Faculty Member: Kira Abercromby (kabercro@calpoly.edu)
Department: Aerospace Engineering

The project entails looking at trajectory options throughout cis-lunar space.  Trajectories, and the subsequent delta-v calculations, to be examined will include those in orbit about the Moon and transfer trajectories between the Earth and the Moon to determine possible options for trajectory paths in cis-lunar space.  Specific orbits might be in near rectilinear Halo orbits, ballistic lunar transfer trajectories, and return transfers from Halo orbits.  Finite burns, rather than impulsive burns, will be explored as well as the inclusion of perturbation effects, attitude of the spacecraft, mass and tank size, and power requirements.  Various types of propellant will be investigated to determination mass, power, and tank size needed.  The requirement for the deliverable is that the code be written in Matlab and incorporated in GMAT.

Faculty Member: Roy Jafari (rojafari@calpoly.edu) and Paul Anderson (pander14@calpoly.edu)
Department: Industrial & Manufacturing Engineering

The widespread popularity and adoption of consumer digital health tools has enabled the detailed study of how everyday behavior can impact health, at scale and in a real-world setting. However due to the rapid deployment of new measurement devices (e.g. consumer activity monitors) one of the key challenges in advancing the research has been the absence of standardization in how patient generated health data (PGHD) is represented. Lack of standardization can lead to isolated efforts across the research community that are difficult to compare or aggregate into collective meaning. Furthermore, data standardization can reduce research costs and could fast track efforts to make a meaningful impact on people’s health.

Learn more about standards in the nascent field of Digital Medicine.

There are several efforts focusing on creating standard semantics that enable meaningful description of data generated from consumer activity monitors. The scope of this project is to develop a tool that can convert data from market-leader wearable sensors into PGHD data standards. The project will involve:

1. Selection of target standards([1],[2],[3]) and selection of the PGHD signals/measurements (e.g., Apple Watch Heathkit activity and sleep data [4], Fitbit activity/sleep data [5], Garmin…) that will be converted to this standard.

2. Design of ETL (Extract/Transform/Load) software that is modular, extensible, well tested.

3. Implementation of tool (including software validation tests)

The aim of this program is to enable the research community and it is the intent to make the output software/tool open source.

Faculty Member: Dennis Derickson (ddericks@calpoly.edu)
Department: Electrical Engineering

In this project, we will work with project sponsors at Raytheon to design and fabricate a 1 by 8 solid state switch that covers the frequency range of 50 MHz to 18 GHz using surface mount components and low-loss dielectric substrates.    We will start by verifying models for p-i-n switch diodes using Keysight Advanced Design systems software.   We will then model the entire switch using a 2.5 dimension electromagnetic simulator to model the parasitic coupling between transmission lines for this star-configuration switch.   The last task will be to do the layout and ready design for fabrication.   If time permits we might be able to do a first pass fabrication of the design.

Faculty Member: Paulo Iscold (piscold@calpoly.edu)
Department: Aerospace Engineering

The Conceptual Design of aircraft concepts requires engineers to estimate a vehicle’s mission performance based on aerodynamics, propulsion, and mass properties. In reviewing student projects, it appears that reasonable academic resources exist to produce aerodynamic and mass properties data, but propulsion lags behind. The intent of this project is to produce a tool that can create installed propulsion data tables for theoretical engines, providing designers with critical insight that avoids the proprietary data limitations of major engine companies. This parametric model will greatly improve the ability to explore aircraft concepts and understand the important balance of these three complimentary disciplines.

Faculty Member: Dongfeng Fang (dofang@calpoly.edu)
Department: Computer Science

Boeing Enterprise Transportation, Warehousing, and Logistic s (TWL) is on a mission to expand its supplier reusable container assets and improve inventory tracking (reduce loss & theft) of these Boeing-owned shipping containers which are passively RFID tagged.  Currently, Boeing operates a fleet of trucks out of the Puget Sound area that pickup goods from regional cross docks, ports, air terminals, and local supplier docks to deliver to Pacific North West  factories.  These trucks currently utilize a  fleet management solution to ensure driver safety &  track GPS routes to manage maintenance requirements. Boeing Licensed Transportation (BLT) is in the market for a new fleet management solution that will integrate with RFID readers for the purpose of tracking goods throughout the supply chain.

Note: the term “Reusable Packaging”, refers to pallets, totes, custom-designed packaging or commercial off-the-shelf containers which can be re-used for transporting material.

The technical challenges include:

• Integrating a fleet management solution with cellular connected RFID readers
• Transmitting cellular data securely to Boeing (signal acquisition)
• Architecting a connectivity & storage solution from Boeing Licensed Transportation vehicle technology to AIT-IMS (Boeing middleware platform for tag management) and Teradata platform
• Successfully track contents of truck providing real-time insight of container location, quantity, and history without the need for manual/ hand-held scanning devices
  • History of container usage can be used to understand container life-span, maintenance costs, etc.

Faculty Member: John Oliver (jyoliver@calpoly.edu)
Department: Computer Engineering Program

Nearly every crime has a digital element, and the amount of digital evidence per crime has grown drastically since the introduction of the smart phone. A computer forensics examiner is often tasked with parsing through several terabytes of data to find a very small amount of digital evidence. This data can also span multiple devices and the evidence that the examiner, making it more difficult to find coherent evidence. For this project, we will be exploring the use of machine learning tools that can be used to enhance examiners ability to be comprehensive in their search for evidence. Machine learning is very good and parsing through large amounts of data and should be useful for identifying aberrant behavior of suspects. Machine learning could be used in a triage-mode, helping the investigator focus their search of evidence at particular events or times. The student and I would both learn how to use the Tensorflow open-source machine learning tool suite.

