scholarly journals A Cloud-Enabled Application Framework for Simulating Regional-Scale Impacts of Natural Hazards on the Built Environment

2020 ◽  
Vol 6 ◽  
Author(s):  
Gregory G. Deierlein ◽  
Frank McKenna ◽  
Adam Zsarnóczay ◽  
Tracy Kijewski-Correa ◽  
Ahsan Kareem ◽  
...  
Keyword(s):  
Natural Hazards ◽  
High Performance ◽  
Information Technologies ◽  
Computational Models ◽  
Natural Hazard ◽  
Regional Scale ◽  
Application Framework ◽  
Modular Architecture ◽  
Engineering Research ◽  
Effective Development

With the goal to facilitate evaluation and mitigation of the risks from natural hazards, the Natural Hazards Engineering Research Infrastructure’s Computational Modeling, and Simulation Center (NHERI SimCenter) is developing computational workflows for regional hazard simulations. These simulations enable research to combine detailed assessments of individual facilities with comprehensive regional-scale simulations of natural hazard effects. By integration of multi-fidelity and multi-resolution models to assess natural hazard impacts on buildings, infrastructure systems and other constructed facilities, the approach enables the engineering analysis of public policies and socio-economic impacts. Effective development of platforms for high-resolution regional simulations requires modular workflows that can integrate state-of-the-art models with information technologies and high-performance computing resources. In this paper, the modular architecture of the computational workflow models is described and illustrated through testbed applications to evaluate regional building damage under an earthquake and a hurricane scenario. Developed and disseminated as open-source software on the NHERI DesignSafe Cyberinfrastructure, the computational models and workflows are enabling multi-disciplinary collaboration on research to mitigate the effects of natural hazard disasters.

scholarly journals Enhancing Research in Natural Hazards Engineering Through the DesignSafe Cyberinfrastructure

2020 ◽  
Vol 6 ◽  
Author(s):  
Ellen M. Rathje ◽  
Clint Dawson ◽  
Jamie E. Padgett ◽  
Jean-Paul Pinelli ◽  
Dan Stanzione ◽  
...  
Keyword(s):  
Natural Hazards ◽  
High Performance ◽  
Natural Hazard ◽  
Research Collaboration ◽  
Field Research ◽  
Data Publishing ◽  
Easy Access ◽  
Engineering Research ◽  
Private And Public ◽  
Access To Data

The DesignSafe cyberinfrastructure (www.designsafe-ci.org) is part of the NSF-funded Natural Hazard Engineering Research Infrastructure (NHERI) and provides cloud-based tools to manage, analyze, understand, and publish critical data for research to understand the impacts of natural hazards. The DesignSafe Data Depot provides private and public disk space to support research collaboration and data publishing through a web interface. The DesignSafe Reconnaissance Portal uses a map interface to provide easy access to data collected to investigate the effects of natural hazards, and the DesignSafe Workspace provides cloud-based tools for simulation, data analytics, and visualization; as well as access to high performance computing (HPC). This paper provides an overview of the DesignSafe cyberinfrastructure and describes specific examples of the use of DesignSafe in research for natural hazards. These examples include electronic data reports that use Jupyter notebooks to allow researchers to interrogate data interactively within the web portal, computational workflows that integrate ensembles of HPC-based simulations and surrogate modeling, and the publication of field research data after natural hazard events that utilize a variety of DesignSafe tools. The paper also provides an overall assessment of current DesignSafe impact and usage, demonstrating how DesignSafe is enhancing research in natural hazards.

scholarly journals The Swiss joint information platform for natural hazards

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Philipp Angehrn ◽  
Sabina Steiner ◽  
Christophe Lienert
Keyword(s):  
Natural Hazards ◽  
Spatial Data ◽  
Natural Hazard ◽  
Regional Scale ◽  
Measurement Data ◽  
User Feedback ◽  
Acceptance Testing ◽  
Spatial Density ◽  
Data Sets ◽  
Information Platform

