Participatory Vulnerability Reduction (PVR): an urban community-based approach for earthquake management

Participation of local people during any disaster is enormous. They possess better knowledge and information about their own community than anyone else from the outside. This study proposes Participatory Vulnerability Reduction (PVR), a community-based approach for disaster management. The concept of PVR was applied to an urban community of Dhaka city (Ward no. 06 of Dhaka North City Corporation) which has been identified by the Comprehensive Disaster Management Programme as one of the most vulnerable areas of the city for earthquake. PVR consists three steps, and in each step, different participatory urban appraisal tools were used. In the first step, the community people assessed the earthquake vulnerability. It was found that some certain parts of the study area are highly vulnerable due to lack of accessibility to the critical facilities, inadequacy of open space, poor construction practice and unsuitable soil condition for building construction. This was followed by analyzing the root causes and effects of these problems. Structural fragility of the buildings, construction of settlements by filling the low-lying areas and development of slums beside taller buildings are the three major causes behind the above vulnerable issues. In the second step, capacity of the community was assessed in terms of resources and their organizational structure. In the final step, local people developed the strategies to overcome the vulnerability and a community-based organizational set up was proposed to coordinate the collective actions. Although developed in local context, application of PVR is not limited for earthquake and it can be replicated for other communities as well.     

Examination of the structural characteristics arising in gypsums by the GPR and MASW methods (Sivas,Turkey)

This study was performed at an area of 50?×?48 m² being defined as a new settlement in the northeast of Sivas. In the study, the discontinuities that are not deep and their geophysical characteristics were examined by the GPR and MASW methods. For interpretation, GPR cross sections were prepared as 2D–3D, and MASW cross sections were prepared as 2D. As for geophysical cross sections, about 10 m depth was examined. It was understood that the reflections observed in the form of hyperbolas in GPR cross sections correspond to areas having low S wave velocity (V_s) in MASW cross sections. It was understood that the S wave velocities are lower than 653 m/s, that the seismic velocities in between 653 and 275 m/s indicate partially deteriorated areas and that the S wave velocities of unweathered gypsums are higher than 1275 m/s at these low-velocity zones. Thus, it was thought that the fill material that may arise in the fracture, crack and deterioration areas arises from intercalation and clastic gypsum units, and that it plays a role in having low value S wave velocities. In all the geophysical cross sections, it was understood that the structures with gypsum are intense at the initial 5 m. And a fracture at the south of the study area, that it was estimated might be longer than 40 m, was determined as the largest gypsum structure. It was understood that this fracture starts from a depth of about 5 m in the west and that it slopes down to 7 m depth in the east. According to these results, it was understood that the damage amount arising in time in the gypsum structures from the effect of water may increase, the study area was defined as risky, and the required importance should be attached to these structures especially in foundation engineering.     

Integration of GIS,AHP and TOPSIS for earthquake hazard analysis

Worldwide, earthquakes and related disasters have persistently had severe negative impacts on human livelihoods and have caused widespread socioeconomic and environmental damage. The severity of these disasters has prompted recognition of the need for comprehensive and effective disaster and emergency management (DEM) efforts, which are required to plan, respond to and develop risk mitigation strategies. In this regard, recently developed methods, known as multi-criteria decision analysis (MCDA), have been widely used in DEM domains by emergency managers to greatly improve the quality of the decision-making process, making it more participatory, explicit, rational and efficient. In this study, MCDA techniques of the Analytical Hierarchical Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), integrated with GIS, were used to produce earthquake hazard and risk maps for earthquake disaster monitoring and analysis for a case study region of Küçükçekmece in Istanbul, Turkey. The five main criteria that have the strongest influence on the impact of earthquakes on the study region were determined: topography, distance to epicentre, soil classification, liquefaction and fault/focal mechanism. AHP was used to determine the weights of these parameters, which were also used as input into the TOPSIS method and GIS (ESRI ArcGIS) for simulating these outputs to produce earthquake hazard maps. The resulting earthquake hazard maps created by both the AHP and TOPSIS models were compared, showing high correlation and compatibility. To estimate the elements at risk, population and building data were used with the AHP and TOPSIS hazard maps for potential loss assessment; thus, we demonstrated the potential of integrating GIS with AHP and TOPSIS in generating hazard maps for effective earthquake disaster and risk management.     

Evaluating climate change adaptation efforts on the US 50 states’ hazard mitigation plans

Climate change brings uncertain risks of climate-related natural hazards. The US Federal Emergency Management Agency (FEMA in Climate change: long-term trends and their implications for emergency management, 2011. https://www.fema.gov/pdf/about/programs/oppa/climate_change_paper.pdf) has issued a policy directive to integrate climate change adaptation actions into hazard mitigation programs, policies, and plans. However, to date there has been no comprehensive empirical study to examine the extent to which climate change issues are integrated into state hazard mitigation plans (SHMPs). This study develops 18 indicators to examine the extent of climate change considerations in the 50 SHMPs. The results demonstrate that these SHMPs treat climate change issues in an uneven fashion, with large variations present among the 50 states. The overall plan quality for climate change considerations was sustained at an intermediate level with regard to climate change-related awareness, analysis, and actions. The findings confirm that climate change concepts and historic extreme events have been well recognized by the majority of SHMPs. Even though they are not specific to climate change, mitigation and adaptation strategies that can help reduce climate change risks have been adopted in these plans. However, the plans still lack a detailed assessment of climate change and more incentives for collaboration strategies beyond working with emergency management agencies.     

