A simulation‐based framework for earthquake risk‐informed and people‐centred decision making on future urban planning

Numerous approaches to earthquake risk modelling and quantification have already been proposed in the literature and/or are well established in practice. However, most of these procedures are designed to focus on risk in the context of current static exposure and vulnerability, and are therefore limited in their ability to support decisions related to the future, as yet partially unbuilt, urban landscape. We propose an end-to-end risk modelling framework that explicitly addresses this specific challenge. The framework is designed to consider the earthquake (ground-shaking) risks of tomorrow’s urban environment, using a simulation-based approach to rigorously capture the uncertainties inherent in future projections of exposure as well as physical and social vulnerability. The framework also advances the state-of-practice in future disaster risk modelling by additionally: (1) providing a harmonised methodology for integrating physical and social impacts of disasters that facilitates flexible characterisation of risk metrics beyond physical damage/asset losses; and (2) incorporating a participatory, people-centred approach to risk-informed decision making. The framework is showcased using the physical and social environment of an expanding synthetic city. This example application demonstrates how the framework may be used to make policy decisions related to future urban areas, based on multiple, uncertain risk drivers

Modelling and quantifying tomorrow's risks from natural hazards

Understanding and modelling future risks from natural hazards is becoming increasingly crucial as the climate changes, human population grows, asset wealth accumulates, and societies become more urbanised and interconnected. This need is recognised by the 2015-2030 Sendai Framework for Disaster Risk Reduction, which emphasises the importance of preparing for the disasters that our world may face tomorrow through strategies/policies that aim to minimise uncontrolled development in hazardous areas. While the vast majority of natural-hazard risk-assessment frameworks have so far focused on static impacts associated with current conditions and/or are influenced by historical context, some authors have sought to provide decision makers with risk-quantification approaches that can be used to cultivate a sustainable future. This Review documents these latter efforts, explicitly examining work that has modelled and quantified the individual components that comprise tomorrow's risk, i.e., future natural hazards affected by climate change, future exposure (e.g., in terms of population, land use, and the built environment), and the evolving physical vulnerabilities of the world's infrastructure. We end with a discussion on the challenges faced by modellers in determining the risks that tomorrow's world may face from natural hazards, and the constraints these place on the decision-making abilities of relevant stakeholders

A Novel People-Centered Approach to Modeling and Decision Making on Future Earthquake Risk

Numerous approaches to earthquake risk modeling and quantification have already been proposed in the literature and/or are well established in practice. However, most of these procedures are designed to focus on risk in the context of current static exposure and vulnerability, and are therefore limited in their ability to support decisions related to the future, as yet partially unbuilt, urban landscape. This paper outlines an end-to-end risk modeling framework that explicitly addresses this specific challenge. The framework is designed to consider the earthquake risks of tomorrow's urban environment, using a simulationbased approach to rigorously capture the uncertainties inherent in future projections of exposure as well as physical and social vulnerability. The framework also advances the state-of-practice in future disaster risk modeling by additionally: (1) providing a harmonized methodology for integrating physical and social impacts of disasters that facilitates flexible characterization of risk metrics beyond physical damage/asset losses; and (2) incorporating a participatory, people-centered approach to riskinformed decision making. It can be used to support decision making on policies related to future urban planning and design, accounting for various stakeholder perspectives on risk

Using metal-ligand binding characteristics to predict metal toxicity: quantitative ion character-activity relationships (QICARs).

Ecological risk assessment can be enhanced with predictive models for metal toxicity. Modelings of published data were done under the simplifying assumption that intermetal trends in toxicity reflect relative metal-ligand complex stabilities. This idea has been invoked successfully since 1904 but has yet to be applied widely in quantitative ecotoxicology. Intermetal trends in toxicity were successfully modeled with ion characteristics reflecting metal binding to ligands for a wide range of effects. Most models were useful for predictive purposes based on an F-ratio criterion and cross-validation, but anomalous predictions did occur if speciation was ignored. In general, models for metals with the same valence (i.e., divalent metals) were better than those combining mono-, di-, and trivalent metals. The softness parameter (sigma p) and the absolute value of the log of the first hydrolysis constant ([symbol: see text] log KOH [symbol: see text]) were especially useful in model construction. Also, delta E0 contributed substantially to several of the two-variable models. In contrast, quantitative attempts to predict metal interactions in binary mixtures based on metal-ligand complex stabilities were not successful

Applying Binomial Statistics to Weighted Monte Carlo

Weighted Monte Carlo calculations requiring a uniform sampling of the problem-space can suffer from diminished statistical significance because many, if not most, of the randomly-chosen sampling points contribute only slightly to the desired result. Their contribution is reduced in size due the variable-size of the weighting terms. In contrast, none of the randomly-chosen points which are favored by variable size weighting terms will have their statistical significance enhanced beyond that of just one random point in the Monte Carlo sampling. A Monte Carlo analysis was used in earlier work to verify both Gauss\u27 Law and Newton\u27s Shell Theorem. Both examples suffered from statistical difficulties since each Monte Carlo sampling point has a weight inversely proportional to the square of the distance between source and field points. The present work analyzes the diminished significance in weighted Monte Carlo for the specific example of Newton\u27s Shell Theorem, describing the geometry in terms of closest approach distance of the spherical mass shell to the field point. Binomial Statistics is used to remedy this diminished statistical significance by providing a prescription for increasing the value of the Monte Carlo sample size needed to assure that the chosen precision remains invariant as the mass-shell geometry is changed

