Designing LMPA-Based Smart Materials for Soft Robotics Applications

This doctoral research, Designing LMPA (Low Melting Point Alloy) Based Smart Materials for Soft Robotics Applications, includes the following topics: (1) Introduction; (2) Robust Bicontinuous Metal-Elastomer Foam Composites with Highly Tunable Mechanical Stiffness; (3) Actively Morphing Drone Wing Design Enabled by Smart Materials for Green Unmanned Aerial Vehicles; (4) Dynamically Tunable Friction via Subsurface Stiffness Modulation; (5) LMPA Wool Sponge Based Smart Materials with Tunable Electrical Conductivity and Tunable Mechanical Stiffness for Soft Robotics; and (6) Contributions and Future Work.Soft robots are developed to interact safely with environments. Smart composites with tunable properties have found use in many soft robotics applications including robotic manipulators, locomotors, and haptics. The purpose of this work is to develop new smart materials with tunable properties (most importantly, mechanical stiffness) upon external stimuli, and integrate these novel smart materials in relevant soft robots. Stiffness tunable composites developed in previous studies have many drawbacks. For example, there is not enough stiffness change, or they are not robust enough. Here, we explore soft robotic mechanisms integrating stiffness tunable materials and innovate smart materials as needed to develop better versions of such soft robotic mechanisms. First, we develop a bicontinuous metal-elastomer foam composites with highly tunable mechanical stiffness. Second, we design and fabricate an actively morphing drone wing enabled by this smart composite, which is used as smart joints in the drone wing. Third, we explore composite pad-like structures with dynamically tunable friction achieved via subsurface stiffness modulation (SSM). We demonstrate that when these composite structures are properly integrated into soft crawling robots, the differences in friction of the two ends of these robots through SSM can be used to generate translational locomotion for untethered crawling robots. Also, we further develop a new class of smart composite based on LMPA wool sponge with tunable electrical conductivity and tunable stiffness for soft robotics applications. The implications of these studies on novel smart materials design are also discussed

Real-time Data Analytics for Condition Monitoring of Complex Industrial Systems

Modern industrial systems are now fitted with several sensors for condition monitoring. This is advantageous because these sensors can provide mass amounts of data that have the potential for aiding in tasks such as fault detection, diagnosis, and prognostics. However, the information valuable for performing these tasks is often clouded in noise and must be mined from high-dimensional data structures. Therefore, this dissertation presents a data analytics framework for performing these condition monitoring tasks using high-dimensional data. Demonstrations of this framework are detailed for challenges related to power generation systems in automobiles, power plants, and aircraft engines. These implementations leverage data collected from state-of-the-art, industry class test-rigs. Results indicate the ability of this framework to develop effective methodologies for condition monitoring of complex systems.Ph.D

NASA SBIR abstracts of 1990 phase 1 projects

The research objectives of the 280 projects placed under contract in the National Aeronautics and Space Administration (NASA) 1990 Small Business Innovation Research (SBIR) Phase 1 program are described. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses in response to NASA's 1990 SBIR Phase 1 Program Solicitation. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 280, in order of its appearance in the body of the report. The document also includes Appendixes to provide additional information about the SBIR program and permit cross-reference in the 1990 Phase 1 projects by company name, location by state, principal investigator, NASA field center responsible for management of each project, and NASA contract number

