About
When visionary companies need to know how their world-changing ideas will perform, they…
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Education
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President, Worldwide Pantnagar Alumni Association (www.wpaa.org) since its inception (~1986)
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High School & Inter
Volunteer Experience
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Elected Member of Board of Education
Golf District 67
- 13 years 9 months
Education
Elected member of Board of Education
https://www.golf67.net/board-of-education -
President
Worldwide Pantnagar Alumni Association
- Present 39 years 1 month
Education
Alumni Association for GB Pant University of Agriculture and Technology, Pantnagar, India
Publications
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An Investigation of the Flame-Burden Interaction during Remelting in an Experimental Aluminum Reverbatory Furnace
TMS 2008
Flame impingement on the burden is routinely encountered during the initial phase of melting in aluminum reverberatory furnaces. This impingement causes an obstructed pathway for the hot gases, and hence the circulation and residence time of the hot gases are greatly impacted. Moreover, as the load melts, the flames gradually achieve an unobstructed path leading to reduced gas residence times. This flame impingement and constantly changing combustion space volume will lead to vastly different…
Flame impingement on the burden is routinely encountered during the initial phase of melting in aluminum reverberatory furnaces. This impingement causes an obstructed pathway for the hot gases, and hence the circulation and residence time of the hot gases are greatly impacted. Moreover, as the load melts, the flames gradually achieve an unobstructed path leading to reduced gas residence times. This flame impingement and constantly changing combustion space volume will lead to vastly different fuel and oxidizer mixing patterns and thus affect the overall furnace performance. Fine tuning the burner operating conditions such as flow rates and injection angles with the changing combustion space could result in significant improvements to the furnace efficiency. However, one has to gain a better understanding of the furnace dynamics to know the suitable parameters to adjust. Physical modeling can be elaborate and expensive to conduct on a regular basis while Computational Fluid Dynamics (CFD) can cost-effectively address this challenge. In this study, the furnace model is created with a particular loading pattern to understand the flame dynamics in the presence of a piled load. This configuration can be thought of as a computational model of the furnace with the burden at a particular stage of the melting process. Thermal efficiency and behavior of the furnace are quantified and the predicted values are compared with the operational data from an experimental reverberatory furnace.
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EXPERIMENTAL AND NUMERICAL STUDY OF FLAME LOAD HEAT TRANSFER IN AN EXPERIMENTAL FURNACE
TMS 2008
Flame impingement on solid objects is a routinely encountered phenomenon in metallurgical operations. This was studied in an experimental furnace in order to obtain heat transfer. In this paper, the same is simulated using a Computational Fluid Dynamics (CFD) approach and the resulting temperature, velocity and chemical composition distributions were compared to the experimental data. This comparative analysis demonstrates the potential of mathematical modeling not only in complementing the…
Flame impingement on solid objects is a routinely encountered phenomenon in metallurgical operations. This was studied in an experimental furnace in order to obtain heat transfer. In this paper, the same is simulated using a Computational Fluid Dynamics (CFD) approach and the resulting temperature, velocity and chemical composition distributions were compared to the experimental data. This comparative analysis demonstrates the potential of mathematical modeling not only in complementing the experiments but also in providing a cost-effective framework for obtaining the data after proper validation with the experimental data.
