Medium Risk Zones Research Articles

Temporal and spatial variability of landscape ecological risk in the Yangtze River Midstream Urban Agglomeration in the context of climate change

The Yangtze River Midstream Urban Agglomeration is a pivotal economic zone in China. Over the past 35 years, climate change has increased ecosystem vulnerability and instability in this area. Therefore, assessing landscape ecological risk (LER) is vital for this region. This study analyzed LER variations from 1985 to 2020 using statistical methods and landscape indices, and forecasted LER changes from 2025 to 2050 with multi-model meteorological data. Results show the following: (1) LER indices have decreased over the last 35 years, with a notable shift from high-risk to medium-risk areas. High LER areas remained concentrated in low-elevation, densely urbanized central regions, indicating severe ecological damage compared to high-elevation areas. (2) Climate change significantly impacts the LER index, with temperature exerting a stronger influence than precipitation. Overall, LER decreases with rising temperatures and precipitation, though some cities exhibit opposite trends. (3) Future multi-Shared Socioeconomic Pathway scenarios suggest a general decrease in LER with increased temperature and decreased precipitation, predominantly resulting in low- and medium-risk zones. High LER areas will persist in low-elevation zones, particularly in the southern and central plains. Given the high LER in the plains, the timely governmental regulation and control measures are essential for ensuring ecologically sustainable development.

Landscape ecological risk assessment and driving factor analysis in southwest china.

Landscape ecological risk assessment and ecological network construction are of great significance for optimizing territorial functions and reducing regional ecological risks. Based on the production-living-ecological space perspective, this study evaluated the spatiotemporal differentiation characteristics of landscape ecological risk and its driving mechanism in Southwest China and constructed a landscape ecological network. The results showed that the proportions of ecological space, production space and living space to the total space in 2020 were 74.35%, 24.55% and 1.10%, respectively. The industrial production space had the highest growth rate, increasing by 9.8 times from 2000 to 2020. During the study period, the average value of the ecological risk index ranged from 0.2 to 0.21 for the whole landscape. The geographical distribution of ecological risk zones showed significant differences, with risk zones showing a transition from high-risk and low-risk to medium-risk zones. A total of 105 ecological corridors and 156 ecological nodes have been constructed in the 2020 ecological network. The northeastern part of the study area needs better landscape connectivity and should be focused on ecological protection. Random Forest (RF) and Geodetector modeling showed that anthropogenic disturbance and land use levels have strong explanatory power for the evolution of ecological risk in the landscape. The interactions between anthropogenic disturbance, natural climate and regional economy are essential factors in the spatiotemporal differentiation of ecological risk. This study provides scientific references for ecological risk research and the promotion of high-quality development in Southwest China.

Dynamic risk evaluation of supersaturated dissolved gas at a confluence with unsteady flow conditions

Dynamic risk evaluation of supersaturated dissolved gas at a confluence with unsteady flow conditions

Flood risk transfer analysis based on the “Source-Sink” theory and its impact on ecological environment: A case study of the Poyang Lake Basin, China

Driven by climate change, the frequent occurrence of regional destructive floods poses a grave threat to socio-economic systems and ecological environments. Previous flood risk studies have disregarded risk transfer within a region, resulting in inadequate flood risk assessment and ineffective disaster prevention and mitigation outcomes. Therefore, this study introduced the "Source-Sink" theory into flood disaster field to constructing flood risk transfer model. Flood risk assessment and transfer was conducted in the Poyang Lake Basin, China, where the impacts of the initial and transfer statuses on ecosystem service values were quantified. The results showed that the flood risk in the Poyang Lake Basin was relatively low, with high spatial distribution characteristics in the central-north areas but low in the surrounding areas. High-risk zones were mainly distributed southwest of the Poyang Lake. The lower-risk zones exhibited a contiguous distribution and were surrounded by higher-risk zones. Following the completion of the flood risk transfer, high-risk zones increased significantly; but there were a few zones where the risk was transferred to other zones, thereby lowering their risks. Flood risk transfer occurs primarily in low- and medium-risk zones, with high-risk zones being the most important growth targets. The change in risk transfer was most evident in the area surrounding Poyang Lake, while that in the Upper Gan River Basin was lower and less sensitive to the transfer effect. Accounting for flood disaster risk, the ecosystem service values of the Poyang Lake Basin decreased by 8.18%, with the most significant impacts observed in the surrounding environment and southwest Poyang Lake. After the completion of the flood risk transfer, the ecosystem service value in the Poyang Lake Basin declined by 24.66%. This study provides a reference point for flood risk management and sustainable regional development that account for risk transfer.

