Synthesis and Characterization of β-Cyclodextrin Polymers

Cyclodextrin polymers (CDPs) are water Joluble polymers composed of either a, fl, or y cyclodextrin (CDl monomers. TI,ese commercially available polymers are synthesized ming epichlorohydrin and consist of CD monomers joined by repeating glycer;l linkers (-(CH2-CHOH-CH2-ln) with an average n value of 12-15. GPC analysis of these polymers indicate two major component peaks that have molecular weights (MW) of 2,000 (one CD/ polymer chain) and 9-10,000 (4-5 CDs/polymer chain). These polymers have been used to study the binding interactions of various fluorescence probes. It has been shown that the pyrene fluorescence lifetime increases and its emission I/III ratio decreases in the hydrophobic CD c.avity. In addition, it has been reported that pyrene exists in a more open, hydrophilic environment when bound to the CDPs than that observed with the CDs. We have used these fluorescence properties to study the binding of pyrene to our synthesized fl-CDPs with shorter linker units. We have shown that as the MW of the synthesized fl-CDPs increases (increase in length of linker units), the pyrene I/III increases and the fluorescence lifetime decreases, indicating a more hydrophilic environment. Competitive experiments involving both fl-CD and commercial fl-CDP indicate that pyrene has a strong affinity for the commercial fl-CDP despite the enhanced hydrophobic environment when complexed with fl-CD. We have calculated a K value for the 1:1 fl-CDP:pyrene complex t\u3c\u27 be 1.9 x 103 using competitive binding experiments

Simulating interacting multiple natural-hazard events for lifecycle consequence analysis

Among different types of natural-hazard interactions (simply multi-hazard interactions hereinafter), some occur through the nature of the hazards themselves, regardless of the presence of any physical assets: they are often called ﾓLevel Iﾔ (or occurrence) interactions. In such cases, one hazard event triggers or modifies the occurrence of another (e.g., severe wind and flooding; liquefaction and landslides triggered by an earthquake), thus creating a dependency between the parameters characterising such hazard events. They differ from ﾓLevel IIﾔ (or consequence) interactions, which instead occur through impacts/consequences on physical assets/components and systems (e.g., accumulation of physical damage or social impact due to earthquake sequences, landslides due to the earthquake-induced collapse of a retaining structure). Multi-hazard Life Cycle Analysis (LCA) aims to quantify the consequences (e.g., repair costs, downtime, and casualty rates) expected throughout a systemﾒs service life, accounting for both Level I and Level II interactions. Nevertheless, the available literature generally considers these interactions mainly defining relevant taxonomies, often qualitatively, without providing a computational framework to simulate a sequence of hazard events in terms of their occurrence times and features and resulting consequences. This paper aims to partly fill this gap by identifying modelling approaches associated with different Level I interactions. It describes a simulation-based approach for generating multi-hazard scenarios (i.e., a sequence of hazard events and associated features through the systemﾒs life cycle) based on the theory of competing Poisson processes. The proposed approach incorporates the different types of interactions in a sequential Monte Carlo sampling method. The method outputs potential sequences of events throughout a systemﾒs life cycle, which can be integrated into LCA frameworks to quantify interacting hazard consequences. A simple application is presented to illustrate the potential of the proposed method.

A Markovian framework for multi-hazard life-cycle consequence analysis of deteriorating structural systems

Multiple-hazard (or simply multi-hazard) interactions are either disregarded or addressed inadequately in most existing computational risk modelling frameworks for natural hazards, leading to inaccurate life-cycle consequence estimates. This, in turn, can lead to ineffective risk-informed decisionmaking for disaster-mitigation strategies and/or resilience-enhancing policies. Probabilistic multi-hazard life-cycle consequence (LCCon) analysis (e.g., assessment of repair costs, downtime, and casualties over an asset’s service life) enables optimal life-cycle management of critical assets under uncertainties. However, despite recent advances, most available LCCon formulations fail to accurately incorporate the damage-accumulation effects due to incomplete (or absent) repairs in between different hazard events. This paper introduces a Markovian framework for efficient multi-hazard LCCon analysis of deteriorating structural systems, appropriately accounting for complex interactions between hazards and their effects on a system’s performance. The proposed framework can be used to test various risk management and adaptation pathways. Specifically, the Markovian assumption is used to model the probability of a system being in any performance level (e.g., damage or functionality state) after multiple hazards inducing either “shock deterioration” or “gradual deterioration”, as well as after potential repair actions given such deteriorating processes. The expected LCCon estimates are then obtained by combining the performance level distribution with suitable system-level consequence models. The proposed framework is illustrated for a case-study reinforced concrete building considering earthquake-induced ground motions and environmentally-induced corrosion deterioration during its service life