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Evaluation of Flow Uniformity around Automotive Pinion Gears during Quenching
5th International Conference on Quenching and Control of Distortion. European Conference on Heat Treatment 2007, Berlin, April 25 – 27, 2007
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How Flames/Load Interaction Affects Furnace Efficiency in Round Top Furnace Operation
Recycling and Waste Processing, TMS
The operation of a round top furnace for melting aluminum involves the lowering of the load into the furnace, closing of the roof and then the firing of the burners until the load is completely melted. When the burners initially fire, the flames will impinge upon the load and will continue to impinge upon the load (to various degrees) until the load is nearly melted. This flame impingement and the varying combustion space configuration affect the mixing of the fuel and oxidizer and thus…
The operation of a round top furnace for melting aluminum involves the lowering of the load into the furnace, closing of the roof and then the firing of the burners until the load is completely melted. When the burners initially fire, the flames will impinge upon the load and will continue to impinge upon the load (to various degrees) until the load is nearly melted. This flame impingement and the varying combustion space configuration affect the mixing of the fuel and oxidizer and thus affect the efficiency of the furnace. In-situ measurements of the furnace efficiency are expensive and difficult to obtain. Computational fluid dynamics is a powerful tool that would allow more efficacious investigation of the efficiency of the furnace under these conditions. However, a complete and detailed transient model of the furnace would be computationally expensive to perform and would result in limited additional information. Instead, a series of ‘snapshots’ of the furnace are modeled. Each snapshot is a computational model of the load at a particular stage of the melting process. For each snapshot, the thermal efficiency and behavior of the furnace are quantified. This paper presents the results from this analysis along with some suggestions on how to improve furnace performance.
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Fluid Flow and its Modeling using Computational Fluid Dynamics
Handbook of Food and Bioprocess Modeling Techniques, Food Science and Technology Volume: 166. CRC Press
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Optimizing Agitation and Quench Uniformity using CFD
Proceedings of the 23rd ASM Heat Treating Society Conference, 2005, p. 271-278
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Numerical Simulation of the Draw Down Phenomenon in Glass Furnace Forehearths
International Journal of Forming Processes
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A Vision for Deploying Flow Modeling in Food Process and Product Development
IFT Symposium
New product and process development typically involves rigorous pilot-plant trials and plant trials before final manufacturing. CFD can guide pilot-plant trials and help design better experiments by providing deeper understanding and insight to engineering problems related to flow, mixing, heat and mass transfer, reactions etc. The benefit can be seen in reducing the number of plant trials and shorten the time-to-market. The state-of-the-art CFD technologies allow food engineers to run…
New product and process development typically involves rigorous pilot-plant trials and plant trials before final manufacturing. CFD can guide pilot-plant trials and help design better experiments by providing deeper understanding and insight to engineering problems related to flow, mixing, heat and mass transfer, reactions etc. The benefit can be seen in reducing the number of plant trials and shorten the time-to-market. The state-of-the-art CFD technologies allow food engineers to run real-life problems on their personal computers or laptop computers without requiring the traditional long learning curve and the engineering time involved in setting up CFD problems. These preprocessing tasks are completely automated allowing a non-CFD engineer to setup a problem literally in a few minutes.
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Droplet dynamics in drop-on-demand printheads: An experimental and numerical study
IMI Conference
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Supercomputing Applications in Thermal Processing Operations for Foods
Science and Engineering on Supercomputers, Computational Mechanics Publications, Springer-Verlag
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Honors & Awards
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International Outstanding Alumnus Award 2020
Pantnagar Alumni Almamater Advancement Association[4A]
Deeply honored and humbled to receive this International Outstanding Alumnus Award from GB Pant Univ of Agriculture and Technology, Pantnagar. Here is the video clip: https://www.youtube.com/watch?v=pAbAB9lxMEk
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1992 Fellow of the North Carolina Supercomputing Center
North Carolina Supercomputing Center
https://fbns.ncsu.edu/faculty/CV/KRS_vita-2017.pdf
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1991 Fellow of the North Carolina Supercomputing Center
North Carolina Supercomputing Center
Post-doc Dr. Ashwini Kumar named 1991 and 1992 Fellow of the North Carolina
Supercomputing Center. -
Gold Medal
GBPUA&T
Languages
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Hindi
Native or bilingual proficiency
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English
Full professional proficiency
Organizations
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Worldwide Pantnagar Alumni Association