Monitoring and Assessment of SBAS-InSAR Deformation for Sustainable Development of Closed Mining Areas—a Case of Nanzhuang Mining Area

Closed mining areas are an important potential resource, and rational use of them are critical to implementing sustainable development strategies. To guide the more reasonable development and utilization of the closed mining areas, we proposed a method of surface deformation monitoring and subsidence risk assessment of the closed mining areas with SBAS-InSAR technology. Based on the analysis of deformation, a risk assessment model integrating subsidence hazard and subsidence vulnerability was proposed. Subsidence hazard include accumulate deformation and the subsidence rate of the last year. The tunnels and the land use types are used to assess the subsidence vulnerability. This method can achieve deformation monitoring and risk assessment of the closed mining areas, and the proposed method is validated by taking the Nanzhuang mining areas as an example. The results showed that the main subsidence areas in the closed mining areas are located in the tunnel in the southwest and the gangue pile area in the northeast of the mining areas, while the deformation in the vegetation-rich forested area is low. The area of low, medium and high subsidence risk zones is 65.5%, 27.8% and 6.7% respectively.

Risk Assessment of Snow Disasters for Animal Husbandry on the Qinghai–Tibetan Plateau and Influences of Snow Disasters on the Well-Being of Farmers and Pastoralists

In the context of global warming, meteorological disasters occur more frequently in various regions which exert increasing influences on human life. Snow disasters are some of the natural disasters that most seriously affect the development of husbandry on the Qinghai–Tibetan Plateau (QTP), so it is necessary to explore their spatio-temporal variations and perform comprehensive risk assessment. Based on the daily snow depth data set in China, obtained by inversion of satellite remote sensing data, the spatio-temporal variation characteristics of snow disasters on the QTP from 1980 to 2019 were studied. The regional difference in the comprehensive risks of snow disasters for the husbandry on the QTP was evaluated from four perspectives, i.e., the risk of hazard factors, sensitivity of hazard-inducing environments, vulnerability of hazard-affected bodies, and disaster prevention and mitigation capacity. The farmer and pastoralist well-being (FPWB) index in five typical regions was constructed to discuss the possible influences of snow disasters on the FPWB since the 21st century. Results show that, in the last 40 years, the frequency, duration, average snow depth, and grade of snow disasters on the QTP all exhibited significant interannual and interdecadal variabilities, and they also displayed a declining long-term trend. The comprehensive risk of snow disasters for the husbandry on the QTP is low in the north while high in the south. The high-risk zone accounts for 1.54% of the total and is mainly located in Kashgar City in the north-western end of the QTP; the sub-high-risk and medium-risk zones are mainly found in the south of the plateau and are distributed in a tripole pattern, separately covering 15.96% and 16.32% of the total area of the plateau; the north of the plateau mainly belongs to low-risk and sub-low-risk zones, which separately account for 43.06% and 23.12% of the total area of the plateau. Since the beginning of the 21st century, the FPWB in five typical regions, namely, Kashgar (I), Shigatse (II), Nagqu (III), Qamdo (IV), and Yushu (V), has been increasing, while the risk of snow disasters has gradually decreased. Every 1% decrease in the risk of snow disasters corresponded to 0.186%, 0.768%, 0.378%, 0.109%, and 0.03% increases in the FPWB index in the five regions. Snow disasters affect FPWB mainly by directly or indirectly damaging material resources (livestock inventories and meat production) and social and financial resources.

Development of digital elevation model for assessment of flood vulnerable areas using Cartosat‐1 and GIS at Thamirabarani river, Tamilnadu, India

AbstractIn recent years, a considerable occurrence of floods at global level impacts the occupation and various segments of the economy. Flood vulnerability is the key paradigm in flood menace management. Assessment of flood vulnerability is essential to investigate the hypothetical onsets of vulnerability. Recent flood inundation in Thamirabarani river basin in Tirunelveli district, Tamil Nadu has caused devastating impacts to the lives around the river basin area. The proposed study integrated remote sensing and GIS techniques to produce flood map of flood inundation area in the nearby Thamirabarani river basin using Cartosat‐1 Satellite based Digital Elevation Model (DEM) derived by means of Leica Photogrammetry Suite to identify flood prone areas. A flow model was designed with the aid of DEM. The DEM classified the flood prone zones into high risk, medium risk and low risk zones using equal interval of classification based on elevation (buffer distance) from the river basin. Based on the nature and extent of flood, the remedial measures were classified as short‐ term, medium‐term and long‐ term measures. The proposed study has recommended some flood mitigation remedial measures to the district administration of Tirunelveli for managing the flood disaster caused during the monsoon rainfall.

Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model

Since 2019, the novel coronavirus has spread rapidly worldwide, greatly affecting social stability and human health. Pandemic prevention has become China’s primary task in responding to the transmission of COVID-19. Risk mapping and the proposal and implementation of epidemic prevention measures emphasize many research efforts. In this study, we collected location information for confirmed COVID-19 cases in Beijing, Shenyang, Dalian, and Shijiazhuang from 5 October 2020 to 5 January 2021, and selected 15 environmental variables to construct a model that comprehensively considered the parameters affecting the outbreak and spread of COVID-19 epidemics. Annual average temperature, catering, medical facilities, and other variables were processed using ArcGIS 10.3 and classified into three groups, including natural environmental variables, positive socio-environmental variables, and benign socio-environmental variables. We modeled the epidemic risk distribution for each area using the MaxEnt model based on the case occurrence data and environmental variables in four regions, and evaluated the key environmental variables influencing the epidemic distribution. The results showed that medium-risk zones were mainly distributed in Changping and Shunyi in Beijing, while Huanggu District in Shenyang and the southern part of Jinzhou District and the eastern part of Ganjingzi District in Dalian also represented areas at moderate risk of epidemics. For Shijiazhuang, Xinle, Gaocheng and other places were key COVID-19 epidemic spread areas. The jackknife assessment results revealed that positive socio-environmental variables are the most important factors affecting the outbreak and spread of COVID-19. The average contribution rate of the seafood market was 21.12%, and this contribution reached as high as 61.3% in Shenyang. The comprehensive analysis showed that improved seafood market management, strengthened crowd control and information recording, industry-catered specifications, and well-trained employees have become urgently needed prevention strategies in different regions. The comprehensive analysis indicated that the niche model could be used to classify the epidemic risk and propose prevention and control strategies when combined with the assessment results of the jackknife test, thus providing a theoretical basis and information support for suppressing the spread of COVID-19 epidemics.

Will Nurses’ Work Still be Valued after the COVID-19 Pandemic?

Many are the aspects we should ponder on, after 17 months from the burst of the COVID-19 pandemic, especially as nurses. Due to the numerous cuts to the public health sector in the last decades in Italy, the sanitary emergency has been a great sacrifice for health professionals, as public health was completely unprepared to withstand it. The Italian government reacted to this lack of preparation with exceptionally urgent measures. Although, these measures were implemented long after the initial state of confusion and of inappropriate management, they brought about stability and led to a containment strategy for the spread of the virus across the nation [1]. The reduction in the number of COVID-19 diagnoses was mainly achieved through social distancing. At first this was only required to a small number of communities affected by high infection rates, but was eventually extended to the rest of the country from March 2020 [2]. The national lockdown during the first COVID-19 wave (from March to May 2020), was replaced by regional lockdowns in the second wave (from November 2020). As of now, regional lockdowns are integrated by the vaccine campaign and Green Pass enforcement. In November 2020 the Italian Prime Minister at the time, issued legislative measures to enforce regional lockdowns, limiting nonessential movements, cafes, restaurants and other public places opening hours. This legislation established to classify the national territory in different levels of restriction based on the infection rate: red zones - highest risk of infection, orange zones - medium high risk and yellow zones with a minor risk of infection. A later legislation introduced the white zone for territories with the lowest risk of infection (DPCM-14th January 2021). The infection rate has been important to establish a region’s tier status; however, it is not the defining parameter anymore. A new legislation from July 2021 (n.105 - 23rd July 2021), opted to classify a region’s tier status according to the hospital bed’s occupancy rate for COVID-19 patients in intensive care and other medical areas.

Geological hazard interpretation and hazard evaluation of open pit mines based on Unmanned Aerial Vehicle images

Over-exploitation of open-pit mines has caused extensive development of geological hazards, posing serious threats to people and buildings in the area. Based on the UAV tilt-tilt photography technology, this paper generates a real-world 3D model of the study area, taking the molybdenum mine of Songshumao in Yangjiajiaozi, Xingcheng City, Liaoning Province as an example, and combines orthophotography, high-precision DEM data and field geological survey research to establish a geohazard interpretation marker for the study area and interpret various types of geohazards such as landslides, landslides, dangerous rocks, ground cracks and unstable slopes in the study area. Based on the hierarchical analysis method combined with the geological environment characteristics, the geological hazard risk evaluation model and index system were established, and five indexes were selected, including geological hazard range, stratigraphic lithology, slope, elevation, vegetation coverage, etc. The study area was divided into high, medium and low risk zones, and the geological hazard risk zoning map was obtained to complete the geological hazard risk evaluation of the study area.