Faculty Member: Melinda Keller (mkeller@calpoly.edu)
Department: Mechanical Engineering

A Net Zero Energy home not only needs to provide all electric power to a home with a system such as Solar PV, but also needs to provide all its heating, cooling, and hot water on site. This project will examine the water within a residence and how it can be modeled with solar power and heat pumps to provide heating, cooling, and hot water meeting a net zero energy goal. [also see Addendum] Moving public opinion away from natural gas and toward heat pumps is a huge project the California Energy Commission is undertaking, and we can help by coming up with thermal models using such tools as Energy Pro, Ansys Work Beach, and Altair Hyperworks to show how the energy budget of a residential home changes with various thermal boundaries and equipment technologies.

Faculty Member: Stephen Klisch (sklisch@calpoly.edu)
Department: Mechanical Engineering

Project 1 – Baseball and softball pitching biomechanics. We will extend our previous work (with youth baseball pitchers) to adult baseball pitchers and youth and/or adult softball pitchers. We will recruit pitchers, possibly conduct DXA scans (with Dr. Reaves from Food Science & Nutrition and his Nutrition students), conduct pitching motion analysis experiments, calculate injury-related pitching arm kinetics (forces, torques), and conduct statistical analyses to investigate associations between kinetics and anthropometric body measures (body mass, arm mass, body are arm segment mass indices).

Project 2 – Gait biomechanics. We will extend our previous work (with adults) to children, including normal weight and overweight children (the latter being at high risk for knee injuries and arthritis). We will recruit children (elementary school age), possibly conduct DXA scans (with Dr. Reaves from Food Science & Nutrition and his Nutrition students), conduct gait motion analysis experiments, calculate knee kinetics (forces, torques), and conduct statistical analyses to investigate associations between kinetics and anthropometric body measures (body mass, body mass index, body fat percentage).

Faculty Member: Maria Pantoja (mpanto01@calpoly.edu)
Department: Computer Science

Thermals are regions of raising hot air formed on the ground through the warming of the surface by sunlight. Thermals are commonly used by birds and glider pilots to extend flight duration, increase cross-country speed, improve range, or simply to conserve energy. This kind of engine less flight using nature sources of lift is called soaring. Once a thermal is encountered, the pilot flies in circles to keep within the thermal, so gaining altitude before flying off to the next thermal and towards the destination. Estimating thermals is not an easy task, pilots look for different indicators like color variation on the ground because the difference in the amount of heat absorbed by the ground varies based on the color/composition, birds circling in an area because, and certain types of cloud formations (cumulus clouds). But the above method is not reliable enough and pilots study the conditions for thermals by estimating solar heating of ground (Cloud cover and Time year/date) and also the lapse rate and dew point of air.

In this project we want to use Machine Learning techniques to develop an algorithm that forecast thermals. We know that pilots record all their autonomous flights in a database with all the gps coordinates, speed, weather conditions and location of thermals. We want to use these database to train an algorithm to automatically predict the location of a thermal given as input the current weather conditions and terrain information (obtained from Google maps). The final product will be a mobile app where you introduce the location where you are and it will return an estimation of the location of the thermals so the pilot can plan the flight path to take to maximize the flight time.

Faculty Member: Christian Eckhardt (eckhardt@calpoly.edu)
Department: Computer Science & Software Engineering

This proposal is about a novel message passing interface (MPI) software, which utilizes multi-core CPUs at all scales (from normal PCs to super-computers) for solving numerical equations of all sorts. Supercomputers are dominating theoretical research for physics, mathematics, chemistry and biology with software’s such as ab initio simulations (“from scratch”). For such calculations, multi processing API’s (application programming interface) are used such as OpenMP or MPI. In short, one writes a program and the MPI software calls this program n-times with shared memory. Matrix calculations are split then over a number of processes, making modern theoretical research possible: The wait time for results is reduced from “days” or even “years” to some hours. Supercomputer are solely using MPI, OpenMP or sometimes similar alternatives. The most prestigious universities are involved in the development. Disclaimer: departments >buying< supercomputer packets of CPU cores, and not very often are more than 128 cores per calculation used due to parallel efficiency deficits above that number. This can be established on a local cluster or even on a better PC as well. (and is, still such an infrastructure is often a bit more expensive than simply buying some time at a supercomputer). This project is the start of our own solution, which will work similar to MPI, but can also access the GPU like OpenMP or CUDA. And we keep things simple, without implementing sophisticated matrix inverter or Eigen-value solver which get the last 5% speed out of the algorithm, since we don’t believe it to be necessary to sacrifice code simplicity for gaining 5% computational time.

Therefore we also do not rely on external libraries such as Boost or ScaLapack.

