research paper about mechanical technology

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Mechanical engineering articles from across Nature Portfolio

Mechanical engineering is the branch of engineering that deals with moving machines and their components. A central principle of mechanical engineering is the control of energy: transferring it from one form to another to suit a specific demand. Car engines, for example, convert chemical energy into kinetic energy.

Latest Research and Reviews

A multi-strategy improved rime optimization algorithm for three-dimensional USV path planning and global optimization

• Jingjun Lou

On the role of surface morphology in impacting-freezing dynamics of supercooled droplets

• S. R. Hosseini
• N. M. Nouri

Design of osteosynthesis plate for detecting bone union using wire natural frequency

• Pisitpong Chancharoen
• Pairat Tangpornprasert
• Chanyaphan Virulsri

Autonomous mining through cooperative driving and operations enabled by parallel intelligence

Long Chen and colleagues show a fully autonomous open-pit mine. Heterogenous machinery and tasks are coordinated using parallel learning and digital twins.

• Fei-Yue Wang

Passive and low-energy strategies to improve sleep thermal comfort and energy resilience during heat waves and cold snaps

• Arfa Aijazi
• Thomas Parkinson
• Stefano Schiavon

Discovering two general characteristic times of transient responses in solid oxide cells

A comprehensive understanding of the transient characteristics in solid oxide cells is crucial when integrated with intermittent renewable energy. Here, authors reveal expressions for two general characteristic times quantifying transient phenomena due to heat and mass transfer lags in SOCs.

• Zhaojian Liang
• Jingyi Wang
• Mengying Li

News and Comment

Micro- and nanorobots for biofilm eradication

Micro- and nanorobots present a promising approach for navigating within the body and eliminating biofilm infections. Their motion can be remotely controlled by external fields and tracked by clinical imaging. They can mechanically disrupt the biofilm matrix and kill the dormant bacterial cells synergistically, thereby improving the effectiveness of biofilm eradication.

• Staffan Kjelleberg

Mechanism of plastic deformation in metal monochalcogenides

Metal monochalcogenides — a class of van der Waals layered semiconductors — can exhibit ultrahigh plasticity. Investigation of the deformation mechanism reveals that on mechanical loading, these materials undergo local phase transitions that, coupled with the concurrent generation of a microcrack network, give rise to the ultrahigh plasticity.

Adaptable navigation of magnetic microrobots

An article in Nature Machine Intelligence presents an adaptable method to control magnetic microrobots’ navigation using reinforcement learning.

• Charlotte Allard

Soft sensing and haptics for medical procedures

Minimally invasive surgery (MIS) lacks sufficient haptic feedback to the surgeon due to the length and flexibility of surgical tools. This haptic disconnect is exacerbated in robotic-MIS, which utilizes tele-operation to control surgical tools. Tactile sensation in MIS and robotic-MIS can be restored in a safe and conformable manner through soft sensors and soft haptic feedback devices.

• Arincheyan Gerald
• Sheila Russo

Propelling the widespread adoption of large-scale 3D printing

3D printing can be used to automate the manufacturing of building elements for large-scale structures such as skyscrapers, aircraft, rockets and space bases without human intervention. However, challenges in materials, processes, printers and software control must first be overcome for large-scale 3D printing to be adopted for widespread applications.

• Wouter De Corte
• Viktor Mechtcherine

Exploration of truss metamaterials with graph based generative modeling

Optimisation tasks in the inverse design of metamaterials with machine learning were limited due to the representations of generative models. Here the author comments a recent publication in Nature Communications which generates a latent space representation that unlocks non-linear optimisations.

• Angkur Jyoti Dipanka Shaikeea

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The Wonders of Thin Structures

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New model predicts how shoe properties affect a runner’s performance

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How to prevent biofilms in space

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Recent Advances in Mechanical Engineering

Select Proceedings of ITME 2019

• Conference proceedings
• © 2021
• Mohammad Muzammil 0 ,
• Arunesh Chandra 1 ,
• Pavan Kumar Kankar 2 ,
• Harish Kumar 3

Aligarh Muslim University, Aligarh, India

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Department of Mechanical Engineering, KIET Group of Institutions, Ghaziabad, India

Department of mechanical engineering, indian institute of technology indore, indore, india, department of mechanical engineering, national institute of technology delhi, new delhi, india.

• Comprises select proceedings of the international conference ITME 2019
• Covers almost all areas of mechanical engineering from design to manufacturing
• Discuses current trends in robotics and mechatronics, rapid prototyping and additive manufacturing

Part of the book series: Lecture Notes in Mechanical Engineering (LNME)

Included in the following conference series:

• ITME: International Conference on Innovative Technologies in Mechanical Engineering

Conference proceedings info: ITME 2019.

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About this book

This book presents selected peer-reviewed papers presented at the International Conference on Innovative Technologies in Mechanical Engineering (ITME) 2019. The book discusses a wide range of topics in mechanical engineering such as mechanical systems, materials engineering, micro-machining, renewable energy, systems engineering, thermal engineering, additive manufacturing, automotive technologies, rapid prototyping, computer aided design and manufacturing. This book, in addition to assisting students and researchers working in various areas of mechanical engineering, can also be useful to researchers and professionals working in various allied and interdisciplinary fields. 

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Birth of Mechanical Engineering and a Glimpse into the Future Trends

Mechanical Technology

Challenges of Mechanical Engineering and in IFToMM: Yesterday and Tomorrow

• Heat and mass transfer
• Fluid dynamics
• Refrigeration and air conditioning
• Conventional and non-conventional machining
• Modelling and Simulation
• Robotics and mechatronics
• Noise, vibration and control
• Smart materials

Table of contents (90 papers)

Front matter, a review on different performance enhancement techniques for solar air heaters.

