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A Rising Tide: Oyster Aquaculture Survey Results, Natalie Lord, Catherine M. Ashcraft, Lindsey Williams, Julia Novak-Colwell Jan 2023

A Rising Tide: Oyster Aquaculture Survey Results, Natalie Lord, Catherine M. Ashcraft, Lindsey Williams, Julia Novak-Colwell

Faculty Publications

This document provides the results from a survey conducted August-October 2021 on the Maine and New Hampshire oyster aquaculture industry. The purpose of the survey was to gain a food system-wide perspective on gender dynamics in the region’s aquaculture industry, inclusive of different genders and identify potential gender-based barriers and opportunities to participation for men, women, and non-binary/third gender oyster aquaculturists. The published survey results include qualitative responses and demographic data for a subset of farmers in the oyster aquaculture industry of Maine and New Hampshire.

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Dataset For Effects Of Single-Session Practice Structure On Motor Skill Acquisition And Alpha And Beta Eeg Oscillations, Audrey Porter, Ronald V. Croce, Wayne Smith Jan 2023

Dataset For Effects Of Single-Session Practice Structure On Motor Skill Acquisition And Alpha And Beta Eeg Oscillations, Audrey Porter, Ronald V. Croce, Wayne Smith

Faculty Publications

Although it is known that practicing a motor skill updates the associated internal model, it is still unclear as to how cortical oscillations linked with the motor skill change under differing practice schedules. The current study investigated α- and β-power changes associated with motor skill acquisition. Firstly, we investigated the behavioral effects of practice on motor learning and retention during repetitive (RP) and variable (VP) practice schedules on an anticipation timing task. Secondly, we investigated changes in cortical α (10-13 HZ) and β (15-30 Hz) event-related synchronization and dyssynchronization (ERS/ERD) under RP and VP during early (EP) and late …

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Learning Infused Quantum-Classical Distributed Optimization Technique For Power Generation Scheduling, Reza Mahroo, Amin Kargarian Jan 2023

Learning Infused Quantum-Classical Distributed Optimization Technique For Power Generation Scheduling, Reza Mahroo, Amin Kargarian

Faculty Publications

The advent of quantum computing can potentially revolutionize how complex problems are solved. This article proposes a two-loop quantum-classical solution algorithm for generation scheduling by infusing quantum computing, machine learning, and distributed optimization. The aim is to facilitate employing noisy near-term quantum machines with a limited number of qubits to solve practical power system optimization problems, such as generation scheduling. The outer loop is a three-block quantum alternating direction method of multipliers (QADMM) algorithm that decomposes the generation scheduling problem into three subproblems, including one quadratically unconstrained binary optimization (QUBO) and two non-QUBOs. The inner loop is a trainable quantum …

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Interfacial Activity And Surface Pka Of Perfluoroalkyl Carboxylic Acids (Pfcas), Ruchi Patel, Luis E. Saab, Philip J. Brahana, Kalliat T. Valsaraj, Bhuvnesh Bharti Jan 2023

Interfacial Activity And Surface Pka Of Perfluoroalkyl Carboxylic Acids (Pfcas), Ruchi Patel, Luis E. Saab, Philip J. Brahana, Kalliat T. Valsaraj, Bhuvnesh Bharti

Faculty Publications

Perfluoroalkyl carboxylic acids (PFCAs) are widely used synthetic chemicals that are known for their exceptional stability and interfacial activity. Despite their industrial and environmental significance, discrepancies exist in the reported pKa values for PFCAs, often spanning three to four units. These disparities stem from an incomplete understanding of how pH influences the ionized state of PFCA molecules in the bulk solution and at the air-water interface. Using pH titration and surface tension measurements, we show that the pKa values of the PFCAs adsorbed at the air-water interface differ from the bulk. Below the equivalence point, the undissociated and dissociated forms …

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Multifunctional Composite With Hybrid Carbon Fiber And Carbonaceous Coconut Particle Reinforcement, Foster Feni, Maryam Jahan, Rong Zhao, Guoqiang Li, Guang Lin Zhao, Patrick F. Mensah Jan 2023