What we do:

– Matrix calculations (multiplying, inverting, Eigenvalue, Eigenvectors …)

– Syncing
– GPU access

How can you imagine that:

#include <simpi.h> //our API
void main(..) //called with an ID and how many processes in sum
{
Matrix A,B,C;
A = …; B = …;
C = SIMPI_matrixmult(A,B); //automatically distributes the work over all processes
SIMPI_synch(); //needed so no process runs ahead while the others are still working
Vectors v[] = SIMPI_Eigen(C);
…
}

Faculty Member: Andrew Danowitz  (adanowit@calpoly.edu)
Department: Computer Engineering Program

This proposal seeks to develop and validate the CAR (confront, address, and replace) framework for addressing biases and inequality in engineering. PI and students have already documented how problematic jargon and terminology commonly used in the engineering classroom can negatively affect the sense of belonging and inclusion for a wide variety of students (CoNECD 2020, postponed for CV19). Currently, however, faculty do not have a common framework for addressing this issue in the classroom: ignoring the terminology may promote color blind racism and leave students with a knowledge gap, confronting the terminology head on may lead to unproductive backlash from certain students (citations available on request). A student researcher on this project has proposed the CAR framework to address this problem. CAR calls on instructors and bystanders to Confront, or identify the problematic terminology, Address how the terminology is problematic and may be exclusionary to various groups, and come to a consensus a Replacement for the term that instructors can use for the rest of the quarter. This project proposes to explore how the CAR framework fits into current theories of race and inclusion with a special emphasis on STEM education. The project also proposes to experimentally apply the CAR framework on sample populations to start developing best practices for handling problematic jargon and terminology in the classroom.

Faculty Member: Moshen B. Kivy  (mbeyrama@calpoly.edu)
Department: Materials Engineering

High entropy alloys (HEAs) are a novel class of multicomponent alloys consisting of four or more specifically selected alloying elements with equi-molar compositions. Since 2004 when the first research outcomes of HEAs were published, these alloys have significantly transformed the conventional alloy design by introducing a vast variety of possible compositions, microstructures and properties. Over the past sixteen years, numerous research projects around the world have reported remarkable mechanical, chemical, and physical properties for HEAs and high entropy ceramics (HECs). Due to the compositional complexity of these materials, computational approaches have proved to be essential tools in design and development of HEAs and HECs. However, in many cases, calculated computational results are not in agreement with the experimental outcomes. Recently, a very few studies have associated this inconsistency to the elemental distribution of the elements in the crystalline structures. However, validating this idea requires further research. In this proposed research project, we will investigate this theory by studying the effect of elemental distributions (atomic positions) on vacancy and interstitial energies (as two examples of point defects) in some simple HEAs. This is a straight forward research project that is doable by undergraduate students. An online Python-based tool that we have developed will be utilized to generate the initial crystal structures with desired compositions. We developed this tool in 2019 as a MATE undergraduate summer project in collaboration with School of Materials Engineering, Purdue University, and published it on the nanoHUB website with student co-authors. After generating the initial defect-free crystal structures (supercells) using this online tool and calculating their cohesive energies, we will introduce the desired point defects to the structures and calculate their formation and cohesive energy. Carbon and/or oxygen will be considered as the interstitial elements in our simulations. All simulations and calculations are planned to be done using Vienna Ab-initio Simulation Package (VASP) as the most efficient and the most reliable software available for atomistic calculations. However, if the current situation of COVID-19 affects this plan (such as purchasing software license, software installation, etc.), Quantum-Espresso (QE) (website) as the open-source alternative software package will be used. Statistical analysis will be conducted on the results using Microsoft Excel. Due to the high efficiency of our calculations, we will be able to study a wide variety of HEA compositions and crystal structures. Although I introduce this atomistic-scale approach in MATE 403 (computational materials analysis), I will closely train and mentor the selected students through this research project regardless of their experience in this area. The results of this project will have a noticeable impact on the current state of the art HEA computational research and studies. Moreover, through this “Learn-by-Doing” research experience, the student will learn how to combine their course materials/knowledge with computational modeling and simulation in order to design microstructures and properties of desired materials. The product of this inclusive theoretical (modeling and simulation) research can be a student co-authored journal publication.

Faculty Member: Benjamin Lutz (blutz@calpoly.edu)
Department: Mechanical Engineering

Student evaluation of teaching (SET) plays a critical role in engineering education. In particular, SET serves two primary functions: (1) offering feedback to instructors to improve teaching and (2) providing administrative stakeholders with data needed to evaluate performance and make personnel decisions. But prior research has shown how these dual purposes can operate in conflict. For instance, a thoughtful critique from a student might help an instructor make better choices in future iterations of the class, but at the same time, that critique could be used as evidence of poor teaching. We argue that this tension can lead to faculty making pedagogical choices that minimize the potential for critical feedback. Further, we argue that such choices can run counter to existing recommendations for student-centered, active learning. As a result, my proposed research project will explore faculty perceptions of SET.

To do so, I will leverage an existing dataset of 29 interviews with engineering faculty at a large, predominantly white, land grant university in the pacific northwest. The interviews explore faculty beliefs about teaching as well as evaluation and probe for the ways in which instructors’ teaching philosophy aligns (or doesn’t align) with the ways in which teaching is evaluated via SET. Specifically, we will work to develop and submit a manuscript that explores the question, How do engineering faculty perceive the role of student evaluation, and how do those perceptions influence their pedagogical approaches?

For this Summer Undergraduate Research Program (SURP) 2020, I propose a project in which two students and I will perform three major tasks. First, we will conduct a thorough review of literature related to SET as well as qualitative methodologies. This step will establish a strong foundation for the subsequent stages of analysis and writing. Second, we will perform qualitative analysis of 29 interview transcripts, develop a codebook that offers a thick rich description of the present research question. Finally, in summation of our efforts, we will compose and submit a journal article The International Journal of Engineering Education.