• Ankur Dwivedi, Harshit Mishra, Vishwas Nagrath

Worker Fatigue Model and Its Ergonomic Application for a Dishwashing Task

• P. Lasin, Vinay V. Panicker

Influence of Backpack Load on Energy Expenditure during Walking

• A. Tamizhinian, Vinay V. Panicker

Low-Carbon Supply Chain Management: A Fuzzy-DEMATEL Analysis of Some Practical Issues of Indian Manufacturing Industries

• Vivek Gupta, Arvind Jayant

Air Jet Erosion Behavior of AA 6082 T6 Aluminum Alloy

• Gyanesh Mangal, Vinod Kumar, Siddhartha

Muscular Discomfort in Occupational Motorcycle Riding

• Mohd Parvez, Abid Ali Khan, Siddharth Bhardwaj

Group Preventive Maintenance Model for Multi-unit Series System: A TLBO Algorithm-Based Approach

• Aseem K. Mishra, Divya Shrivastava, Harsh Gupta

Parametric Investigation of a Rotational Parabolic-Tapered Cantilever with Elliptical Sectional Area Exposed to Variable Thermal Gradient and Axial Dynamic Load

• Rakesh Ranjan Cahnd, Amit Tyagi

Analysis of E-Glass Fiber Wheel Rim by Using ANSYS

• Pankaj Singh Bisht, Ankita Awasthi

Modeling and Simulation of a Distillation Column to Separate an Automotive Fuel

• Asma Iqbal, Syed Akhlaq Ahmad

Data Acquisition System for Measurement of Biomechanical Variables in Sit-to-Stand Task

• Siddharth Bhardwaj, Abid Ali Khan, Mohammad Muzammil

Fabrication and Tribological Behavior of Copper Plain Bearing Lubricated with Biodegradable Oil

• Uzma Iqbal, Asma Iqbal, Siddharth Bhardwaj

A Neural Network-Based Classification for Finger Motion While Grasping Different Sized Objects

• Salman Mohd Khan, Abid Ali Khan, Omar Farooq

Condition Monitoring in Additive Manufacturing Using Support Vector Machine

• Durgesh Nainwal, Pavan Kumar Kankar, Prashant Kumar Jain

Analyses of Temperature and Thermal Stresses of a Ceramic-Coated Diesel Engine Valve

• Subodh Kumar Sharma, Krishna V. Ojha, D. Pradhan, Pratibha Kumari, Ajay kumar

Study on Optoelectronic Properties of Slurry Coated Binary Cadmium Chalcogenide Films

• Vipin Kumar, Vandana Grace Masih, V. K. Sachan

An Integrated Maintenance Management: A Practical Approach

• B. Hari Prasad, Mahesh Bhardwaj

Synthesis and Flexural Behavior of Silica Coated ABOw Reinforced Aluminum Matrix Composites for Structural Application

• Neeraj Pandey, S. C. Ram, I. Chakrabarty, M. R. Majhi

Advancement and Challenges in Latent Heat Thermal Energy Storage System

• Jayesh Kumar, Pushpendra Singh, Rajesh Kumar

Editors and Affiliations

Mohammad Muzammil

Arunesh Chandra

Pavan Kumar Kankar

Harish Kumar

About the editors

Dr. M. Muzammil is a Senior Professor in the Department of Mechanical Engineering of the Z H College of Engineering and Technology at Aligarh Muslim University Aligarh, India. He is currently in charge of industrial and production engineering and heads the ergonomics research division. He works in the field of ergonomics and human factors engineering. Much of his work has focused on improving the design and performance of industrial systems. His research interests include green ergonomics, active noise and vibration control, tool design and productivity improvement. He is also working on various projects in the field of biomedical engineering.  Some of them are Parkinson's disease mitigation device, exoskeleton systems for stroke inflicted and old aged patients, bionic kidneys, etc. He has supervised more than 30 doctoral and postgraduate theses and has completed several research projects. He has published more than 100 research articles in leading journals and international and national conferences. Among the journals in which his articles have been published are Quality Engineering, International Review of Industrial Ergonomics, Theoretical Issues in Ergonomics Science, Occupational Ergonomics, Journal of Occupational Safety and Ergonomics, Work: A Journal of Prevention, Assessment and Rehabilitation and Rehabilitation and Journal of Low Frequency Noise, Vibration and Active Control, etc. He is a co-author of three books. He has provided consultancy to various industries. He is also a member of the editorial board of prestigious international journals. He has been a coordinator and member of the advisory committee/organizer of various international/national workshops and conferences. He has given numerous lectures at various renowned universities.

Dr. Arunesh Chandra is currently serving as a Professor in the Department of Mechanical Engineering at KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India. He obtained his B.Tech. degree in Mechanical Engineering from Govt. College, Satna, Madhya Pradesh, M.Tech. degree from National Institute of Foundry and Forge Technology, Ranchi, Jharkhand and Ph.D. from the Department of Mechanical Engineering of National Institute of Technology, Kurukshetra, Haryana. He has more than 16 years of teaching/research experience. He has more than 30 research papers in various international and national journals, conferences and a patent  granted in the design of helmet by Government of India in the year 2019. His current research areas include ergonomics, quality management, virtual reality.  He has reviewed various research papers and is an editorial board member of Journal of Mechanical and Mechanics Engineering, International Journal of Engineering Research in Mechanical and Civil Engineering and MAT Journals. He received a Certificate of Appreciation & Award from KIET group of Institutions for superior performance in academics. He has also authored two books for undergraduate students Laboratory Manual Engineering Mechanics Lab and Elements of Mechanical Engineering. 

Dr. Pavan Kumar Kankar is currently working as an Associate Professor in Discipline of Mechanical Engineering, Indian Institute of Technology Indore. He is having more than 14 years of teaching and research experience. He had obtained his Ph.D. from Indian Institute of Technology Roorkee, India. His research interests include vibration, design, condition monitoring of mechanical components, nonlinear dynamics, soft computing, etc. He has published more than 100 papers in refereed journals and conferences. He is a reviewer of many journals including Journal of Sound and Vibration, Applied Acoustics, European Journal of Mechanics - A/Solids, Journal of Vibration and Control, IEEE Transactions on Industrial Electronics, Journal of Mechanical Science and Technology. He has been awarded certificate of outstanding contribution in reviewing for Applied Acoustics Journal in June 2017 and awarded outstanding reviewer status for Journal of Sound and Vibration in November 2015. He also served as a guest editor of the special issue of various journals including Advances in Mechanical Engineering, International Journal of Rotating Machinery and Shock and Vibration Journal. He is a member of professional bodies like the American Society of Mechanical Engineers, Society for Reliability and Safety (SRESA), Tribology Society of India and International Institute of Acoustics and Vibration (IIAV).