The contribution of teacher education to universities: a case study for international teacher educators

This paper reports on the initial stage of a research project which aims to develop deeper understanding of the contribution teacher education, as a sub-discipline within Education, makes to Higher Education in England. The study is located in the intersection between the domains of teacher education and higher education scholarship, which in England represents a contested and ambiguous professional space. Tensions between competing accountability measures, pulling away from university-based to exclusively school-based teacher education, are exacerbated by proposed policy changes arising from the government's recent market review. Findings drawn from analysis of qualitative data from a national survey are discussed in the context of Elizabeth Povinelli's critique of late liberalism and previous scholarship on the nature of teacher educators’ work. Evidence from the study demonstrates numerous benefits to higher education of hosting teacher education departments, including contributions to standard metrics, regional development and knowledge exchange within a strategic social justice agenda. However, teacher educators themselves may find articulating these benefits difficult, because of marginalisation from the dominant ways of achieving and accounting for excellence in the modern university. These findings offer a cautionary tale to international colleagues whose governments may be embarking on equivalent paths of teacher education reform

Future exposure modelling for risk-informed decision making in urban planning

Population increases and related urban expansion are projected to occur in various parts of the world over the coming decades. These future changes to the urban fabric could fundamentally alter the exposure to natural hazards and the associated vulnerability of people and the built environment with which they interact. Thus, modelling, quantifying, and reducing future urban disaster risk require forward-looking insights that capture the dynamic form of cities. This paper specifically focuses on the exposure component of dynamic natural-hazard disaster risk, by considering urban planning as the centre of future exposure characterisation in a given region. We use the information provided by urban plans and propose an integrated data structure for capturing future exposure to hazards. The proposed data structure provides the necessary detailing for both future physical and socio-demographic exposure in disaster risk modelling. More specifically, it enables users to develop a comprehensive multi-level, multi-scale exposure dataset, characterising attributes of land use, buildings, households and individuals. We showcase the proposed data schema using the virtual urban testbed Tomorrowville. In this case study, we also demonstrate how simplified algorithmic procedures and disaggregation methods can be used to populate the required data. This implementation demonstrates how the proposed exposure data structure can effectively support the development of forward-looking urban visioning scenarios to support decision-making for risk-sensitive and pro-poor urban planning and design in tomorrow's cities

Onto what planes should Coulomb stress perturbations be resolved?

[1] Coulomb stress maps are produced by computing the tensorial stress perturbation due to an earthquake rupture and resolving this tensor onto planes of a particular orientation. It is often assumed that aftershock fault planes are ‘‘optimally oriented’’; in other words, the regional stress and coseismic stress change are used to compute the orientation of planes most likely to fail and the coseismic stress is resolved onto these orientations. This practice assumes that faults capable of sustaining aftershocks exist at all orientations, an assumption contradicted by the observation that aftershock focal mechanisms have strong preferred orientations consistent with mapped structural trends. Here we systematically investigate the best planes onto which stress should be resolved for the Landers, Hector Mine, Loma Prieta, and Northridge earthquakes by quantitatively comparing observed aftershock distributions with stress maps based on optimally oriented planes (two- and three-dimensional), main shock orientation, and regional structural trend. We find that the best model differs between different tectonic regions but that in all cases, models that incorporate the regional stress field tend to produce stress maps that best fit the observed aftershock distributions, although not all such models do so equally well. Our results suggest that when the regional stress field is poorly defined, or in structurally complex areas, the best model may be to fix the strike of the planes upon which the stress is to be resolved to that of the main shock but allow the dip and rake to vary

Towards the production of radiotherapy treatment shells on 3D printers using data derived from DICOM CT and MRI: preclinical feasibility studies

Background: Immobilisation for patients undergoing brain or head and neck radiotherapy is achieved using perspex or thermoplastic devices that require direct moulding to patient anatomy. The mould room visit can be distressing for patients and the shells do not always fit perfectly. In addition the mould room process can be time consuming. With recent developments in three-dimensional (3D) printing technologies comes the potential to generate a treatment shell directly from a computer model of a patient. Typically, a patient requiring radiotherapy treatment will have had a computed tomography (CT) scan and if a computer model of a shell could be obtained directly from the CT data it would reduce patient distress, reduce visits, obtain a close fitting shell and possibly enable the patient to start their radiotherapy treatment more quickly. Purpose: This paper focuses on the first stage of generating the front part of the shell and investigates the dosimetric properties of the materials to show the feasibility of 3D printer materials for the production of a radiotherapy treatment shell. Materials and methods: Computer algorithms are used to segment the surface of the patient’s head from CT and MRI datasets. After segmentation approaches are used to construct a 3D model suitable for printing on a 3D printer. To ensure that 3D printing is feasible the properties of a set of 3D printing materials are tested. Conclusions: The majority of the possible candidate 3D printing materials tested result in very similar attenuation of a therapeutic radiotherapy beam as the Orfit soft-drape masks currently in use in many UK radiotherapy centres. The costs involved in 3D printing are reducing and the applications to medicine are becoming more widely adopted. In this paper we show that 3D printing of bespoke radiotherapy masks is feasible and warrants further investigation