Ecological risk analysis of countries along the belt and road based on LUCC: Taking Kuwait as a typical case

On account of the uneven level of ecological and environmental protection in the countries along the Belt and Road, infrastructure construction and investment cooperation around natural resource-intensive industries such as steel, energy, and nonferrous metals can easily induce serious ecological problems. It is necessary and practical to provide enterprises with timely and effective ecological circumstantial information of Belt and Road and pilot the establishment of the Belt and Road infrastructure construction activities with appropriate ecological risk prevention and control mechanisms. In this study, we researched the ecological risk level distribution of the countries along the Belt and Road by using ESA global land cover data and ecological risk index mode of land use. Kuwait, one of the most representative countries along the Belt and Road, was selected to analyze its spatial distribution of ecological risk by using ordinary Kriging interpolation. The results show several aspects. There existed high-ranking ecological risks in the following countries: Saudi Arabia in the Middle East, Turkmenistan in the Central Asian, Mongolia in East Asia and Pakistan in South Asia and so on; the medium ecological risks appear in the following countries: Ukraine in Eastern Europe, India, Bangladesh in South Asian, Kazakhstan and Kyrgyzstan in Central Asia the low ecological risk countries mainly include Russia, most Eastern European countries represented by Poland, and most Southeast Asian countries represented by Thailand. In the case, Kuwait's risk level is high in urban areas, medium in desert areas, and low along the Persian Gulf, showing a layered and striped distribution. Most areas in Kuwait are medium ecological risk zones with a relatively small area of high ecological risk and low ecological risk areas clustered in the eastern part of Kuwait. To effectively lower the ecological risk levels of countries along B&R, we suggest establishing B&R ecological risk prevention and control mechanisms while ecological conservation technologies are also worth noting.

Multidimensional dynamic healthcare personnel (HCP)-centric model from a low-income and middle-income country to support and protect COVID-19 warriors: a large prospective cohort study

ObjectivesHealthcare personnel (HCP) are at an increased risk of acquiring COVID-19 infection especially in resource-restricted healthcare settings, and return to homes unfit for self-isolation, making them apprehensive about COVID-19 duty...

Saving and Supporting Health Care Workers During the COVID-19 Pandemic in a Developing Country Using a Multidimensional Healthcare Personnel Centric Policy

Background: Health care personnel (HCP) are at an increased risk of acquiring COVID infection during this pandemic especially in developing countries like India, where they work in resource restricted healthcare settings and return to homes, unfit for safe self-isolation. Thus, many HCP were reluctant to accept COVID-19 duty as they were apprehensive about their safety and concerned about carrying the infection home to their families.Methods: We describe a novel multidimensional HCP-centric evidence-based, dynamic policy to address the expressed concerns of HCPs. The hospital was divided into three zones: high, medium, and low risk zones. In the high risk and medium risk zones, we organized pre-duty holistic training, provided on-duty support, ensured post duty HCP welfare, and send them all home after they tested negative for COVID-19. To minimize transmission, we provided appropriate PPE, ensured its proper use, kept all communication paperless. To reduce morbidity, we recruited only willing low risk HCP, aged Findings: Between 31st March-20th July 2020, we clinically screened 5553 outpatients, of whom 3012 (54.2%) were COVID suspects and they were kept in the medium risk zone. Among them, 346(11.4%) were COVID+ve (57.2% male) and managed in the high-risk zone of whom 19(5.4%) died. One ( 0.08%) of the 1224 HCP in high-risk zone tested positive; 6(0.62%) of the 960 HCP in medium risk zone and 23(0.18%) of the 12600 HCP in the low risk zone. All the 30 COVID +ve HCP have since recovered and none were critically ill.This multidimensional HCP centric policy resulted in very low transmission rates Interpretation: A multidimensional HCP centric policy was effective in ensuring safety, satisfaction, and welfare of HCP in a resource poor setting and resulted in a willing workforce to fight the pandemic.Funding Statement: None.Declaration of Interests: None of the authors has any conflict of interest to declare.Ethics Approval Statement: Ethical clearance for reporting the results of our HCP protocol and feedback was taken from the Institutional Ethics Committee (Letter No INT/IEC/2020/SPL997; Dated 25.07.2020) and the need for individual informed consent was waived. This retrospective study was conducted in accordance with the Declaration of Helsinki and ICMR guidelines.