Faculty Member: Theresa Migler-VonDollen  (tmigler@calpoly.edu)
Department: Computer Science & Software Engineering

In 1972 Richard M. Karp published a paper, “Reducibility Among Combinatorial Problems” that changed our understanding of the limitations of computing forever. He proposed that there are particular problems (of which he highlighted 21) that are more difficult than others. He called these problems “complete” and showed that they were all reducible to one another in the sense that if any one of these problems could be solved by an efficient algorithm, they all could be. Since 1972, thousands of additional problems have been added to this set. I propose a careful study of the original 21 problems of Karp with the purpose of making clear and explicit the reductions that create this class of problems. Then I propose to create a framework from which researchers and practitioners alike can classify their problems of interest. This would allow for less wasted time in trying to find efficient algorithms for problems that could quickly be shown to be complete. Practitioners would then be able to focus their attention and resources on efficient approximation algorithms.

Faculty Member: Pauline Faure (pfaure@calpoly.edu)
Department: Aerospace Engineering

The project tackles the concept development of a novel nano-reaction control system for small satellites and it will be carried out in collaboration with a local aerospace small business, Maverick Space Systems. The project overall goal is to establish the concept design of high performance, safe, and green miniature thruster system that will enable small spacecraft to expand their on-orbit capabilities. In particular, the students will define the functions of the system based on the stakeholders’ needs and overall assess the feasibility of the system to be developed. The students will also be responsible for generating various ideas and alternatives for the design of the system, which they will then assess to determine the concept presenting the best balance between performances, cost, risk, and development time. At the end of the SURP period, the students will present their analysis and recommendations to Maverick Space Systems during an industry review. Upon passing the review, the students will be able to pursue the project beyond SURP by manufacturing and testing the first prototype of the nano-reaction control system.

Faculty Member: Jonathan Ventura (jventu09@calpoly.edu)
Department: Computer Science & Software Engineering

A Computed Tomography (CT) scan combines many X-ray measurements to produce a volumetric reconstruction of internal organs and bones. CT is a critical component of cancer diagnosis and treatment planning. However, X-ray itself is harmful to the patient and thus it is desirable to reduce the amount of exposure required to reconstruct a usable image. Low-dose CT reduces patient exposure but also results in a lower quality reconstruction. In this project we will explore the use of deep learning to denoise the raw CT data before reconstruction. In particular, we will build upon an existing self-supervised approach developed in my lab for low-light microscope image denoising and extend it to be used for raw CT data denoising.

Faculty Member: Jennifer Peuker (jpeuker@calpoly.edu)
Department: Mechanical Engineering

While we have guidelines to design to for thermal comfort, we all know of buildings and spaces that are not comfortable and people are either too cold or too hot. When people are not comfortable—if they have access to a thermostat, most will adjust it without thought for the overall building energy usage. This research project will investigate occupant satisfaction and what influences their perception of thermal comfort in classroom settings—specifically the psychological influences on thermal comfort. It asks the question of whether we can influence people to believe that the room conditions are acceptable. The ultimate objective for the research is use the thermal comfort data to be able to reduce energy usage in buildings for heating and cooling. For the project this summer we will: use a Cal Poly created app to collect data about people’s thermal comfort perception, measure room conditions to create a model to predict indoor conditions in classrooms, and determine trends in historical data. For this project, we need (1) students who can or want to learn about mobile/web-based app development/maintenance, (2) students who want to learn how to process large amounts of data to determine trends and model the results, (3) any student who is interested in making an impact on the world by ultimately helping us reduce our energy usage. This project is wide open for applications and has the possibility to have far reaching impact, especially in the energy usage sector.

Faculty Member: Dongfeng Fang (dofang@calpoly.edu)
Department: Computer Science & Software Engineering

As the Internet-of-Things (IoT) becomes increasingly popular and widely adopted, more and more IoT applications are integrated into our lives, such as smart home and vehicular networks. Smart Home is a big trend as an application of many IoT applications. Due to wireless communication vulnerabilities, there are many security issues that exist in Smart Home systems. We have initialized the Smart Home system at Spring Quarter with all devices and their connections. With all the work in Spring Quarter, we will be able to remotely work on modelling the system and analyze the role of each device and the connections for each link. After system modelling, a security study will be carried out for each node and link. For each node, we will study the potential security problems in both hardware and software perspectives based on current security problems and academic research focus. For each link, we are going to analyze different wireless protocols including: WiFi, Bluetooth Low Energy, and Zigbee. Based on the node and link analysis, an overall system security analysis will be derived theoretically. Our analysis will not be only theoretical, but will include hands-on penetration tests based on IoT devices in students house. Besides smart home system, IoT is also widely adopted in vehicular networks. Tracking systems are used for a lot of applications in vehicular networks with wireless communications. How to provide security and privacy in these tracking systems is critical. There are manyrese arch focus and industrial work we can utilized as a theorical study. Possible existed data can be utilized to study tractor security problems.