Multifunctional Composite With Hybrid Carbon Fiber And Carbonaceous Coconut Particle Reinforcement, Foster Feni, Maryam Jahan, Rong Zhao, Guoqiang Li, Guang Lin Zhao, Patrick F. Mensah

Faculty Publications

The utilization of multifunctional composite materials presents significant advantages in terms of system efficiency, cost-effectiveness, and miniaturization, making them highly valuable for a wide range of industrial applications. One approach to harness the multifunctionality of carbon fiber reinforced polymer (CFRP) is to integrate it with a secondary material to form a hybrid composite. In our previous research, we explored the use of carbonaceous material derived from coconut shells as a sustainable alternative to inorganic fillers, aiming to enhance the out-of-plane mechanical performance of CFRP. In this study, our focus is to investigate the influence of carbonized coconut shell particles on …

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Editorial: Application Of Periodic Structure Theory With Finite Element Approach, Chitaranjan Pany, Guoqiang Li Jan 2023

Editorial: Application Of Periodic Structure Theory With Finite Element Approach, Chitaranjan Pany, Guoqiang Li

Faculty Publications

No abstract provided.

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Toward The Development Of Plasticity Theories For Application To Small-Scale Metal Structures, Bin Zhang, K. L. Nielsen, J. W. Hutchinson, W. J. Meng Jan 2023

Toward The Development Of Plasticity Theories For Application To Small-Scale Metal Structures, Bin Zhang, K. L. Nielsen, J. W. Hutchinson, W. J. Meng

Faculty Publications

Experiments are performed on micron-scale single-crystal prototypical structural elements experiencing combined torsion and bending to gather data on their load-carrying capacity in the range of size and strain relevant to micron-scale structures for which little data are available. The observed strengthening dependence on size for the structural elements is in general accord with trends inferred from prior tests such as indentation and pure torsion. In addition, the experiments systematically reveal the strengthening size-dependence of structural elements whose surface has been passivated by a very thin Cr coating, an effect shown to have substantial strengthening potential. A state-of-the-art strain gradient plasticity …

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Study On Soft Robotic Pinniped Locomotion, Dimuthu D.K. Arachchige, Tanmay Varshney, Umer Huzaifa, Iyad Kanj, Thrishantha Nanayakkara, Yue Chen, Hunter B. Gilbert, Isuru S. Godage Jan 2023

Study On Soft Robotic Pinniped Locomotion, Dimuthu D.K. Arachchige, Tanmay Varshney, Umer Huzaifa, Iyad Kanj, Thrishantha Nanayakkara, Yue Chen, Hunter B. Gilbert, Isuru S. Godage

Faculty Publications

Legged locomotion is a highly promising but under-researched subfield within the field of soft robotics. The compliant limbs of soft-limbed robots offer numerous benefits, including the ability to regulate impacts, tolerate falls, and navigate through tight spaces. These robots have the potential to be used for various applications, such as search and rescue, inspection, surveillance, and more. The state-of-the-art still faces many challenges, including limited degrees of freedom, a lack of diversity in gait trajectories, insufficient limb dexterity, and limited payload capabilities. To address these challenges, we develop a modular soft-limbed robot that can mimic the locomotion of pinnipeds. By …

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Dynamic Modeling And Validation Of Soft Robotic Snake Locomotion, Dimuthu D.K. Arachchige, Sanjaya Mallikarachchi, Iyad Kanj, Dulanjana M. Perera, Yue Chen, Hunter B. Gilbert, Isuru S. Godage Jan 2023

Dynamic Modeling And Validation Of Soft Robotic Snake Locomotion, Dimuthu D.K. Arachchige, Sanjaya Mallikarachchi, Iyad Kanj, Dulanjana M. Perera, Yue Chen, Hunter B. Gilbert, Isuru S. Godage