A Markovian framework to model life-cycle consequences of infrastructure systems in a multi-hazard environment

Existing frameworks for multi-hazard life-cycle consequence (LCCon) analysis typically disregard the interactions between multiple hazards and obtain the total LCCon as the sum of the consequences caused by the individual hazards modelled independently. This practice leads to inaccurate life-cycle consequence estimates and ineffective risk-informed decision-making for disaster-mitigation strategies and/or resilience-enhancing policies. In addition, most available LCCon formulations fail to accurately incorporate the damage-accumulation effects due to incomplete (or absent) repairs between different hazard events. To address these challenges, this paper introduces a Markovian framework for efficient multi-hazard LCCon analysis of deteriorating structural systems, appropriately accounting for complex interactions between hazards and their effects on a system’s performance. The changes in the system’s performance level (e.g., damage or functionality state) are quantified with transition probability matrices following the Markovian assumption and the expected LCCon estimates are obtained by combining the performance level distribution with suitable system-level consequence models, which can include direct asset losses as well as socio-economic consequences. To showcase the framework applicability, a simple road network with a single case-study ordinary reinforced concrete bridge subject to earthquake-induced ground motions and environmentally-induced corrosion deterioration is investigated, estimating consequences in terms of community welfare loss

Seismic Fragility Analysis of Deteriorating Reinforced Concrete Buildings from a Life-Cycle Perspective

Structural systems in seismically-active regions typically undergo multiple ground-motion sequences during their service life (including multiple mainshocks, mainshocks triggering other earthquakes on nearby fault segments, mainshock-aftershock, and aftershock-aftershock sequences). These successive ground motions can lead to severe structural/non-structural damage and significant direct/indirect earthquake-induced losses. Nevertheless, the effects of a pre-damaged state during ground-motion sequences are often neglected in assessing structural performance. Additionally, environmentally-induced deterioration mechanisms may exacerbate the consequences of such groundmotion sequences during the structural system’s designed lifetime. Yet, such combined effects are commonly overlooked. This paper proposes an end-to-end computational methodology to derive timeand state-dependent fragility relationships (i.e., explicitly depending on time and the damage state achieved by a system during a first shock) for structural systems subjected to chloride-induced corrosion deterioration and earthquake-induced ground-motion sequences. To this aim, a vector-valued probabilistic seismic demand model is developed. Such a model relates the dissipated hysteretic energy in the ground-motion sequence to the maximum inter-storey drift induced by the first shock and the intensity measure of the second shock for a given corrosion deterioration level. Moreover, a vectorvalued generalised logistic model is developed to estimate the probability of collapse, conditioning on the same parameters as above. An appropriate chloride-penetration model is then used to model the timevarying evolution of fragility relationships’ parameters using a plain Monte-Carlo approach, capturing the continuous nature of the deterioration processes (i.e., gradual and shock deterioration). The significant impact of such a multi-hazard threat on structural fragility is demonstrated by utilising a casestudy reinforced concrete building. Due to deteriorating effects, reductions up to 33.3% can be noticed in the fragility median values