Zoneamento de incêndios florestais na estação ecológica Águas Emendadas, Distrito Federal (Brasil)

O aumento no número de ocorrências de incêndios florestais no bioma Cerrado é considerado uma ameaça à sua conservação. Dessa forma, as áreas protegidas por meio das Unidades de Conservação (UC) são fundamentais para a proteção dos biomas brasileiros. No entanto, mesmo essas áreas são acometidas por incêndios que comprometem suas integridades. Neste sentido, este estudo teve como objetivo elaborar o zoneamento do risco de incêndio florestal da UC Estação Ecológica Águas Emendadas por meio do método multicritério aditivo, validá-lo com as cicatrizes dos incêndios ocorridos entre os anos de 2011 a 2015 e avaliar a espacialidade do risco a incêndios florestais. Foi observado que nenhuma área da UC estudada foi classificada como zona de risco Extremo, no entanto mais de 60% da UC foi classificada em zonas de Alto ou Muito Alto risco a incêndios. A validação mostrou que 80% dos incêndios ocorreram sobre áreas com risco mediano a incêndios florestais como formações savânicas ou campestres. Foi obtido um Índice Global de Moran para o risco de incêndios florestais no valor de 0.83 indicando uma elevada autorrelação espacial, além disso, o Índice Local de Moran identificou como regiões mais críticas as áreas de interface de vegetação nativa e áreas urbanas.

Reclaimed Asphalt Pavement (RAP) Based on a Geospatial Information System (GIS)

Abstract A Geospatial Information System (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geospatial data. Reclaimed Asphalt Pavement (RAP) based on the GIS is one of the indirect and efficient methods in identifying areas. In this work, an analytical computational process combined with a spatial analysis was used to identify pavement zones for a city. The zoning results were categorized in four classes, including very high, high, medium risk, and low risk zones. The high and very high risk zones have been considered as a whole. The work circumstances include the Mean Profile Depth (MPD) data as a function of the number of wheel passes and the temperature; ten (10) specimens were selected from a set of 23 specimens. The results showed a good correlation between the parameters, including the number of wheels passing, the temperature, and the MPD.

Geotecnologias aplicadas na análise do risco de contaminação de poços de água no município de Sorocaba, SP

Em decorrência do crescimento da cidade de Sorocaba e da quantidade de empresas que se instalam todos os anos no município, o presente estudo teve como objetivo avaliar os riscos de contaminação dos poços de água próximos a áreas contaminadas utilizando técnicas de geoprocessamento. Para o levantamento das áreas contaminadas foi utilizado o inventário disponibilizado pela Companhia Ambiental do Estado de São Paulo (CETESB), e a localização dos poços outorgados do município foram obtidos através da base de dados do Departamento de Águas e Energia Elétrica (DAEE). A concentração de áreas contaminadas foi avaliada por meio do estimador de densidade de Kernel, e os valores foram ordenados em três diferentes classes de riscos de contaminação, sendo baixo, médio e alto. Os resultados demonstraram que 17,3% das áreas contaminadas estão inseridas na zona de alto risco, enquanto as zonas de risco médio obtiveram 50,0% dos pontos de contaminação. As zonas de alto e médio risco contemplam 57 poços de água, apresentando riscos de contaminação eminentes, podendo comprometer a saúde humana a partir do consumo e uso da água destes poços. A utilização de ferramentas de geoprocessamento na análise de riscos de contaminação mostrou-se eficaz, permitindo a seleção de zonas prioritárias para a gestão e monitoramento de poços de água.

