BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230619T100000
DTEND;TZID=America/New_York:20230619T120000
DTSTAMP:20260404T083535
CREATED:20230613T144457Z
LAST-MODIFIED:20230613T144457Z
UID:10007579-1687168800-1687176000@seasevents.nmsdev7.com
SUMMARY:CBE PhD Thesis Defense: "Electrochemical and Heterogeneous Catalysis for Selected Industrial Commodities"
DESCRIPTION:            Novel high-surface-area catalysts were synthesized for selected industrial chemical reactions\, conducted in heterogeneous reactors and electrochemical reactors. Atomic layer deposition (ALD) was used to synthesize highly dispersed metal catalysts and to deposit uniform oxide thin films on porous supports. \n            The interaction between Cu catalyst and its oxide support was studied for the water-gas-shift reaction\, a critically important reaction for maximizing the H2 production from syngas. The ALD-prepared Cu catalyst demonstrated ten times more reactivity than the impregnated Cu catalyst with the same metal loading and surface area. The selected oxide supports did not show promotion effects for the reaction\, but some mild stabilization over long-term aging was observed. In another case\, the selective oxidation of butane to maleic anhydride was studied on an ALD-prepared vanadium phosphate catalyst with eight times more surface area compared to the commercial bulk catalyst. Furthermore\, an ALD-prepared CaO/MgAl2O4 catalyst was studied for the aldol condensation of furfural and ketones/aldehydes to form precursors of lubricant oils and surfactants. The side reaction\, Cannizaro reaction\, was investigated for the long-term use of this catalyst. \n            Lastly\, ammonia synthesis was studied in a solid oxide electrochemical cell made with the state-of-the-art proton conductor BZCYYb (BaZr0.1Ce0.7Y0.1Yb0.1O3−δ). Instead of using both high temperature and high pressure in the commercial Haber-Bosch process\, this reaction was carried out under ambient pressure. The proton recombination was found to be barrierless on the cell surface\, greatly limiting the selectivity to ammonia. The implications of this phenomenon and its suppression were discussed.
URL:https://seasevents.nmsdev7.com/event/cbe-phd-thesis-defense-electrochemical-and-heterogeneous-catalysis-for-selected-industrial-commodities/
LOCATION:Towne 225
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230620T100000
DTEND;TZID=America/New_York:20230620T233000
DTSTAMP:20260404T083535
CREATED:20230615T130946Z
LAST-MODIFIED:20230615T130946Z
UID:10007582-1687255200-1687303800@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Computationally-constrained Dynamically-feasible Search-based Motion Planning"
DESCRIPTION:Planning fast and autonomous robotic motion in unstructured\, cluttered environments remains a core challenge of the robotics community. The robot’s motion must be agile and dynamic\, operating near the limit of its physical capabilities\, to reach its goal location as quickly as possible. Fast motion in turn creates a need for fast plan computation over large and complex areas of the robots environment. Search-based planning\, entailing search over trajectory-based graphs\, offers a theoretically grounded method to plan optimal motion that is dynamically feasible. However\, the computational footprint of this approach is often too burdensome\, as graph search speed scales inversely with the size of the planning graph. To tackle this challenge\, we concentrate on designing a sparse planning graph and dynamically determining the required graph size based on obstacle density. \nWe introduce a method for selecting vertices and edges in a motion primitive graph grounded in statistical dispersion\, which ensures guarantees on planner completeness. By minimizing dispersion of graph vertices in the trajectory cost-induced metric space\, our approach efficiently covers the space of feasible trajectories. Our motion primitive graphs outperform baseline methods\, with lower dispersion\, fewer iterations of graph search\, and fewer tunable parameters. \nWhile this method can generate high-quality graphs of a specified size\, the selection of this size has significant effects on planner performance. Sparser graphs may miss a narrow corridor that the plan must traverse\, while denser ones may result in excessive computation time. We address this tradeoff with a framework consisting of two parts: offline maximization of planner completeness for several graph sizes\, and online dynamic adjustment of the graph size based on empirical planner performance. Through real world experiments in cluttered pine forests\, we demonstrate the real-time adaptability of the planner to different environments\, enabling flight up to 2.5 m/s in varying tree densities. \nFinally\, we explore the integration of trajectory optimization with search-based planning\, highlighting the potential synergies between these approaches and providing design tradeoffs.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-computationally-constrained-dynamically-feasible-search-based-motion-planning/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230620T120000
DTEND;TZID=America/New_York:20230620T130000
