Scenario-based risk framework selection and assessment model development for natural disasters: a case study of typhoon storm surges

2015 ◽  
Vol 80 (3) ◽  
pp. 2037-2054 ◽  
Author(s):  
Mengya Li ◽  
Jun Wang ◽  
Xiaojing Sun
Keyword(s):  
Natural Disasters ◽  
Model Development ◽  
Storm Surges ◽  
Assessment Model ◽  
Risk Framework ◽  
Selection And Assessment

Demand Response Process Assessment Model: Development and Case Study Assessment

2021 ◽  
pp. 103609
Author(s):  
İLİSULU Fadime ◽  
Ayça KOLUKISA TARHAN ◽  
Kubilay KAVAK
Keyword(s):  
Demand Response ◽  
Model Development ◽  
Assessment Model ◽  
Process Assessment ◽  
Response Process

scholarly journals Assessing the economic impacts of drought from the perspective of profit loss rate: a case study of the sugar industry in China

2015 ◽  
Vol 3 (2) ◽  
pp. 1527-1556
Author(s):  
Y. Wang ◽  
L. Lin ◽  
H. Chen
Keyword(s):  
Time Series ◽  
Natural Disasters ◽  
Economic Impact ◽  
Loss Rate ◽  
Sugar Industry ◽  
Economic Impacts ◽  
Assessment Model ◽  
Human Society ◽  
Sugar Price

Abstract. Natural disasters have enormous impacts on human society, especially on the development of the economy. To support decision making in mitigation and adaption to natural disasters, assessment of economic impacts is fundamental and of great significance. Based on a review of the literature of economic impact evaluation, this paper proposes a new assessment model of economic impact from drought by using the sugar industry in China as a case study, which focuses on the generation and transfer of economic impacts along a simple value chain involving only sugarcane growers and a sugar producing company. A perspective of profit loss rate is applied to scale economic impact with a model based on cost-and-benefit analysis. By using analysis of "with-and-without", profit loss is defined as the difference in profits between disaster-hit and disaster-free scenarios. To calculate profit, analysis on a time series of sugar price is applied. With the support of a linear regression model, an endogenous trend in sugar price is identified, and the time series of sugar price "without" disaster is obtained using an autoregressive error model to separate impact by disasters from the internal trend in sugar price. Unlike the settings in other assessment models, representative sugar prices, which represent value level in disaster-free condition and disaster-hit condition, are integrated from a long time series that covers the whole period of drought. As a result, it is found that in a rigid farming contract, sugarcane growers suffer far more than the sugar company when impacted by severe drought, which may promote the reflections on economic equality among various economic bodies at the occurrence of natural disasters.

LONG-TERM EVALUATION OF STORM SURGES BY NEURAL NETWORK — CASE STUDY IN ISE BAY —

2018 ◽  
Vol 74 (2) ◽  
pp. I_601-I_606
Author(s):  
Yuji ARAKI ◽  
Tomohiro YASUDA ◽  
Nobuhito MORI
Keyword(s):  
Neural Network ◽  
Storm Surges ◽  
Ise Bay ◽  
Term Evaluation

scholarly journals Optimizing the Environmental and Economic Sustainability of Remote Community Infrastructure

2020 ◽  
Vol 12 (6) ◽  
pp. 2208 ◽  
Author(s):  
Jamie E. Filer ◽  
Justin D. Delorit ◽  
Andrew J. Hoisington ◽  
Steven J. Schuldt
Keyword(s):  
Environmental Impacts ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Assessment Model ◽  
Remote Communities ◽  
Remote Community ◽  
Rural Villages ◽  
Sustainable Technologies ◽  
Study Results

Remote communities such as rural villages, post-disaster housing camps, and military forward operating bases are often located in remote and hostile areas with limited or no access to established infrastructure grids. Operating these communities with conventional assets requires constant resupply, which yields a significant logistical burden, creates negative environmental impacts, and increases costs. For example, a 2000-member isolated village in northern Canada relying on diesel generators required 8.6 million USD of fuel per year and emitted 8500 tons of carbon dioxide. Remote community planners can mitigate these negative impacts by selecting sustainable technologies that minimize resource consumption and emissions. However, the alternatives often come at a higher procurement cost and mobilization requirement. To assist planners with this challenging task, this paper presents the development of a novel infrastructure sustainability assessment model capable of generating optimal tradeoffs between minimizing environmental impacts and minimizing life-cycle costs over the community’s anticipated lifespan. Model performance was evaluated using a case study of a hypothetical 500-person remote military base with 864 feasible infrastructure portfolios and 48 procedural portfolios. The case study results demonstrated the model’s novel capability to assist planners in identifying optimal combinations of infrastructure alternatives that minimize negative sustainability impacts, leading to remote communities that are more self-sufficient with reduced emissions and costs.

scholarly journals Operational and Safety Management at Intersections: Can the Turbo-Roundabout Be an Effective Alternative to Conventional Solutions?

