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The approach to evaluation of health risks to aviation crew discussed in this paper is an alternative to the common clinical practice, i.e. stratification of the risks of diseases and complications which is sometimes underestimated by members of aircrew medical certification boards. The approach consists of ranking health issues by severity and impact on flight safety, and risk probability. The updated risk evaluation matrix was used successfully in cardiovascular diagnostics of aircrews. In aeromedicine, this approach is aimed at objective cardiovascular risk evaluation and prevention of accidents and serious incidents in consequence of problems with the cabin crew health.

Teknolojinin hızla büyümesi ile artan fosil yakıt tüketimine bağlı olarak oluşan hava kirliliği ve küresel ısınma, bir çok ülke için büyük sorun oluşturan problemlerdendir. Bu sorunlarla başa çıkmak için, yenilenebilir kaynakları içeren dağıtık enerji kaynakları (DEK), modern güç sistemlerine geleneksel üretime alternatif olarak eklenmektedirler. Bununla birlikte, rüzgâr enerjisi ve fotovoltaik enerji gibi bazı kaynakların belirsiz doğası, güç sisteminin değişken çıkışına ve kararsızlığına yol açmaktadır. Sanal Güç Santrali (SGS), güç sistemindeki bu zorlukların üstesinden gelmek için uygun bir çözümdür. SGS, yenilenebilir ve yakıt bazlı üretim sistemleri, depolama sistemleri ve yönetilebilir yüklerden oluşan dağıtık enerji kaynaklarını bir araya toplamaktadır. Bu çalışmada, bir Rüzgâr Enerjisi Santrali (RES), bir Fotovoltaik Enerji Santrali (FVES), bir Konvansiyonel Enerji Santrali (KES) ve bir Pompaj Depolamalı Hidroelektrik Santral (PDHS) içeren bir SGS'nin optimum işletme stratejisi, Gün Öncesi Piyasasında (GÖP) maksimum kâr elde edecek şekilde belirlenmiştir. Kesintili yenilenebilir enerji üretimi için belirsizlik analizi, belirsiz parametrelerin (rüzgâr hızı ve güneş radyasyonu) geçmiş verilere dayanan senaryolarla modellenmesi ile yapılmıştır. Ayrıca, düşük kâr senaryoları riski, bir risk ölçütü olan Koşullu Riske Maruz Değer (CVaR) kullanılarak değerlendirilmiştir., The air pollution and global warming because of the increasing usage of fossil fuels with the rapid growth of technology are one of the major problems for many countries. To cope with these problems, distributed energy resources (DERs) including renewable sources are adding into the modern power systems as an alternative to traditional generation. However, the uncertain nature of some sources such as wind power and photovoltaic power leads to variable output and instability of the power system. Virtual Power Plant (VPP) is a convenient solution to overcome these challenges in the power system. It aggregates various DERs including renewable-based and fueled-based generation, storage systems and dispatchable loads. In this study, optimum operating strategy of a VPP consisting of a Wind Power Plant (WPP), a Photovoltaic Power Plant (PVPP), a Conventional Power Plant (CPP) and a Pumped Hydro Storage Plant (PHSP) is determined to maximize the profit in a Day Ahead Market (DAM). The uncertainty analysis for the intermittent renewable power generation is made by modeling the uncertain parameters (wind speed and solar radiation) with scenarios based upon historical data. Moreover, the risk of low profit scenarios is evaluated by using Conditional Value at Risk (CVaR) as a risk measure.

