The American Water Resources Association (AWRA) has started our first inaugural Diversity, Equity, and Inclusion Scholarship which includes one-year association membership and complimentary conference registration for each of up to three scholarship winners from under-represented groups in the water resources field. Please forward this announcement to all science and engineering departments, student groups, and DEI programs at your university to spread the news and make sure students do not miss out. AWRA prides itself on providing multi-disciplinary community, conversation, and connection in the field of water resources. We are committed to diversity, equity, and inclusion in our membership and programs and realize that there are systemic barriers to entrance in the water resources field. To help address and remove these barriers, AWRA’s Board of Directors has established a Diversity, Equity, and Inclusion Scholarship. It is our intent to continue to offer this scholarship each year.
The Goal: Bring diverse perspectives and support the career advancement of under-represented professionals in the field of water resources.
The Benefits: Each year, up to three scholarship winners will each receive one-year of AWRA professional membership and one free conference registration of their choice. In addition, scholarship winners will be matched with a mentor from among AWRA’s leadership ranks, such as a board member, committee chair, or state section chair.
The Philadelphia Section of the Society of Tribologists and Lubrication Engineers (STLE) is offering undergraduate and graduate students the opportunity to apply for a scholarship for the 2022-2023 academic year. While preference will be given to those students studying or doing research related to tribology, the applications are open to any sophomore or above pursuing a Bachelors or Graduate degree in the Physical Sciences, Engineering, Tribology, Mathematics or similar studies with a GPA of 3.0 or higher.
The application is linked below & the deadline is May 31st. Award decisions will be made by the end of June.
The Section awarded 39 scholarships ranging from $500 to $1,500 each over the last three years and has given nearly $85,000 to 68 deserving students over the past seven years. Thanks to our generous corporate and individual donors, our scholarship levels have remained constant throughout the global pandemic.
In addition to the award, scholarship winners are profiled on the Section website (STLE Philadelphia Section link) and in the STLE magazine, Tribology and Lubrication Technology. Profiles of last year’s awardees are attached. Two UMD students were among our awardees. We also invite the students to either make a presentation or display a poster at one of our Section meetings.
Graduate Women in Engineering (GWE) is hosting a luncheon session with IonQ, a quantum computing startup based in College Park. Founded by former UMD professor, Dr. Chris Monroe, IonQ’s goal is to take trapped ion computing out of the lab, and into the market. If you are interested in learning more about quantum computing, and future career opportunities at IonQ, join us for lunch with them on 04/15 at 12PM. We will be walking to IonQ HQ from campus. Make sure to RSVP soon; we only have 10 spots! To learn more about IonQ, visit their website at https://ionq.com/.
Professor Dr. Mohammad Modarres, Chair + Dr. Enrique Lopez Droguett, Co-Chair Professor Mark Fuge Professor Katrina Groth Professor Balakumar Balachandran Professor Gregory Baecher, Dean’s Representative
Title: A Physics-Informed Neural Network Framework for Big Machinery Data in Prognostics and Health Management for Complex Engineering Systems
Abstract:
Big data analysis and data-driven models (DDMs) have become essential tools in prognostics and health management (PHM). Despite this, several challenges remain to successfully apply these techniques to complex engineering systems (CESs). Indeed, current state-of-the-art applications are treated as black-box algorithms, where research efforts have focused on developing complex DDMs, overlooking or neglecting the importance of the data preprocessing stages prior to training these models. Guidelines to adequately prepare data sets collected from CESs to train DDMs in PHM are frequently unclear or inexistent. Furthermore, these DDMs do not consider prior knowledge on the system’s physics of degradation, which gives little-to-no control over the data interpretation in reliability applications such as maintenance planning.
In this context, this dissertation presents a physics-informed neural network (PINN) architecture for remaining useful life (RUL) estimation based on big machinery data (BMD) collected from sensor monitoring networks (SMNs) in CESs. The main outcomes of this work are twofold. First, a systematic guide to preprocess BMD for diagnostics and prognostics tasks is developed based on expert knowledge and data science techniques. Second, a PINN-inspired PHM framework is proposed for RUL estimation through an open-box approach by exploring the system’s physics of degradation through partial differential equations (PDEs). The PINN-RUL framework aims to discover the system’s underlying physics-related behaviors, which could provide valuable information to create more trustworthy PHM models.
The data preprocessing and RUL estimation frameworks are validated through three case studies, including the C-MAPSS benchmark data set and two data sets corresponding to real CESs. Results show that the proposed preprocessing methodology can effectively generate data sets for supervised PHM models for CESs. Furthermore, the proposed PINN-RUL framework provides an interpretable latent variable that can capture the system’s degradation dynamics. This is a step forward to increase interpretability of prognostic models by mapping the RUL estimation to the latent space and its implementation as a state of health classifier. The PINN-RUL framework is flexible as it allows incorporating available physics-based models (PBMs) to its architecture. As such, this framework takes a step forward in bridging the gap between statistic-based PHM and physics-based PHM methods.
Professor Dr. Johan Larsson, Chair Professor Dr. Amir Riaz Professor James Duncan Professor Kenneth Kiger Professor Dr. James D. Baeder,Representative
Title: A multi-fidelity approach to sensitivity estimation in large eddy simulation.