Dielectrophoretic characterization of particles and erythrocytes

Medical lab work, such as blood testing, will one day be near instantaneous and inexpensive via capabilities enabled by the fast growing world of microtechnology. In this research study, sorting and separation of different ABO blood types have been investigated by applying alternating and direct electric fields using class=SpellE\u3edielectrophoresis in microdevices. Poly(dimethylsiloxane) (PDMS) microdevices, fabricated by standard photolithography techniques have been used. Embedded perpendicular platinum (Pt) electrodes to generate forces in AC dielectrophoresis were used to successfully distinguish positive ABO blood types, with O+ distinguishable from other blood types at \u3e95% confidence. This is an important foundation for exploring DC dielectrophoretic sorting of blood types. The expansion of red blood cell sorting employing direct current insulative class=SpellE\u3edielectrophoresis (DC-iDEP) is novel. Here Pt electrodes were remotely situated in the inlet and outlet ports of the microdevice and an insulating obstacle generates the required dielectrophoretic force. The presence of ABO antigens on the red blood cell were found to affect the class=SpellE\u3edielectrophoretic deflection around the insulating obstacle thus sorting cells by type. To optimize the placement of insulating obstacle in the microchannel, COMSOL Multiphysics® simulations were performed. Microdevice dimensions were optimized by evaluating the behaviors of fluorescent polystyrene particles of three different sizes roughly corresponding to the three main components of blood: platelets (2-4 µm), erythrocytes (6-8 µm) and leukocytes (10-15 µm). This work provided the operating conditions for successfully performing size dependent blood cell insulator based DC dielectrophoresis in PDMS microdevices. In subsequent studies, the optimized microdevice geometry was then used for continuous separation of erythrocytes. The class=SpellE\u3emicrodevice design enabled erythrocyte collection into specific channels based on the cell’s deflection from the high field density region of the obstacle. The channel with the highest concentration of cells is indicative of the ABO blood type of the sample. DC resistance measurement system for quantification of erythrocytes was developed with single PDMS class=SpellE\u3emicrochannel system to be integrated with the DC- class=SpellE\u3eiDEP device developed in this research. This lab-on-a-chip technology application could be applied to emergency situations and naturalcalamities for accurate, fast, and portable blood typing with minimal error

Dielectrophoretic characterization of particles and erythrocytes

Medical lab work, such as blood testing, will one day be near instantaneous and inexpensive via capabilities enabled by the fast growing world of microtechnology. In this research study, sorting and separation of different ABO blood types have been investigated by applying alternating and direct electric fields using class=SpellE\u3edielectrophoresis in microdevices. Poly(dimethylsiloxane) (PDMS) microdevices, fabricated by standard photolithography techniques have been used. Embedded perpendicular platinum (Pt) electrodes to generate forces in AC dielectrophoresis were used to successfully distinguish positive ABO blood types, with O+ distinguishable from other blood types at \u3e95% confidence. This is an important foundation for exploring DC dielectrophoretic sorting of blood types. The expansion of red blood cell sorting employing direct current insulative class=SpellE\u3edielectrophoresis (DC-iDEP) is novel. Here Pt electrodes were remotely situated in the inlet and outlet ports of the microdevice and an insulating obstacle generates the required dielectrophoretic force. The presence of ABO antigens on the red blood cell were found to affect the class=SpellE\u3edielectrophoretic deflection around the insulating obstacle thus sorting cells by type. To optimize the placement of insulating obstacle in the microchannel, COMSOL Multiphysics® simulations were performed. Microdevice dimensions were optimized by evaluating the behaviors of fluorescent polystyrene particles of three different sizes roughly corresponding to the three main components of blood: platelets (2-4 µm), erythrocytes (6-8 µm) and leukocytes (10-15 µm). This work provided the operating conditions for successfully performing size dependent blood cell insulator based DC dielectrophoresis in PDMS microdevices. In subsequent studies, the optimized microdevice geometry was then used for continuous separation of erythrocytes. The class=SpellE\u3emicrodevice design enabled erythrocyte collection into specific channels based on the cell’s deflection from the high field density region of the obstacle. The channel with the highest concentration of cells is indicative of the ABO blood type of the sample. DC resistance measurement system for quantification of erythrocytes was developed with single PDMS class=SpellE\u3emicrochannel system to be integrated with the DC- class=SpellE\u3eiDEP device developed in this research. This lab-on-a-chip technology application could be applied to emergency situations and naturalcalamities for accurate, fast, and portable blood typing with minimal error

