15 | 0 | | | |
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| Description: | Persistent concerns of grammar and style. Analysis and discussion of clear sentence and paragraph structure and of organization in complete technical documents. Guidelines for effective layout and graphics. Examples and exercises stressing audience analysis, graphic aids, editing, and readability. Videotaped work in oral presentation of technical projects. Writing assignments include descriptions of mechanisms, process instructions, basic proposals, letters and memos, and a long formal report. This online course will include content on Canvas, video meetings on Google Hangouts, and other technology as it becomes necessary. You should have a stable high-speed Internet connection and should be available on Fridays for an hour at either 10 am, 11 am, or 12 pm (for a video-chat with the instructor and classmates) Prerequisites: Satisfaction of the English composition proficiency requirement of the School and junior standing. |
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| | 01 | TBA | | TBA | Dahlheimer | No Final | 12 | 12 | 0 | Desc: | This online course will include content on Canvas, video meetings on Google Hangouts, and other technology as it becomes necessary. You should have a stable high-speed Internet connection and should be available on Fridays for an hour at either 10 am, 11 am, or 12 pm (for a video-chat with the instructor and classmates) |
| | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | TBA | | TBA | Dahlheimer | No Final | 12 | 13 | 0 | Desc: | This online course will include content on Canvas, video meetings on Google Hangouts, and other technology as it becomes necessary. You should have a stable high-speed Internet connection and should be available on Fridays for an hour at either 10 am, 11 am, or 12 pm (for a video-chat with the instructor and classmates) |
| | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 04 | TBA | | Remote / EN | Hamilton | No Final | 12 | 12 | 0 | Desc: | This online course will include content on Canvas, video meetings on Google Hangouts, and other technology as it becomes necessary. You should have a stable high-speed Internet connection and should be available on Fridays for an hour at either 10 am, 11 am, or 12 pm (for a video-chat with the instructor and classmates) |
| | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | TBA | | TBA | Kruessel | No Final | 0 | 3 | 0 | | | |
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| | 01 | M-W-F-- | 4:00P-8:30P | TBA | Karunamoorthy | See Instructor | 25 | 9 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | TBA | | TBA | Kruessel | No Final | 0 | 35 | 0 | | | |
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| Description: | Designed for PhD students engaged in their own research projects, this course (coupled with E60 5507) enables students to strengthen research communication skills critical for their professional development. The paired courses open with a three-week instructional module, E60 5506, that provides an overview of the process of writing, publishing, and presenting a peer-reviewed STEM research article or comparable project with attention to clear and convincing data presentation, analysis, and explanation. During those same three weeks, students also meet in a highly interactive small course, E60 5507, for which students must register concurrently. This first instructional module is followed by three weeks of independent work during which students draft their manuscripts. Students may meet as needed with the course instructors and/or selected faculty from the Engineering Communication Center during this time. After the three-week period of independent work, E60 5507 resumes for two more weeks. Due to the condensed format of the course, participation in the online meetings throughout the instructional modules is mandatory (June 1-18 and July 13-23). |
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| | 01 | MTWR--- | 1:00P-2:15P | TBA | Krone | No Final | 0 | 32 | 0 | | | |
| 02 | MTWR--- | 1:00P-2:15P | TBA | Schwelle | No Final | 0 | 35 | 0 | | | |
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| | 01 | MTWR--- | 2:30P-3:45P | TBA | Krone | No Final | 13 | 12 | 0 | | | |
| 02 | MTWR--- | 2:30P-3:45P | TBA | Schwelle | No Final | 13 | 13 | 0 | | | |
| 03 | MTWR--- | 2:30P-3:45P | TBA | Hamilton | No Final | 15 | 13 | 0 | | | |
| 04 | MTWR--- | 2:30P-3:45P | TBA | Essner | No Final | 15 | 14 | 0 | | | |
| 05 | MTWR--- | 2:30P-3:45P | TBA | Matteucci | No Final | 15 | 15 | 0 | | | |
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| | 01 | -T-R--- | 5:30P-9:15P | TBA | Ivanovich | See Instructor | 20 | 7 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | MTWR--- | 9:00A-11:00A | TBA | Hoven | See Instructor | 20 | 8 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | Study of probability and statistics together with engineering applications. Probability and statistics: random variables, distribution functions, density functions, expectations, means, variances, combinatorial probability, geometric probability, normal random variables, joint distribution, independence, correlation, conditional probability, Bayes theorem, the law of large numbers, the central limit theorem. Applications: reliability, quality control, acceptance sampling, linear regression, design and analysis of experiments, estimation, hypothesis testing. Examples are taken from engineering applications. Prerequisites: Math 233 or equivalent. |