Simulating multi-hazard event sets for life cycle consequence analysis

In the context of natural hazard risk quantification and modeling of hazard interactions, some literature separates “Level I” (or occurrence) interactions from “Level II” (or consequence) interactions. The Level I interactions occur inherently due to the nature of the hazards, independently of the presence of physical assets. In such cases, one hazard event triggers or modifies the occurrence of another (e.g., flooding due to heavy rain, liquefaction and landslides triggered by an earthquake), thus creating a dependency between the features characterizing such hazard events. They differ from Level II interactions, which instead occur through impacts/consequences on physical assets/components and systems (e.g., accumulation of physical damage or social impacts due to earthquake sequences, landslides due to the earthquake-induced collapse of a retaining structure). Multi-hazard life cycle consequence (LCCon) analysis aims to quantify the consequences (e.g., repair costs, downtime, casualty rates) throughout a system’s service life and should account for both Level I and II interactions. The available literature generally considers Level I interactions – the focus of this study – mainly defining relevant taxonomies, often qualitatively, without providing a computational framework to simulate a sequence of hazard events incorporating the identified interrelations among them. This paper addresses this gap, proposing modeling approaches associated with different types of Level I interactions. It describes a simulation-based method for generating multi-hazard event sets (i.e., a sequence of hazard events and associated features throughout the system’s life cycle) based on the theory of competing Poisson processes. The proposed approach incorporates the different types of interactions in a sequential Monte Carlo sampling method. The method outputs multi-hazard event sets that can be integrated into LCCon frameworks to quantify interacting hazard consequences. An application incorporating several hazard interactions is presented to illustrate the potential of the proposed method.</p

Developing and Deploying Security Applications for In-Vehicle Networks

Radiological material transportation is primarily facilitated by heavy-duty on-road vehicles. Modern vehicles have dozens of electronic control units or ECUs, which are small, embedded computers that communicate with sensors and each other for vehicle functionality. ECUs use a standardized network architecture--Controller Area Network or CAN--which presents grave security concerns that have been exploited by researchers and hackers alike. For instance, ECUs can be impersonated by adversaries who have infiltrated an automotive CAN and disable or invoke unintended vehicle functions such as brakes, acceleration, or safety mechanisms. Further, the quality of security approaches varies wildly between manufacturers. Thus, research and development of after-market security solutions have grown remarkably in recent years. Many researchers are exploring deployable intrusion detection and prevention mechanisms using machine learning and data science techniques. However, there is a gap between developing security system algorithms and deploying prototype security appliances in-vehicle. In this paper, we, a research team at Oak Ridge National Laboratory working in this space, highlight challenges in the development pipeline, and provide techniques to standardize methodology and overcome technological hurdles.Comment: 10 pages, PATRAM 2

Simulation-based flood fragility and vulnerability analysis for expanding cities

Accurately quantifying flood-induced impacts on buildings and other infrastructure systems is essential for risk-sensitive planning and decision-making in expanding urban regions. Flood-induced impacts are directly related to the physical components of assets damaged due to contact with water. Such components include building contents (e.g., appliances, furniture) and other non-structural components whose damage/unavailability can severely impact the buildingsﾒ functionality. Conventional fragility analysis approaches for flooding do not account for the physical damage to the individual components, mostly relying on empirical methods based on historical data. However, recent studies proposed simulation-based, assembly-based fragility models that account for the damage to the building components. Such fragility models require developing detailed inventories of vulnerable components of households and identifying building archetypes to be considered in a building portfolio for the region of interest. Content inventories and building portfolios have so far been obtained for specific socio-economic contexts such as the United States of America. However, building types and their content can significantly differ between countries, making the available fragility models and computational frameworks unsuitable for flood vulnerability analysis in rapidly expanding cities characterised by extensive informal settlements, such as low- and middle-income countries. This paper details how to adapt the available methodologies for flood vulnerability assessment to the context of formal and informal settlements of expanding cities in the global south. It also details the development of content inventories for households in these cities using field surveys. The proposed survey is deployed in various areas vulnerable to floods in Kathmandu, Nepal. Based on the survey results, each component within the household is associated with a corresponding flood capacity (resistance) distribution (in terms of water height and flood duration). These distributions are then employed in a simulation-based probabilistic framework to obtain fragility relationship and consequence models. The relevant differences between the results obtained in this study and those from previous studies are then investigated for a case-study building type. In addition, the influence of socio-economic factors (e.g., household income) and past flood experience (possibly resulting in various flood-risk mitigation strategies at a household level) on the resulting flood impacts is also included in the model