Dr. Harish Kumar is currently working as Assistant Professor in National Institute of Technology Delhi. He has more than 15 years of research and academic experience and served as Scientist at different grades in CSIR - National Physical Laboratory, India. He has been an active researcher in the areas of mechanical measurement and metrology. He has worked as a guest researcher at National Institute of Standards and Technology, USA in2016. He has been instrumental in the ongoing redefinition of the kilogram in India. He has authored more than 70 publications in peer-reviewed journals and conferences. He is an active reviewer of many reputed journals related to measurement, metrology, and related areas. 

Bibliographic Information

Book Title : Recent Advances in Mechanical Engineering

Book Subtitle : Select Proceedings of ITME 2019

Editors : Mohammad Muzammil, Arunesh Chandra, Pavan Kumar Kankar, Harish Kumar

Series Title : Lecture Notes in Mechanical Engineering

DOI : https://doi.org/10.1007/978-981-15-8704-7

Publisher : Springer Singapore

eBook Packages : Engineering , Engineering (R0)

Copyright Information : Springer Nature Singapore Pte Ltd. 2021

Hardcover ISBN : 978-981-15-8703-0 Published: 29 December 2020

Softcover ISBN : 978-981-15-8706-1 Published: 30 December 2021

eBook ISBN : 978-981-15-8704-7 Published: 28 December 2020

Series ISSN : 2195-4356

Series E-ISSN : 2195-4364

Edition Number : 1

Number of Pages : XVI, 735

Number of Illustrations : 82 b/w illustrations, 271 illustrations in colour

Topics : Engineering Thermodynamics, Heat and Mass Transfer , Engineering Fluid Dynamics , Machinery and Machine Elements , Vibration, Dynamical Systems, Control , Computer-Aided Engineering (CAD, CAE) and Design , Control, Robotics, Mechatronics

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Home > Engineering > MIE > ME_THESES

Mechanical Engineering Masters Theses Collection

Theses from 2024 2024.

TECHNICAL EVALUATION OF FLOATING OFFSHORE WIND PLANTS AND INSTALLATION OPERATIONS , CENGIZHAN CENGIZ, Mechanical Engineering

Heat Transfer Enhacement of Latent Heat Thermal Enery Storage , Joe Hatem T. Saba, Mechanical Engineering

Theses from 2023 2023

Device Design for Inducing Aneurysm-Susceptible Flow Conditions Onto Endothelial Cells , hans f. foelsche, Mechanical Engineering

Thermal Conductivity and Mechanical Properties of Interlayer-Bonded Graphene Bilayers , Afnan Mostafa, Mechanical Engineering

Wind-Wave Misalignment Effects on Multiline Anchor Systems for Floating Offshore Wind Turbines , Doron T. Rose, Mechanical Engineering

Theses from 2022 2022

A Simplified Fluid Dynamics Model of Ultrafiltration , Christopher Cardimino, Mechanical Engineering

Local Nanomechanical Variations of Cold-sprayed Tantalum Coatings , Dhrubajyoti Chowdhury, Mechanical Engineering

Aerodynamically Augmented Air-Hockey Pucks , Madhukar Prasad, Mechanical Engineering

Analysis of Low-Induction Rotors for Increased Power Production , Jack E. Rees, Mechanical Engineering

Application of the New IEC International Design Standard for Offshore Wind Turbines to a Reference Site in the Massachusetts Offshore Wind Energy Area , Samuel C. Roach, Mechanical Engineering

Applications of Thermal Energy Storage with Electrified Heating and Cooling , Erich Ryan, Mechanical Engineering

Theses from 2021 2021

Design and Testing of a Foundation Raised Oscillating Surge Wave Energy Converter , Jacob R. Davis, Mechanical Engineering

Wind Turbine Power Production Estimation for Better Financial Agreements , Shanon Fan, Mechanical Engineering

Finite Element Analysis of Impact and Cohesion of Cold Sprayed Particles onto Non-Planar Surfaces , Zhongkui Liu, Mechanical Engineering

Mechanical Design and Analysis: High-Precision Microcontact Printhead for Roll-to-Roll Printing of Flexible Electronics , Mehdi Riza, Mechanical Engineering

Jet Breakup Dynamics of Inkjet Printing Fluids , Kashyap Sundara Rajan, Mechanical Engineering

Ground Source Heat Pumps: Considerations for Large Facilities in Massachusetts , Eric Wagner, Mechanical Engineering

Theses from 2020 2020

Modeling of Electrical Grid Systems to Evaluate Sustainable Electricity Generation in Pakistan , Muhammad Mustafa Amjad, Mechanical Engineering

A Study on Latent Thermal Energy Storage (LTES) using Phase Change Materials (PCMs) 2020 , Ritvij Dixit, Mechanical Engineering

SunDown: Model-driven Per-Panel Solar Anomaly Detection for Residential Arrays , Menghong Feng, Mechanical Engineering

Nozzle Clogging Prevention and Analysis in Cold Spray , Alden Foelsche, Mechanical Engineering

Short Term Energy Forecasting for a Microgird Load using LSTM RNN , Akhil Soman, Mechanical Engineering

Optimization of Thermal Energy Storage Sizing Using Thermodynamic Analysis , Andrew Villanueva, Mechanical Engineering

Fabrication of Binder-Free Electrodes Based on Graphene Oxide with CNT for Decrease of Resistance , Di Zhang, Mechanical Engineering

Theses from 2019 2019

Computational Fluid Dynamics Models of Electromagnetic Levitation Experiments in Reduced Gravity , Gwendolyn Bracker, Mechanical Engineering

Forecasting the Cost of Electricity Generated by Offshore Wind Turbines , Timothy Costa, Mechanical Engineering