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| | 01 | MTWR--- | 2:00P-4:00P | TBA | Kurenok | See Instructor | 30 | 26 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | Machine learning is the scientific study of algorithms and statistical models that computer systems use to automatically extract patterns from large volumes of data to provide insight information for decision making. This pervasive field sits at the intersection of computer science, statistics, linear algebra and optimization. This course provides a broad introduction to machine learning and statistical pattern classification with emphasis on Electrical and Systems Engineering applications. Students will study theoretical foundations of learning and several important supervised and unsupervised machine learning methods including linear model of regression and classification, logistic regression, Bayesian learning methods, neural networks, nearest neighbor method, principal component analysis, support vector machines methods and clustering. The course will take the format of lectures and small chapter projects in areas such as imaging, signal processing and control. Python programming language will be used for demonstration and course projects. Pre-requisites: ESE326, Math 233, linear algebra and CSE 131 or equivalent |
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| | 01 | MTWR--- | 9:00A-11:00A | TBA | Zhang | See Instructor | 20 | 9 | 0 | | | |
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| | 01 | MTWR--- | 5:30P-7:30P | TBA | Kurenok | See Instructor | 40 | 23 | 0 | | | |
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| | 01 | MTWR--- | 5:30P-7:30P | TBA | Kurenok | See Instructor | 40 | 11 | 0 | | | |
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| | 01 | MTWR--- | 10:00A-12:00P | TBA | Kurenok | See Instructor | 20 | 8 | 0 | | | |
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| | 01 | TBA | | TBA | [TBA] | Default - none. | 0 | 0 | 0 | Desc: | Contact Linda Buckingham lbuck@wustl.edu for registration information |
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| 11 | TBA | | TBA | Flores | Default - none. | 0 | 0 | 0 | | | |
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| Description: | The aim of this course is to introduce to students the general meaning, terminology and ideas behind nanotehnology and its potential application in various industries. The topics covered will include nanoparticles - properties, synthesis and applications, carbon nanotubes - properties, synthesis and applications, ordered and disordered nanostructured materials and their applications, quantum wells, wires and dots, catalysis and self-assembly, polymers and biological materials, nanoelectronics and nanophotonics, nanomanufacturing and functional nano-devices, health effects and nanotoxicity etc. Pre-requisite: none, students with background in general physics, chemistry and biology should be able to comprehend the material. |
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| | 01 | -TWR--- | 5:30P-9:30P | TBA | Agarwal | See Instructor | 30 | 25 | 0 | | | |
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| | 01 | TBA | | TBA | [TBA] | Default - none. | 0 | 0 | 0 | Desc: | Contact Linda Buckingham lbuck@wustl.edu for registration information |
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| 34 | TBA | | TBA | Meacham | Default - none. | 0 | 0 | 0 | | |
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| | 01 | MTWR--- | 5:30P-9:30P | TBA | Brandon | See Instructor | 35 | 28 | 0 | | | |
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| | 01 | MTWR--- | 3:00P-4:30P | TBA | Holland | See Instructor | 30 | 18 | 0 | | | |
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| | 01 | M-W-F-- | 4:00P-7:00P | TBA | Karunamoorthy | See Instructor | 35 | 37 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | The Energy Analysis and Design Project is designed to provide mechanical engineering skills in energy applications, renewable energy, and technologies related to energy which can involve heat transfer, thermodynamics, and fluid mechanics. The project topic can be chosen by the student or can be developed by both the student and faculty sponsor. The subsequent research and analysis, conducted under the guidance and direction of the faculty sponsor, results in a final project report that is approved by the faculty sponsor. The course is normally completed over one or two semesters. Recent projects have included: Energy Modeling and Efficiency Improvements: A Comparison of TRACE 700 and eQuest, Analysis of Hydroelectric Power, Optimization of Residential Solar Thermal Heating in the United States, Analysis of Ocean Thermal Energy Conversion Systems, Laboratory Plug Load Analysis and Case Study, Modeling and Optimizing Hydronic Radiant Heating and Cooling Systems using Comsol Multiphysics, CFD Analysis in HVAC Applications, Energy Analysis of Waste Disposal Methods, CFD Analysis of Containment Solutions for Data Center Cooling, Energy Recovery Ventilation, Comparative Study of Green Building Rating Systems, Grid Energy Storage, Protection of Permafrost Under the Quinghai-Tibet Railway by Heat Pipe Technology, Investing in Residential Solar Photovoltaic Systems, How Piping Layout Effects Energy Usage, and Comparison of Building Energy Savings Between China and the United States. |
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| | 24 | TBA | | TBA | Brandon | No Final | 0 | 0 | 0 | Desc: | Contact Linda Buckingham lbuck@wustl.edu for registration information |
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| | 01 | TBA | | TBA | [TBA] | Default - none. | 0 | 0 | 0 | Desc: | Contact Linda Buckingham lbuck@wustl.edu for registration information |
| | | |
| 03 | TBA | | TBA | Agarwal | Default - none. | 0 | 0 | 0 | | | |
| 25 | TBA | | TBA | Wagenseil | Default - none. | 0 | 0 | 0 | | |
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| | 01 | TBA | | TBA | [TBA] | Default - none. | 0 | 0 | 0 | Desc: | Contact Linda Buckingham lbuck@wustl.edu for registration information |
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| 15 | TBA | | TBA | Peters | Default - none. | 0 | 1 | 0 | | | |
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| | 00 | TBA | | TBA | [TBA] | Default - none. | 0 | 0 | 0 | | | |
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| | 01 | TBA | | TBA | [TBA] | Default - none. | 1 | 0 | 0 | | | |
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