Faculty Member: Franz Kurfess (fkurfess@calpoly.edu)
Department: Computer Science & Software Engineering

The goal of this project is to continue preliminary research conducted in two classes in the F19 quarter on the use of Artificial Intelligence and Machine Learning methods for the recognition of sharks and other objects in aerial video footage obtained by drones. While this initial work confirmed that the approach is viable, and the results deliver accuracy rates of about 80-90% with limited data sets and training efforts, we believe that there is significant room for improvement through a more concentrated effort by an interdisciplinary team of 2-5 students with backgrounds in Computer Science and related fields, and interest or backgrounds in marine biology. We have an existing collaboration with Dr. Chris Lowe from the Shark Lab at CSU Long Beach, who can provide us with drone video footage. The project also can include a biology student with an emphasis on marine biology. As a member of the Cal Poly’s Center for Coastal Marine Science (CCMS) advisory board, I have contacts with faculty and students in this area, primarily Dr. Ben Ruttenberg, the CCMS Director. The project will also benefit from the collaboration of Jeanine Scaramozzino, Cal Poly’s CSAM librarian. She has a background in Marine Biology, Geographical information systems, and Unmanned Aerial Vehicles, and is well-connected with shark researchers. The focus will be on the following aspects: Increase the available data sets by labeling more images containing sharks and other objects, and make them available to the wider research community.

1. Improve the machine learning models through longer training times and modifications of the computational models and architectures.

2. Explore the use of special-purpose hardware such as Intel’s Neural Compute Stick to port a trained model onto a low-power computing module that can be installed on a consumer-grade drone for real-time shark spotting as the drone flies over a coastal area.

Faculty Member: Dianne DeTurris (ddeturri@calpoly.edu)
Department: Aerospace Engineering

This research focuses on quantifying complexity in the development of modern aerospace systems. Qualitative methods are available to define problem domains and describe system vulnerabilities due to complexity (Snowden, Bonabeau). Recently, a baseline quantitative approach has been applied to aerospace (Tamaskar). The proposed research will be geared toward use of quantifying complexity in the conceptual design phase as a way to allocate resources for having the best chance of managing complexity. The complexity measurement process will hopefully be generalized for wider applicability through use of existing design structure matrix (DSM) methods (Eppinger).

References:
Bonabeau, E., 2007. Understanding and managing complexity risk. MIT Sloan Management Review, 48(4), p.62.
Snowden, D.J., and Boone, M.E., 2007. A leader’s framework for decision making. Harvard business review, 85(11), p.68.
Tamaskar, S., Neema, K. and DeLaurentis, D., 2014. Framework for measuring complexity of aerospace systems.
Research in Engineering Design, 25(2), pp.125-137.
Eppinger, S., and Browning, T. Design Structure Matrix Methods and Applications. MIT Press, Reprint, 2016.

Faculty Member: Siyuan (Simon) Xing (sixing@calpoly.edu)
Department: Mechanical Engineering

Recently, there is a growing interest in legged robots. The legged robots need to handle physical interactions with the ground, which significantly challenges traditional design methods for non-contact robots. Numerical methods are used extensively to study the dynamics of such robots in both academia and industry. This project will investigate the locomotion of a hopping robot using Stateflow, a MATLAB toolbox for numerical study of systems with physical interactions. The robot will be modeled in Stateflow, and its locomotion will be simulated. From the simulation, the effects of system parameters (e.g., robot mass, spring coefficients, and forward speed) on the dynamic performance and gaits of the robot will be explored. Finally, the animations of hopper’s locomotion will be generated to provide a better understanding of the dynamics of the legged robot.

Faculty Member: Nianpin Cheng (ncheng@calpoly.edu)
Department: Industrial & Manufacturing Engineering

Guaranteeing each player in competitive youth sports programs such as baseball, basketball or soccer plays for an equal amount of time is not only one of the top concerns for players and coaches, but also an inclusive practice. However, coaches have been struggling in creating a time allocation sheet that ensures every player plays for the same amount of time because there is currently no solution readily accessible for coaches to use online. Ensuring each player plays for an equal or close to equal amount of time each game and no player stays on the bench consecutively for two quarters per game are all requirements that make it very difficult for coaches to come up with a weekly schedule to balance the players’ game time. The objective of this research project is to use goal programming to develop an optimization model for this problem and also make the solution readily available to coaches. This would be an easy to use solution that could be extended to many youth sports. The PI has already built a preliminary solution for one YMCA youth basketball team in San Luis Obispo and received positive feedback. In this project, two undergraduate students will be advised to create a solution that can be extended to other youth sports and help make the solution accessible to more youth sports coaches via internet and/or mobile applications.

Faculty Member: Jean Lee (jlee473@calpoly.edu)
Department: Materials Engineering

Gypsum is one of the main products of H. M. Holloway, a local company with offices in San Luis Obispo county that is a leader in soil amendments. H. M. Holloway’s raw gypsum ore is mainly comprised of three different materials: gypsum (calcium sulfate dihydrate or CaSO4 • 2H2O), quartz (SiO2), and calcium bentonite clay. Each of these three component materials holds potential economic value for H. M. Holloway, and the process of beneficiating the raw gypsum ore separates these three materials from each other. This project is a collaboration with H. M. Holloway to develop and conduct proof-of-concept testing of inexpensive, efficient, and environmentally-friendly methods of beneficiating the raw gypsum.

Beneficiation based on mechanical and electromagnetic principles is the primary focus of this project, although other approaches to beneficiation may be explored based on interest and time. The mechanical and electromagnetic approaches include the following:

Separation via agitation or milling of the raw gypsum ore using different front end screening techniques, as bentonite clay has been observed to often have a smaller particle size than the other constituents of the raw gypsum ore.