Optical-Fiber-Based Laser-Induced Cavitation for Dynamic Mechanical Characterization of Soft Materials , Qian Feng, Mechanical Engineering

On the Fuel Spray Applications of Multi-Phase Eulerian CFD Techniques , Gabriel Lev Jacobsohn, Mechanical Engineering

Topology Network Optimization of Facility Planning and Design Problems , Ravi Ratan Raj Monga, Mechanical Engineering

The Promise of VR Headsets: Validation of a Virtual Reality Headset-Based Driving Simulator for Measuring Drivers’ Hazard Anticipation Performance , Ganesh Pai Mangalore, Mechanical Engineering

Ammonia Production from a Non-Grid Connected Floating Offshore Wind-Farm: A System-Level Techno-Economic Review , Vismay V. Parmar, Mechanical Engineering

Calculation of Scalar Isosurface Area and Applications , Kedar Prashant Shete, Mechanical Engineering

Theses from 2018 2018

Electroplating of Copper on Tungsten Powder , Richard Berdos, Mechanical Engineering

A NUMERICAL FLUTTER PREDICTOR FOR 3D AIRFOILS USING THE ONERA DYNAMIC STALL MODEL , Pieter Boersma, Mechanical Engineering

Streamwise Flow-Induced Oscillations of Bluff Bodies - The Influence of Symmetry Breaking , Tyler Gurian, Mechanical Engineering

Thermal Radiation Measurement and Development of Tunable Plasmonic Thermal Emitter Using Strain-induced Buckling in Metallic Layers , Amir Kazemi-Moridani, Mechanical Engineering

Restructuring Controllers to Accommodate Plant Nonlinearities , Kushal Sahare, Mechanical Engineering

Application and Evaluation of Lighthouse Technology for Precision Motion Capture , Soumitra Sitole, Mechanical Engineering

High Strain Rate Dynamic Response of Aluminum 6061 Micro Particles at Elevated Temperatures and Varying Oxide Thicknesses of Substrate Surface , Carmine Taglienti, Mechanical Engineering

The Effects of Mechanical Loading and Tumor Factors on Osteocyte Dendrite Formation , Wenbo Wang, Mechanical Engineering

Microenvironment Regulates Fusion of Breast Cancer Cells , Peiran Zhu, Mechanical Engineering

Design for Sustainability through a Life Cycle Assessment Conceptual Framework Integrated within Product Lifecycle Management , Renpeng Zou, Mechanical Engineering

Theses from 2017 2017

Improving the Efficiency of Wind Farm Turbines using External Airfoils , Shujaut Bader, Mechanical Engineering

Evaluation Of Impedance Control On A Powered Hip Exoskeleton , Punith condoor, Mechanical Engineering

Experimental Study on Viscoelastic Fluid-Structure Interactions , Anita Anup Dey, Mechanical Engineering

BMI, Tumor Lesion and Probability of Femur Fracture: a Probabilistic Biomechanics Approach , Zhi Gao, Mechanical Engineering

A Magnetic Resonance Compatible Knee Extension Ergometer , Youssef Jaber, Mechanical Engineering

Non-Equispaced Fast Fourier Transforms in Turbulence Simulation , Aditya M. Kulkarni, Mechanical Engineering

INCORPORATING SEASONAL WIND RESOURCE AND ELECTRICITY PRICE DATA INTO WIND FARM MICROSITING , Timothy A. Pfeiffer, Mechanical Engineering

Effects of Malformed or Absent Valves to Lymphatic Fluid Transport and Lymphedema in Vivo in Mice , Akshay S. Pujari, Mechanical Engineering

Electroless Deposition & Electroplating of Nickel on Chromium-Nickel Carbide Powder , Jeffrey Rigali, Mechanical Engineering

Numerical Simulation of Multi-Phase Core-Shell Molten Metal Drop Oscillations , Kaushal Sumaria, Mechanical Engineering

Theses from 2016 2016

Cold Gas Dynamic Spray – Characterization of Polymeric Deposition , Trenton Bush, Mechanical Engineering

Intent Recognition Of Rotation Versus Translation Movements In Human-Robot Collaborative Manipulation Tasks , Vinh Q. Nguyen, Mechanical Engineering

A Soft Multiple-Degree of Freedom Load Cell Based on The Hall Effect , Qiandong Nie, Mechanical Engineering

A Haptic Surface Robot Interface for Large-Format Touchscreen Displays , Mark Price, Mechanical Engineering

Numerical Simulation of High Velocity Impact of a Single Polymer Particle during Cold Spray Deposition , Sagar P. Shah, Mechanical Engineering

Tunable Plasmonic Thermal Emitter Using Metal-Coated Elastomeric Structures , Robert Zando, Mechanical Engineering

Theses from 2015 2015

Thermodynamic Analysis of the Application of Thermal Energy Storage to a Combined Heat and Power Plant , Benjamin McDaniel, Mechanical Engineering

Towards a Semantic Knowledge Management Framework for Laminated Composites , Vivek Premkumar, Mechanical Engineering

A CONTINOUS ROTARY ACTUATION MECHANISM FOR A POWERED HIP EXOSKELETON , Matthew C. Ryder, Mechanical Engineering

Optimal Topological Arrangement of Queues in Closed Finite Queueing Networks , Lening Wang, Mechanical Engineering

Creating a New Model to Predict Cooling Tower Performance and Determining Energy Saving Opportunities through Economizer Operation , Pranav Yedatore Venkatesh, Mechanical Engineering

Theses from 2014 2014

New Generator Control Algorithms for Smart-Bladed Wind Turbines to Improve Power Capture in Below Rated Conditions , Bryce B. Aquino, Mechanical Engineering

UBOT-7: THE DESIGN OF A COMPLIANT DEXTEROUS MOBILE MANIPULATOR , Jonathan Cummings, Mechanical Engineering

Design and Control of a Two-Wheeled Robotic Walker , Airton R. da Silva Jr., Mechanical Engineering

Free Wake Potential Flow Vortex Wind Turbine Modeling: Advances in Parallel Processing and Integration of Ground Effects , Nathaniel B. Develder, Mechanical Engineering