Failure mode and effects analysis (FMEA) is one of the most important risk assessment tools which has been extensively used in different industries and organizations. In the conventional FMEA, sometimes the difference between some failure modes cannot be distinguished. In order to evaluate various failure modes more precisely, a novel fuzzy hybrid model for FMEA is proposed in this paper. In this method, fuzzy weighted risk priority number (FWRPN) is considered instead of RPN for each failure. The weights of the three factors and the weights of failure modes are computed by extended fuzzy AHP and fuzzy MULTIMOORA methods, respectively. The proposed fuzzy MULTIMOORA method calculates the weight of each failure based on three criteria of time, cost, and profit through fuzzy linguistic terms. After calculating FWRPN for each failure, corrective actions are performed for eliminating the identified failures or decreasing the effects of them. Then, corrected fuzzy weighted risk priority number (CFWRPN) is computed for each failure. Finally, the average of FWRPNs (AFWRPNs) with the average of CFWRPNs (ACFWRPNs) are compared to evaluate the effectiveness of corrective actions by a novel ranking fuzzy numbers method. In addition, the proposed ranking fuzzy number method is also used in both previously mentioned fuzzy multi-criteria decision making (MCDM) methods. Eventually, Kerman Steel Industries Factory is considered as a case study to demonstrate the applicability and benefits of the proposed fuzzy hybrid method. A sensitivity analysis is performed to validate the obtained results. Findings show that AFWRPNs decreased by 56% compared to ACFWRPNs.

Risk response planning is a widely concerned issue. Project managers usually struggle to control different kinds of risks. In project risk management, after evaluating risks, the final process relates to choosing desirable responses to the risks. In this paper, a comprehensive framework confronts the issue in three main phases. In the first phase, all the risks, responses and their relations in a geothermal drilling project are detected. These relations imply there are inner dependent and outer dependent relations. In the second phase, ANP, DEMATEL and fuzzy theory play important roles in weighting risks and responses. In the third phase, to enable a more realistic solution, a zero-one integer programming reflects a budget constraint and other required constraints. After obtaining the optimal responses, the effect of budget is analyzed. In addition, the influences of risks on each other are discussed more deeply. Collectively, this study offers a new perspective on how to handle project risks and choose their responses.

Failure mode and effects analysis (FMEA) is a structured method used during a given stage of the system life cycle to understand all probable failure modes and the effects of their occurrences. The risk priority number (RPN) is calculated in FMEA to select more critical failure modes by multiplying three factors: occurrence, detection, and severity. In the literature, these three factors are defined qualitatively without any underlying model, and multiple definitions and conflicting interpretations exist for each factor. As the interrelationships between the three RPN factors are not known, previous research has treated each factor as a criterion in multiple criteria decision making, under the assumption that the three factors are independent of each other. In this paper, we present a general model to explain the functional relationship among the three factors. Using the model, we discuss the unique role of each factor for comparing the risk of different failure modes.

Tripping-related falls are the leading cause of unintentional deaths in the elderly. Tripping risk must be evaluated by considering intrinsic and extrinsic factors affecting the interactions between humans and the environment. The goal of this study is to develop a new tripping risk evaluation system based on human behavior simulation in an “as-is” environment model, i.e., environment model reflecting detailed environmental geometry. First, a three-dimensional (3D) as-is environment model is automatically constructed from laser-scanned point clouds in the environment. From this model, potential tripping-hazard regions are automatically detected. Finally, the tripping risk of detected hazard region is quantitatively evaluated based on a combined human behavior and Monte Carlo simulation. The simulated tripping risk is compared with that measured using real humans, and it is revealed that the dimensional limit of risk evaluation accuracy in terms of barrier height on a walking terrain is very close to 10 mm.

The presented work deals with hygro-thermal numerical simulation and mould growth risk evaluation between concrete foundation and frame of multi-story building made of CLT element modules. Structural CLT modules represent an approach towards wood material utilization in construction as its strength achieves markedly higher values then common structural wooden elements and makes rapid erection of the building possible. Although there are great promises that the novel CLT structures will gain ground in high-rise buildings market with apparent benefits in sustainability and inhabitant comments regarding ambience and acoustics, it is important to analyse their structural health and hygro-thermal conditions. The highest risk of unfavourable hygro-thermal conditions is usually presented in location characterized by thermal bridge, such as foundation, window-wall, wall-roof and wall-floor junctions. It is also of significant importance to analyse junctions between materials, whether wood, composite, mortar or concrete. A certain combination of thermal and humidity conditions in exposed time causes mould growth initiation that may lead to deterioration of structural material and unhealthy indoor environment. In this case study, the moisture content and air-flow in the junction and open space in structural design details between the first floor (of concrete) housing joint warehouse and technical spaces and the residential upper floors made of CLT modules is analysed. Conditions leading to probable moisture-derived mould issues and design parameters leading to sufficient ventilation according to Mould Index modelling are presented.