2021 ◽  
Vol 13 (9) ◽  
pp. 5103
Author(s):  
Vincenzo Gallelli ◽  
Giusi Perri ◽  
Rosolino Vaiana
Keyword(s):  
Traffic Congestion ◽  
Safety Management ◽  
Environmental Benefits ◽  
Assessment Model ◽  
Pollutant Emission ◽  
Emission Rates ◽  
The European Union ◽  
European Union Policy ◽  
Union Policy

The European Union policy strategies on the sustainability of the transport system pursue the goals of maximizing safety and environmental benefits and reducing the severity and frequency of crashes, congestion, and pollutant emission rates. A common issue is the planning of the most effective solution for operational and safety management at intersections. In this study, an egg turbo roundabout is proposed as the alternative solution to a conventional roundabout in Southern Italy which suffers from traffic congestion. A comparative analysis is carried out using microsimulation techniques to investigate the safety effects and operational improvements of converting a traditional priority intersection into standard roundabout or turbo roundabout layout. In particular, the VISSIM software is used to explore the most relevant operational performance measures: queue length, travel times and delays. The lowest values of these measurements are recorded for the simulated turbo roundabout, thus making this scheme more appropriate in terms of operational performances. With regard to safety analysis, the Surrogate Safety Assessment Model (SSAM) is used to collect information on the predicted number of conflicts, the probability, and severity of the potential collisions. The results suggest that, for the specific case study, the safety levels of the standard roundabout and the turbo roundabout are approximately comparable.

The Power of Art to Cope With Trauma: Psychosocial Intervention After the Tsunami in Japan

2020 ◽  
pp. 002216782098214
Author(s):  
Tami Gavron
Keyword(s):  
Natural Disasters ◽  
Psychosocial Intervention ◽  
Cultural Context ◽  
Psychosocial Interventions ◽  
Kindergarten Teachers ◽  
Japanese Culture ◽  
Art Making ◽  
Cultural Expression ◽  
The Arts

This article describes the significance of an art-based psychosocial intervention with a group of 9 head kindergarten teachers in Japan after the 2011 tsunami, as co-constructed by Japanese therapists and an Israeli arts therapist. Six core themes emerged from the analysis of a group case study: (1) mutual playfulness and joy, (2) rejuvenation and regaining control, (3) containment of a multiplicity of feelings, (4) encouragement of verbal sharing, (5) mutual closeness and support, and (6) the need to support cultural expression. These findings suggest that art making can enable coping with the aftermath of natural disasters. The co-construction underscores the value of integrating the local Japanese culture when implementing Western arts therapy approaches. It is suggested that art-based psychosocial interventions can elicit and nurture coping and resilience in a specific cultural context and that the arts and creativity can serve as a powerful humanistic form of posttraumatic care.

scholarly journals Investigation of Nanogrids for Improved Navy Installation Energy Resilience

2021 ◽  
Vol 11 (9) ◽  
pp. 4298
Author(s):  
Alissa Kain ◽  
Douglas L. Van Bossuyt ◽  
Anthony Pollman
Keyword(s):  
National Security ◽  
Natural Disasters ◽  
Systems Engineering ◽  
Critical Loads ◽  
Electrical Energy ◽  
Terrorist Attacks ◽  
Military Bases ◽  
Specific Interest ◽  
The Military

Military bases perform important national security missions. In order to perform these missions, specific electrical energy loads must have continuous, uninterrupted power even during terrorist attacks, adversary action, natural disasters, and other threats of specific interest to the military. While many global military bases have established microgrids that can maintain base operations and power critical loads during grid disconnect events where outside power is unavailable, many potential threats can cause microgrids to fail and shed critical loads. Nanogrids are of specific interest because they have the potential to protect individual critical loads in the event of microgrid failure. We present a systems engineering methodology that analyzes potential nanogrid configurations to understand which configurations may improve energy resilience and by how much for critical loads from a national security perspective. This then allows targeted deployment of nanogrids within existing microgrid infrastructures. A case study of a small military base with an existing microgrid is presented to demonstrate the potential of the methodology to help base energy managers understand which options are preferable and justify implementing nanogrids to improve energy resilience.

scholarly journals Predictive Maintenance in Building Facilities: A Machine Learning-Based Approach

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1044
Author(s):  
Yassine Bouabdallaoui ◽  
Zoubeir Lafhaj ◽  
Pascal Yim ◽  
Laure Ducoulombier ◽  
Belkacem Bennadji
Keyword(s):  
Machine Learning ◽  
Model Development ◽  
Predictive Maintenance ◽  
Data Availability ◽  
Machine Learning Techniques ◽  
Automation System ◽  
Building Maintenance ◽  
Collection Data ◽  
Iot Devices

The operation and maintenance of buildings has seen several advances in recent years. Multiple information and communication technology (ICT) solutions have been introduced to better manage building maintenance. However, maintenance practices in buildings remain less efficient and lead to significant energy waste. In this paper, a predictive maintenance framework based on machine learning techniques is proposed. This framework aims to provide guidelines to implement predictive maintenance for building installations. The framework is organised into five steps: data collection, data processing, model development, fault notification and model improvement. A sport facility was selected as a case study in this work to demonstrate the framework. Data were collected from different heating ventilation and air conditioning (HVAC) installations using Internet of Things (IoT) devices and a building automation system (BAS). Then, a deep learning model was used to predict failures. The case study showed the potential of this framework to predict failures. However, multiple obstacles and barriers were observed related to data availability and feedback collection. The overall results of this paper can help to provide guidelines for scientists and practitioners to implement predictive maintenance approaches in buildings.

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