Buckling of Particle-Laden Interfaces , Theo Dias Kassuga, Mechanical Engineering

Modeling Dynamic Stall for a Free Vortex Wake Model of a Floating Offshore Wind Turbine , Evan M. Gaertner, Mechanical Engineering

An Experimental Study of the C-Start of a Mechanical Fish , Benjamin Kandaswamy Chinna Thambi, Mechanical Engineering

Measurement and Verification - Retro-Commissioning of a LEED Gold Rated Building Through Means of an Energy Model: Are Aggressive Energy Simulation Models Reliable? , Justin M. Marmaras, Mechanical Engineering

Development of a Support Structure for Multi-Rotor Wind Turbines , Gaurav Murlidhar Mate, Mechanical Engineering

Towards Accessible, Usable Knowledge Frameworks in Engineering , Jeffrey Mcpherson, Mechanical Engineering

A Consistent Algorithm for Implementing the Space Conservation Law , Venkata Pavan Pillalamarri Narasimha Rao, Mechanical Engineering

Kinetics of Aluminization and Homogenization in Wrought H-X750 Nickel-Base Superalloy , Sean Reilly, Mechanical Engineering

Single-Phase Turbulent Enthalpy Transport , Bradley J. Shields, Mechanical Engineering

CFD Simulation of the Flow around NREL Phase VI Wind Turbine , Yang Song, Mechanical Engineering

Selection of Outputs for Distributed Parameter Systems by Identifiability Analysis in the Time-scale Domain , Teergele, Mechanical Engineering

The Optimization of Offshore Wind Turbine Towers Using Passive Tuned Mass Dampers , Onur Can Yilmaz, Mechanical Engineering

Design of a Passive Exoskeleton Spine , Haohan Zhang, Mechanical Engineering

TURBULENT TRANSITION IN ELECTROMAGNETICALLY LEVITATED LIQUID METAL DROPLETS , Jie Zhao, Mechanical Engineering

Theses from 2013 2013

Optimization of Mixing in a Simulated Biomass Bed Reactor with a Center Feeding Tube , Michael T. Blatnik, Mechanical Engineering

Continued Development of a Chilled Water System Analysis Tool for Energy Conservation Measures Evaluation , Ghanshyam Gaudani, Mechanical Engineering

Application of Finite Element Method in Protein Normal Mode Analysis , Chiung-fang Hsu, Mechanical Engineering

Asymmetric Blade Spar for Passive Aerodynamic Load Control , Charles Mcclelland, Mechanical Engineering

Background and Available Potential Energy in Numerical Simulations of a Boussinesq Fluid , Shreyas S. Panse, Mechanical Engineering

Techno-Economic Analysis of Hydrogen Fuel Cell Systems Used as an Electricity Storage Technology in a Wind Farm with Large Amounts of Intermittent Energy , Yash Sanghai, Mechanical Engineering

Multi Rotor Wind Turbine Design And Cost Scaling , Preeti Verma, Mechanical Engineering

Activity Intent Recognition of the Torso Based on Surface Electromyography and Inertial Measurement Units , Zhe Zhang, Mechanical Engineering

Theses from 2012 2012

Simulations of Non-Contact Creep in Regimes of Mixed Dominance , Maija Benitz, Mechanical Engineering

Techniques for Industrial Implementation of Emerging Semantic Technologies , Jay T. Breindel, Mechanical Engineering

Environmental Impacts Due to Fixed and Floating Offshore Wind Turbines , Micah K. Brewer, Mechanical Engineering

Physical Model of the Feeding Strike of the Mantis Shrimp , Suzanne M. Cox, Mechanical Engineering

Investigating the Relationship Between Material Property Axes and Strain Orientations in Cebus Apella Crania , Christine M. Dzialo, Mechanical Engineering

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Modular, scalable hardware architecture for a quantum computer

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Quantum computers hold the promise of being able to quickly solve extremely complex problems that might take the world’s most powerful supercomputer decades to crack.

But achieving that performance involves building a system with millions of interconnected building blocks called qubits. Making and controlling so many qubits in a hardware architecture is an enormous challenge that scientists around the world are striving to meet.

Toward this goal, researchers at MIT and MITRE have demonstrated a scalable, modular hardware platform that integrates thousands of interconnected qubits onto a customized integrated circuit. This “quantum-system-on-chip” (QSoC) architecture enables the researchers to precisely tune and control a dense array of qubits. Multiple chips could be connected using optical networking to create a large-scale quantum communication network.

By tuning qubits across 11 frequency channels, this QSoC architecture allows for a new proposed protocol of “entanglement multiplexing” for large-scale quantum computing.

The team spent years perfecting an intricate process for manufacturing two-dimensional arrays of atom-sized qubit microchiplets and transferring thousands of them onto a carefully prepared complementary metal-oxide semiconductor (CMOS) chip. This transfer can be performed in a single step.

“We will need a large number of qubits, and great control over them, to really leverage the power of a quantum system and make it useful. We are proposing a brand new architecture and a fabrication technology that can support the scalability requirements of a hardware system for a quantum computer,” says Linsen Li, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this architecture.

Li’s co-authors include Ruonan Han, an associate professor in EECS, leader of the Terahertz Integrated Electronics Group, and member of the Research Laboratory of Electronics (RLE); senior author Dirk Englund, professor of EECS, principal investigator of the Quantum Photonics and Artificial Intelligence Group and of RLE; as well as others at MIT, Cornell University, the Delft Institute of Technology, the U.S. Army Research Laboratory, and the MITRE Corporation. The paper appears today in Nature .

Diamond microchiplets

While there are many types of qubits, the researchers chose to use diamond color centers because of their scalability advantages. They previously used such qubits to produce integrated quantum chips with photonic circuitry.

Qubits made from diamond color centers are “artificial atoms” that carry quantum information. Because diamond color centers are solid-state systems, the qubit manufacturing is compatible with modern semiconductor fabrication processes. They are also compact and have relatively long coherence times, which refers to the amount of time a qubit’s state remains stable, due to the clean environment provided by the diamond material.

In addition, diamond color centers have photonic interfaces which allows them to be remotely entangled, or connected, with other qubits that aren’t adjacent to them.