In order to set up a mathematical model suitable for nautical navigational environment risk evaluation and systematically master the navigational environment risk characteristics of the Qiongzhou Strait in a quantitative way, a risk assessment model with approach steps is set up based on the grey fixed weight cluster (GFWC). The evaluation index system is structured scientifically through both literature review and expert investigation. The relative weight of each index is designed to be obtained via fuzzy analytic hierarchy process (FAHP); Index membership degree of every grey class is proposed to be achieved by fuzzy statistics (FS) to avoid the difficulty of building whiten weight functions. By using the model, nautical navigational environment risk of the Qiongzhou Strait is determined at a “moderate” level according to the principle of maximum membership degree. The comprehensive risk evaluation of the Qiongzhou Strait nautical navigational environment can provide theoretical reference for implementing targeted risk control measures. It shows that the constructed GFWC risk assessment model as well as the presented steps are workable in case of incomplete information. The proposed strategy can excavate the collected experts’ knowledge mathematically, quantify the weight of each index and risk level, and finally lead to a comprehensive risk evaluation result. Besides, the adoptions of probability and statistic theory, fuzzy theory, aiming at solving the bottlenecks in case of uncertainty, will give the model a better adaptability and executability.

Cascading failure forecast of complex power grids is the premise of revealing the propagation mechanism of power system blackouts, keeping cascading failures from wantonly spreading and developing early preventive strategies against cascading failures. This paper summarizes the existing cascading failure forecast methods, and introduces the application of pattern search method, model method and risk evaluation method to cascading failure forecast of power grids in detail. Finally, the paper proposes the future research direction of cascading failure forecast of complex grids according to the present research.

As reliability requirements become increasingly demanding for many engineering systems, conventional system reliability demonstration testing (SRDT) based on the number of failures depends on a large sample of system units. However, for many safety critical systems, such as missiles, it is prohibitive to perform such testing with large samples. To reduce the sample size, existing SRDT methods utilize test data from either system level or component level. In this paper, an aggregation-based SRDT methodology is proposed for hierarchical systems by utilizing multilevel reliability information of components, subsystems, and the overall system. Analytical conditions are identified for the proposed method to achieve lower consumer risk. The performances of different SRDT design strategies are evaluated and compared according to their consumer risks. A numerical case study is presented to illustrate the proposed methodology and demonstrate its validity and effectiveness.

The potential risks of the increasing variety and volume of engineered nanomaterials (ENMs) entering into the ecosystem remain poorly quantified. In recent years, information essential to evaluate the ecological risks of ENMs has increased. However, the data are highly fragmented, limited, or severely lacking. This limits the usefulness of the information to support holistic screening and prioritization of potentially harmful ENMs. To screen and prioritize ENMs risks, we adopted a two-phased approach. First, a holistic framework model was developed to integrate a diverse set of factors aimed to assess the potential hazard, exposure, and in turn, risk to the ecosystem of ENMs from a given consumer nanoproduct. Secondly, using published literature we created a database of consumer nanoproduct categories, and types based on embedded ENMs type. The database consisted of eight consumer product categories, eleven different types of ENMs, and twenty-three nanoproduct types. The model results indicates the largest quantities of ENMs were released from sunscreens, textiles, cosmetics and paints with dominant ENMs quantities in descending order (based on quantity) as nTiO2 > nZnO > nSiO2 > nAg, and nFe2O3. In addition, according to the results from this study, nAg from washing machine were found to likely the highest risk to the environment. Overall, our model-derived results based on the case study illustrated: (i) the holistic framework's ability to screen, prioritize, rank, and compare ENMs potential exposure and risks among different nanoproducts categories and types, (ii) the derived risk estimations could support nanowastes classification with likelihood of non-uniformity of nanowastes classes even from the same nanoproduct category (e.g. cosmetics), and (iii) the lack of a mass-based criteria specific for EMNs impedes realistic exposure and risk evaluation in the ecological systems. Keywords: Aquatic systems, Hazard, Exposure assessment, Nanowastes, Analytic hierarchy, ENMs risk ranking