–

Calcium bentonite clay has significant cation exchange capacity, and in particular it is known to be able to exchange some of its cations with iron cations (iron is not regarded as deleterious to the clay). We seek to take advantage of this property by exchanging the iron cation in hematite (Fe2O3, or rust) with cations in the clay. With iron introduced into the clay, we will explore using a magnet as another means of separating the calcium bentonite clay from the other two materials.

–

Gypsum is also known to have a significant cation exchange capacity, which implies that the surface of gypsum particles is charged. Static electricity that is induced on a cloth, for example, will be investigated as a means of attracting gypsum particles and separating it from the other two materials.

–

Using the piezoelectric property of quartz, the removal of quartz from the other two materials will be examined by pressing the raw gypsum between two plates, with one of the plates being charged.

Faculty Member: Ryan Nugent (rnugent@calpoly.edu)
Department: Aerospace Engineering

The purpose of this project is to develop a deep space communication system for small spacecraft. The project’s overall goal is to establish the conceptual design of an efficient, low power, and low cost deep space communication system. This communications system will enable small spacecraft to expand their on-orbit capabilities and enable a larger number of players access to deep space research. In particular, the students will define the functions of the system based on the stakeholders’ needs and assess the overall feasibility of the system to be developed. The students will also be responsible for generating various ideas and alternatives for the design of the system, which they will then perform trade studies to determine the best balance between performance, cost, risk, and development time. Finally, based on their analysis, the students will have a design that is ready to be manufactured and tested in the future. At the end of the SURP period, the students will present their technical approach which lead to the communication system prototype. In addition, the students will also present their assessment of the communication system performances and provide recommendations to complete the system after SURP.

Faculty Member: Taufik (taufik@calpoly.edu)
Department: Electrical Engineering

In 2013 the California legislature passed a mandate aimed to reduce greenhouse gas emissions, meet air quality standards, and achieve a carbon free electric power grid by establishing a target of 1,325 megawatts (MW) of energy storage for the state’s three investor-owned utilities: Pacific Gas & Electric (243 MW), Southern California Edison (422 MW), and San Diego Gas & Electric (156 MW). In response to this aggressive target, the three utility companies have been actively installing utility scale energy storage utilizing mainly three battery technologies: Lead-Acid, Lithium-Ion, and Vanadium Redox Flow. The lead-acid and lithium-ion technologies have been widely used, and their operation and characteristics have been thoroughly studied and well understood. This helps utility engineers in knowing the technical impacts of connecting these batteries to the power grid. The picture, however, is not the same for the Vanadium Redox Flow Battery (VFRB). This is mainly due to its unpopularity from its large physical size and higher cost compared to the other technologies. However, the past few years the VFRB technology has gained increased interest among utility companies because of its decreasing cost and its long life cycle: in excess of 15,000-20,000 charge/discharge cycles which are far beyond the life cycle of the other two technologies which is usually in the order of 4,000-5,000 charge/discharge cycles. This research project aims to develop an improved VFRB model which takes into account the coupling effects between the electrochemical and the thermal behaviors of VFRB. The proposed enhanced model will provide a very useful tool for utility engineers during critical system planning wherein the model can provide accurate performance and operating characteristics of the VFRB when connected to electric power grid or microgrids.

Faculty Member: Hani Alzraiee (halzraie@calpoly.edu)
Department: Civil & Environmental Engineering

Unmanned Aerial Vehicles (UAV) are an emerging technology that serve a range of applications for construction purposes including the creation of site survey maps, jobsite monitoring for routine progress reports, and structural inspections. As a relatively new asset to construction, expanding awareness of the benefits UAVs offer and developing concise implementation plans will increase access to this technology and improve the industry at large. The purpose of this research is to investigate the application of UAVs in the preconstruction and planning phases of a project to develop a framework for drone deployment by companies currently using traditional methods. Proper utilization of UAVs in the construction industry is expected to enhance project scheduling, reduce project costs of construction tasks, streamline progress-tracking, and improve overall jobsite safety. However, even with the benefits drones can provide, they have not yet been widely utilized by the construction industry. This is due to various factors including regulatory issues, a lack of standards and best practices of using this technology, and construction practitioner’s hesitancy to take the leap and invest in a promising but not-yet-widely-adopted product. These implementation challenges indicate a major hindrance to drone adoption is not a perceived lack of merit but rather the natural growing pains of an emerging technology. Therefore, presenting new concepts, experiments, and case studies, as well as defining methodologies and best practices for current and future integration of UAVs in various stages of the construction life cycle is integral in spurring the acceptance of this rising technology. This study emphasizes UAV integration in preconstruction and planning stages as these tasks are most representative of the initial uses of drones in a company and they are less risky than future implementations involving flying around and over active job sites. In order to implement the concept, data collection of construction sites using UAVs will be conducted and analyzed using cloud-based computation platforms. A framework that outlines the most efficient use of drones in various tasks and provides comparisons to the traditional alternatives will be implemented. The outcome of this research is expected to improve construction productivity and safety. Drone use in construction is a rising technology. Providing students an opportunity to research and investigate this topic and use their skills to improve it will be an extremely unique addition to their portfolios and will set them apart from their peers. In the coming years, drone utilization has the potential to become a new standard in the construction industry. Interested students will have the opportunity to learn about this rising technology first-hand and their work through SURP will give them a chance to be prepared and present findings to become a part of this transition as it is happening. The research completed by this program will set precedent for further education of drone use in construction at Cal Poly by increasing awareness of this technology in the student body. Cal Poly already has strong connections with many companies in the construction and civil engineering industries. The recent addition of CE 415: Advanced Building Information Modeling for Civil Engineering and this proposed work involving drones in construction points to a future where Cal Poly can emerge as a leader in colligate education of state-of-the-art construction technology resulting in successful graduates and potential partnerships with companies specializing in the field of Virtual Design and Construction (VDC).