President
- Present
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Craig Bradshaw
I'm excited to share the latest article from our group, authored by Shahzad Yousaf, myself, Rushikesh Kamalapurkar and Omer San. In the paper titled "A gray-box model for unitary air conditioners developed with symbolic regression" we present a new model for use in building energy modeling (BEM, e.g. Energy Plus), building controls, or equipment mapping purposes. The model uses the same inputs as typical equipment models in BEM and can be trained with as little as 5 experimental data points, which is a major advantage compared to statical models. This link will provide free access to the article until Dec. 8, 2024:
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Stefan Brenner
Unleash Your Engineering Skills with MathWorks Contests 🏆🛠️ Calling all engineers and MATLAB enthusiasts! MathWorks is hosting a series of exciting contests designed to challenge your skills and inspire innovation. Whether you're a seasoned professional or a curious learner, these contests offer a unique platform to showcase your expertise and creativity. Why Participate? 🚀 Innovative Challenges: Tackle real-world engineering problems and push the boundaries of what's possible with MATLAB and Simulink. 🧠 Skill Development: Enhance your technical skills and gain new insights through hands-on problem-solving. 🤝 Community Engagement: Connect with a global community of engineers and share ideas, solutions, and experiences. 🏅 Recognition and Rewards: Earn recognition for your work and compete for exciting prizes. Upcoming Contests: Stay tuned for announcements on upcoming contests and how you can participate. Each contest is a chance to learn, innovate, and make an impact in the engineering community. For more details and to get involved, check out the MathWorks contests page here 🔗 https://spr.ly/6049SUmT9 Join us in this journey of exploration and innovation. Let's engineer the future together! 🌟 #Engineering #MATLAB #Simulink #Innovation #Contests #SkillDevelopment #MathWorks
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Raymond Shaw
Two Michigan Technological University Physics alumni recently developed and deployed a time-gated, time-correlated, single-photon counting lidar that provides an incredibly high-resolution view of clouds. My small contribution was to help develop the theory needed to obtain an accurate estimate of cloud droplet number concentration by profiling through the base of a cloud. It’s an exciting result that gets at one of the fundamental challenges of remote cloud measurements with lidar or radar: separating the relative contributions of number and size of cloud droplets. Learn more about it in this news story… or by checking out the paper in npj Climate and Atmospheric Science (link at the end of the news story).
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ashor elmargane
3D-printing advance mitigates three defects simultaneously for failure-free metal parts University of Wisconsin-Madison engineers have found a way to simultaneously mitigate three types of defects in parts produced using a prominent additive manufacturing technique called laser powder bed fusion. Led by Lianyi Chen, an associate professor of mechanical engineering at UW-Madison, the team discovered the mechanisms and identified the processing conditions that can lead to this significant reduction in defects. The researchers detailed their findings in a paper published on November 16, 2024, in the International Journal of Machine Tools and Manufacture. "Previous research has normally focused on reducing one type of defect, but that would require the usage of other techniques to mitigate the remaining types of defects," Chen says. "Based on the mechanisms we discovered, we developed an approach that can mitigate all the defects - pores, rough surfaces and large spatters - at once. In addition, our approach allows us to produce a part much faster without any quality compromises." Multiple industries, including aerospace, medical and energy, are increasingly interested in using additive manufacturing, also known as 3D printing, to produce metal parts with complex shapes that are difficult or impossible to create using conventional methods. But the big challenge is that metal parts created with additive manufacturing have defects - like pores, or "voids," rough surfaces and large spatters - that significantly compromise the finished part's reliability and durability. These quality problems prevent 3D-printed parts from being used for critical applications where failure is not an option. By providing a path for simultaneously increasing part quality and manufacturing productivity, the UW-Madison team's advance could lead to widespread industry adoption of laser powder bed fusion. Laser powder bed fusion uses a high-energy laser beam to melt and fuse thin layers of metal powder, constructing a part layer by layer from the bottom up. In this research, the UW-Madison team used an innovative ring-shaped laser beam, provided by a leading laser company called nLight, instead of the usual Gaussian-shaped beam. The ring-shaped laser beam played a key role in this breakthrough - as did critical "in-situ" experiments, says Jiandong Yuan, the lead author of the paper and a PhD student in Chen's group. To see how the material behaved within the part as it was printing, researchers went to the Advanced Photon Source, an ultra-bright, high-energy synchrotron X-ray user facility at Argonne National Laboratory. Combining high-speed synchrotron X-ray imaging, theoretical analysis and numerical simulation, the researchers revealed the defect mitigation mechanisms, which involve phenomena that reduce instabilities in the laser powder bed fusion process.