With the increment for liquefied natural gas (LNG) demand, LNG carriers are becoming larger in size. The operational safety of the carriers and the associated terminals is increasingly attracting attention. This is particularly true when a large LNG vessel approaches a terminal, requiring a detailed investigation of ship handling in port waters, especially in certain unusual cases. A full mission simulator provides an effective tool for research and training in operations of both port terminals and ships. This paper presents an experimental design methodology of the full mission simulation. The details as to how the simulation is achieved are described, and the simulation strategies applicable to LNG ships are specified. A typical case study is used to demonstrate and verify the proposed design methodology. The proposed methodology of the full mission simulation provides guidance for port safety research, risk evaluation and seafarer training. © 2017 Institute of Marine Engineering, Science & Technology

The stampede happened in Shanghai bund in 2014 is wailsome and the “crowded condition” in Guangzhou Lighting Festival in 2012 is still vivid in our mind. As one of the biggest stadiums in China, the number of audience of each ball game in Tianhe Sports Center was more than 40,000. Is there a potential of large stampede resulted in by so huge crowd gathered? This paper tries to study and clean up the characteristics of disaster-bearing body, disaster-pregnant environment and disaster-causing factors through literatures by virtue of the theory of crisis cause model, establish risk evaluation index by using analytical hierarchy process and further research the potential of large stampede happened in Tianhe Sports Center by taking Tianhe Sports Center as the example and combining with field survey.

This research aims at developing methods to meet safety targets for sense and avoid (SAA) sensors of unmanned aircraft systems (UAS) through integrity and continuity risk evaluation. This paper bui...

The paper demonstrated and discussed a methodology to evaluate evacuation capacity of urban underground road by considering the system from a series of important views (i.e. guiding system, evacuation facility, evacuation management, etc). Due to the different nature of the criteria involved in the assessment activity, the Analytic Hierarchy Process and the set-valued statistics methodology had been chosen to compare and appraise those indexes that are incommensurable and may originate from distinct and separate areas. And then the fuzzy comprehensive evaluation model was developed by risk evaluation and calculation of emergency evacuation capacity, which is beneficial to find the most effective way to enhance evacuation capacity. Finally, a case of urban underground ring road in Chongqing, China was analyzed using the established model in order to find the most effective way to improve the evacuation capacity.

Background: The widespread application of nanotechnology in the last decades, the increasing likelihood of human exposure to nano-sized materials, together with the still limited knowledge concerning their toxicological profile, require a careful risk assessment, particularly in occupational settings. However, a specific “risk assessment paradigm” for these peculiar xenobiotics has not yet been defined. Objective: The aim of this review was to address those critical aspects that currently prevent the achievement of a suitable risk evaluation in order to point out priorities of research helpful to develop and implement an effective guidance for nano-risk assessment. Method: Literature search concerning NM physico-chemical characterization, toxicological behavior and exposure assessment strategies was analyzed to extrapolate opportunities, challenges and criticisms in the application of the general chemical risk assessment steps to the nano-sized toxicological field. Results: Uncertainties on the role of the physico-chemical properties in nanomaterial toxicity, the complexity in extrapolating dose-response relationships, and practical difficulties in measuring nanomaterial exposure emerged as challenging issues for the application of a traditional risk assessment approach to nano-sized exposures. Conclusion: Future investigations on these topics appear necessary to define an effective, nanofocused risk evaluation strategy that should be dynamically improved and verified as more substantial information become available. Such a suitable risk assessment process should provide adequate estimates of nanomaterial risks to guide the adoption of appropriate risk communication and management strategies for the protection and the safety of the workers.

With the deepening of the reform of national defense and the military, the defense strength of China has been greatly enhanced, and the number of military engineering projects has also increased year by year. The complexity and large-scale construction of engineering projects make it difficult for the traditional military’s engineering project management to meet current needs. This puts forward higher requirements for the military’s engineering project management ideas and methods. The refined and intelligent military engineering project management has become our military’s Matters that need to be focused on. Building Information Modeling (BIM) is a hot technology and a new production management method in the current construction industry, which provides us with a more advanced and intelligent military engineering construction project management idea. This paper identifies the risks of applying BIM technology to military engineering projects by consulting a large amount of data, and uses SPSS software to conduct neural network analysis of the identified risks and proposes corresponding measures to promote the extensive use of BIM in military engineering project management.