“The conventional assumption in the field is that the inhomogeneity of the diamond color center is a drawback compared to identical quantum memory like ions and neutral atoms. However, we turn this challenge into an advantage by embracing the diversity of the artificial atoms: Each atom has its own spectral frequency. This allows us to communicate with individual atoms by voltage tuning them into resonance with a laser, much like tuning the dial on a tiny radio,” says Englund.

This is especially difficult because the researchers must achieve this at a large scale to compensate for the qubit inhomogeneity in a large system.

To communicate across qubits, they need to have multiple such “quantum radios” dialed into the same channel. Achieving this condition becomes near-certain when scaling to thousands of qubits. To this end, the researchers surmounted that challenge by integrating a large array of diamond color center qubits onto a CMOS chip which provides the control dials. The chip can be incorporated with built-in digital logic that rapidly and automatically reconfigures the voltages, enabling the qubits to reach full connectivity.

“This compensates for the in-homogenous nature of the system. With the CMOS platform, we can quickly and dynamically tune all the qubit frequencies,” Li explains.

Lock-and-release fabrication

To build this QSoC, the researchers developed a fabrication process to transfer diamond color center “microchiplets” onto a CMOS backplane at a large scale.

They started by fabricating an array of diamond color center microchiplets from a solid block of diamond. They also designed and fabricated nanoscale optical antennas that enable more efficient collection of the photons emitted by these color center qubits in free space.

Then, they designed and mapped out the chip from the semiconductor foundry. Working in the MIT.nano cleanroom, they post-processed a CMOS chip to add microscale sockets that match up with the diamond microchiplet array.

They built an in-house transfer setup in the lab and applied a lock-and-release process to integrate the two layers by locking the diamond microchiplets into the sockets on the CMOS chip. Since the diamond microchiplets are weakly bonded to the diamond surface, when they release the bulk diamond horizontally, the microchiplets stay in the sockets.

“Because we can control the fabrication of both the diamond and the CMOS chip, we can make a complementary pattern. In this way, we can transfer thousands of diamond chiplets into their corresponding sockets all at the same time,” Li says.

The researchers demonstrated a 500-micron by 500-micron area transfer for an array with 1,024 diamond nanoantennas, but they could use larger diamond arrays and a larger CMOS chip to further scale up the system. In fact, they found that with more qubits, tuning the frequencies actually requires less voltage for this architecture.

“In this case, if you have more qubits, our architecture will work even better,” Li says.

The team tested many nanostructures before they determined the ideal microchiplet array for the lock-and-release process. However, making quantum microchiplets is no easy task, and the process took years to perfect.

“We have iterated and developed the recipe to fabricate these diamond nanostructures in MIT cleanroom, but it is a very complicated process. It took 19 steps of nanofabrication to get the diamond quantum microchiplets, and the steps were not straightforward,” he adds.

Alongside their QSoC, the researchers developed an approach to characterize the system and measure its performance on a large scale. To do this, they built a custom cryo-optical metrology setup.

Using this technique, they demonstrated an entire chip with over 4,000 qubits that could be tuned to the same frequency while maintaining their spin and optical properties. They also built a digital twin simulation that connects the experiment with digitized modeling, which helps them understand the root causes of the observed phenomenon and determine how to efficiently implement the architecture.

In the future, the researchers could boost the performance of their system by refining the materials they used to make qubits or developing more precise control processes. They could also apply this architecture to other solid-state quantum systems.

This work was supported by the MITRE Corporation Quantum Moonshot Program, the U.S. National Science Foundation, the U.S. Army Research Office, the Center for Quantum Networks, and the European Union’s Horizon 2020 Research and Innovation Program.

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A new future of work: The race to deploy AI and raise skills in Europe and beyond

At a glance.

Amid tightening labor markets and a slowdown in productivity growth, Europe and the United States face shifts in labor demand, spurred by AI and automation. Our updated modeling of the future of work finds that demand for workers in STEM-related, healthcare, and other high-skill professions would rise, while demand for occupations such as office workers, production workers, and customer service representatives would decline. By 2030, in a midpoint adoption scenario, up to 30 percent of current hours worked could be automated, accelerated by generative AI (gen AI). Efforts to achieve net-zero emissions, an aging workforce, and growth in e-commerce, as well as infrastructure and technology spending and overall economic growth, could also shift employment demand.

By 2030, Europe could require up to 12 million occupational transitions, double the prepandemic pace. In the United States, required transitions could reach almost 12 million, in line with the prepandemic norm. Both regions navigated even higher levels of labor market shifts at the height of the COVID-19 period, suggesting that they can handle this scale of future job transitions. The pace of occupational change is broadly similar among countries in Europe, although the specific mix reflects their economic variations.

Businesses will need a major skills upgrade. Demand for technological and social and emotional skills could rise as demand for physical and manual and higher cognitive skills stabilizes. Surveyed executives in Europe and the United States expressed a need not only for advanced IT and data analytics but also for critical thinking, creativity, and teaching and training—skills they report as currently being in short supply. Companies plan to focus on retraining workers, more than hiring or subcontracting, to meet skill needs.

Workers with lower wages face challenges of redeployment as demand reweights toward occupations with higher wages in both Europe and the United States. Occupations with lower wages are likely to see reductions in demand, and workers will need to acquire new skills to transition to better-paying work. If that doesn’t happen, there is a risk of a more polarized labor market, with more higher-wage jobs than workers and too many workers for existing lower-wage jobs.

Choices made today could revive productivity growth while creating better societal outcomes. Embracing the path of accelerated technology adoption with proactive worker redeployment could help Europe achieve an annual productivity growth rate of up to 3 percent through 2030. However, slow adoption would limit that to 0.3 percent, closer to today’s level of productivity growth in Western Europe. Slow worker redeployment would leave millions unable to participate productively in the future of work.