Advanced Occupancy Measurement Using Sensor Fusion

With roughly about half of the energy used in buildings attributed to Heating, Ventilation, and Air conditioning (HVAC) systems, there is clearly great potential for energy saving through improved building operations. Accurate knowledge of localised and real-time occupancy numbers can have compelling control applications for HVAC systems. However, existing technologies applied for building occupancy measurements are limited, such that a precise and reliable occupant count is difficult to obtain. For example, passive infrared (PIR) sensors commonly used for occupancy sensing in lighting control applications cannot differentiate between occupants grouped together, video sensing is often limited by privacy concerns, atmospheric gas sensors (such as CO2 sensors) may be affected by the presence of electromagnetic (EMI) interference, and may not show clear links between occupancy and sensor values. Past studies have indicated the need for a heterogeneous multi-sensory fusion approach for occupancy detection to address the short-comings of existing occupancy detection systems. The aim of this research is to develop an advanced instrumentation strategy to monitor occupancy levels in non-domestic buildings, whilst facilitating the lowering of energy use and also maintaining an acceptable indoor climate. Accordingly, a novel multi-sensor based approach for occupancy detection in open-plan office spaces is proposed. The approach combined information from various low-cost and non-intrusive indoor environmental sensors, with the aim to merge advantages of various sensors, whilst minimising their weaknesses. The proposed approach offered the potential for explicit information indicating occupancy levels to be captured. The proposed occupancy monitoring strategy has two main components; hardware system implementation and data processing. The hardware system implementation included a custom made sound sensor and refinement of CO2 sensors for EMI mitigation. Two test beds were designed and implemented for supporting the research studies, including proof-of-concept, and experimental studies. Data processing was carried out in several stages with the ultimate goal being to detect occupancy levels. Firstly, interested features were extracted from all sensory data collected, and then a symmetrical uncertainty analysis was applied to determine the predictive strength of individual sensor features. Thirdly, a candidate features subset was determined using a genetic based search. Finally, a back-propagation neural network model was adopted to fuse candidate multi-sensory features for estimation of occupancy levels. Several test cases were implemented to demonstrate and evaluate the effectiveness and feasibility of the proposed occupancy detection approach. Results have shown the potential of the proposed heterogeneous multi-sensor fusion based approach as an advanced strategy for the development of reliable occupancy detection systems in open-plan office buildings, which can be capable of facilitating improved control of building services. In summary, the proposed approach has the potential to: (1) Detect occupancy levels with an accuracy reaching 84.59% during occupied instances (2) capable of maintaining average occupancy detection accuracy of 61.01%, in the event of sensor failure or drop-off (such as CO2 sensors drop-off), (3) capable of utilising just sound and motion sensors for occupancy levels monitoring in a naturally ventilated space, (4) capable of facilitating potential daily energy savings reaching 53%, if implemented for occupancy-driven ventilation control

Development of Fast, Distributed Computational Schemes for Full Body Bio-Models and Their Application to Novel Action Potential Block in Nerves Using Ultra-Short, High Intensity Electric Pulses

An extremely robust and novel scheme for computing three-dimensional, time-dependent potential distributions in full body bio-models is proposed, which, to the best of our knowledge, is the first of its kind. This simulation scheme has been developed to employ distributed computation resources, to achieve a parallelized numerical implementation for enhanced speed and memory capability. The other features of the numerical bio-model included in this dissertation research, are the ability to incorporate multiple electrodes of varying shapes and arbitrary locations. The parallel numerical tool also allows for user defined, current or potential stimuli as the excitation input. Using the available computation resources at the university, a strong capability for extremely large bio-models was developed. So far a maximum simulation comprised of 6.7 million nodes has been achieved for a full rat bio-model with a 1 mm spatial resolution at an average of 30 seconds per iteration. The ability to compute the resulting potential distribution in a full animal body allows for realistic and accurate studies of bio-responses to electrical stimuli. For example, the voltages computed from the full-body models at various sites and tissue locations could be used to examine the potential for using nanosecond, high-intensity, pulsed electric fields for blocking neural action or action potential (AP) propagation. This would be a novel, localized, and reversible method of controlling neural function without tissue damage. It could potentially be used in electrically managed pain relief, non-lethal incapacitation, and neural/muscular therapy. The above concept has quantitatively been evaluated in this dissertation. Specifically, the effects of high-intensity (kilo-Volt), ultra-short (∼100 nanosecond) electrical pulses have been evaluated, and compared with available experimental data. Good agreement with available data is demonstrated. It is also shown that nerve membrane electroporation, brought about by the high-intensity, external pulsing, could indeed be instrumental in halting AP propagation. Simulations based on a modified distributed cable model to represent nerve segments have been used to demonstrate a numerical proof-of-concept