Abstract:
An approach to compute approximate sensitivities in a large eddy simulation (LES) is proposed and assessed. The multi-fidelity sensitivity analysis (MFSA) solves a linearized mean equation, where the mean equation is based on the LES solution. This requires closure modeling which makes the computed sensitivities approximate. The closure modeling is based on inferring the eddy viscosity from the LES data and predicting the change in turbulence (or the perturbed eddy viscosity) using a simple algebraic model. The method is assessed for the flow over a NACA0012 airfoil at a fixed angle of attack, with the Reynolds number as the varying parameter and the lift, drag, skin friction, and pressure coefficients as the quantities-of-interest. The results show the importance of accurate closure modeling, specifically that treating the eddy viscosity as “frozen” is insufficiently accurate. Also, predictions obtained using the algebraic model for closing the perturbed eddy viscosity are closer to the true sensitivity than results obtained using the fully RANS-based method which is the state-of-the-art and most common method used in industry. The proposed method aims to complement, rather than replace, the current state-of-the-art method in situations in which sensitivities with higher fidelity are required.
Professor Miao Yu, Chair/Advisor Professor Amir Baz Professor Balakumar Balachandran Professor Nikhil Chopra Professor Timothy Horiuchi, Dean’s Representative
Title: PASSIVE AND ACTIVE GRADED-INDEX ACOUSTIC METAMATERIALS: SPATIAL AND FREQUENCY DOMAIN MULTIPLEXING
Abstract:
Acoustic metamaterials, similar to their electromagnetic counterparts, are artificial subwavelength materials designed to manipulate sound waves. By tailoring the material’s effective properties such as bulk modulus, mass density, and reflective index, these materials can be designed to achieve unprecedented acoustic waves control and realize functional devices of novel properties. Specifically, high-refractive-index acoustic metamaterials have an effective refractive index much larger than air, enabling wave compression in space and a strong concentration of wave energy. Another type of acoustic metamaterials closely related to high-index acoustic metamaterials is graded-index metamaterials, which can be obtained by gradually varying material compositions or geometry over a volume of high-index acoustic metamaterials. The overall goal of this dissertation is to achieve a fundamental understanding of passive and active graded-index acoustic metamaterials for spatial and frequency domain multiplexing and explore their applications in far-field acoustic imaging and sonar systems. Three research thrusts have been pursued. In the first thrust,the spatial domain multiplexing of passive graded-index acoustic metamaterials has been investigated for enhancing far-field acoustic imaging. An array of passive graded-index acoustic metamaterials has been designed and developed to achieve a far-field acoustic imaging system. Parametric studies have been carried out to facilitate the performance optimization of the imaging system. The performance of the metamaterial-based imaging system has been investigated and compared to the scenario without the metamaterials. In the second thrust, frequency-domain multiplexing with active graded-index acoustic metamaterials has been investigated. An active graded-index metamaterial system with a number of active unit cells has been designed and fabricated. A fundamental understanding of the frequency multiplexing properties of the metamaterials has been developed through numerical and experimental studies. In the third thrust, the capabilities of an acoustic sensing system with active graded-index metamaterials as an emitter for shape, size, and surface classification have been explored.
Professor Nikhil Chopra, Chair/Advisor Professor Miao Yu Professor Yancy Diaz-Mercado Professor Shapour Azarm Professor Dinesh Manocha, Dean’s Representative Dr. Brian Sadler
Title: On the Control of Robotic Parasitic Antenna Arrays
Abstract:
Wireless networking is challenging in safety, security, and rescue contexts where network infrastructure may be damaged or compromised. Radio communication between ground robots at the lower end of the Very High Frequency (low-VHF) band is generally more reliable in complex indoor and urban environments when compared to communication systems such as Wi-Fi and cellular which operate at Ultra High Frequencies (UHF) and higher frequencies. Exciting antenna design research in the last 5 to 10 years has approached what is theoretically possible to create compact, moderately high bandwidth antennas at low-VHF. At the beginning of this dissertation research, we discovered that we could distribute these low-VHF antennas across closely positioned ground robots to create a robotic parasitic antenna array. When these robots are optimally positioned, they create a directional signal through the mutual coupling of their antennas. Consequently, these low-VHF arrays have the potential to extend the communication range of a reliable signal in urban and indoor environments with a proportionally small amount of robotic motion.
In this dissertation, we research the control of robotic platforms constituting these arrays from two perspectives. First, we research how robots control their positions to optimize or maintain the gain of a single robotic parasitic array to improve the quality of a communication link. Then, we investigate where these robots should collect to form an array in a network of robotic parasitic arrays to increase a metric of overall network connectivity.
To improve individual network communication links, we consider a two-element parasitic array formed by a static antenna and a ground robot and propose a technique by which this array can optimize its gain in a direction of interest. First, we propose and test an optimization approach for actuating spacing between the two antennas and passive antenna length to increase gain. Next, we propose and test an approach for using robotic motion to rotate the antenna array. In these experiments, we show that the robotic parasitic antenna array can provide a gain of 2 dB which is close to twice the effective transmission power in line-of-sight and non-line-of-sight conditions.