Faculty Member: Joseph Callenes-Sloan (jcallene@calpoly.edu)
Department: Computer Engineering Program

The world is facing a long term crisis with high energy demands and climate change. Roughly 80% of the world’s energy consumption is from fossil fuels. The energy systems we use today were designed and built around using fossil fuels, with rigid infrastructures and centralized control and generation. In order to reach significantly higher levels of efficiency and sustainability, the future of energy generation and consumption will need to be very different from what we have today. To fully support the heterogeneous, decentralized and integrated architecture of these systems, ubiquitous communications across the system will be necessary. Many of those communications will also be used for critical and automated decision making. Security for these signals and systems is essential. The first part of the project focuses on building highly decentralized and heterogeneous systems that achieve high flexibility, efficiency, and security. At the same time, many emerging computing infrastructures increasingly utilize a variety of devices (e.g. IoT, mobile, edge, cloud, etc.) in a hierarchal fashion which exposes the entire system to significant cyber-attacks and side-channel vulnerabilities. The second part of the project will investigate cross-layer approaches for verifying, protecting against, and recovering from exploits including hardware and software-based attacks. Open source tools and RISCV-based processor designs will be used for the study.

Faculty Member: Mohamed Awwad (mawwad@calpoly.edu)
Department: Industrial & Manufacturing Engineering

California is America’s top wine producer, making 90% of all U.S. wine. California is the world’s fourth-leading wine producer after Italy, France, and Spain. Realizing the importance of wine production to both the local and national economies, the Cal Poly Wine and Viticulture department was established more than three decades ago. The Wine and Viticulture program at Cal Poly is the largest of its kind in the U.S. and emphasize the Cal Poly learn-by-doing philosophy while educating its students. To provide Cal Poly students with a more extensive practical experience, the Cal Poly Wine and Viticulture Department launched the Cal Poly Wine Club. The Cal Poly wine commercial and business activities have witnessed rapid growth in the past few years. They will expand massively in the coming years with the Cal Poly Wine and Viticulture department controlling more components of the wine supply and distribution operations from growing to delivery to the end consumer. The main goal of this research project is to allow an interdisciplinary team of Cal Poly Engineering students the opportunity to analyze, improve and plan the complex post-prohibition wine supply chain with an application on the Cal Poly wine supply chain operations. The student researchers will work immediately on providing a solution to some of the problems faced by the Cal Poly Wine and Viticulture department in their e-commerce sales and distribution processes. Additionally, and under the supervision of the PI’s, the students will work on providing a technically-sound plan for the continuously growing Cal Poly wine operations and investigating the feasibility of incorporating modern technology such as the blockchain technology.

Faculty Member: Alicia Johnstone (aijohnst@calpoly.edu)
Department: Aerospace Engineering

This project will focus on developing an autonomous thermal control system designed to keep payloads on long duration missions within safe temperature limits. This project is part of a larger effort to develop the first CubeSat deployment system designed specifically for lunar and interplanetary missions. Students will define the thermal system requirements based on a range of potential thermal profiles, including transfer orbits to Mars, the asteroid belt, and beyond, and then develop the thermal control system to keep onboard components within the specified range. Students will explore both active and passive methods of thermal control as well as the associated control law behind the control system. Finally, thermal system design documentation will be generated, including schematics, drawings, and lists of off the shelf components required.

Faculty Member: Charles Birdsong (cbirdson@calpoly.edu)
Department: Mechanical Engineering

Cal Poly submitted a proposal and into the Indy Autonomous Challenge Competition in winter 2020. The judges graded our proposal as “Exceptional” and accepted our team “IndyCarPoly” into the competition. Our team so far includes faculty from Computer Science, Mechanical Engineering and Ag. Engineering. We are still working on recruiting students to work on the project. I hope to use SURP as a means to get students started on this project and then recruit them to join the team for the whole competition. The competition challenges teams to develop software to program a formula racecar to drive around the Indianapolis Speed Way at over 100 mph autonomously. This competition is unique because the sponsors will provide the Indy formula car and the software environment so teams are only responsible for writing computer code. This is attractive because we do not need to focus on raising a significant amount of money and developing our own vehicle and hardware. I hope to use SURP to recruit students onto our team and get them started with the project.

Faculty Member: Arnold Deffo (adeffo@calpoly.edu)
Department: Aerospace Engineering

Modeling an airplane is a key step in aircraft structural analysis, which itself is an important step before structural testing. During the early stages of design, one possible model is the beam model whereby the structure is modeled as a collection of beams forming the skeleton of the aircraft. As such, beams are structural elements that are central to design and analysis problems in aerospace engineering. In the beam model, the aircraft wing is often approximated as a cantilevered beam subject to transverse loads due to the lift distribution. However, because an actual wing has a non-uniform chordwise pressure distribution, the resultant lift distribution generally creates torsion of the wing in addition to bending. For homogeneous, isotropic beams, the analysis often consists of treating the torsion and bending cases independently as the resulting governing equations are uncoupled. However, for composite wings, it is not possible to decouple these two deformations. In this work, we investigate the free vibration behavior of a composite wing under coupled torsion-bending. Because of the formidable challenge associated with doing so in the most general case, we limit ourselves to structures with uniform spanwise geometric and material properties. Specifically, our numerical solution is based on the Rayleigh-Ritz method where we use the uncoupled mode shapes for torsion and bending as assumed modes to approximate the natural frequencies and mode shapes of the wing. The resulting mode shapes and natural frequencies are then compared to ones from the literature as a way to study the validity of the approach adopted in this work. We conclude with a sensitivity study to determine the effect of the bendingtorsion coupling stiffness and inertial coupling on the natural frequencies and predicted mode shapes.

