基于Aspen Plus的Safety Analysis功能计算调节阀故障时的安全阀尺寸

安全阀作为化工生产中的最后一道安全屏障,其选型的准确与否直接关系到生产安全。目前国内大部分设计院计算安全阀时都是基于安全阀设计规范编辑Excel公式,代入手册中查得物性数据得到泄放量及泄放面积。由于安全阀计算涉及的工况、物性参数较多,且各个工况下使用的计算公式均不相同,使得安全阀的选型成为化工设计中的一个难点。通过工程经验总结,以调节阀故障工况为例,利用Aspen Plus软件自带的Safety Analysis功能计算安全阀的泄放量与泄放面积,并核算调节阀入口、出口管径,大幅提高了工作效率与准确性。

CAUSALITY DIAGRAM BASED SAFETY ANALYSIS OF MICRO TURBOJET ENGINE

An improved safety analysis based on the causality diagram for the complex system of micro aero-engines is presented.The study is examined by using the causality diagram in analytical failure cases due to rupture or pentration in the receiver of micro turbojet engine casing,and the comparisons are also made with the results from the traditional fault tree analysis.Experimental results show two main advantages：（1）Quantitative analysis which is more reliable for the failure analysis in jet engines can be produced by the causality diagram analysis;（2）Graphical representation of causality diagram is easier to apply in real test cases and more effective for the safety assessment.

Safety analysis of wheel brake system based on STAMP/STPA and Monte Carlo simulation

The wheel brake system safety is a complex problem which refers to its technical state, operating environment, human factors, etc., in aircraft landing taxiing process. Usually, professors consider system safety with traditional probability techniques based on the linear chain of events. However, it could not comprehensively analyze system safety problems, especially in operating environment, interaction of subsystems, and human factors. Thus,we consider system safety as a control problem based on the system-theoretic accident model, the processes(STAMP) model and the system theoretic process analysis(STPA) technique to compensate the deficiency of traditional techniques. Meanwhile,system safety simulation is considered as system control simulation, and Monte Carlo methods are used which consider the range of uncertain parameters and operation deviation to quantitatively study system safety influence factors in control simulation. Firstly,we construct the STAMP model and STPA feedback control loop of the wheel brake system based on the system functional requirement. Then four unsafe control actions are identified, and causes of them are analyzed. Finally, we construct the Monte Carlo simulation model to analyze different scenarios under disturbance. The results provide a basis for choosing corresponding process model variables in constructing the context table and show that appropriate brake strategies could prevent hazards in aircraft landing taxiing.

NEW IDEAS AND METHODS ON GEOMECHANICAL SAFETY ANALYSIS OF TOXIC AND RADIOACTIVE WASTE REPOSITORIES IN SALT MINE

In view of the need for geomechanical safety analysis of repositories in salt rock, failure criteria,creep rupture criteria,material models,pillar design methods and criteria for the assessment of barrier efficiency as well as investigations of the interaction between hydraulics and mechanics for the case of uncontrolled flooded repositories are necessary. The introduction of damage mechanics and of the Hou/Lux material model including damages into geomechanical safety analysis of repositories in salt rock can reduce some previous deficits in knowledge and modelling. This article will be as a part of geotechnical assessment to introduce the Hou/Lux material model,a new concept of hydro-mechanical coupling and a pillar design method as well as criteria for the assessment of efficiency of geological barriers.

Aseismic safety analysis of a prestressed concrete containment vessel for CPR1000 nuclear power plant

Abstract： The containment vessel of a nuclear power plant is the last barrier to prevent nuclear reactor radiation. Aseismic safety analysis is the key to appropriate containment vessel design. A prestressed concrete containment vessel （PCCV） model with a semi-infinite elastic foundation and practical arrangement of tendons has been established to analyze the aseismic ability of the CPR1000 PCCV structure under seismic loads and internal pressure. A method to model the prestressing tendon and its interaction with concrete was proposed and the axial force of the prestressing tendons showed that the simulation was reasonable and accurate. The numerical results show that for the concrete structure, the location of the cylinder wall bottom around the equipment hatch and near the ring beam are critical locations with large principal stress. The concrete cracks occurred at the bottom of the PCCV cylinder wall under the peak earthquake motion of 0.50 g, however the PCCV was still basically in an elastic state. Furthermore, the concrete cracks occurred around the equipment hatch under the design internal pressure of 0.4MPa, but the steel liner was still in the elastic stage and its leak-proof function soundness was verified. The results provide the basis for analysis and design of containment vessels.

