Mechanical Engineering Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1661

Browse

Start date: 2020End date: 2024

Search Results

Now showing 1 - 10 of 48
  • Thumbnail Image
    Item
    Quantized topological energy pumping and Weyl points in Floquet synthetic dimensions with a driven-dissipative photonic molecule
    (Nature Physics, 2024-02-26) Sridhar, Sashank; Ghosh, Sayan; Dutt, Avik
    Topological effects manifest in a wide range of physical systems, such as solid crystals, acoustic waves, photonic materials and cold atoms. These effects are characterized by `topological invariants' which are typically integer-valued, and lead to robust quantized channels of transport in space, time, and other degrees of freedom. The temporal channel, in particular, allows one to achieve higher- dimensional topological effects, by driving the system with multiple incommensurate frequencies. However, dissipation is generally detrimental to such topological effects, particularly when the systems consist of quantum spins or qubits. Here we introduce a photonic molecule subjected to multiple RF/optical drives and dissipation as a promising candidate system to observe quantized transport along Floquet synthetic dimensions. Topological energy pumping in the incommensurately modulated photonic molecule is enhanced by the driven-dissipative nature of our platform. Furthermore, we provide a path to realizing Weyl points and measuring the Berry curvature emanating from these reciprocal-space (k-space) magnetic monopoles, illustrating the capabilities for higher-dimensional topological Hamiltonian simulation in this platform. Our approach enables direct k-space engineering of a wide variety of Hamiltonians using modulation bandwidths that are well below the free-spectral range (FSR) of integrated photonic cavities.
  • Thumbnail Image
    Item
    Opportunity Denied
    (2024-08-01) Anand, Davinder K.
    After a considerable amount of discussion, I decided to touch on a topic mostly ignored in the engineering curriculum. That is the participation of Black people in the areas of engineering and technology. The issue of Black Lives Matter and the widespread protests in 2020 have forced us to examine the long-standing opportunities in technology denied to this community. In this paper I review a brief history of how we got to this point and the challenges inherent in the educational system. At the end I discuss some deeply ingrained and difficult-to-change issues and present some final thoughts on this very complex situation. - Davinder K. Anand.
  • Thumbnail Image
    Item
    Tactile Sensing and Grasping Through Thin-Shell Buckling
    (Wiley, 2024-06-09) Barvenik, Kieran; Coogan, Zachary; Librandi, Gabriele; Pezzulla, Matteo; Tubaldi, Eleonora
    Soft and lightweight grippers have greatly enhanced the performance of robotic manipulators in handling complex objects with varying shape, texture, and stiffness. However, the combination of universal grasping with passive sensing capabilities still presents challenges. To overcome this limitation, a fluidic soft gripper is introduced based on the buckling of soft, thin hemispherical shells. Leveraging a single fluidic pressure input, the soft gripper can grasp slippery and delicate objects while passively providing information on this physical interaction. Guided by analytical, numerical, and experimental tools, the novel grasping principle of this mechanics-based soft gripper is explored. First, the buckling behavior of a free hemisphere is characterized as a function of its geometric parameters. Inspired by the free hemisphere's two-lobe mode shape ideal for grasping purposes, it is demonstrated that the gripper can perform dexterous manipulation and gentle gripping of fragile objects in confined spaces and underwater environments. Last, the soft gripper's embedded capability of detecting contact, grasping, and release conditions during the interaction with an unknown object is proved. This simple buckling-based soft gripper opens new avenues for the design of adaptive gripper morphologies with tactile sensing capabilities for applications ranging from medical and agricultural robotics to space and underwater exploration.
  • Thumbnail Image
    Item
    Programmable Control of Nanoliter Droplet Arrays Using Membrane Displacement Traps
    (Wiley, 2023-08-15) Harriot, Jason; Yeh, Michael; Pabba, Mani; DeVoe, Don L.
    A unique droplet microfluidic technology enabling programmable deterministic control over complex droplet operations is presented. The platform provides software control over user-defined combinations of droplet generation, capture, ejection, sorting, splitting, and merging sequences to enable the design of flexible assays employing nanoliter-scale fluid volumes. The system integrates a computer vision system with an array of membrane displacement traps capable of performing selected unit operations with automated feedback control. Sequences of individual droplet handling steps are defined through a robust Python-based scripting language. Bidirectional flow control within the microfluidic chips is provided using an H-bridge channel topology, allowing droplets to be transported to arbitrary trap locations within the array for increased operational flexibility. By enabling automated software control over all droplet operations, the system significantly expands the potential of droplet microfluidics for diverse biological and biochemical applications by combining the functionality of robotic liquid handling with the advantages of droplet-based fluid manipulation.