Demand will change for a range of occupations through 2030, including growth in STEM- and healthcare-related occupations, among others

This report focuses on labor markets in nine major economies in the European Union along with the United Kingdom, in comparison with the United States. Technology, including most recently the rise of gen AI, along with other factors, will spur changes in the pattern of labor demand through 2030. Our study, which uses an updated version of the McKinsey Global Institute future of work model, seeks to quantify the occupational transitions that will be required and the changing nature of demand for different types of jobs and skills.

Our methodology

We used methodology consistent with other McKinsey Global Institute reports on the future of work to model trends of job changes at the level of occupations, activities, and skills. For this report, we focused our analysis on the 2022–30 period.

Our model estimates net changes in employment demand by sector and occupation; we also estimate occupational transitions, or the net number of workers that need to change in each type of occupation, based on which occupations face declining demand by 2030 relative to current employment in 2022. We included ten countries in Europe: nine EU members—the Czech Republic, Denmark, France, Germany, Italy, Netherlands, Poland, Spain, and Sweden—and the United Kingdom. For the United States, we build on estimates published in our 2023 report Generative AI and the future of work in America.

We included multiple drivers in our modeling: automation potential, net-zero transition, e-commerce growth, remote work adoption, increases in income, aging populations, technology investments, and infrastructure investments.

Two scenarios are used to bookend the work-automation model: “late” and “early.” For Europe, we modeled a “faster” scenario and a “slower” one. For the faster scenario, we use the midpoint—the arithmetical average between our late and early scenarios. For the slower scenario, we use a “mid late” trajectory, an arithmetical average between a late adoption scenario and the midpoint scenario. For the United States, we use the midpoint scenario, based on our earlier research.

We also estimate the productivity effects of automation, using GDP per full-time-equivalent (FTE) employee as the measure of productivity. We assumed that workers displaced by automation rejoin the workforce at 2022 productivity levels, net of automation, and in line with the expected 2030 occupational mix.

Amid tightening labor markets and a slowdown in productivity growth, Europe and the United States face shifts in labor demand, spurred not only by AI and automation but also by other trends, including efforts to achieve net-zero emissions, an aging population, infrastructure spending, technology investments, and growth in e-commerce, among others (see sidebar, “Our methodology”).

Our analysis finds that demand for occupations such as health professionals and other STEM-related professionals would grow by 17 to 30 percent between 2022 and 2030, (Exhibit 1).

By contrast, demand for workers in food services, production work, customer services, sales, and office support—all of which declined over the 2012–22 period—would continue to decline until 2030. These jobs involve a high share of repetitive tasks, data collection, and elementary data processing—all activities that automated systems can handle efficiently.

Up to 30 percent of hours worked could be automated by 2030, boosted by gen AI, leading to millions of required occupational transitions

By 2030, our analysis finds that about 27 percent of current hours worked in Europe and 30 percent of hours worked in the United States could be automated, accelerated by gen AI. Our model suggests that roughly 20 percent of hours worked could still be automated even without gen AI, implying a significant acceleration.

These trends will play out in labor markets in the form of workers needing to change occupations. By 2030, under the faster adoption scenario we modeled, Europe could require up to 12.0 million occupational transitions, affecting 6.5 percent of current employment. That is double the prepandemic pace (Exhibit 2). Under a slower scenario we modeled for Europe, the number of occupational transitions needed would amount to 8.5 million, affecting 4.6 percent of current employment. In the United States, required transitions could reach almost 12.0 million, affecting 7.5 percent of current employment. Unlike Europe, this magnitude of transitions is broadly in line with the prepandemic norm.

Both regions navigated even higher levels of labor market shifts at the height of the COVID-19 period. While these were abrupt and painful to many, given the forced nature of the shifts, the experience suggests that both regions have the ability to handle this scale of future job transitions.

Businesses will need a major skills upgrade

The occupational transitions noted above herald substantial shifts in workforce skills in a future in which automation and AI are integrated into the workplace (Exhibit 3). Workers use multiple skills to perform a given task, but for the purposes of our quantification, we identified the predominant skill used.

Demand for technological skills could see substantial growth in Europe and in the United States (increases of 25 percent and 29 percent, respectively, in hours worked by 2030 compared to 2022) under our midpoint scenario of automation adoption (which is the faster scenario for Europe).

Demand for social and emotional skills could rise by 11 percent in Europe and by 14 percent in the United States. Underlying this increase is higher demand for roles requiring interpersonal empathy and leadership skills. These skills are crucial in healthcare and managerial roles in an evolving economy that demands greater adaptability and flexibility.

Conversely, demand for work in which basic cognitive skills predominate is expected to decline by 14 percent. Basic cognitive skills are required primarily in office support or customer service roles, which are highly susceptible to being automated by AI. Among work characterized by these basic cognitive skills experiencing significant drops in demand are basic data processing and literacy, numeracy, and communication.

Demand for work in which higher cognitive skills predominate could also decline slightly, according to our analysis. While creativity is expected to remain highly sought after, with a potential increase of 12 percent by 2030, work activities characterized by other advanced cognitive skills such as advanced literacy and writing, along with quantitative and statistical skills, could decline by 19 percent.

Demand for physical and manual skills, on the other hand, could remain roughly level with the present. These skills remain the largest share of workforce skills, representing about 30 percent of total hours worked in 2022. Growth in demand for these skills between 2022 and 2030 could come from the build-out of infrastructure and higher investment in low-emissions sectors, while declines would be in line with continued automation in production work.

Business executives report skills shortages today and expect them to worsen

A survey we conducted of C-suite executives in five countries shows that companies are already grappling with skills challenges, including a skills mismatch, particularly in technological, higher cognitive, and social and emotional skills: about one-third of the more than 1,100 respondents report a shortfall in these critical areas. At the same time, a notable number of executives say they have enough employees with basic cognitive skills and, to a lesser extent, physical and manual skills.

Within technological skills, companies in our survey reported that their most significant shortages are in advanced IT skills and programming, advanced data analysis, and mathematical skills. Among higher cognitive skills, significant shortfalls are seen in critical thinking and problem structuring and in complex information processing. About 40 percent of the executives surveyed pointed to a shortage of workers with these skills, which are needed for working alongside new technologies (Exhibit 4).