Construction projects are risky in both physical implementation and management. The characteristics of the risk reinforce the necessity of efficient management to increase the chances of success without commitment to its goals. This study explores the correlation of delay and the schedule performance index (SPI) to evaluate the risk of a construction project completed with time overruns. The hypothesis that the SPI of projects with a delay is distinct from those projects without a delay is assumed. A database with 19 elements was used to test this hypothesis and to calculate limit values to the SPI. Therefore, the risk of delay will be small when the observed SPI is greater than the superior limit and large when the SPI is below the inferior limit. The simplicity involved in the calculation of these values showed an advantage in comparison with other methods of risk evaluation. Another strong point observed is that any company can determine the value of risk by considering its own history and support decisions like doing corrective actions.

This paper describes a risk evaluation method for RC (ramping capability) shortage. Two major uncertainties in power systems are considered: failure of generating units and NLFE (net load forecast error). The failure probability of generating units is calculated using a Markov-chain-based capacity state model. The NLFE is assumed to follow a normal distribution, which is represented using a seven-step approximation. The risk of RC shortage is evaluated using an index termed the RSE (RC shortage expectation), which is defined as the sum of the probabilities that the RC requirement will be not satisfied by the system. A case study was then carried out using a modified IEEE-RTS-96 to investigate the applicability of the method. Sensitivity analysis was performed to determine the relationship between the RSE and the installed capacity of wind farms, the reserve requirement, and the failure rate of the largest unit.

Water and mud inrush is one of the typical geological disasters during tunnel construction in karst areas. In order to effectively control the water and mud inrush risk and guarantee the safety of tunnel construction, an unascertained measure model of water and mud inrush risk evaluation is established based on unascertained measure theory. First, according to geological factors and engineering factors in tunnel zone, unfavorable geology, formation lithology, ground water level, topography and geomorphology, attitude of rocks, contact zones between soluble rock and non-soluble rock, crack in rock stratum, surrounding rock grade, construction technology level, and management level are selected as risk evaluation indexes of water and mud inrush, which constitutes the index system of water and mud inrush risk evaluation. Through collecting and collating information of typical water and mud inrush examples of karst tunnels, the uncertainty measure function of each evaluation index is obtained based on the measured data. Meanwhile, the index weight of each factor is ascertained by entropy-information theory, and the risk grade of water and mud inrush is judged by credible degree recognition criteria. In engineering application, the water and mud inrush risk of Qiyueshan tunnel is evaluated based on the established unascertained measure model. The results show that: (1) The evaluation results agree well with practical construction situation. (2) The unascertained measure model is scientific and reasonable, which can achieve the risk level evaluation of water and mud inrush systematically. (3) The unascertained measure model provides an effective method for water and mud inrush risk evaluation of karst tunnels, which can be applied to practical engineering.

Risk management is understood as a process supporting decision making through systemic assessment of possible courses of action, identification of hazards and benefits, and indication of the best way to carry out aviation tasks. The article presents a method of qualitative and quantitative risk assessment on the basis of military aviation incident analysis. The procedure of the suggested approach is contained in a probability and severity degree estimation algorithm and in subsequent steps: of identifying the risk factor (CZN) of a given category, analysis of risk associated with a given CZN, determination of risk, defining correcting actions, risk forecasting and its verification over the following assessment period. A simplified block diagram presents a proposal of the implementation of a qualitative and quantitative risk estimation procedure with the use of the TURAWA IT system, which function in the air forces.

