| Your selection returns no results. |
|
Monday, August 28, 2017
|
|
11:00 AM
-
1:00 PM
|
-
EAS PhD Program (CSE Option / MNE) PhD Proposal Defense by Mr. Wen Jin
- Location: Textiles Building 101E
- Contact: Mechanical Engineering Department
- Description: Engineering and Applied Science PhD Program (CSE Option / Mechanical Engineering) PhD PROPOSAL DEFENSE by Mr. Wen Jin
DATE:
August 28, 2017
TIME:
11:00 a.m. 1:00 p.m.
LOCATION:
Textile Building, Room 101E
TOPIC:
Computational Investigation of the Impingement of Water Droplets on Freezing Superhydrophobic Surfaces
ABSTRACT:
Wind provides a clean and renewable source of energy that has great potential, particularly in the cold climate areas. However, in cold climates, ice formation on wind turbine blades is common and becomes a serious challenge. Ice formation can reduce the aerodynamic performance of wind turbines by increasing drag and causing flow separation. Also, heavy ice buildup on the blades may unbalance the turbine and cause catastrophic failures. Most importantly, ice layers formed on rotating blades can detach with significant momentum and cause fatal accidents or damage nearby facilities. Recently, several laboratory experiments show that water droplets impacting freezing superhydrophobic surfaces (SHS) can bounce off the surface before any ice is formed. The SHS are hydrophobic surfaces that are enhanced by adding micro-textures, such as posts or pillars, on the surface and/or by chemical hydrophobic coatings. Although the efficacy of SHS in preventing ice formation during the impact of millimeter-size water droplets has been established by various laboratory studies, further investigation is needed to determine whether such surfaces can prevent ice formation on wind turbine blades under real-world conditions, where micron-size droplets impact the surface at high speeds. This work presents computational simulations of the impingement of micron-size water droplets on freezing SHS at various Weber numbers, droplet initial temperatures, and surface temperatures. The simulation results are from an in-house volume-of-fluid based, free-surface flow solver with phase change. While the surface has been assumed smooth in these simulations, the effects of the surface micro-textures on the contact angle and thermal contact resistance were taken into account. The first objective was to investigate the conditions under which the droplets bounce off the surface or stick to the surface and freeze. The transition between the bouncing and sticking regimes is determined. Then, analyzing the timescales for droplet freezing and drop-surface contact, a theoretical model was developed for predicting the above transition. The predictions of the theoretical model are compared against the transition conditions observed in the computational simulations and experiments. Next, it is proposed to enhance the flow solver to include the surface micro-textures, which requires a robust numerical method for capturing the contact line pinning on complex surface textures in 3D. The proposed numerical method for contact line pinning and the preliminary 2D results are presented. The enhanced flow solver will enable a detailed investigation of the effects of surface texture geometry and the air entrapment under the droplet and between surface textures. The study will lead to design of textured super-ice-phobic surfaces that are specially engineered for the flow fields around wind turbine blades.
ADVISOR:
Dr. Mehdi Raessi
COMMITTEE MEMBERS:
Dr. Sankha Bhowmick, Dr. Gaurav Khanna, Dr. Jun Li
Open to the public. All MNE and EAS students are encouraged to attend.
For more information, please contact Dr. Raessi (mraessi@umassd.edu, 508-999-8496).
Thank you,
Sue Cunha, Administrative Assistant
Department of Mechanical Engineering
College of Engineering
University of Massachusetts Dartmouth
285 Old Westport Road
Dartmouth, MA 02747-2300
Science & Engineering Building, Room 116E
508-999-8492/Telephone
508-999-8881/Fax
scunha@umassd.edu
- Topical Areas: Faculty, General Public, Students, Students, Graduate, Students, Undergraduate, University Community, College of Engineering, Mechanical Engineering, Lectures and Seminars
|
|
Tuesday, August 29, 2017
|
|
10:00 AM
-
12:00 PM
|
-
Oral Comprehensive Exam for Doctoral Candidacy by: Prinkle Sharma
- Location: Science & Engineering Building, Lester W. Cory Conference Room: Room 213A
- Cost: Free
- Contact: ECE: Electrical & Computer Engineering Department
- Description: Topic: Admire: Artificial Intelligence Approach to Detect Misbehavior and Invoke Revocation in Vehicular Environment
Location: Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A
Abstract:
Autonomous Vehicle Technology (AVT) offers fundamental restructure of the transportation. Connected Vehicles Technology (CVT) further enhances Intelligent Transportation Systems (ITS). Despite the maturity of the technology, the deployment in the real-world standstills partially due to security concerns. IEEE 1609.2 provides security mechanisms by defining secure message formats and procedures. Traditional approaches such as public key infrastructure (PKI) are insufficient due to the rapid dynamics and privacy requirements of Vehicular Ad-Hoc Networks (VANET). By injecting malware to VANET devices or by stealing certificates an attacker can fabricate application or management messages, compromising the security provided with IEEE 1609.2. Solutions to secure backend in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications include Security Credential Management System (SCMS). It supports certificate provision with privacy preservation and operation efficiency as PKI for Vehicle Networks or "Vehicular PKI".