From a network perspective, we research where robots should form arrays to maintain a metric of overall connectivity. However, existing control formulations for maintaining connectivity are not general enough to support this new capability. We first propose a generalized model that we integrate into a Fiedler value maximization approach for maintaining communication. Afterward, we develop approaches for allocating a finite number of robots for forming these robotic parasitic arrays while ensuring that our metric for overall network connectivity between robotic parasitic array forming robots remains lower bounded.
Dr. Keir C. Neuman Professor Peter Chung Professor Paul Paukstelis Professor Don DeVoe Professor Jason Kahn, Dean’s Representative
Title of Dissertation: EFFECT OF MISMATCHED BASE PAIRS ON DNA PLECTONEMES
Abstract: Base pair mismatches in DNA occur during replication and can result in mutations and certain types of cancer. The exact mechanism by which mismatch repair proteins recognize mismatches is still not well understood. Structures of mismatch recognition proteins bound to a mismatch indicate that the process involves introducing a sharp bend in the DNA and flipping out the mismatched base. Under external torsional stress, an elastic rod with a defect would buckle at the defect, provided the defect reduces the local bending stiffness. In vivo, if the same energetic scenario prevails, it could localize (or pin) the mismatch at the plectoneme end loop (plectoneme refers to a structure formed by the DNA when it buckles and its helical axis wraps or writhes around itself in the presence of a critical torsional stress) and make the mismatched base pair more accessible to the mismatch repair protein. In genomic DNA, however, the entropic cost associated with plectoneme localization could make pinning unfavorable. Magnetic-tweezers-based studies of DNA supercoiling, performed at high salt concentrations, have shown that in DNA harboring a single mismatch, the plectoneme will always localize at the mismatch. Theoretical studies have predicted that under physiological salt concentrations, plectoneme localization becomes probabilistic. However, both experimental and theoretical approaches are currently limited to positively supercoiled DNA. In the current dissertation, we aim to study plectoneme localization, in physiologically relevant conditions, using state-of-the-art molecular dynamics (MD) simulations and single molecule magnetics tweezers-based experiments.
In order to simulate plectoneme localization we first develop a framework using the widely available sequence and salt dependent OxDNA2 model. We verify that the OxDNA2 model can quantitively reproduce a reduction in bending rigidity due to the presence of the mismatch(es), similar to all-atom MD simulations. We then verify that the current framework can reproduce the experimentally observed plectoneme pinning (at the location of the mismatches). Next, we simulate plectoneme pinning under physiologically relevant conditions. We find that the plectoneme pinning (at the location of the mismatches) becomes probabilistic and this probability of plectoneme pinning increases with an increase in the number of mismatches. We also simulate a longer 1010 base pair long DNA to study the influence of entropic effects on plectoneme pinning.
Next, we extend the simulation framework to simulate a negatively supercoiled, i.e., under-wound, DNA molecule. In vivo, DNA is maintained in a negatively supercoiled state. Negative supercoiling can result in local melting at the mismatched base pairs: this local melting would further reduce the local bending rigidity at the mismatched base pairs and could enhance plectoneme pinning. We find that negative supercoiling significantly enhances plectoneme pinning in comparison with equivalent levels of positive supercoiling. We also find that the mismatched base pairs are locally melted and the plectoneme end loop is bent significantly more as compared to the positive supercoiling case. Additionally, we simulate the 1010 base pair long DNA under two different negative super-helical densities, i.e., two different degrees of unwinding. We find that the super helical density does not affect the plectoneme pinning probabilities. We also conduct simulations of DNA under different stretching forces (0.3 pN, 0.4 pN and 0.6 pN). Negatively supercoiled DNA under relatively high stretching force (~0.6 pN) absorbs tortional stress by locally melting instead of supercoiling. Simulations of DNA under different forces allow us to study the effect of mismatches on the competition between supercoiling and local melting in a negatively supercoiled DNA. We find that higher stretching forces, up to a maximum set by the onset of melting, increase plectoneme pinning at the location of mismatch.
Finally, we propose and develop a single molecule assay to validate the simulations results presented in the previous chapters. Previous single-molecule magnetic tweezers measurements of mismatch DNA buckling and pinning were limited to the high force (~2 pN) – high salt (>0.5 M NaCl) regime. We propose to overcome this limitation by attaching a small gold nano-bead via a di-thiol group close to the mismatched base pairs, which permits direct observation of transient DNA buckling at the mismatch. We fabricate a DNA substrate that can be used to directly observe plectoneme pinning at the mismatch. We perform single-molecule magnetic tweezers measurements to verify that the presence of the di-thiol group does not result in anomalous pinning in an intact DNA molecule.
Come stop by for a SAMPE BBQ on April 6 at 5:30 and learn about the composite bridge competition and the additive manufacturing competitions! More details in the attached flyer. If you have any questions, please contact Colleen at cmmurray@umd.edu.
Clemson University is looking to fill multiple faculty positions in Mechanical Engineering. They are looking for faculty at all ranks and candidates with exceptional credentials could be considered for endowed faculty positions as well.