DTSTAMP:20260404T083535
CREATED:20230613T154734Z
LAST-MODIFIED:20230613T154734Z
UID:10007580-1687262400-1687266000@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis Defense: “Design\, Characterization\, and Fabrication of Low-Cost\, Passive\, and Biodegradable Sensors For Precision Agriculture”
DESCRIPTION:With the global population projected to reach 9.1 billion people by 2050 there is a need to develop highly efficient agricultural systems that maximize crop yield. Precision Agriculture (PA) systems enabled by the Internet of Things (IoT) offer a potential solution through improvements in labor\, resource\, and time efficiency to improve agricultural output. PA systems enable this by providing a detailed characterization of field environment (e.g.\, soil moisture\, pH\, temperature\, etc.) so that these resources can be properly deployed spatially and temporally. To realize these systems\, sensors that give information about the state of the field are required. However\, for the technology to be scalable and practically implemented\, these sensors must balance performance and cost. These requirements limit the materials and methods that can be used to develop the technology\, including many that are common in modern sensor development. Additionally\, the challenge of biocompatibility and biodegradability must be addressed. \nIn this work\, a passive RF sensing system is presented for the detection of soil moisture. First\, a fabrication process for a fully biodegradable cellulose nanofibril (CNF) based composite substrate is presented. By using small quantities of CNF\, we are able to planarize the surface of a pulp-based cardstock paper to achieve smooth surfaces that are suitable for the fabrication of electrical structures. Next\, the hygroscopic properties of cellulose are leveraged to develop a capacitive sensor that utilizes the substrate as the sensing mechanism. By utilizing screen printing\, we repeatably produce capacitive structures with a high degree of fidelity. We demonstrate the ability to detect both humidity and soil moisture over a wide range and show the ability of the sensor to operate within the 902 – 928 MHz band. Additionally\, sensor cycling and repeatability is demonstrated\, a key requirement for in-field application. \nFinally\, integration and packaging of the sensor is investigated. Capacitive structures are integrated into a wired PCB system and are shown to exhibit good performance. Natural wax-based packagings are also explored\, with mechanical characterization of various wax mixtures conducted to choose a suitable candidate. We show that the selected wax mixture can protect devices in a soil environment while still enabling capacitive sensing\, demonstrating the ability for natural waxes to be used as a suitable packaging material for biodegradable sensors.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-defense-design-characterization-and-fabrication-of-low-cost-passive-and-biodegradable-sensors-for-precision-agriculture/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Dissertation or Thesis Defense
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230620T130000
DTEND;TZID=America/New_York:20230620T140000
DTSTAMP:20260404T083535
CREATED:20230616T131007Z
LAST-MODIFIED:20230616T131007Z
UID:10007585-1687266000-1687269600@seasevents.nmsdev7.com
SUMMARY:PSOC@Penn Seminar: Michael Tobin
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/psocpenn-seminar-michael-tobin/
LOCATION:Towne 327
CATEGORIES:Seminar,Doctoral,Graduate,Student
ORGANIZER;CN="PSOC":MAILTO:manu@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230621T100000
DTEND;TZID=America/New_York:20230621T110000
DTSTAMP:20260404T083535
CREATED:20230620T124224Z
LAST-MODIFIED:20230620T124224Z
UID:10007592-1687341600-1687345200@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis Defense: "Addressing Stiffness-induced Challenges In Modeling and Identification of Rigid Body Systems with Frictional Impact"
DESCRIPTION:Imperfect but useful dynamical models have enabled significant progress in planning and controlling robotic locomotion and manipulation. Traditionally\, these models have been physics-based\, with accuracy relying upon manual calibration only feasible in laboratory environments. As robotics expands into complex real-world applications\, models must instead be automatically fit to limited data. One major challenge is modeling frictional contact\, especially during collisions involved in common robotics tasks. Rapid deformation under impact manifests as extreme sensitivity to initial conditions and material properties. Thus\, even slight errors in state estimation and system identification can lead to significant prediction errors. Consequently\, model inaccuracy or the sim-to-real gap often hinders the development of performant robotics algorithms. \nWhen only a few parameters are unknown\, physical models can be optimized using advanced techniques to overcome these challenges. However\, even with accurately identified parameters\, roboticists must make inaccurate rigid-body approximations to reduce the computational burdens of physical simulation to meet faster-than-real-time requirements. An alternative black-box approach