Settlement of Shallow Foundations on Cohesionless Soils Based on SPT Value Using Multi-Objective Feature Selection

Accurate prediction of settlement for shallow footings on cohesionless soil is a complex geotechnical problem due to large uncertainties associated with soil. Prediction of the settlement of shallow footings on cohesionless soil is based on in situ tests as it is difficult to find out the properties of soil in the laboratory and standard penetration test (SPT) is the most often used in situ test. In data driven modelling, it is very difficult to choose the optimal input parameters, which will govern the model efficiency along with a better generalization. Feature subset selection involves minimization of both prediction error and the number of features, which are in general mutual conflicting objectives. In this study, a multi-objective optimization technique is used, where a non-dominated sorting genetic algorithm (NSGA II) is combined with a learning algorithm (neural network) to develop a prediction model based on SPT data based on the Pareto optimal front. Pareto optimal front gives the user freedom to choose a model in terms of accuracy and model complexity. It is also shown how NSGA II can be effectively applied to select the optimal parameters and besides minimizing the error rate. The developed model is compared with existing models in terms of different statistical criteria and found to be more efficient.     

Prediction of Engineering Properties of Basalt Rock in Jordan Using Ultrasonic Pulse Velocity Test

Basalt is an extrusive igneous rock derived from Lava and spread over different localities in Jordan. It can be used in industrial applications, and as construction materials. Before using basalt, it is essential to determine its dry density, porosity, uniaxial compressive strength, and Brazilian tensile strength. The testing procedure and sample preparation used to determine the engineering properties are time-consuming and need expertise. Hence, the ultrasonic pulse velocity (UPV) test, a quick and non-destructive evaluation method, was used to determine the engineering properties. Empirical relationships for determination of dry density, porosity, uniaxial compressive strength, Brazilian tensile strength, and tangent modulus of elasticity were deduced. Good correlation coefficients (R²?=?0.832–0.929) were obtained between UPV and dry density, porosity, uniaxial compressive strength, Brazilian tensile strength and modulus of elasticity. These correlations were limited to intact basalt with UPV?≥?4000 m/s.     

北方集中供热系统气象风险评估初探

供热管网爆裂、跑冒滴漏是北方集中供热城市面临的常见问题,供热管网出现大型故障往往是在室外寒冷的隆冬时节,如果间断或限额供热时间过长,将会造成严重的社会和经济影响。同时在极端低温情况下,可能会造成热源供应不足,出现限额供热现象,不能保证室内舒适度,影响人们的正常生活。本文提出了能源供应气象风险评估和热网维修寒冷风险评估方法,并进行了案例评估,以期为未来进行相关风险评估提供参考。     

基于岩石图像深度学习的岩性自动识别与分类方法

岩石岩性的识别与分类对于地质分析极为重要,采用机器学习的方法建立识别模型进行自动分类是一条新的途径。基于Inception-v3深度卷积神经网络模型,建立了岩石图像集分析的深度学习迁移模型,运用迁移学习方法实现了岩石岩性的自动识别与分类。采用此方法对所采集的173张花岗岩图像、152张千枚岩图像和246张角砾岩图像进行了学习和识别分类研究,通过训练学习建立岩石图像深度学习迁移模型,并分别采用训练集和测试集中的岩石图像对模型进行了检验分析。对于训练集中的岩石图像,每组岩石分别用3张图像测试,三种岩石的岩性分类均正确,且分类概率值均达到90%以上,显示了模型良好的鲁棒性;对于测试集中的岩石图像,每组岩石分别采用9张图像进行识别分析,三种岩石的岩性分类均正确,并且千枚岩组图像分类概率均高于90%,但是花岗岩组2张图像和角砾岩组的1张图像分类概率值不足70%,概率值较其他岩石图像低,推测其原因是训练集中相同模式的岩石图像较少,导致模型的泛化能力减小。为了提高识别精确度,对准确率较低的岩石图像进行截取,分别取其中的3张图像加入训练集进行再训练,增加与测试图像具有相同模式的训练样本;在新的模型中,对3张图像进行二次检验,测试概率值均达到85%以上,说明在数据足够的状况下模型具有良好的学习能力。与传统的机器学习方法相比,所提出的岩石图像深度学习方法具有以下优点:第一,模型通过搜索图像像素点提取物体特征,不需要手动提取待分类物体特征;第二,对于图像像素大小,成像距离及光照要求低;第三,采用适当的训练集可获得较好的识别分类效果,并具有良好鲁棒性和泛化能力。     

Study on the Development Laws of Bed-Separation Under the Hard-Thick Magmatic Rock and its Fracture Disaster-Causing Mechanism

Based on the analysis of dynamic phenomena under the condition of high-located hard-thick (HLHT) stratum of one coal mine, along with the similar material simulation and theoretical analysis, the characteristics of bed separation development and cracks distribution under the HLHT stratum are studied. This paper proposes a discriminating method for overlying strata Three Zones considering the influence of HLHT stratum. The development laws of cracks and disaster-causing mechanism of hard-thick magmatic rock in different strata are respectively analyzed. The studies show that in line with the working face advancing direction, the height of bed separation under the magmatic rock increases in the trend of “Increase–Stability–Decrease”, and the width of bed separation increases linearly. The width of bed separation reaches the maximum before the first breaking of magmatic rock, the bed separation completely closes after the breaking. There are no obvious bed separations during the period migration of magmatic rock. Along the direction of the height of roof, the development of bed separation is characterized by bottom-up jump based on the key strata. The analyzed results of “Three zone” height obtained by the discriminate method of overlying strata Three Zones which is based on the key strata theory and the S–R instability theory are in line with the actual facts. When the hard-thick magmatic rock is in the fractured zone, large amounts of gas and water are easy to accumulate in the bed separation space and “O” ring space around the gob. The first breaking of magmatic rock may induce bed separation gas outburst and water inrush. When the hard-thick magmatic rock is in the sagging zone, the long-term stability of magmatic rock will not cause serious disasters. But with the adjacent working face mining, bed separation gas and water often become a safety hazard.