MERLIN-Expo merges and integrates advanced exposure assessment methodologies, allowing the building of complex scenarios involving several pollution sources and targets. The assessment of exposure and risks to human health from chemicals is of major concern for policy and ultimately benefits all citizens. The development and operational fusion of the advanced exposure assessment methodologies envisaged in the MERLIN-Expo tool will have a significant impact in the long term on several policies dealing with chemical safety management. There are more than 30 agencies in Europe related to exposure and risk evaluation of chemicals, which have an important role in implementing EU policies, having especially tasks of technical, scientific, operational and/or regulatory nature. The main purpose of the present paper is to introduce MERLIN-Expo and to highlight its potential for being effectively integrated within the group of tools available to assess the risk and exposure of chemicals for EU policy. The main results show that the tool is highly suitable for use in site-specific or local impact assessment, with minor modifications it can also be used for Plant Protection Products (PPPs), biocides and REACH, while major additions would be required for a comprehensive application in the field of consumer and worker exposure assessment.

The routine method using statistical analysis theory with enough historical data to predict risk factor probability (index failure probability) has defects, as historical data, especially the ones that far away from today, often can not precisely reflect the current situation of the gas network. Therefore, the risk factor probability should be predicted or evaluated by rational using the historical data and combining with the current situation. This paper presented a risk factor probability comprehensive evaluation model which considers historical data as well as the experts' analysis of the object system in recent years, namely, the risk factor probability evaluation model based on information revision, and employed for risk evaluation of the city gas transmission and distribution system with a case study.

This paper provides new integrity and continuity risk evaluation methods for fault detection and exclusion (FDE) using receiver autonomous integrity monitoring (RAIM). These methods are developed for both solution separation (SS) and Chi-squared RAIM: they capture the fact that exclusion enables continuity risk reduction in exchange for a higher integrity risk. The two approaches are implemented in an example advanced RAIM (ARAIM) application for worldwide vertical guidance of aircraft using multiconstellation Global Navigation Satellite Systems (GNSS).

Given the security problems of the urban rail transportation, this paper proposes a methodology for congestion risk evaluation and precaution in order to guarantee the safety of passengers and improve the operation efficiency in metro stations. To begin with, we selected the retention rate of the platform, the waiting rate of the ticket gate and the transfer efficiency as the indexes for the station congestion precaution system and created models to calculate the threshold respectively. By reasonably combining these three indexes, a congestion warning level function was set up to evaluate the congestion risk and determine the warning level. The characteristics of the proposed model are its quick decision results and ease of handling. With the determined warning level, some strategies are suggested to relieve the pressure. Finally, a practical application in Beijing’s GuoMao metro station was performed to verify the feasibility and practicability of the proposed congestion precaution model.

The paper proposes a framework for the selection of optimal configuration of line compensation devices, thyristor controlled series capacitors (TCSC) and conventional fixed series capacitors, for reducing the risk of subsynchronous resonance (SSR) in the network while maintaining required power transfer. The methodology developed in the paper is based on the robust risk evaluation of SSR that takes into consideration the severity of subsynchronous resonance and probability of its occurrence. The subsynchronous resonance risk index developed previously is used to assess the severity of subsynchronous resonance. The line outage model is employed to determine the probability of contingencies potentially leading to subsynchronous resonance. It is demonstrated that with relatively small participation of TCSC, even with the most basic control, in series compensation of lines, the risk of SSR can be successfully managed.

In this paper, the authors introduce a new risk evaluation model for evaluating the navigation safety zone for an entire ship route. This model considers a new algorithm to determine the navigational safety zone in real-time, and also takes the navigation officers’ perception while navigating a ship into consideration. The risk quantification has been developed using a questionnaire and incorporated into the new model. A simulation was carried out for the Osaka bay area in order to verify the usefulness of the proposed model. A new approach was employed to monitor the level of navigation safety along a ship route. The entire ship route is divided into small sections as a gridded matrix. The level of navigation safety can be quantified by means of a safety index on the basis of the ship’s navigation data within a specified distance range. The results show that the comparison between risks identified for different sections across the entire ship route is easy, which helps determine the navigational safety zone quickly. This model is expected to be able to serve as a new tool for managing safety throughout an entire ship route area in real-time in order to support the port safety authority or vessel traffic service center.