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Jonathan Liscouët, Eng., Ph.D.
I'm pleased to share our latest open-access publication, "Physics-Based Reliability Modeling for Control Applications: Adaptive Control Allocation," in IEEE Access. https://lnkd.in/g-VjD-Tx This work presents a systematic approach to integrating physics-based reliability models within control systems. By addressing the limitations of conventional degradation models, we introduce a reliability framework that utilizes stress-derived variables, enabling real-time, physics-informed reliability assessments. Our approach is validated through simulations on a hexarotor UAV, demonstrating improved reliability predictions and adaptive workload distribution to extend system longevity. Special thanks to Joshua Desrosiers, Zac Heit, Ishimwe Uwantare, Andrew Goodchild Remoundos, and Anas Senouci for their dedicated work. #UAV #ReliabilityEngineering #PhysicsBasedModeling #AdaptiveControl #AerospaceEngineering #IEEE #Hexarotor #ControlSystems #ReliabilityModeling #UnmannedAerialVehicles #SafetyInnovation
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Remi Dingreville
Starting the 4th of July weekend with a bit of a celebration: new paper on ML-accelerated mod/sim out!💥 Materials simulations based on direct numerical solvers is the primary way we conduct computational materials research today. These solvers are accurate but computationally expensive. In this paper, we are rethinking materials simulation by blending direct numerical solvers with neural operators. This approach is based on a U-Net neural network conditioned on time. The idea is to learn the multiple dynamics occurring during the simulation via this machine-learned approach to speed up the simulation time and feed the predictions back to the direct numerical solvers to keep the error bonded and course-correct the physics from time to time. These are some of the first steps towards the future of mod/sim. Great collaboration with George Karniadakis group, notably Vivek Oommen leading the charge. More details in our open access paper here:
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Jagjit Nanda
It was a wonderful opportunity to host Prof. Yue Qi from Brown University at the joint SLAC-Stanford Battery Center, https://lnkd.in/gUhGKsTx Prof. Qi gave the Mechanics and Computation seminar at Stanford's Mechanical Engineering titled, " From Atoms to Devices --- Multiscale Modeling the Interfaces in Solid-State Batteries"
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Victor M Zavala
Just came across this excellent paper by optimization legend, Prof. Olvi Mangasarian (former professor at UW-Madison Computer Sciences), on nonlinear optimal control. I am well aware (as many others) of all the incredible contributions of Prof. Mangasarian to optimization and machine learning (e.g., MFCQ conditions, algorithms for complementarity and classification problems) but I was not aware of his work on optimal control. I have always admired the deep intellect and broad contributions of legendary researchers such as Prof. Mangasarian, simply incredible. I also recently became aware that Prof. Mangasarian worked in the chemical industry (Shell) for seven years prior to starting his academic career at UW-Madison. Some of his seminal papers (like the one below) come from his time in the chemical industry. #optimization #controls #chemicalengineering
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Gabriele Mogni
Toyota Research Institute of North America (TRINA) has partnered with Xanadu to leverage quantum computing for advancements in materials science. This collaboration aims to develop quantum algorithms for simulating and optimizing materials, especially focusing on 2D materials for quantum sensing applications. A significant part of the research involves using quantum embedding theory to enhance simulation accuracy, which is crucial for identifying materials with potential applications in energy technologies and sensors. The project underscores the potential of quantum computing in revolutionizing materials science. For more details, visit The Quantum Insider: https://lnkd.in/embCpyGh #materials #materialsscience #materialsengineering #computationalchemistry #modelling #chemistry #researchanddevelopment #research #MaterialsSquare #ComputationalChemistry #Tutorial #DFT #simulationsoftware #simulation
