activity
20182025
most citedStructural engineering from an inverse problems perspective

56 citations · 120 across the 10 of their papers we have counts for

collaborators

11 papers

physics.comp-ph2025

Implicit and explicit treatments of model error in numerical simulation

Danny Smyl

Numerical simulations of physical systems exhibit discrepancies arising from unmodeled physics and idealizations, as well as numerical approximation errors stemming from discretiza…

cs.LG2024★ 4 cited

Machine learning for structural design models of continuous beam systems via influence zones

Adrien Gallet, Andrew Liew, Iman Hajirasouliha +1

This work develops a machine learned structural design model for continuous beam systems from the inverse problem perspective. After demarcating between forward, optimisation and i…

eess.SY2023

Influence zones for continuous beam systems

Adrien Gallet, Andrew Liew, Iman Hajirasouliha +1

Unlike influence lines, the concept of influence zones is remarkably absent within the field of structural engineering, despite its existence in the closely related domain of geote…

cs.CV2021★ 19 cited

Investigation of condominium building collapse in Surfside, Florida: A video feature tracking approach

Xiangxiong Kong, Danny Smyl

On June 24, 2021, a 12-story condominium building (Champlain Towers South) in Surfside, Florida partially collapsed, resulting in one of the deadliest building collapses in United…

math.OC2021★ 56 cited

Structural engineering from an inverse problems perspective

Adrien Gallet, Samuel Rigby, Tyler Tallman +7

The field of structural engineering is vast, spanning areas from the design of new infrastructure to the assessment of existing infrastructure. From the onset, traditional entry-le…

math.NA2020★ 19 cited

An efficient Quasi-Newton method for nonlinear inverse problems via learned singular values

Danny Smyl, Tyler N. Tallman, Dong Liu +1

Solving complex optimization problems in engineering and the physical sciences requires repetitive computation of multi-dimensional function derivatives. Commonly, this requires co…