In this study, an analytical framework is developed to determine the hazards posed by an uncontrolled fire burning indoors. This scenario, unlike unconfined outdoor fires, has received little attention in the literature and associated engineering methods for risk evaluation are unavailable. The present analyses are limited to overventilated fires burning in large non-combustible buildings. Hazards are evaluated on the basis of thermal radiation and firebrand transport. Thermal radiation is assessed using a solid flame radiation model; transport of firebrands is evaluated taking into consideration the convective ceiling layer established by the fire plume. Given the considerably different geometry of the scenario of interest herein, as compared to unconfined fires, efforts are placed in developing a rigorous physical and mathematical approach so as to make the developed methodology sufficiently general. The model derived is validated against limited heat flux data obtained for free-burn fires (up to 50 MW) involving Class 2 commodity rack storage arrays. In addition, general trends are investigated using a hypothetical sample scenario. Results show that thermal radiation is the main phenomenon driving the hazards encountered in indoor fires; firebrand transport, due to ceiling confinement, presents a much lesser hazard.

Aim: To identify the possible risks associated with critical quality attribute of combined eye drops for the treatment of glaucoma using of common risk evaluation methodologies for plannig a drug quality on the stage of pharmaceutical development. Methods: The paper used method of causal analysis. The maximal number of factors has been define to identify potential factors that provide most significant impact on the drug quality and Ishikawa diagram - graphical representation of causes and effects has been built.Results: Analysis allowed to organize the possible factors affecting the drug quality in the generalized categories: quality control methods, medicines and excipients, primary packaging, proper manufacturing conditions and the stage of the process. The most important factors that are carriers of the risk factors and may lead to negative effects have been identified for the generalized categories.Conclusions: Determined at the stage of pharmaceutical development potential critical quality attribute of AFI, excipients and primary packaging, critical parameters of the process, provide a better understanding, reduction and adoption of risk in subsequent stages of the life cycle of the drug

Cracking of concrete structures during the hardening phase often seriously compromises not only structure integrity but also durability and long-term service life. Especially for large massive structures, for example, concrete submerged tunnel, the reliable crack risk evaluation at the hardening phase is critical to the successful design. Mineral additives such as silica fume (SF), blast furnace slag (BFS), and fly ash (FA) have been used extensively in production of high-performance concrete in the last decades. The mineral additives such as FA and BFS not only reduce the hydration heat during the hardening phase but also have significant influence on the development of mechanic and viscoelastic properties at an early age. The main objective of the research is to propose a design methodology to select the appropriate composition of concrete for construction of the submerged tunnel. The influence of mineral additives such as FA and BFS on the risk of cracking during the hardening phase was investigated for the massive concrete structure. Five types of concrete mixes denoted as SV40, 40% BFS, 60% BFS, 40% FA, and 60% FA concrete are considered in the current study, and the measurement to reduce the initial temperature is also considered for 60% FA concrete. First, the well-documented material models are verified by calibration of restraint stress development in the TSTM test by using the finite element method (FEM), and then the 3D thermal-structural analysis is performed to assess the cracking risk for the submerged tunnel during the hardening phase. Based on analysis results, the 60% FA concrete has both the lowest maximum temperature and the lowest stress/strength ratio, and the cracking-free design based on the current study ensures the successful construction of the submerged tunnel. The financial contribution of the Norwegian Research Council is gratefully acknowledged. The NOR-CRACK partners were the Norwegian University of Science and Technology (project leader), Skanska Norge ASA, Elkem ASA Materials, Norcem AS, Fesil ASA, and the Norwegian Public Roads Administration. The paper is mainly based on the PhD project performed by Guomin Ji [19].

International audience; Condition-Based Probabilistic Safety Assessment (CB-PSA) makes use of the information made available during operation by sensors and/or inspections on the state of components and systems. This allows specializing the PSA to the conditions of the components and systems, reducing the uncertainty on the risk measures quantified. In this paper, we demonstrate the CB-PSA with reference to a spontaneous Steam Generator Tube Rupture (SGTR) accident scenario in a Pressurized Water Reactor (PWR). Results show that the updated risk measures are capable of reflecting the actual state of the SG in the tailored risk evaluation.

CBM development is a major concern in national energy projects. With high investment, high risks and high yield, CBM enables many investors generate the project plans while expressing concerns at the same time regarding the risks. Focusing on the development of risk assessment model in CBM development and applications, this paper proposes the CBM development risk assessment model of multi-information fusion, describing in detail the composite structure and application methods of the model, and eventually proves the model feasibility and significance by practical instances.