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Prabha Sundaravadivel
In our latest review article exploring the transformative impact of automation on environmental sensing, my co-authors (Dr. Shekhar Suman Borah, Dr. Aadi Khanal) and I provided an overview of methods and practices such as transfer learning, edge computing, sensor fusion, and robotics. These approaches contribute to overcoming traditional limitations in the spatio-temporal applications. Thanks to my co-authors for their invaluable contributions! Special thanks to Dr. Borah for leading the efforts in this article! Here is the link to our article: https://lnkd.in/gpveHDXS #EnvironmentalSensing #Automation #Technology #Innovation #EnvironmentalMonitoring #robotics #UAVs #AUVs #transferlearning #edgecomputing
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Mostafa Mobasher
Last year, I got invited to contribute a review chapter on Mechanics of Ice to Eleseviers' Comprehensive Mechanics of Materials (https://lnkd.in/gCkFiQyV) Reference work. I am glad to share this review chapter which I worked on putting together with Ravindra Duddu and Haim Waisman. The chapter as we view it, presents an overview of what someone would need to get started on modeling ice as a solid material. We cover a wide range of topics including 1-the basics (microstructure variations, testing and charecterization, strain-rate dependence) 2-mechanical constitutive models (LEFM, continuum damage, phase-field, viscoplastic) 3-applications in two main areas: a) glacier flow, ice shelf, and ice sheet modeling, b) ice and hail impact on engineering structures We also reflect on curent ongoing research, and possible extensions in the future including perspectives on the incorporation of data-science and open-source resources for researchers. Enjoy the read!
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Aliasghar Moj Arab, PhD
Humbled to share our latest research on "High-Resolution Safety Verification for Evasive Obstacle Avoidance in Autonomous Vehicles," now published in the IEEE Open Journal of Vehicular Technology. Our paper introduces a novel functional safety verification method tailored for evasive maneuvers in Autonomous Vehicles (AVs), drawing inspiration from the #ISO26262 Hazard Analysis and Risk Assessment (HARA) framework. By focusing on critical scenarios such as evasive maneuvers, our approach significantly enhances the resolution of safety assessments, thereby contributing to the advancement of safer and more sustainable autonomous transportation. This research builds upon our patented "Safe Agile Hazard Avoidance System for Autonomous Vehicles" (US20240001964A1), which revolutionizes agile safety responses in real-world AV applications. This work was a continuation of my Ph.D. research at Rutgers University which was partially funded and sponsored by National Science Foundation (NSF) and my current collaborations with North Carolina Agricultural and Technical State University and Center for Regional and Rural Connected Communities (CR2C2). Dive into the full paper here: ⇒ https://lnkd.in/eCEQNCBQ Special thanks to Dr. Milad Khaleghi, Dr. Alireza Partovi, PhD, Dr. Alireza Abbaspour, Chaitanya Shinde Dr. Yashar Mousavi, Dr. Vahid Azimi, and Prof. Ali Karimoddini for their invaluable contributions that have made this work truly unique. We also extend our gratitude to the peer reviewers and editors for their insightful comments. Excited about the opportunity to further enhance AVs safety in collaboration. Feel free to contact me at aliasghar.arab@nyu.edu or mojarab@genauto.ai to explore potential collaborations. #AutonomousVehicles #SafetyEngineering #Innovation #GeneralAutonomy #GenAuto #GenAutoAI
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David Coit