Faculty Publications

Soft robotic snakes made of compliant materials can continuously deform their bodies and, therefore, mimic the biological snakes' flexible and agile locomotion gaits better than their rigid-bodied counterparts. Without wheel support, to date, soft robotic snakes are limited to emulating planar locomotion gaits, which are derived via kinematic modeling and tested on robotic prototypes. Given that the snake locomotion results from the reaction forces due to the distributed contact between their skin and the ground, it is essential to investigate the locomotion gaits through efficient dynamic models capable of accommodating distributed contact forces. We present a complete spatial dynamic model …

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The Potential Benefit Of Pseudo High Thermal Conductivity For Laser Powder Bed Fusion Additive Manufacturing, Huan Ding, Selami Emanet, Yehong Chen, Shengmin Guo Jan 2023

The Potential Benefit Of Pseudo High Thermal Conductivity For Laser Powder Bed Fusion Additive Manufacturing, Huan Ding, Selami Emanet, Yehong Chen, Shengmin Guo

Faculty Publications

This study examined the impact of transient pseudo high thermal conductivity to the fabrication of crack-free parts with Laser Powder-Bed-Fusion (L-PBF) based additive manufacturing (AM) method. Thermal diffusivity and thermal conductivity of L-PBF samples made by mixtures of IN939 alloy and Si powders were investigated. At temperatures above 800°C, the as-fabricated Si-doped IN939 was observed to exhibit an exceptionally high thermal conductivity, which can be attributed to the occurrence of endothermic reactions. This pseudo high thermal conductivity can effectively minimize the thermal stress and offers a potential solution to produce crack-free L-PBF parts for nonweldable alloys.

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Optimizing Pier Design To Mitigate Scour: A Comprehensive Review And Large Eddy Simulation Study, A. M. Aly, F. Khaled Jan 2023

Optimizing Pier Design To Mitigate Scour: A Comprehensive Review And Large Eddy Simulation Study, A. M. Aly, F. Khaled

Faculty Publications

Scour-induced sediment erosion poses a significant threat to the safety and longevity of infrastructure, including bridges, wind turbines, elevated buildings, and coastal infrastructure. Despite the well-known destructive consequences of scour, accurate models that capture the complexity of its dynamics remain elusive, impeding the development of effective countermeasures. We provide a comprehensive review of existing literature on scour dynamics and examine the fluid dynamics and bed shear stress surrounding bridge piers. We propose CFD (Computational Fluid Dynamics) simulations with LES (Large-Eddy Simulation). The current paper demonstrate that LES is a more effective technique than RANS (Reynolds averaged Navier-Stokes) for investigating bridge …

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Show Us The Data: Global Covid-19 Wastewater Monitoring Efforts, Equity, And Gaps, Colleen C. Naughton, Fernando A. Roman, Ana Grace F. Alvarado, Arianna Q. Tariqi, Matthew A. Deeming, Krystin F. Kadonsky, Kyle Bibby, Aaron Bivins, Gertjan Medema, Warish Ahmed, Panagis Katsivelis, Vajra Allan, Ryan Sinclair, Joan B. Rose Jan 2023

Show Us The Data: Global Covid-19 Wastewater Monitoring Efforts, Equity, And Gaps, Colleen C. Naughton, Fernando A. Roman, Ana Grace F. Alvarado, Arianna Q. Tariqi, Matthew A. Deeming, Krystin F. Kadonsky, Kyle Bibby, Aaron Bivins, Gertjan Medema, Warish Ahmed, Panagis Katsivelis, Vajra Allan, Ryan Sinclair, Joan B. Rose

Faculty Publications

A year since the declaration of the global coronavirus disease 2019 (COVID-19) pandemic, there were over 110 million cases and 2.5 million deaths. Learning from methods to track community spread of other viruses such as poliovirus, environmental virologists and those in the wastewater-based epidemiology (WBE) field quickly adapted their existing methods to detect SARS-CoV-2 RNA in wastewater. Unlike COVID-19 case and mortality data, there was not a global dashboard to track wastewater monitoring of SARS-CoV-2 RNA worldwide. This study provides a 1-year review of the “COVIDPoops19” global dashboard of universities, sites, and countries monitoring SARS-CoV-2 RNA in wastewater. Methods to …