  • Thumbnail Image
    Item
    An Energy Consumption Intensity Ranking System for Rapid Energy Efficiency Evaluation of a Cluster of Commercial Buildings
    (ASHRAE Transactions, 2023-06) Aditya Ramnarayan, Andres Sarmiento, Armin Gerami, Michael Ohadi; Professor Michael Ohadi
    Buildings in the U.S. account for roughly 74% of electricity usage and about 40% of all primary energy use associated with greenhouse gas (GHG) emissions. The Nationally Determined Contribution (NDC) for the U.S., as determined in the Paris Agreement, sets a goal of reducing GHG emissions by ~50% compared to 2005 levels by 2030 while working towards achieving net-zero emissions by 2050. To meet these carbon reduction targets, the U.S. must substantially reduce of energy consumption and improve buildings' energy efficiency. To this end, this study introduces an energy consumption ranking tool that can be used to analyze the energy consumption profile of a cluster of buildings/campuses and provide an efficient tool to measure, monitor, and reduce end-use energy and CO2 emissions. The tool bases its rankings on a standard benchmark or a targeted energy efficiency goal. The tool generates a band of ranking, from the best to the worst energy efficiency performance, which directs the attention of building designers, operators, and government regulation/enforcement agencies to buildings having subpar energy efficiency performance. The proposed methodology is extrapolated to encompass a broad range of energy and CO2 consumption metrics in various building types and climate zones, thus having local, regional, and international applications. Using end-use energy utility data from the relevant database for the selected cluster of buildings and campuses, a total square footage area of ~26 million square feet of buildings and campuses was taken as the sample set for performing virtual audits using the custom-developed software. Using dynamic scatter plots and several ranking metrics, buildings with an underwhelming energy performance are identified for detailed energy audits. Once the outliers are spotted, energy modeling is performed to identify and delineate the root cause for the high energy use pattern for the facility. A breakdown of utilities and their corresponding energy analytics are visualized, thus highlighting the range of energy efficiency improvements and the potential for electrification. For the case example studied, the virtual audits are projected to result in minimum annual energy savings of 1,280,461 MMBtu and a corresponding minimum annual GHG reduction of 91,309 metric tons of CO2.
  • Thumbnail Image
    Item
    Crystal Strengths at Micro- and Nano-Scale Dimensions
    (MDPI, 2020-02-05) Armstrong, Ronald W.; Elban, Wayne L.
    Higher strength levels, achieved for dimensionally-smaller micro- and nano-scale materials or material components, such as MEMS devices, are an important enabler of a broad range of present-day engineering devices and structures. Beyond such applications, there is an important effort to understand the dislocation mechanics basis for obtaining such improved strength properties. Four particular examples related to these issues are described in the present report: (1) a compilation of nano-indentation hardness measurements made on silicon crystals spanning nano- to micro-scale testing; (2) stress–strain measurements made on iron and steel materials at micro- to nano-crystal (grain size) dimensions; (3) assessment of small dislocation pile-ups relating to Griffith-type fracture stress vs. crack-size calculations for cleavage fracturing of α-iron; and (4) description of thermally-dependent strain rate sensitivities for grain size strengthening and weakening for macro- to micro- to nano-polycrystalline copper and nickel materials.
  • Thumbnail Image
    Item
    Virtual Modeling of User Populations and Formative Design Parameters
    (MDPI, 2020-10-03) Knisely, Benjamin M.; Vaughn-Cooke, Monifa
    Human variability related to physical, cognitive, socio-demographic, and other factors can contribute to large differences in human performance. Quantifying population heterogeneity can be useful for designers wishing to evaluate design parameters such that a system design is robust to this variability. Comprehensively integrating human variability in the design process poses many challenges, such as limited access to a statistically representative population and limited data collection resources. This paper discusses two virtual population modeling approaches intended to be performed prior to in-person design validation studies to minimize these challenges by: (1) targeting recruitment of representative population strata and (2) reducing the candidate design parameters being validated in the target population. The first approach suggests the use of digital human models, virtual representations of humans that can simulate system interaction to eliminate candidate design parameters. The second approach suggests the use of existing human databases to identify relevant human characteristics for representative recruitment strata in subsequent studies. Two case studies are presented to demonstrate each approach, and the benefits and limitations of each are discussed. This paper demonstrates the benefit of modeling prior to conducting in-person human performance studies to minimize resource burden, which has significant implications on early design stages.