A New Method to Assess Coal Burst Risks Using Dynamic and Static Loading Analysis

Mining-induced seismicity is one of the dynamic energy sources that can trigger coal burst. This paper presents a new methodology to assess coal burst risks under different loading conditions by examining seismic energy attenuation and fracture size. Two new indices are proposed: (1) Dynamic Load Index (DLI) quantifies the magnitude of dynamic loading induced by seismic events, based on the relationships between the seismic energy, peak particle velocity and dynamic stress; (2) dynamic–static loading assessment index, $$I_{\text{PD}}$$, links the DLI with passive velocity tomography (PVT) to assess the coal burst risks in a longwall panel under dynamic and static loading. A total of 3080 seismic records were examined to validate $$I_{\text{PD}}$$ in a typical burst-prone longwall panel in China. Based on the rate of occurrence of high-magnitude seismic events, $$I_{\text{PD}}$$ thresholds were determined to identify low-, medium- and high-risk coal burst zones. Using this new zoning approach, coal burst risks were assessed in the same longwall panel while mining through a fault structure. The proposed risk classes correlated well with the recorded high-magnitude seismic events with energies over 10 kJ. The analysis indicated that 69% of the high-magnitude events occurred in the high-risk zones, where $$I_{\text{PD}}$$ was between 0.35 and 1; and 31% of the events occurred in the medium-risk zones, where $$I_{\text{PD}}$$ was between 0.2 and 0.35.

Risk Assessment of An Earthquake-Collapse-Landslide Disaster Chain by Bayesian Network and Newmark Models.

Severe natural disasters and related secondary disasters are a huge menace to society. Currently, it is difficult to identify risk formation mechanisms and quantitatively evaluate the risks associated with disaster chains; thus, there is a need to further develop relevant risk assessment methods. In this research, we propose an earthquake disaster chain risk evaluation method that couples Bayesian network and Newmark models that are based on natural hazard risk formation theory with the aim of identifying the influence of earthquake disaster chains. This new method effectively considers two risk elements: hazard and vulnerability, and hazard analysis, which includes chain probability analysis and hazard intensity analysis. The chain probability of adjacent disasters was obtained from the Bayesian network model, and the permanent displacement that was applied to represent the potential hazard intensity was calculated by the Newmark model. To validate the method, the Changbai Mountain volcano earthquake–collapse–landslide disaster chain was selected as a case study. The risk assessment results showed that the high-and medium-risk zones were predominantly located within a 10 km radius of Tianchi, and that other regions within the study area were mainly associated with very low-to low-risk values. The verified results of the reported method showed that the area of the receiver operating characteristic (ROC) curve was 0.817, which indicates that the method is very effective for earthquake disaster chain risk recognition and assessment.

Probabilistic modelling of wildfire occurrence based on logistic regression, Niassa Reserve, Mozambique

Fires are one of the main factors for disturbances in Niassa Reserve-Mozambique, with economic and environmental impacts. There are cyclical records of fire occurrences across the reserve. However, studies on the main causative factors and identification of more susceptible locations are very limited. In this perspective, this study had as objectives: (1) determine the main significant factors for wildfire occurrences; (2) Map the probability of wildfire occurrences, using logistic regression. Independent variables included vegetation index (NDVI), climatic, topographic and socioeconomic data. The analysis period was from 2001 to 2015 and comprised the months with more occurrences of wildfire (May to December). According to the results, the main factors that determine the occurrence of fires were: NDVI, temperature, elevation, followed by precipitation, slope, relative humidity and human settlements. The spatial distribution of probability of fire occurrence reveals that zones with high and very high risk are located at the west and central west zones (areas with higher accumulation of dry biomass); medium risk zones are located in the centre of the reserve, while in central east and east zones the probability of fire occurrence is low and very low risk. Results showed that the expectation of wildfire ignition using logistic regression presented good precision (area under the curve 74%).

Seismic Response of Cold Formed Steel Frames Sheathed by Fiber Cement Boards

In this paper, the seismic performance of cold formed steel shear walls sheathed by fiber cement boards (FCB) is investigated. Of particular interest is the seismic response modification factor of FCB shear walls. Nonlinear incremental dynamic analyses of multi-story cold formed steel framed structures were carried out following an approach adopted by FEMA-P695 on the description of building seismic behavior. Different scaled earthquake records in three different earthquake prone regions located on low, medium and high seismic risk zones in Iran were taken into account. One, two and three story CFS archetype buildings were analyzed using models created in OpenSees software to predict structural performance of the buildings. Nonlinear dynamic time history analyses were carried out employing OpenSees software utilizing 2D models of a FCB braced wall tower. A stick model was created whose behavior was fitted to the lateral resistance versus deformation of each story that braced elements in the model. The elements were defined via material Pinching4 to construct a uniaxial material exhibiting pinched load-deformation response and demonstrate degradation under cyclic loading. The results show that most relevant codes which suggest the value of seismic response modification factor equal to 2 for cold formed steel shear walls sheathed by FCB are acceptable only for up to three story buildings in low seismic risk zone, up to two story in medium seismic zone and one story in high seismic risk zone.