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  1. ( , 12th National Conference on Earthquake Engineering)
    This paper investigates the effects of near-fault pulse-type ground motions on the structural response of a 3-story steel structure with nonlinear viscous dampers using the real-time hybrid simulation (RTHS) testing method. The real time loop of action and reaction between the experimental and numerical partitions executed in the RTHS enabled the accurate capturing of the velocity pulse effects of pulse-type ground motions. An ensemble of 10 natural pulse-type ground motions at the design basis earthquake (DBE) level is used for the RTHS. The accuracy of RTHS under high velocity loading is demonstrated, and thereby, is a validated method for experimentallymore »investigation of the complicated structural behavior of structures with rate-dependent damping devices. The test results showed that the dampers are essentially effective in earthquake hazard mitigation effects involving pulse-type ground motions. The average peak story drift ratio under the set of pulse-type ground motions is 1.08% radians with a COV value less than 0.3, which indicates that the investigated structure would achieve the ASCE 7-10 seismic performance objective for Occupancy Category III structures under the DBE level pulse-type ground motions.« less
    Free, publicly-accessible full text available June 1, 2023
  2. ; ; ; ; ; ; ; ; ; ; et al ( , Renewable and Sustainable Energy Reviews)
    Free, publicly-accessible full text available October 1, 2022
  3. ; ; ( , IEEE Big Data)
    Accepted Manuscript Full Text Available
  4. ; ; ; ; ( , International Conference on Computing Communication and Networking Technologies)
    In this preliminary study, we consider the server allocation problem for edge computing system deployment. Our goal is to minimize the average turnaround time of application requests/tasks, generated by all mobile devices/users in a geographical region. We consider two approaches for edge cloud deployment: the flat deployment, where all edge clouds co-locate with the base stations, and the hierarchical deployment, where edge clouds can also co-locate with other system components besides the base stations. In the flat deployment, we demonstrate that the allocation of edge cloud servers should be balanced across all the base stations, if the application request arrivalmore »rates at the base stations are equal to each other. We also show that the hierarchical deployment approach has great potentials in minimizing the system’s average turnaround time. We conduct various simulation studies using the CloudSim Plus platform to verify our theoretical results. The collective findings trough theoretical analysis and simulation results will provide useful guidance in practical edge computing system deployment.« less
    Accepted Manuscript Full Text Available
  5. ; ; ( , 17th International Refrigeration and Air Conditioning Conference at Purdue)
    Accepted Manuscript Full Text Available
  6. ; ; ; ; ; ; ; ; ; ; et al ( , Computing and Software for Big Science)
    Abstract The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hardmore »scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.« less
    Free, publicly-accessible full text available December 1, 2023
  7. ; ; ; ; ; ; ; ; ; ; et al ( , Computing and Software for Big Science)
    Abstract The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed tomore »meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.« less
    Free, publicly-accessible full text available December 1, 2023
  8. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review D)
    Free, publicly-accessible full text available May 1, 2023
  9. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review D)
    Free, publicly-accessible full text available May 1, 2023
  10. ; ; ; ; ; ; ; ; ; ; et al ( , The European Physical Journal C)
    Abstract The energy response of the ATLAS calorimeter is measured for single charged pions with transverse momentum in the range $$10more »situ single-particle measurements. The calorimeter response to single-pions is observed to be overestimated by $${\sim }2\%$$ ∼ 2 % across a large part of the $$p_{\text {T}}$$ p T spectrum in the central region and underestimated by $${\sim }4\%$$ ∼ 4 % in the endcaps in the ATLAS simulation. The uncertainties in the measurements are $${\lesssim }1\%$$ ≲ 1 % for $$15« less
    Free, publicly-accessible full text available March 1, 2023