The recent IEEE Transactions on Reliability issue (vol. 73, no. 1, March 2024) commemorates the 75 year history of the journal. The paper 'The Ten Most Cited Papers From IEEE Transaction on Reliability' written by Phillip Laplante, CSDP, PE, MBA, PhD lists the papers with the most citations in the 75 year history of the journal. I am proud to be #4 on the list with my paper 'Reliability Optimization of Series-Parallel Systems Using Genetic Algorithms' by David Coit & Alice Smith (vol. 45, no. 2, 1996). In addition to #4 on the 75 year list, it is the #1 most cited paper in the last 30 years based on the paper's metrics. This paper is from the first technical chapter (and least interesting, in my opinion) from my PhD dissertation at University of Pittsburgh, and was actually written about 1994 or 1995. The paper demonstrates that the combinatorial nature of the redundancy allocation problem can be exploited to obtain superior solutions by removing constraints and restrictions on the problem structure artificially imposed by mathematicians solving the problem, as opposed to the engineers who formulated the problem. #rutgers #reliability #industrialengineering #universityofpittsburgh #reliabilityoptimization #rutgersise
2 Comments -
Madhur Behl
Our Cavalier Autonomous Racing car is tearing down the Brickyard front straight at Indianapolis Motor Speedway, and I wouldn’t blame you for thinking #autonomousracing is all about #AI. But there’s so much more to it. While deep neural networks play their crucial roles in our autonomy stack (more on this later); where the rubber truly meets the road (literally), we rely on physics-based models, Model Predictive Control, optimal control design, and non-linear state estimation. These aren’t just theoretical #robotics and #control concepts - they’re the backbone that makes the race car stable and effective on the track. It’s incredibly satisfying to see these techniques come together in real-world testing. The driving force? Our incredible students. 🎓 💪 Here are two recent research papers from our group on the subject of #vehicledynamics modeling for autonomous racing: 📄 Scalable Deep Kernel Gaussian Process for Vehicle Dynamics in Autonomous Racing - Published at CoRL 2023 🔗 https://lnkd.in/eubAWntt 📄 Deep Dynamics: Vehicle Dynamics Modeling With a Physics-Constrained Neural Network for Autonomous Racing - Published in RA-L, to be presented at IROS 2024 🔗 https://lnkd.in/eU7xqVTW UVA Engineering UVA Engineering Link Lab Indy Autonomous Challenge #autonomousvehicles #safeautonomy
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Shahria Alam
Our paper, "Seismic life-cycle cost evaluation of steel-braced frames: Comparing conventional BRBF with emerging SCVDF and HBF systems," has received the Featured Paper Award from Engineering Structures, Elsevier! A special congratulations to my former PhD student, Dr. Xin Yan, and my current Postdoc, Dr. Navid Rahgozar, for their invaluable contributions. This is a testament to their high-quality work! This research sheds light on the life-cycle economic benefits of innovative self-centering viscous energy-dissipative braced frames (SCVDFs) and hybrid braced frames (HBFs) compared to traditional buckling-restrained braced frames (BRBFs). By employing dynamic analyses and Monte Carlo simulations, we explored the impact of residual inter-story drift limits, initial construction costs, and discount rates on the economic viability of these systems. This recognition highlights the importance of advancing structural resilience while considering long-term economic impacts. #SeismicEngineering #StructuralResilience #EngineeringInnovation #FeaturedPaper #ResearchExcellence #Elsevier #ASCE #NSERC Natural Sciences and Engineering Research Council of Canada (NSERC) #UBC #UBCO #StructuralEngineering #EarthquakeEngineering #EERI
20 Comments -
Jordan Sarasan
Check out "Engineering Dynamics" by Keith Hjelmstad, designed to help engineering students master the dynamics of particles and rigid bodies. This book uses a consistent problem-solving framework and provides extensive MATLAB codes to aid in exploring and visualizing concepts. #EngineeringDynamics #MATLAB https://spr.ly/6048QFUXa
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Colleen Witzenburg
Check out Daniel Pearce’s latest paper, "Evaluation of an Inverse Method for Quantifying Spatially Variable Mechanics," published in the Journal of Biomechanical Engineering! It’s all about using a novel inverse method to get insights into spatially variable mechanics. If you love biomechanics and cutting-edge techniques, this one's for you! Head over to the official journal to dive into the details: https://lnkd.in/gbPwRMSH
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