Companies see retraining as key to acquiring needed skills and adapting to the new work landscape

Surveyed executives expect significant changes to their workforce skill levels and worry about not finding the right skills by 2030. More than one in four survey respondents said that failing to capture the needed skills could directly harm financial performance and indirectly impede their efforts to leverage the value from AI.

To acquire the skills they need, companies have three main options: retraining, hiring, and contracting workers. Our survey suggests that executives are looking at all three options, with retraining the most widely reported tactic planned to address the skills mismatch: on average, out of companies that mentioned retraining as one of their tactics to address skills mismatch, executives said they would retrain 32 percent of their workforce. The scale of retraining needs varies in degree. For example, respondents in the automotive industry expect 36 percent of their workforce to be retrained, compared with 28 percent in the financial services industry. Out of those who have mentioned hiring or contracting as their tactics to address the skills mismatch, executives surveyed said they would hire an average of 23 percent of their workforce and contract an average of 18 percent.

Occupational transitions will affect high-, medium-, and low-wage workers differently

All ten European countries we examined for this report may see increasing demand for top-earning occupations. By contrast, workers in the two lowest-wage-bracket occupations could be three to five times more likely to have to change occupations compared to the top wage earners, our analysis finds. The disparity is much higher in the United States, where workers in the two lowest-wage-bracket occupations are up to 14 times more likely to face occupational shifts than the highest earners. In Europe, the middle-wage population could be twice as affected by occupational transitions as the same population in United States, representing 7.3 percent of the working population who might face occupational transitions.

Enhancing human capital at the same time as deploying the technology rapidly could boost annual productivity growth

About quantumblack, ai by mckinsey.

QuantumBlack, McKinsey’s AI arm, helps companies transform using the power of technology, technical expertise, and industry experts. With thousands of practitioners at QuantumBlack (data engineers, data scientists, product managers, designers, and software engineers) and McKinsey (industry and domain experts), we are working to solve the world’s most important AI challenges. QuantumBlack Labs is our center of technology development and client innovation, which has been driving cutting-edge advancements and developments in AI through locations across the globe.

Organizations and policy makers have choices to make; the way they approach AI and automation, along with human capital augmentation, will affect economic and societal outcomes.

We have attempted to quantify at a high level the potential effects of different stances to AI deployment on productivity in Europe. Our analysis considers two dimensions. The first is the adoption rate of AI and automation technologies. We consider the faster scenario and the late scenario for technology adoption. Faster adoption would unlock greater productivity growth potential but also, potentially, more short-term labor disruption than the late scenario.

The second dimension we consider is the level of automated worker time that is redeployed into the economy. This represents the ability to redeploy the time gained by automation and productivity gains (for example, new tasks and job creation). This could vary depending on the success of worker training programs and strategies to match demand and supply in labor markets.

We based our analysis on two potential scenarios: either all displaced workers would be able to fully rejoin the economy at a similar productivity level as in 2022 or only some 80 percent of the automated workers’ time will be redeployed into the economy.

Exhibit 5 illustrates the various outcomes in terms of annual productivity growth rate. The top-right quadrant illustrates the highest economy-wide productivity, with an annual productivity growth rate of up to 3.1 percent. It requires fast adoption of technologies as well as full redeployment of displaced workers. The top-left quadrant also demonstrates technology adoption on a fast trajectory and shows a relatively high productivity growth rate (up to 2.5 percent). However, about 6.0 percent of total hours worked (equivalent to 10.2 million people not working) would not be redeployed in the economy. Finally, the two bottom quadrants depict the failure to adopt AI and automation, leading to limited productivity gains and translating into limited labor market disruptions.

Four priorities for companies

The adoption of automation technologies will be decisive in protecting businesses’ competitive advantage in an automation and AI era. To ensure successful deployment at a company level, business leaders can embrace four priorities.

Understand the potential. Leaders need to understand the potential of these technologies, notably including how AI and gen AI can augment and automate work. This includes estimating both the total capacity that these technologies could free up and their impact on role composition and skills requirements. Understanding this allows business leaders to frame their end-to-end strategy and adoption goals with regard to these technologies.

Plan a strategic workforce shift. Once they understand the potential of automation technologies, leaders need to plan the company’s shift toward readiness for the automation and AI era. This requires sizing the workforce and skill needs, based on strategically identified use cases, to assess the potential future talent gap. From this analysis will flow details about the extent of recruitment of new talent, upskilling, or reskilling of the current workforce that is needed, as well as where to redeploy freed capacity to more value-added tasks.

Prioritize people development. To ensure that the right talent is on hand to sustain the company strategy during all transformation phases, leaders could consider strengthening their capabilities to identify, attract, and recruit future AI and gen AI leaders in a tight market. They will also likely need to accelerate the building of AI and gen AI capabilities in the workforce. Nontechnical talent will also need training to adapt to the changing skills environment. Finally, leaders could deploy an HR strategy and operating model to fit the post–gen AI workforce.

Pursue the executive-education journey on automation technologies. Leaders also need to undertake their own education journey on automation technologies to maximize their contributions to their companies during the coming transformation. This includes empowering senior managers to explore automation technologies implications and subsequently role model to others, as well as bringing all company leaders together to create a dedicated road map to drive business and employee value.

AI and the toolbox of advanced new technologies are evolving at a breathtaking pace. For companies and policy makers, these technologies are highly compelling because they promise a range of benefits, including higher productivity, which could lift growth and prosperity. Yet, as this report has sought to illustrate, making full use of the advantages on offer will also require paying attention to the critical element of human capital. In the best-case scenario, workers’ skills will develop and adapt to new technological challenges. Achieving this goal in our new technological age will be highly challenging—but the benefits will be great.

Eric Hazan is a McKinsey senior partner based in Paris; Anu Madgavkar and Michael Chui are McKinsey Global Institute partners based in New Jersey and San Francisco, respectively; Sven Smit is chair of the McKinsey Global Institute and a McKinsey senior partner based in Amsterdam; Dana Maor is a McKinsey senior partner based in Tel Aviv; Gurneet Singh Dandona is an associate partner and a senior expert based in New York; and Roland Huyghues-Despointes is a consultant based in Paris.

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