<p><strong>Abstract.</strong> The Swiss Joint Information Platform for Natural Hazards (GIN) has been realized from 2008 to 2010 as part of the Swiss federal government’s OWARNA project, which aimed at optimizing warning and alerting procedures against natural hazard. The first online-version of the platform went productive in 2011 with the primary goal of providing measured and forecast natural hazard data in form of processed cartographic, graphic and other multimedia products to professional users &amp;ndash; before, during and after natural hazard events. In Switzerland water-, weather-, snow- and earthquake-related hazards are the most relevant ones.</p><p>In 2013, an online survey showed that the platform does not fully meet user expectations, particularly as to user experience and usability of its cartographic, web-based user interface. Revaluation and redesign of the overall platform were necessary in order to improve map legibility, caused by the complexity of data, large data amounts, and high spatial density of online, real-time measurement data locations. A new web design and user interaction concept have been developed in 2014 and eventually put online in June 2017. User acceptance testing by means of surveys and direct user feedback sessions were key factors in this perennial redesign process. The GIN platform now features important novel technical and graphical elements: The starting page is based on a dashboard containing virtual dossiers (Fig. 1), with which users configure their desired information, data, and map bundles individually, or use predefined adaptable views on various existing data sets. In addition, there is a new overall spatial search function to query data parameters. A responsive approach further improves the usability of the platform. The focus of these new features is on multi-views involving maps, diagrams, tables, text products, as well as selected geographical areas on maps, and fast data queries (Fig. 2). Current user feedback suggests that the new GIN platform design is well received, and that it is moving closer to its very goal: online monitoring and management of natural hazard events by enhanced usability, more targeted and higher personalization.</p><p>Several Swiss Cantons (i.e., the political entities in Switzerland below the federation) actively participated, and still participate, in the conceptual GIN platform development process through advisory board meetings and consultations. On the operational level, Cantons actively provide and contribute further natural hazard information and measurement data from their own natural hazard monitoring networks. These additional Cantonal regional-scale data sets help to fill spatial data gaps, where no Federal data is available. GIN thusly integrates natural hazard data from Federal and Cantonal levels (and partly even private level), which adds value to all stakeholders on various political levels involved in natural hazard management (Federal, Cantonal, Regional, Communal crisis committees). Stakeholders not only use GIN’s ample database and cartographic product portfolio to accomplish their early warning and crisis management tasks, but also benefit from seamless, secure and reliable IT-services, provided by the Swiss Federal Government. With the new GIN platform, Switzerland has a powerful, integrative, and comprehensive tool for monitoring and responding to natural hazard events.</p>

scholarly journals Curation and Publication of Simulation Data in DesignSafe, a Natural Hazards Engineering Open Platform and Repository

Publications ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 51
Author(s):  
Maria Esteva ◽  
Craig Jansen ◽  
Pedro Arduino ◽  
Mahyar Sharifi-Mood ◽  
Clint N. Dawson ◽  
...  
Keyword(s):  
Natural Hazards ◽  
High Performance ◽  
Simulation Data ◽  
Simulation Research ◽  
Engineering Research ◽  
Open Platform ◽  
Large Numbers ◽  
Resultant Data ◽  
Active Research ◽  
Ease Of Access

Most open repositories present a similar interface and workflow to publish data resultant from different types of research methods. Publishing simulation datasets is challenging due to the iterative nature of simulations that generate large numbers and sizes of files, and their need for detailed documentation. DesignSafe is a web-based open platform for natural hazards engineering research where users can conduct simulations in high performance computing resources, curate, and publish their data. Working closely with experts, we completed a data design project for curation and representation of simulation datasets. The design involved the creation of a data and metadata model that captures the main processes, data, and documentation used in natural hazards simulation research. The model became the foundation to design an interactive curation pipeline integrated with the rest of the platform functions. In the curation interface, users are guided to move, select, categorize, describe, and register relations between files corresponding to the simulation model, the inputs and the outputs categories. Curation steps can be undertaken at any time during active research. To engage users, the web interactions were designed to facilitate managing large numbers of files. The resultant data landing pages show the structure and metadata of a simulation process both as a tree, and a browsing interface for understandability and ease of access. To evaluate the design, we mapped real simulation data to interactive mockups and sought out experts’ feed-back. Upon implementing a first release of the pipeline, we evaluated the data publications and made necessary enhancements.

scholarly journals StEER: A Community-Centered Approach to Assessing the Performance of the Built Environment after Natural Hazard Events