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Aircraft Wastewater Surveillance For Early Detection Of Sars-Cov-2 Variants — John F. Kennedy International Airport, New York City, August–September 2022, Robert C. Morfino, Stephen M. Bart, Andrew Franklin, Benjamin H. Rome, Andrew P. Rothstein, Thomas W.S. Aichele, Siyao Lisa Li, Aaron Bivins, Ezra T. Ernst, Cindy R. Friedman Jan 2023

Aircraft Wastewater Surveillance For Early Detection Of Sars-Cov-2 Variants — John F. Kennedy International Airport, New York City, August–September 2022, Robert C. Morfino, Stephen M. Bart, Andrew Franklin, Benjamin H. Rome, Andrew P. Rothstein, Thomas W.S. Aichele, Siyao Lisa Li, Aaron Bivins, Ezra T. Ernst, Cindy R. Friedman

Faculty Publications

No abstract provided.

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Machine Learning Approach For Predicting Bridge Components’ Condition Ratings, Md Manik Mia, Sabarethinam Kameshwar Jan 2023

Machine Learning Approach For Predicting Bridge Components’ Condition Ratings, Md Manik Mia, Sabarethinam Kameshwar

Faculty Publications

Information on bridge condition rating is critical to make decisions regarding rehabilitation or replacement of bridges. Currently, bridge components’ condition ratings are evaluated manually using inspection reports. Markov chain and Petri net models are most commonly used for predicting future values of bridge parameters, however, applicability of these models for a regional or statewide portfolio of bridges may be limited. The existing data based models have low prediction accuracy. Hence, a data and machine learning based approach is presented herein for predicting the future condition values of major components—deck, superstructure and substructure—in a portfolio of bridges with an objective to …

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Semi-Parametric Control Architecture For Autonomous Underwater Vehicles Subject To Time Delays, Ignacio Carlucho, Dylan Stephens, William Ard, Corina Barbalata Jan 2023

Semi-Parametric Control Architecture For Autonomous Underwater Vehicles Subject To Time Delays, Ignacio Carlucho, Dylan Stephens, William Ard, Corina Barbalata

Faculty Publications

This paper presents a data-driven model-based control system for autonomous underwater vehicles (or AUVs) subject to input delays. This work is motivated by the input time delays that can arise in underwater robotics due to communication restrictions and sensor malfunctions. Such delays can highly degrade the performance of classical control structures resulting in unpredictable system behaviours. The proposed control architecture addresses such limitations. The approach incorporates a linear dynamic representation of the system obtained using the Koopman operator in an observer/state prediction formulation. The proposed control architecture is designed based on discrepancies between the data-driven estimation of the system's behaviour …

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Event-Triggered Control Under Unknown Input And Unknown Measurement Delays Using Interval Observers, Michael Malisoff, Frederic Mazenc, Corina Barbalata Jan 2023

Event-Triggered Control Under Unknown Input And Unknown Measurement Delays Using Interval Observers, Michael Malisoff, Frederic Mazenc, Corina Barbalata

Faculty Publications

We provide a new input-to-state stabilizing event-triggered feedback design for linear systems with unknown input delays, unknown measurement delays, and unknown additive disturbances. Our trigger times are computed using only the matrices defining the system and time-lagged sampled state values. We use the theory of positive systems, interval observers, and a vector version of Halanay's inequality. We illustrate our method using a marine robotic model.

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Personalized Federated Deep Reinforcement Learning-Based Trajectory Optimization For Multi-Uav Assisted Edge Computing, Zhengrong Song, Chuan Ma, Ming Ding, Howard H. Yang, Yuwen Qian, Xiangwei Zhou Jan 2023

Personalized Federated Deep Reinforcement Learning-Based Trajectory Optimization For Multi-Uav Assisted Edge Computing, Zhengrong Song, Chuan Ma, Ming Ding, Howard H. Yang, Yuwen Qian, Xiangwei Zhou