has attempted to address these issues\, in which dynamical models are learned from scratch\, for instance using deep neural networks (DNN’s). While DNNs in theory can capture any dynamical behavior\, they have empirically struggled with the stiff behaviors associated with contact. \nThe dissertation instead focuses on scaling physical model identification to the high-dimensional setting and quantifying the limited accuracy of low-fidelity physics models. We consider rigid bodies undergoing rigid contact\, for which infinite stiffness is represented as constrained optimization inside the dynamics. By careful treatment of these constraints\, we demonstrate that infinitely-stiff dynamics can be identified by optimizing a non-stiff objective. In conjunction\, we use DNN’s in a white-box setting to model purely physical quantities\, specifically reconstructing geometries from scratch. We then consider how the simplified rigid-body view of collisions lacks fidelity to correctly predict the outcomes of nearly-simultaneous collisions—such as heel and toe strikes during a foot step. We develop a theoretical basis to capture partial knowledge of such events as uncertain set-valued outcomes\, and again use numerical optimization to compute approximations of such sets.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-defense-addressing-stiffness-induced-challenges-in-modeling-and-identification-of-rigid-body-systems-with-frictional-impact/
LOCATION:Moore 216\, 200 S. 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Dissertation or Thesis Defense
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230622T130000
DTEND;TZID=America/New_York:20230622T143000
DTSTAMP:20260404T083535
CREATED:20230615T155111Z
LAST-MODIFIED:20230615T155111Z
UID:10007584-1687438800-1687444200@seasevents.nmsdev7.com
SUMMARY:MSE PhD Defense: Autonomous Stimuli-Responsive Metamaterials Based on Liquid Crystal Elastomers
DESCRIPTION:Numerous responsive materials have been developed in recent decades and applied toward engineering challenges ranging from medicine to robotics. For example\, polydimethylsiloxane (PDMS)\, hydrogels\, shape memory polymers (SMPs)\, liquid crystal elastomers (LCEs)\, and many other materials can be engineered to respond to many environmental stimuli\, such as non-polar solvents\, humidity\, heat\, light\, magnetic fields\, and electric fields. However\, there are some major limitations with most responsive materials: they typically respond slowly to the environment\, and the deformation triggered by the environmental input is often small. In this dissertation\, we propose to address these limitations by integrating responsive materials with mechanical metamaterials that are governed by scale-independent nonlinear mechanisms. These mechanisms can amplify and speed up the deformation of the responsive materials beyond what is possible for the responsive material\nby itself. \nIn this dissertation\, we specifically focus on the use of nonlinear mechanisms to improve the responsiveness of LCEs to changing heat or light in the environment\, enabling autonomous\, large-amplitude\, rapid deformation in engineered systems. We demonstrate the potential utility of this strategy in several contexts. First\, we engineer a metamaterial based on rotating squares with hinges consisting of LCE-PDMS bilayers. These bilayers\, combined with geometric properties\, such as the hinge thickness\, determine how the metamaterial deforms in response to temperature variations in the environment\, including the possibility of achieving either local or global deformation changes in response to localized temperature variations. Next\, we build a kirigami-inspired robot that autonomously changes its trajectory in response to the environment\, without any electronic controlsystem. The LCEs govern the behavior of modular “control units” that can be placed throughout the kirigami. These\, in turn\, locally impose mechanical constraints that control how the kirigami bends\, and thereby where the robot moves. Finally\, with the goal of attaining autonomous functional changes beyond what simple mechanical constraints can achieve\, we explore the idea of using LCEs\, in combination with hydrogels\, to regulate pneumatic circuits. We integrate LCEs with modular mechanical valves. We achieve basic logic gates and construct fluidic networks that can regulate the output pressure based on the local environment. We use this strategy to autonomously control the trajectory and function soft pneumatic robots. These prototypes illustrate the potential for designing autonomous intelligent materials that rapidly and autonomously undergo large-amplitude shape and functional transformations in response to their environment. The principles developed in this dissertation can\, in principle\, be implemented at smaller length scales in the future\, e.g.\, to develop responsive/intelligent metamaterial systems for micro- or medical robotics.
URL:https://seasevents.nmsdev7.com/event/mse-phd-defense-autonomous-stimuli-responsive-metamaterials-based-on-liquid-crystal-elastomers/
LOCATION:Towne 227 (MEAM Conference Room)\, 220 S. 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
END:VCALENDAR