2021 ◽  
Vol 7 ◽  
Author(s):  
Tracy Kijewski-Correa ◽  
David B. Roueche ◽  
Khalid M. Mosalam ◽  
David O. Prevatt ◽  
Ian Robertson
Keyword(s):  
Built Environment ◽  
Case Studies ◽  
Natural Hazards ◽  
Natural Hazard ◽  
Open Data ◽  
Data Access ◽  
Performance Study ◽  
The Bahamas ◽  
Engineering Research ◽  
The Impact

Since its founding in 2018, the Structural Extreme Events Reconnaissance (StEER) Network has worked to deepen the capacity of the Natural Hazards Engineering (NHE) community for coordinated and standardized assessments of the performance of the built environment following natural hazard events. This paper positions StEER within the field of engineering reconnaissance and the Natural Hazards Engineering Research Infrastructure (NHERI), outlining its organizational model for coordinated community-led responses to wind, seismic, and coastal hazard events. The paper’s examination of StEER’s event response workflow, engaging a range of hardware and delivering a suite of products, demonstrates StEER’s contributions in the areas of: workflow and data standardization, data reliability to enable field-observation-driven research &amp; development, efficiency in data collection and dissemination to speed knowledge sharing, near-real- time open data access for enhanced coordination and transparency, and flexibility in collaboration modes to reduce the “overhead” associated with reconnaissance and foster broad NHE community engagement in event responses as part of field and virtual assessment structural teams (FAST/VAST). StEER’s creation of efficient systems to deliver well-documented, reliable data suitable for diverse re-uses as well as rapidly disseminated synopses of the impact of natural hazard events on the built environment provide a distinctive complement to existing post-event reconnaissance initiatives. The implementation of these policies, protocols and workflows is then demonstrated with case studies from five events illustrating StEER’s different field response strategies: the Nashville, Tennessee Tornadoes (2020) – a Hazard Gradient Survey; the Palu Earthquake and Tsunami in Indonesia (2018) – a Representative Performance Study; the Puerto Rico Earthquakes (2019/2020) – using Targeted Case Studies; Hurricane Laura (2020) – leveraging Rapid Surveys to enable virtual assessments; and Hurricane Dorian (2019) in the Bahamas – a Phased Multi-Hazard Investigation. The use of these strategies has enabled StEER to respond to 36 natural hazard events, involving over 150 different individuals to produce 45 published reports/briefings, over 5000 publicly available app-based structural assessments, and over 1600 km (1000 mi) of street-level panoramic imagery in its first 2years of operation.

scholarly journals Identification and Quantification of Coumarins by UHPLC-MS in Arabidopsis Thaliana Natural Populations

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1804
Author(s):  
Izabela Perkowska ◽  
Joanna Siwinska ◽  
Alexandre Olry ◽  
Jérémy Grosjean ◽  
Alain Hehn ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
High Performance ◽  
Biological Activities ◽  
Natural Populations ◽  
Biologically Active ◽  
Stress Factors ◽  
Mass Spectrometry Analysis ◽  
Engineering Research ◽  
Spectrometry Analysis ◽  
Model Plant Arabidopsis Thaliana

Coumarins are phytochemicals occurring in the plant kingdom, which biosynthesis is induced under various stress factors. They belong to the wide class of specialized metabolites well known for their beneficial properties. Due to their high and wide biological activities, coumarins are important not only for the survival of plants in changing environmental conditions, but are of great importance in the pharmaceutical industry and are an active source for drug development. The identification of coumarins from natural sources has been reported for different plant species including a model plant Arabidopsis thaliana. In our previous work, we demonstrated a presence of naturally occurring intraspecies variation in the concentrations of scopoletin and its glycoside, scopolin, the major coumarins accumulating in Arabidopsis roots. Here, we expanded this work by examining a larger group of 28 Arabidopsis natural populations (called accessions) and by extracting and analysing coumarins from two different types of tissues–roots and leaves. In the current work, by quantifying the coumarin content in plant extracts with ultra-high-performance liquid chromatography coupled with a mass spectrometry analysis (UHPLC-MS), we detected a significant natural variation in the content of simple coumarins like scopoletin, umbelliferone and esculetin together with their glycosides: scopolin, skimmin and esculin, respectively. Increasing our knowledge of coumarin accumulation in Arabidopsis natural populations, might be beneficial for the future discovery of physiological mechanisms of action of various alleles involved in their biosynthesis. A better understanding of biosynthetic pathways of biologically active compounds is the prerequisite step in undertaking a metabolic engineering research.