  • Thumbnail Image
    Item
    Design and Validation of a Method to Characterize Human Interaction Variability
    (MDPI, 2020-09-17) Cage, Kailyn; Vaughn-Cooke, Monifa; Fuge, Mark
    Human interactions are paramount to the user experience, satisfaction, and risk of user errors. For products, anthropometry has traditionally been used in product sizing. However, structured methods that accurately map static and dynamic capabilities (e.g., functional mapping) of musculoskeletal regions for the conceptualization and redesign of product applications and use cases are limited. The present work aims to introduce and validate the effectiveness of the Interaction Variability method, which maps product components and musculoskeletal regions to determine explicit design parameters through limiting designer variation in the classification of human interaction factors. This study enrolled 16 engineering students to evaluate two series of interactions for (1) water bottle and (2) sunglasses applications enabling method validity and designer consistency assessments. For each interaction series, subjects identified and characterized product applications, components, and human interaction factors. Primary interactions, product mapping, and application identification achieved consensus between ranges of 31.25% and 100.00%, with significance (p < 0.1) observed at consensus rates of ≥75.00%. Significant levels of consistency were observed amongst designers, for at least one measure in all phases except anthropometric mapping for the sunglasses application indicating method effectiveness. Interaction variability was introduced and validated in this work as a standardized approach to identify, define, and map human and product interactions, which may reduce unintended use cases and user errors, respectively, in consumer populations.
  • Thumbnail Image
    Item
    Battery Stress Factor Ranking for Accelerated Degradation Test Planning Using Machine Learning
    (MDPI, 2021-01-30) Saxena, Saurabh; Roman, Darius; Robu, Valentin; Flynn, David; Pecht, Michael
    Lithium-ion batteries power numerous systems from consumer electronics to electric vehicles, and thus undergo qualification testing for degradation assessment prior to deployment. Qualification testing involves repeated charge–discharge operation of the batteries, which can take more than three months if subjected to 500 cycles at a C-rate of 0.5C. Accelerated degradation testing can be used to reduce extensive test time, but its application requires a careful selection of stress factors. To address this challenge, this study identifies and ranks stress factors in terms of their effects on battery degradation (capacity fade) using half-fractional design of experiments and machine learning. Two case studies are presented involving 96 lithium-ion batteries from two different manufacturers, tested under five different stress factors. Results show that neither the individual (main) effects nor the two-way interaction effects of charge C-rate and depth of discharge rank in the top three significant stress factors for the capacity fade in lithium-ion batteries, while temperature in the form of either individual or interaction effect provides the maximum acceleration.
  • Thumbnail Image
    Item
    Wave Propagation Studies in Numerical Wave Tanks with Weakly Compressible Smoothed Particle Hydrodynamics
    (MDPI, 2021-02-22) Chakraborty, Samarpan; Balachandran, Balakumar
    Generation and propagation of waves in a numerical wave tank constructed using Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) are considered here. Numerical wave tank simulations have been carried out with implementations of different Wendland kernels in conjunction with different numerical dissipation schemes. The simulations were accelerated by using General Process Graphics Processing Unit (GPGPU) computing to utilize the massively parallel nature of the simulations and thus improve process efficiency. Numerical experiments with short domains have been carried out to validate the dissipation schemes used. The wave tank experiments consist of piston-type wavemakers and appropriate passive absorption arrangements to facilitate comparisons with theoretical predictions. The comparative performance of the different numerical wave tank experiments was carried out on the basis of the hydrostatic pressure and wave surface elevations. The effect of numerical dissipation with the different kernel functions was also studied on the basis of energy analysis. Finally, the observations and results were used to arrive at the best possible numerical set up for simulation of waves at medium and long distances of propagation, which can play a significant role in the study of extreme waves and energy localizations observed in oceans through such numerical wave tank simulations.