Volume 1 – Symposium: Tuesday, March 8

Group A: Digital Hydraulics Group B: Intelligent Control Group C: Valves Group D | G | K: Fundamentals Group E | H | L: Mobile Hydraulics Group F | I: Pumps Group M: Hydraulic Components:Group A: Digital Hydraulics Group B: Intelligent Control Group C: Valves Group D | G | K: Fundamentals Group E | H | L: Mobile Hydraulics Group F | I: Pumps Group M: Hydraulic Component

Model-based Design Framework for Shape Memory Alloy Wire Actuation Devices.

While Shape Memory Alloys (SMAs) have exceptional actuation characteristics such as high energy density, silent operation, flexible packaging, etc., they have not found widespread use in commercial applications because of the significant learning curve required of engineers before they are capable of designing actuation devices using this unique material. An SMA actuation device design framework consisting of grammar, design methods, and design process enables engineers of different backgrounds to make efficient and appropriate design decisions in different stages of the design process. A reference SMA actuation device structure built on a generalized actuation device hierarchical structure using the actuation device grammar works as a reference structure to identify and populate device design options, and to model and analyze the device actuation performance as well as to enlighten non-expert engineers about the essential elements of SMA actuation devices. Design methods consisting of modular modeling, model aggregation and performance prediction, and visualization approaches support design decisions to serve diverse stakeholders of actuation device design by exposing the effects of individual device elements not only for SMA actuation devices, but also for a wide range of actuation devices. A multi-stage design process is formalized to help engineers create a detailed design including a three-step decoupled equilibrium design procedure which prevents potential iteration by decoupling the force and deflection of actuation output behavior, and hides the complexity of material and SMA architectural models from engineers while still exposing the impact of design parameters. The design framework makes SMA design knowledge more accessible to engineers with different levels of expertise and roles in device development by systematically organizing and presenting the device grammar, design methods, and design process. A design tool software platform based on the framework enables the creation of computer-aided design tools to support a variety of design tasks, which were demonstrated in two use case examples. By having the SMA actuation device design framework, the acceptance of the SMA actuation technology into both research and commercial applications can be increased to utilize promising SMA actuation benefits, and the device development cycle leading to these applications can be streamlined.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120684/1/wonhekim_1.pd

JUNO Conceptual Design Report

The Jiangmen Underground Neutrino Observatory (JUNO) is proposed to determine the neutrino mass hierarchy using an underground liquid scintillator detector. It is located 53 km away from both Yangjiang and Taishan Nuclear Power Plants in Guangdong, China. The experimental hall, spanning more than 50 meters, is under a granite mountain of over 700 m overburden. Within six years of running, the detection of reactor antineutrinos can resolve the neutrino mass hierarchy at a confidence level of 3-4$\sigma$, and determine neutrino oscillation parameters $\sin^2\theta_{12}$, $\Delta m^2_{21}$, and $|\Delta m^2_{ee}|$ to an accuracy of better than 1%. The JUNO detector can be also used to study terrestrial and extra-terrestrial neutrinos and new physics beyond the Standard Model. The central detector contains 20,000 tons liquid scintillator with an acrylic sphere of 35 m in diameter. $\sim$17,000 508-mm diameter PMTs with high quantum efficiency provide $\sim$75% optical coverage. The current choice of the liquid scintillator is: linear alkyl benzene (LAB) as the solvent, plus PPO as the scintillation fluor and a wavelength-shifter (Bis-MSB). The number of detected photoelectrons per MeV is larger than 1,100 and the energy resolution is expected to be 3% at 1 MeV. The calibration system is designed to deploy multiple sources to cover the entire energy range of reactor antineutrinos, and to achieve a full-volume position coverage inside the detector. The veto system is used for muon detection, muon induced background study and reduction. It consists of a Water Cherenkov detector and a Top Tracker system. The readout system, the detector control system and the offline system insure efficient and stable data acquisition and processing.Comment: 328 pages, 211 figure