scholarly journals Supervised Domain Adaptation for Automated Semantic Segmentation of the Atrial Cavity

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 898
Author(s):  
Marta Saiz-Vivó ◽  
Adrián Colomer ◽  
Carles Fonfría ◽  
Luis Martí-Bonmatí ◽  
Valery Naranjo
Keyword(s):  
High Performance ◽  
Computational Models ◽  
Domain Adaptation ◽  
Semantic Segmentation ◽  
Patient Specific ◽  
Mr Images ◽  
Training Samples ◽  
Volumetric Images ◽  
Acquisition Costs ◽  
Left And Right

Atrial fibrillation (AF) is the most common cardiac arrhythmia. At present, cardiac ablation is the main treatment procedure for AF. To guide and plan this procedure, it is essential for clinicians to obtain patient-specific 3D geometrical models of the atria. For this, there is an interest in automatic image segmentation algorithms, such as deep learning (DL) methods, as opposed to manual segmentation, an error-prone and time-consuming method. However, to optimize DL algorithms, many annotated examples are required, increasing acquisition costs. The aim of this work is to develop automatic and high-performance computational models for left and right atrium (LA and RA) segmentation from a few labelled MRI volumetric images with a 3D Dual U-Net algorithm. For this, a supervised domain adaptation (SDA) method is introduced to infer knowledge from late gadolinium enhanced (LGE) MRI volumetric training samples (80 LA annotated samples) to a network trained with balanced steady-state free precession (bSSFP) MR images of limited number of annotations (19 RA and LA annotated samples). The resulting knowledge-transferred model SDA outperformed the same network trained from scratch in both RA (Dice equals 0.9160) and LA (Dice equals 0.8813) segmentation tasks.

Pipeline Vulnerability to Natural Hazards

2015 ◽  
Author(s):  
José Vicente Amórtegui
Keyword(s):  
Stress State ◽  
Risk Analysis ◽  
Natural Hazards ◽  
Natural Hazard ◽  
Weather Conditions ◽  
Monitoring Systems ◽  
System Vulnerability ◽  
Preventive Actions ◽  
Strength And Stiffness ◽  
External Forces

The strength and stiffness of the pipelines allow them to tolerate the effects of natural hazards for some period of time. The amount of time depends on the strength and deformability, the stress state, the age, the conditions of installation and operation of the pipeline and their geometric arrangement with regard to the hazardous process. Accordingly, some of the hazards due to weather conditions and external forces would not be time independent. In consequence the designing of monitoring systems to predict the behavior of the pipelines against natural hazards is required in order to carry out the preventive actions which are necessary to avoid failure of the pipes due to the exposition to those hazards. In this paper a method for assessing the transport system vulnerability is developed, a function for risk analysis is proposed (which is determined by the probability of the natural hazard, the pipeline’s vulnerability to the hazard and the consequences of the pipe rupture). The elements that are part of that evaluation are presented and illustrated by means of examples.

Real-time modeling of retractable self-launching glider using spreadsheets

2017 ◽  
Vol 89 (6) ◽  
pp. 791-796
Author(s):  
Yasser A. Nogoud ◽  
Attie Jonker ◽  
Shuhaimi Mansor ◽  
A.A.A. Abuelnuor
Keyword(s):  
Control System ◽  
High Performance ◽  
Cost Effective ◽  
Visual Presentation ◽  
Content Type ◽  
Spreadsheet Model ◽  
Time Modeling ◽  
Model Complex ◽  
Effective Development ◽  
And Control

Purpose This paper aims to propose a spreadsheet method for modeling and simulation of a retraction system mechanism for the retractable self-launching system for a high-performance glider. Design/methodology/approach More precisely, the method is based on parametric link design using Excel spreadsheets. Findings This method can be used for kinematic and dynamic analysis, graphical plotting and allows simulation of control kinematics with the ability to make quick and easy parametric changes to a design. It also has the ability to calculate the loads imposed on each component in the control system as a function of input loads and position. Practical implications This paper shows that it is possible to model complex control systems quickly and easily using spreadsheet programs already owned by most small companies. The spreadsheet model is a parametric model, and it gives a simple visual presentation of the control system with interactive movement and control by the user. Originality/value This spreadsheet model in conjunction with a simple CAD program enables the rapid and cost-effective development of control system components.