Faculty Member: Bruno DeSilva (bcdasilv@calpoly.edu)
Department: Computer Science & Software Engineering

Software development is strongly dependent on source code management tools and platforms such as Git, GitHub, Bitbucket, and GitLab. Software teams also rely on issue tracking systems such as Jira, Bugzilla, and GitHub Issues, to manage tasks during the development and maintenance life-cycle of software applications. By using those systems, software developers leave a massive amount of valuable data regarding the product or service they develop and the process they follow to build and maintain these products/services – we call it software repository data. However, software repository data is only partially explored by services such as GitHub and, when these data are utilized to provide useful information to developers, it is usually provided through web-based user interfaces. These interfaces are not always convenient for developers when they have to make quick decisions during team meetings or when they are juggling through multiple screens that they have to use to carry out their engineering tasks. Therefore, in this project, we propose to implement an intelligent voice assistant skill for software developers and software teams to run on well-known smart voice assistant platforms such as Amazon Alexa and Google Assistant. Our voice assistant application backend will have access to the user (developer) software repository (including code, issue tracking, pull requests, test code, build data, etc.) to gather data and answer questions such as “Alexa, who was the last contributor to the module Customer.py?”, “Alexa, who has written more tests for Post.java?”, “Hey Google, who has been assigned the highest number of issues in this sprint?”, “Who has contributed with more lines of code [in general] [or in the file Sort.py]?”, “How many pending pull requests we have?”, “What’s our avg bug fixing time?”, “What’s our median pull request review time?”, “What’s the priority of issue #10?”, and some more complex questions, such as, “Who should review file App.js?”, “Who should be assigned to issue #15?”, “Have we increased test coverage in the last two sprints?”, “How much of our codebase has grown over time?”

Faculty Member: Dale Dolan (dsdolan@calpoly.edu)
Department: Electrical Engineering

The energy and associated economic losses due to soiling on both residential and utility scale PV (photovoltaic) systems can be both significant and avoidable. Regular losses of up to 5% but sometimes reaching 10-15% have been reported which is of interest to system operators. Modules may be cleaned to reduce losses, but this comes with an offsetting economic cost. This research project will investigate reduction of soiling through control of the stowing angle of modules when not generating energy. This is a much more economically efficient method and can be done without any additional equipment being added to the system. I have obtained access to allow control of the tracking system at the Cal Poly Goldtree Solar Farm to allow this project to be completed 100% remotely. All control and data collection can be accomplished via a web based dashboard that allows us to monitor the performance of the farm in real time and to collect data that can be analyzed for optimization. The angle that the modules are stored while not producing energy affects the wind loading that is experienced but also may increase or decrease the amount of soiling that collects on the module but would also affect the self cleaning of the modules from dew, condensation, and rain. It is desired to determine an optimal strategy such that these competing interests can be optimized.

Faculty Member: Dale Dolan (dsdolan@calpoly.edu)
Department: Electrical Engineering

The Cal Poly Solar farm has been built as a single axis tracking facility with two different types of panels. Both conventional single cell solar panels and twin cell solar cells have been used in its construction. Twin Cell panels typically perform better than their conventional counterparts when shaded by other panels in the row in front of them in a fixed tilt system. However neither module performs well when even a small portion is shaded. Backtracking is a technique where the single axis tracker avoids shading other rows by sub-optimally tracking the sun until it is high enough in the sky that this is not necessary. This is relatively straightforward in a field that is flat or at least has all controlled modules in the same array. However the Cal Poly Solar farm installation has significant variation in terrain and this was transferred to the modules in adjacent rows such that they are not in the same plane nor are they parallel. As a result there is significant error in the backtracking algorithm that was not designed for this case which is seen by significant power losses in both of the types of panels. The subject of this research project will be to investigate and identify the areas where there is significant power loss from row to row shading. We will then determine how to adjust the limited input parameters into the existing algorithm to adjust such that performance is improved. The parameters will need to be adjusted for all 12 trackers and they will need to be determined every day. This is too time intensive for a plant operator to do every day manually and through a process of trial and error as they have been doing. As a result the parameters are only adjusted a few times per year and thus great quantities of energy are lost. We will develop an automated process for determining the parameters and through remote control validate the model used. I have obtained access to allow control of the tracking system at the Cal Poly Goldtree Solar Farm to allow this project to be completed 100% remotely. All control and data collection can be accomplished via a web based dashboard that allows us to monitor the performance of the farm in real time and to collect data that can be analyzed for optimization. The angle that the modules are tracking to can be monitored in real time and it can be determined through power monitoring if any modules are being shaded or not. It is desired to determine an optimal strategy such that the competing interests of operational time invested and energy gain achieved can be optimized.