Faculty Publications

In the era of 5G mobile communication, there has been a significant surge in research focused on unmanned aerial vehicles (UAVs) and mobile edge computing technology. UAVs can serve as intelligent servers in edge computing environments, optimizing their flight trajectories to maximize communication system throughput. Deep reinforcement learning (DRL)-based trajectory optimization algorithms may suffer from poor training performance due to intricate terrain features and inadequate training data. To overcome this limitation, some studies have proposed leveraging federated learning (FL) to mitigate the data isolation problem and expedite convergence. Nevertheless, the efficacy of global FL models can be negatively impacted by …

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Ransomware Detection Using Federated Learning With Imbalanced Datasets, A. Vehabovic, H. Zanddizari, N. Ghani, G. Javidi, S. Uluagac, M. Rahouti, E. Bou-Harb, M. Safaei Pour Jan 2023

Ransomware Detection Using Federated Learning With Imbalanced Datasets, A. Vehabovic, H. Zanddizari, N. Ghani, G. Javidi, S. Uluagac, M. Rahouti, E. Bou-Harb, M. Safaei Pour

Faculty Publications

Ransomware is a type of malware which encrypts user data and extorts payments in return for the decryption keys. This cyberthreat is one of the most serious challenges facing organizations today and has already caused immense financial damage. As a result, many researchers have been developing techniques to counter ransomware. Recently, the federated learning (FL) approach has also been applied for ransomware analysis, allowing corporations to achieve scalable, effective detection and attribution without having to share their private data. However, in reality there is much variation in the quantity and composition of ransomware data collected across multiple FL client sites/regions. …

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Simulating Stellar Merger Using Hpx/Kokkos On A64fx On Supercomputer Fugaku, Patrick Diehl, Gregor Dais, Kevin Huck, Dominic Marcello, Sagiv Shiber, Hartmut Kaiser, Dirk Pfluger Jan 2023

Simulating Stellar Merger Using Hpx/Kokkos On A64fx On Supercomputer Fugaku, Patrick Diehl, Gregor Dais, Kevin Huck, Dominic Marcello, Sagiv Shiber, Hartmut Kaiser, Dirk Pfluger

Faculty Publications

The increasing availability of machines relying on non-GPU architectures, such as ARM A64FX in high-performance computing, provides a set of interesting challenges to application developers. In addition to requiring code portability across different parallelization schemes, programs targeting these architectures have to be highly adaptable in terms of compute kernel sizes to accommodate different execution characteristics for various heterogeneous workloads. In this paper, we demonstrate an approach to code and performance portability that is based entirely on established standards in the industry. In addition to applying Kokkos as an abstraction over the execution of compute kernels on different heterogeneous execution environments, …

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Traveler: Navigating Task Parallel Traces For Performance Analysis, Sayef Azad Sakin, Alex Bigelow, R. Tohid, Connor Scully-Allison, Carlos Scheidegger, Steven R. Brandt, Christopher Taylor, Kevin A. Huck, Hartmut Kaiser, Katherine E. Isaacs Jan 2023

Traveler: Navigating Task Parallel Traces For Performance Analysis, Sayef Azad Sakin, Alex Bigelow, R. Tohid, Connor Scully-Allison, Carlos Scheidegger, Steven R. Brandt, Christopher Taylor, Kevin A. Huck, Hartmut Kaiser, Katherine E. Isaacs

Faculty Publications

Understanding the behavior of software in execution is a key step in identifying and fixing performance issues. This is especially important in high performance computing contexts where even minor performance tweaks can translate into large savings in terms of computational resource use. To aid performance analysis, developers may collect an execution trace - a chronological log of program activity during execution. As traces represent the full history, developers can discover a wide array of possibly previously unknown performance issues, making them an important artifact for exploratory performance analysis. However, interactive trace visualization is difficult due to issues of data size …

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Improving Social Media Use For Disaster Resilience: Challenges And Strategies, Nina S.N. Lam, Michelle Meyer, Margaret Reams, Seungwon Yang, Kisung Lee, Lei Zou, Volodymyr Mihunov, Kejin Wang, Ryan Kirby, Heng Cai Jan 2023

Improving Social Media Use For Disaster Resilience: Challenges And Strategies, Nina S.N. Lam, Michelle Meyer, Margaret Reams, Seungwon Yang, Kisung Lee, Lei Zou, Volodymyr Mihunov, Kejin Wang, Ryan Kirby, Heng Cai