However, timely misbehavior detection and certificate revocation remain an open problem. This work aims at enhancing privacy-preserving credential management with efficiency for SCMS. It utilizes context-adaptive machine learning technique to detect misbehaviors and revoke certificates and cast them out of the system to secure V2X communications. This approach works in two phases at three levels: Phase 1: Revelation to detect misbehavior while preserving privacy and Phase 2: Reaction to revoke certificates for credential management. Revelation phase reveals misbehaving vehicles on the local and cooperative levels. It emulates human logic in shaping mistrust before ending a relation, using the toolset, called Context Adaptive Machine Learning Tool (CAMLeT), to be developed. Revocation is done on three different levels; Local, Cooperative and Regional, each applying CAMLeT to perform a fact-analysis on misbehavior detection.
The work contributes to privacy-preserved security credential management with efficiency. Its novelty lies at timely misbehavior detection and revocation for the vehicular environment. By applying artificial intelligence using CAMLeT, data centric analysis accelerates misbehavior detection. Granting local autonomous instead of the global decision, scalability of credential management is achieved. The work presents an autonomous driving framework where vehicles cooperate with each other to seek safe and secure driving.
Note: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Hong Liu
Committee Members: Dr. Paul J. Fortier, Dr. Honggang Wang, Department of Electrical & Computer Engineering, UMass Dartmouth; Dr. Jonathan Petit, Senior Director of Research, OnBoard Security; Dr. Kavitha Chandra, Department of Electrical & Computer Engineering, UMass Lowell
*For further information, please contact Dr. Hong Liu at 508.999.8514, or via email at hliu@umassd.edu.
- Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering
|
|
Wednesday, August 30, 2017
|
|
12:30 PM
-
2:30 PM
|
-
Oral Comprehensive Exam for Doctoral Candidacy by: Paul C. Proffitt
- Location: > See description for location
- Cost: Free
- Contact: ECE: Electrical & Computer Engineering Department
- Description: Topic: High Clutter, Close Range, Wi-Fi Imaging and Probabilistic, Learning Classifier
Location: Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A
Abstract:
This proposal plans on using Wi-Fi signal processing and neural networks to identify static and moving objects in a room, which involves many challenges such as very close range, high clutter, running real-time, classifying rough images, and many other problems to be encountered. Radar usually involves distant targets, but creating and identifying images indoors at close range with only Wi-Fi signals is a whole other world of processing. In the past few years, people have worked on using Wi-Fi for identifying actions, but this proposal plans on using Wi-Fi on static (non-moving) and moving objects. The images created will be barely identifiable due to the low resolution of Wi-Fi, but the images need to be classified (identified). Classifying the resultant images will be a challenge and requires some form of Artificial Intelligence (AI).
There are two major portions to this proposal. The first is the signal processing portion, where images are created, and the second is the image classification portion, using AI neural networks.
In the signal processing portion, images will be created by using Wi-Fi signals transmitted and received on Ettus Universal Software Radio Peripheral (USRP) hardware and directional antennas. This situation is unlike typical radar, which has the luxury of transmitting then listening due to large distances to targets. Further, GNU Radio, the interface to USRp's, will allow the proposer to develop new algorithms. The proposer has become a near expert in GNU Radio development.
In the image classification phase, the images created will be very blob-like with different reflective intensities. These are not your typical images for a classifier. These images need some form of intelligence to classify them, and the system needs to improve its classification over time. AI neural networks will be employed and developed to work on the images such as developing weights and new algorithms to improve classification..
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advsior: Dr. Honggang Wang
Committee Members: Dr. Dayalan P. Kasilingam and Dr. Liudong Xing, Department of Electrical & Computer Engineering; Dr. Shaoen Wu, Department of Computer Science, Ball State University
*For further information, please contact Dr. Honggang Wang at 508.999.8469, or via email at hwang1@umassd.edu.
- Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering
|
|
10:00 AM
-
12:00 PM
|
-
Oral Comprehensive Exam for Doctoral Candidacy by: Zhouzhou Li
- Location: Science & Engineering Building, Lester W. Cory Conference Room: Room 213A
- Cost: Free
- Contact: ECE: Electrical & Computer Engineering Department
- Description: Topic: A Practical & Efficient Security Scheme for Body Area Networks
Location: Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A
Abstract:
A body area network (BAN) is a wireless network of wearable computing devices. BAN's application domains include health care, sports, entertainment, military, etc. Most of the BAN nodes are resource-constrained, heterogeneous, dynamically deployed with high density. These constraints increase the interoperability difficulties of BAN nodes. BAN's communication is entirely within, on, and in the immediate proximity of a human body. Due to the openness of wireless environment and the significance and privacy of people's physiological data, BAN is easy to incur various attacks. Therefore, strict security mechanisms are required to enable a secure BAN.
