Special Issue "New Directions in Hazard and Disaster Science: Advances in Applied Sciences"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental and Sustainable Science and Technology".

Deadline for manuscript submissions: 30 April 2020.

Special Issue Editor

Prof. Dr. Jason K. Levy
E-Mail Website
Guest Editor
Disaster Preparedness and Emergency Management, University of Hawaii, Kapolei, HI 96707, USA
Interests: disaster risk governance; sustainable hazard mitigation; emergency management decision making; natural–technologic (na-tech) crises; health-related emergencies; fluvial and marine disasters; global climate change

Special Issue Information

Dear Colleagues,

Hazards, risk and disasters—including geologic and hydrological processes, intentional threats, and health-related crises—are a growing menace to sustainability, economic development, and global security. For example, there are a wide variety of natural hazards (volcanic eruptions, earthquakes, landslides, mudflows, sinkholes, snow avalanches, flooding, and tsunamis) that pose a critical threat to pivotal infrastructure systems and life safety. Every year, terrorist attacks, severe natural events, and epidemics damage cause injuries and deaths on a large scale. Advances in hazard and disaster science and management are needed to cope with potentially hazardous human threats as well as geoprocesses.

This Special Issue examines a new set of applied science tools in the Big Data era that that can help to reduce the impact of these natural, technologic, intentional, and health-related threats. There are advances in applied sciences that can directly reduce the likelihood, impact, and vulnerability of communities to disaster: remote sensing; electrical, electronics, and communications engineering; nanotechnology and applied nanosciences; mechanical and civil engineering; applied biosciences and bioengineering; environmental and sustainable science and technology; applied physics; computing and artificial intelligence; earth sciences and geography; and applied industrial technologies. For example, new approaches in data science and machine learning capitalize on the ubiquity of risk and hazard data sets, as well as advances in remote sensing, global position systems, and GIS. These solutions also provide new opportunities for the analysis and management of all types of disaster risks.

Prof. Dr. Jason K. Levy
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Applied industrial technologies for managing natural hazards
  • Environmental and sustainable science and technology and disaster prevention
  • Technologic risks and critical infrastructure protection
  • Systems engineering for disaster risk reduction
  • Geohazards analysis with earth sciences and geography

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Evaluating Seismic Soil Liquefaction Potential Using Bayesian Belief Network and C4.5 Decision Tree Approaches
Appl. Sci. 2019, 9(20), 4226; https://doi.org/10.3390/app9204226 - 10 Oct 2019
Abstract
Liquefaction is considered a damaging phenomenon of earthquakes and a major cause of concern in civil engineering. Therefore, its predictory assessment is an essential task for geotechnical experts. This paper investigates the performance of Bayesian belief network (BBN) and C4.5 decision tree (DT) [...] Read more.
Liquefaction is considered a damaging phenomenon of earthquakes and a major cause of concern in civil engineering. Therefore, its predictory assessment is an essential task for geotechnical experts. This paper investigates the performance of Bayesian belief network (BBN) and C4.5 decision tree (DT) models to evaluate seismic soil liquefaction potential based on the updated and relatively large cone penetration test (CPT) dataset (which includes 251 case histories), comparing them to a simplified procedure and an evolutionary-based approach. The BBN model was developed using the K2 machine learning algorithm and domain knowledge (DK) with data fusion methodology, while the DT model was created using a C4.5 algorithm. This study shows that the BBN model is preferred over the others for evaluation of seismic soil liquefaction potential. Owing to its overall performance, simplicity in practice, data-driven characteristics, and ability to map interactions between variables, the use of a BBN model in assessing seismic soil liquefaction is quite promising. The results of a sensitivity analysis show that ‘equivalent clean sand penetration resistance’ is the most significant factor affecting liquefaction potential. This study also interprets the probabilistic reasoning of the robust BBN model and most probable explanation (MPE) of seismic soil liquefied sites, based on an engineering point of view. Full article
Show Figures

Figure 1

Open AccessArticle
Dome Roof Fall Geohazards of Full-Seam Chamber with Ultra-Large Section in Coal Mine
Appl. Sci. 2019, 9(18), 3891; https://doi.org/10.3390/app9183891 - 17 Sep 2019
Abstract
The roof fall hazard is more likely to take place within chamber with ultra-large section, which would not only damage mechanical equipment, but also cause casualties. In this paper, the strap joint chamber of the Tashan coal mine is studied, and finite and [...] Read more.
The roof fall hazard is more likely to take place within chamber with ultra-large section, which would not only damage mechanical equipment, but also cause casualties. In this paper, the strap joint chamber of the Tashan coal mine is studied, and finite and discrete element method (FDEM) is used to establish the numerical model of the roof fall of the chamber dome. The simulation results show that the chamber dome mainly undergoes shear failure and forms a large number of cracks. With further development and penetration of cracks, a distinct roof separation is found in the chamber dome. When the crack develops to the dome surface of the chamber, under the effect of the mine pressure, the coal body is separated from the surface of the chamber and the roof fall hazard occurs. Based on the mechanism of roof fall hazard of the chamber dome, it is concluded that improving the shear strength of the surrounding rock and reducing the crack penetration are the main ways to control the roof fall. Therefore, the high-strength anchor bolt and cable support is adopted to fill the cracks and improve the shear strength of the surrounding rock. The result showed that the roof separation of the chamber dome in the field is confined to 0.012 m. The surrounding rock is well controlled and no roof fall occurs. Full article
Show Figures

Figure 1

Open AccessArticle
The Prevention and Control Mechanism of Rockburst Hazards and Its Application in the Construction of a Deeply Buried Tunnel
Appl. Sci. 2019, 9(17), 3629; https://doi.org/10.3390/app9173629 - 03 Sep 2019
Abstract
Rockburst hazards induced by high geostress are particularly prominent during the construction of underground engineering. Prevention and control of rockburst is still a global challenge in the field of geotechnical engineering, which is of great significance. Based on the tunnel group of the [...] Read more.
Rockburst hazards induced by high geostress are particularly prominent during the construction of underground engineering. Prevention and control of rockburst is still a global challenge in the field of geotechnical engineering, which is of great significance. Based on the tunnel group of the Jinping II hydropower station of China, this paper analyzed the mechanical principle of support in the process of construction, and discussed in detail the active release and passive support by numerical simulation and field application. The results show that as two active measures, stress relieve holes and advanced stress relief blasting can release the energy of the microseismic source and transfer the high stress to the deeper surrounding rock, make the surface rock wall with a relatively low stress act as a protective barrier. Their stress release rate is about 12% and 33% in this project, respectively. In term of passive measure, the combined rapid support, which is mainly composed of water swelling anchor and nano-admixture shotcrete, is also an effective way to prevent and control the rockburst under high geostress. Full article
Show Figures

Figure 1

Back to TopTop