Faculty Publications

This paper develops a social media-disaster resilience analysis framework by categorizing types of social media use and their challenges to better understand and assess its role in disaster resilience research and management. The framework is derived primarily from several case studies of Twitter use in three hurricane events in the United States–Hurricanes Isaac, Sandy, and Harvey. The paper first outlines four major contributions of social media data for disaster resilience research and management, which include serving as an effective communication platform, providing ground truth information for emergency response and rescue operations, providing information on people’s sentiments, and allowing predictive modeling. …

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Achieving Online And Scalable Information Integrity By Harnessing Social Spam Correlations, Hailu Xu, Pinchao Liu, Boyuan Guan, Qingyang Wang, Dilma Da Silva, Liting Hu Jan 2023

Achieving Online And Scalable Information Integrity By Harnessing Social Spam Correlations, Hailu Xu, Pinchao Liu, Boyuan Guan, Qingyang Wang, Dilma Da Silva, Liting Hu

Faculty Publications

Malicious web links, social rumors, fraudulent advertisements, faked comments, and biased propaganda are overwhelmingly influencing online social networks. Enabling information integrity is a hot topic in both academia and industry. Traditional social spam detection techniques rely on centralized processing, focusing only on one specific set of data sources, thereby ignoring the social spam correlations between distributed data sources. In this paper, we propose an online and scalable misinformation detection system, named Spiral, to uncover social spam by leveraging the correlations between different social data sources in geo-distributed sites. The key insight in our approach is to amplify the effectiveness of …

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John Lewis And The Politics Of Love: Book Review, Neil Fulton Jan 2023

John Lewis And The Politics Of Love: Book Review, Neil Fulton

Faculty Publications

No abstract provided.

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Making South Dakota History: An Introduction To The Special Impeachment Issue, Hannah Haksgaard, Tyler Moore, Gabrielle Unruh Jan 2023

Making South Dakota History: An Introduction To The Special Impeachment Issue, Hannah Haksgaard, Tyler Moore, Gabrielle Unruh

Faculty Publications

In September 2020, South Dakota’s Attorney General Jason Ravnsborg was driving on a rural highway when he struck and killed a pedestrian. After pleading guilty to two criminal misdemeanors, Ravnsborg was impeached, convicted, removed from state office, and barred from holding it again. This was South Dakota’s first impeachment of a constitutional officer. To chronicle this historic first, the South Dakota Law Review is publishing a special issue containing ten essays authored by those directly involved with the impeachment. This essay introduces the special issue by describing the factual and procedural background for Ravnsborg’s impeachment, providing a brief summary of …

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"To An Athlete Dying Young": For Tom Horton (May 9, 1955 - November 15, 2022), Frank Pommersheim Jan 2023

"To An Athlete Dying Young": For Tom Horton (May 9, 1955 - November 15, 2022), Frank Pommersheim

Faculty Publications

No abstract provided.

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The Trial Of Thomas More - Robert Bolt's A Man For All Seasons, Jonathan Van Patten Jan 2023

The Trial Of Thomas More - Robert Bolt's A Man For All Seasons, Jonathan Van Patten

Faculty Publications

The path from Magna Carta to the United States Constitution and the Bill of Rights runs through the trial of Thomas More. Robert Bolt's magnificent portrayal of that trial in A Man for All Seasons provides an opportunity to learn and reflect on how a political trial can teach us about the meaning of justice. The search for universals must be rooted in the particulars. The particulars in this case will also resonate with modern audiences who seek to understand their own politics in times of crisis.