scholarly journals Landscape analysis for multi-hazard prevention in Orco and Soana valleys, Northwest Italy

2015 ◽  
Vol 15 (9) ◽  
pp. 1963-1972 ◽  
Author(s):  
L. Turconi ◽  
D. Tropeano ◽  
G. Savio ◽  
S. K. De ◽  
P. J. Mason
Keyword(s):  
Natural Hazards ◽  
Natural Hazard ◽  
Thematic Maps ◽  
Italian Alps ◽  
Alpine Environment ◽  
Natural Risk ◽  
Mountainous Regions ◽  
Morphological Studies ◽  
Field Evidence ◽  
Different Types

Abstract. The study area (600 km2), consisting of Orco and Soana valleys in the Western Italian Alps, experienced different types of natural hazards, typical of the whole Alpine environment. Some of the authors have been requested to draw a civil protection plan for such mountainous regions. This offered the special opportunity (1) to draw a lot of unpublished historical data, dating back several centuries mostly concerning natural hazard processes and related damages, (2) to develop original detailed geo-morphological studies in a region still poorly known, (3) to prepare detailed thematic maps illustrating landscape components related to natural conditions and hazards, (4) to thoroughly check present-day situations in the area compared to the effects of past events and (5) to find adequate natural hazard scenarios for all sites exposed to risk. The method of work has been essentially to compare archival findings with field evidence in order to assess natural hazard processes, their occurrence and magnitude, and to arrange all such elements in a database for GIS-supported thematic maps. Several types of natural hazards, such as landslides, rockfalls, debris flows, stream floods and snow avalanches cause huge damage to lives and properties (housings, roads, tourist sites). We aim to obtain newly acquired knowledge in this large, still poorly understood area as well as develop easy-to-interpret products such as natural risk maps.

scholarly journals Assessing the risk posed by natural hazards to infrastructures

2016 ◽  
Author(s):  
Unni Marie Kolderup Eidsvig ◽  
Krister Kristensen ◽  
Bjørn Vidar Vangelsten
Keyword(s):  
Quantitative Analysis ◽  
Natural Hazards ◽  
Natural Hazard ◽  
Quality Level ◽  
Quantitative Methodology ◽  
Cascading Effects ◽  
Natural Event ◽  
Ranking Criteria ◽  
Adverse Weather ◽  
Restoration Effort

Abstract. This paper proposes a model for assessing the risk posed by natural hazards to infrastructures. The model prescribes a three level analysis with increasing level of detail, moving from qualitative to quantitative analysis. The focus is on a methodology for semi-quantitative analysis to be performed at the second level. The purpose of this type of analysis is to perform a screening of the scenarios of natural hazards threatening the infrastructures, identifying the most critical scenarios and investigating the need for further analyses (third level). The proposed semi-quantitative methodology considers the frequency of the natural hazard, different aspects of vulnerability including the physical vulnerability of the infrastructure itself and the societal dependency on the infrastructure. An indicator-based approach is applied, ranking the indicators on a relative scale according to pre-defined ranking criteria. The proposed indicators, which characterize conditions that influence the probability of an infrastructure break-down caused by a natural event, are defined as 1) Robustness and buffer capacity, 2) Level of protection, 3) Quality/Level of maintenance and renewal, 4) Adaptability and quality in operational procedures and 5) Transparency/complexity/degree of coupling. Further indicators describe the societal consequences of the infrastructure failure, such as Redundancy and/or substitution, Restoration effort/duration, Preparedness, early warning and emergency response and Dependencies and cascading effects. The aggregated risk estimate is a combination of the semi-quantitative vulnerability indicators, as well as quantitative estimates of the frequency of the natural hazard, the potential duration of the infrastructure malfunctioning (depending e.g. on the required restoration effort) and the number of users of the infrastructure. Case studies for two Norwegian municipalities are presented where risk posed by adverse weather and natural hazards to primary road, water supply and power network is assessed. The application examples show that the proposed model provides a useful tool for screening of potential undesirable events, contributing to a targeted reduction of the risk.

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