Graduate Studies, UNL

 

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

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First Advisor

Lily Wang

Degree Name

Doctor of Philosophy (Ph.D.)

Committee Members

Benjamin Riggan, Bruno Masiero, Josephine Lau, Xiaoyue Cheng

Department

Architectural Engineering

Date of this Version

3-30-2026

Document Type

Dissertation

Citation

A dissertation presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of requirements for the degree Doctor of Philosophy

Major: Architectural Engineering

Under the supervision of Professor Lily Wang

Lincoln, Nebraska, May 2026

Comments

Copyright 2026, Samuel Underwood. Used by permission

Abstract

Restaurants exhibit noise levels that vary with occupancy over a typical operating day. When noise levels become excessive, customer comfort is diminished. While many previous works have surveyed noise levels in restaurants over short time intervals, there has been little work to comprehensively examine noise levels over a full operating day, while also tracking occupancy levels and thoroughly measuring unoccupied acoustical parameters. This dissertation work contributes to the existing body of restaurant acoustics work by measuring unoccupied and occupied acoustical conditions in 21 restaurants in the Midwest, correlating user reviews, scores, and crowdsourced noise levels measured in 943 venues in New York City, and proposing a hybrid simulation approach to restaurant noise prediction that utilizes discrete event simulation and room acoustics simulation to predict levels across all seats in a given venue. Results suggest that restaurant noise levels vary both spatially and temporally by a practically significant margin, and that crowdsourced noise levels correlate with complaint rates in online reviews. Reviews that contained noise complaints, on average, were 1 star lower than all other online restaurant reviews. Exploration of the hybrid simulation approach in 10 case study restaurants did not indicate practically significant improvement in mean prediction accuracy compared to existing models, but the proposed method may prove useful in analyzing complex restaurant layouts. Ultimately, this dissertation establishes a foundation for future work related to auditory accessibility in restaurants.

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