Dam risk analysis requires a systematic process to ensure that hydrologic variables (e.g. precipitation, discharge and water surface level) contribute to each other. However, the existing dam risk approach showed a limitation in assessing the interdependencies across the variables. This study aimed to develop Bayesian network based dam risk analysis model to better characterize the interdependencies. It was found that the proposed model provided advantages which would enable to better identify and understand the interdependencies and uncertainties over dam risk analysis. The proposed model also provided a scenario-based risk evaluation framework which is a function of the failure probability and the consequence. This tool would give dam manager a framework for prioritizing risks more effectively.

Purpose – The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes. Design/methodology/approach – A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes. Findings – A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies. Practical implications – The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method. Originality/value – This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.

The purpose of this paper is to propose a modified version of Failure Mode and Effects Analysis (FMEA) to alleviate its drawbacks. FMEA is an important tool in risk evaluation and finding the priority of potential failure modes for corrective actions. In the proposed method, the Universal Generating Function (UGF) approach has been used to improve the assessment capability of the conventional Risk Priority Number (RPN) in ranking. The new method is named as URPN. It generates the most number of unique values in comparison with the previous methods and considers relative importance for the parameters while it is easy to compute. More unique numbers help to avoid from having the same priority level for different failure modes which represent various risk levels. A case study has been employed to demonstrate that the URPN not only can improve the shortcomings but also is able to provide accurate values for risk assessment. Copyright © 2015 John Wiley & Sons, Ltd.

In order to achieve the sustainable development of energy, Ultra High Voltage (UHV) power transmission construction projects are being established in China currently. Their high-tech nature, the massive amount of money involved, and the need for multi-agent collaboration as well as complex construction environments bring many challenges and risks. Risk management, therefore, is critical to reduce the risks and realize sustainable development of projects. Unfortunately, many traditional risk assessment methods may not perform well due to the great uncertainty and randomness inherent in UHV power construction projects. This paper, therefore, proposes a risk evaluation index system and a hybrid risk evaluation model to evaluate the risk of UHV projects and find out the key risk factors. This model based on a cloud model and fuzzy comprehensive evaluation (FCE) method combines the superiority of the cloud model for reflecting randomness and discreteness with the advantages of the fuzzy comprehensive evaluation method in handling uncertain and vague issues. For the sake of proving our framework, an empirical study of “Zhejiang-Fuzhou” UHV power transmission construction project is presented. As key contributions, we find the risk of this project lies at a “middle” to “high” level and closer to a “middle” level, the “management risk” and “social risk” are identified as the most important risk factors requiring more attention, and some risk control recommendations are proposed. This article demonstrates the value of our approach in risk identification, which seeks to improve the risk control level and the sustainable development of UHV power transmission construction projects.

According to the nonlinear dynamic characteristic of coal seam floor water inrush, coal seam floor water inrush risk evaluation which includes 4 first level indicators,14 level two indexes was built based BP neural network. According to the test collection of engineering data, coal seam floor water inrush risk evaluation system based VB and MATLAB is reliable. Application to a mine coal seam No.2 working face was verified. The results show that, the evaluation method in water inrush is feasible, reasonable.

Propane dispersion after the continuous leaking in the residential building is numerically simulated with FLUENT by computational fluid dynamic method. The variation characteristics of the concentration contribution and explosive range of propane are analyzed. The propane diffusion scope and explosive area increase with time. The highest concentration appears in the kitchen while the lowest concentration appears in the bedroom. Propane explosive area appears only in the kitchen and in the sunroom. Obvious stratification of the propane over the vertical height is due to gravity. The concentration, diffusion scope, and explosive area decrease with the number of windows open. The explosive range appears in the kitchen and the sunroom, but does not appear in the bedroom, the living room, or the bathroom. The research results can provide scientific support and references for risk evaluation, accident prevention and emergency rescue of propane hazards in the building. © 2015 American Institute of Chemical Engineers Environ Prog, 34: 973–981, 2015