The Received Signal Strength Indicator (RSSI) based physical layer security mechanisms are promising in BANs due to the security, availability, and reciprocity of RSSI data. However, these mechanisms are facing critical challenges before they can be practically applied to real BAN systems. First, when RSSI values are used for node authentication, they are not always accurate to decide a node's location. Second, when RSSI (reciprocity) is used as the keying material for symmetric key generation, the corresponding key generation rate is limited by RSSI reciprocity level and data fluctuation. If the body movement is not significant, the RSSI fluctuation (entropy) and reciprocity is not ideal. Third, during key reconciliation, even if only check symbols are passed to the other side (to save energy and keep security), the detail check symbol calculation and error-correcting algorithms still need to satisfy the performance requirement. In this proposal, we will focus on the solutions for the above basic problems by reviewing literature and proposing our new secure scheme for BANs.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Co-Advisors: Dr. Honggang Wang and Dr. Hua Fang
Committee Members: Dr. Paul J. Fortier and Dr. Liudong Xing, Department of Electrical & Computer Engineering; Dr. Shaoen Wu, Department of Computer Science, Ball State University
*For further information, please contact Dr. Honggang Wang at 508.999.8469, or via email at hwang1@umassd.edu.
- Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering
|
|
Thursday, August 31, 2017
|
|
8:00 AM
-
5:00 PM
|
|
|
Friday, September 1, 2017
|
|
8:00 AM
-
5:00 PM
|
-
New International Student Orientation
- Location: Woodland Commons
- Contact: International Student & Scholar Center
- Description: Mandatory orientation for all new international students
- Topical Areas: Faculty, General Public, Staff and Administrators, Students, University Community, International Students and Scholar Center
|
|
12:00 PM
-
1:00 PM
|
|
|
3:30 PM
-
5:00 PM
|
-
Department of Fisheries Oceanography / SMAST seminar - September 6, 2017 - Rob Stephenson
- Location: New Bedford
, New Bedford, MA
- Contact: > See Description for contact information
- Description: How Must We Change to Undertake Coastal Management
Rob Stephenson
Canada Department of Fisheries & Oceans
Wednesday, September 6, 2017
3:30 pm - 4:30 pm
SMAST E, Room 101/102
836 South Rodney French Boulevard, New Bedford, MA
The management of fisheries, aquaculture and other uses of the ocean is changing. Marine activities are being governed by evolving domestic policies and international agreements that require ecosystem-based and integrated management approaches, and there is increasing market (and general public) pressure for certification of sustainability and social license . Future activities will undoubtedly be audited against a greater range of conservation, social, economic and institutional criteria with higher standards and with explicit consideration of tradeoffs and cumulative effects. Further, coastal activities face the uncertainty of rapidly evolving ecosystems, and there is need for management that can anticipate and adapt to change. This poses a great challenge for science, for governments and for industries. In this presentation I review results and conclusions from a series of recent studies aimed at improving science for integrated management of fisheries and other activities, and with the view to identifying key needs for research going forward. I suggest we need to review and agree core concepts related to sustainability and to modify governance systems to enable integrated management. Major ongoing challenges include 1) the need for scientifically based performance measures associated with a diverse set of ecological, economic, social and institutional (governance) objectives, 2) interdisciplinary or transdisciplinary evaluations of coastal management scenarios, 3) a participatory approach to governance in which there can be evaluation of long-term consequences and tradeoffs among conflicting objectives, and 4) a rigorous approach to the evaluation and management of cumulative effects.
To view a video of an SMAST seminar (post-October 1, 2014), go to http://www.umassd.edu/smast/newsandevents/seminarseries/ and click on a highlighted title.
For more information, please contact cfox@umassd.edu
- Topical Areas: University Community, Lectures and Seminars
|
|
12:00 PM
-
9/8
»
|
-
The Jewish Culture Book Club, Friday September 8th, 2017
- Location: MacLean Campus Center
, 285 Old Westport Road, Dartmouth, MA
- Contact: Center for Jewish Culture
- Description: Jewish Book Club "A Horse walks into a Bar" Novel by David Grossman
- Topical Areas: Students, Students, Graduate, Students, Law, Students, Undergraduate, University Community, Religious Studies
|
|
Saturday, September 2, 2017
|
|
«
9/1
-
9/8
»
|
-
The Jewish Culture Book Club, Friday September 8th, 2017
- Location: MacLean Campus Center
, 285 Old Westport Road, Dartmouth, MA
- Contact: Center for Jewish Culture
- Description: Jewish Book Club "A Horse walks into a Bar" Novel by David Grossman
- Topical Areas: Students, Students, Graduate, Students, Law, Students, Undergraduate, University Community, Religious Studies
|