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Historical Global And Regional Spatiotemporal Patterns In Daily Temperature, Md Adilur Rahim, Robert V. Rohli, Rubayet Bin Mostafiz, Nazla Bushra, Carol J. Friedland Jan 2023

Historical Global And Regional Spatiotemporal Patterns In Daily Temperature, Md Adilur Rahim, Robert V. Rohli, Rubayet Bin Mostafiz, Nazla Bushra, Carol J. Friedland

Faculty Publications

The abrupt increase in surface air temperature over the last few decades has received abundant scholarly and popular attention. However, less attention has focused on the specific nature of the warming spatially and seasonally, using high-resolution reanalysis output based on historical temperature observations. This research uses the European Centre for Medium-range Weather Forecasts (ECMWF) Reanalysis Version 5 (ERA5) output to identify spatiotemporal features of daily mean surface air temperature, defined both as the mean of the maximum and minimum temperatures over the calendar day (“meanmaxmin”) and as the mean of the 24 hourly observations per day (“meanhourly”), across the terrestrial …

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Analytical Advances In Homeowner Flood Risk Quantification Considering Insurance, Building Replacement Value, And Freeboard, Md Adilur Rahim, Rubayet Bin Mostafiz, Carol J. Friedland, Robert V. Rohli, Nazla Bushra Jan 2023

Analytical Advances In Homeowner Flood Risk Quantification Considering Insurance, Building Replacement Value, And Freeboard, Md Adilur Rahim, Rubayet Bin Mostafiz, Carol J. Friedland, Robert V. Rohli, Nazla Bushra

Faculty Publications

An accurate economic loss assessment for natural hazards is vital for planning, mitigation, and actuarial purposes. The widespread and costly nature of flood hazards, with the economically disadvantaged disproportionately victimized population, makes flood risk assessment particularly important. Here, flood risk is assessed as incurred by the homeowner vs. the flood insurer for insured U.S. properties through the derivation of average annual loss (AAL). AAL is estimated and partitioned using Monte Carlo simulation at the individual home scale, considering insurance coverage and deductible, and the first-floor height (i.e., height of the first floor above the ground), to determine the AAL proportion …

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Freeboard Life-Cycle Benefit-Cost Analysis Of A Rental Single-Family Residence For Landlord, Tenant, And Insurer, Ehab Gnan, Rubayet Bin Mostafiz, Md Adilur Rahim, Carol J. Friedland, Robert V. Rohli, Arash Taghinezhad, Ayat Al Assi Jan 2023

Freeboard Life-Cycle Benefit-Cost Analysis Of A Rental Single-Family Residence For Landlord, Tenant, And Insurer, Ehab Gnan, Rubayet Bin Mostafiz, Md Adilur Rahim, Carol J. Friedland, Robert V. Rohli, Arash Taghinezhad, Ayat Al Assi

Faculty Publications

Flood risk to single-family rental housing remains poorly understood, leaving a large and increasing population underinformed to protect themselves, including regarding insurance. This research introduces a life-cycle benefit-cost analysis for the landlord, tenant, and insurer [i.e., (U.S.) National Flood Insurance Program (NFIP)] to optimize freeboard [i.e., additional first-floor height above the base flood elevation (BFE)] selection for a rental single-family home. Flood insurance premium; apportioned flood risk among the landlord, tenant, and NFIP by insurance coverage and deductible; rental loss; moving and displacement costs; freeboard construction cost; and rent increase upon freeboard implementation are considered in estimating net benefit (NB) …

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Flood Damage And Shutdown Times For Industrial Process Facilities: A Vulnerability Assessment Process Framework, Carol J. Friedland, Fatemeh Orooji, Ayat Al Assi, Matthew L. Flynn, Rubayet Bin Mostafiz Jan 2023

Flood Damage And Shutdown Times For Industrial Process Facilities: A Vulnerability Assessment Process Framework, Carol J. Friedland, Fatemeh Orooji, Ayat Al Assi, Matthew L. Flynn, Rubayet Bin Mostafiz

Faculty Publications

Much of the U.S. petrochemical infrastructure is heavily concentrated along the western coast of the Gulf of Mexico within the impact zone of major tropical cyclone events. Flood impacts of recent tropical disturbances have been exacerbated by an overall lack of recognition of the vulnerabilities to process systems from water intrusion, as well as insufficient disaster mitigation planning. Vulnerability assessment methods currently call for the aggregation of qualitative data to survey the susceptibility of industrial systems to floodwater damage. A means to quantify these consequences is less often employed, resulting in a poor translation of the threat of flood hazards …

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