Application of causality diagram in system safety analysis

Causality Diagram (CD) is a new graphical knowledge representation based on probability theory. The application of this methodology in the safety analysis of the gas explosion in collieries was discussed in this paper, and the Minimal Cut Set, the Minimal Path Set and the Importance were introduced to develop the methodology. These concepts are employed to analyze the influence each event has on the top event ? the gas explosion, so as to find out about the defects of the system and accordingly help to work out the emphasis of the precautionary work and some preventive measures as well. The results of the safety analysis are in accordance with the practical requirements; therefore the preventive measures are certain to work effectively. In brief, according to the research CD is so effective in the safety analysis and the safety assessment that it can be a qualitative and quantitative method to predict the accident as well as offer some effective measures for the investigation, the prevention and the control of the accident.

Probabilistic Safety Analysis of High Speed and Conventional Lines Using Bayesian Networks

A Bayesian network approach is presented for probabilistic safety analysis(PSA)of railway lines.The idea consists of identifying and reproducing all the elements that the train encounters when circulating along a railway line,such as light and speed limit signals,tunnel or viaduct entries or exits,cuttings and embankments,acoustic sounds received in the cabin,curves,etc.In addition,since the human error is very relevant for safety evaluation,the automatic train protection(ATP)systems and the driver behaviour and its time evolution are modelled and taken into account to determine the probabilities of human errors.The nodes of the Bayesian network,their links and the associated probability tables are automatically constructed based on the line data that need to be carefully given.The conditional probability tables are reproduced by closed formulas,which facilitate the modelling and the sensitivity analysis.A sorted list of the most dangerous elements in the line is obtained,which permits making decisions about the line safety and programming maintenance operations in order to optimize them and reduce the maintenance costs substantially.The proposed methodology is illustrated by its application to several cases that include real lines such as the Palencia-Santander and the Dublin-Belfast lines.

Upgrade to Nuclear Power Plant Krsko Internal Flooding Probabilistic Safety Analysis

The original internal flooding probabilistic safety analysis （PSA） study of Krsko Nuclear Power Plant （two-loop Pressurized Water Reactor （PWR） plant of Westinghouse design） was performed in mid nineties and limited to reactor core damage risk （Level 1 PSA）. In 2003, it was, together with other safety and hazard analyses, subject to the Periodic Safety Review （PSR）. In the PSR, it was stated that methodological PSA approaches and guidelines have evoluted during the past decade and several observations were provided, concerning the area screening process, residual risk and treatment of plant damage states and risk from radioactivity releases （i.e., Level 2 PSA）. In order to address the PSR observations, upgrade ofKrsko NPP internal flooding PSA was undertaken. The area screening process was revisited in order to cover the areas without automatic reactor trip equipment. The model was extended to Level 2. Residual risk was estimated at both Level 1 and Level 2, in terms of core damage frequency （CDF） and large early release frequency （LERF）, respectively.

Environment and Safety Analysis for ITER HC-SB TBM

Environment and safety analysis of test blanket module （ TBM ） is an important part of ITER safety design process. The aim is to ensure that the TBM do not adversely affect the safety of ITER and environment around ITER. Accurate calculations of all radioactivity and potential harmfulness are very important to environment and safety analysis, nuclear waste disposing and the reactor running, and so on.

Analysis on Operational Safety and Efficiency of FAO System in Urban Rail Transit

This paper discusses two urgent problems that need to be solved in fully automatic operation(FAO)for urban rail transit.The first is the analysis of safety in FAO,while another is the analysis of efficiency in FAO.Firstly,this paper establishes an operational safety evaluation index system from the perspective of operation for the unique or typical risk sources of the FAO system,and uses the analytic hierarchy process(AHP)to evaluate the indicators,analyzes various factors that affect the safe operation of FAO,and provides safety management recommendations for FAO lines operation to maintain the FAO system specifically.Secondly,taking the Yanfang Line as an example,this paper uses OpenTrack software to analyze the efficiency of FAO operation,and conducts simulation calculations for key links such as the mainline tracking interval,train entry and exit,and return limit interval.The fault impact surface of the FAO trains is simulated and discussed to verify whether FAO can meet the long-term operation requirements of Yanfang Line.Finally,this paper compares the simulation data of FAO on the Yanfang Line with manual operation(MO)to verify the advantages of FAO and guide the engineering construction of subsequent fully automated driving lines.

Safety Analysis of the Eco-Approach and Departure Application at a Signalized Corridor

Various intelligent transportation systems and strategies for reducing vehicle fuel consumption and emissions have been developed. Energy and emissions could be reduced with the compromise of travel time in some environment-focused Connected Vehicle(CV) applications, which highlighted performance measures in terms of mobility and sustainability. Nevertheless, few studies have focused on safety assessment of such CV applications. In this study, a CV-based eco-driving application, namely, Eco-Approach and Departure(EAD), is selected as an example. A microscopic safety analysis tool, Surrogate Safety Assessment Model(SSAM), is utilized to assess the safety influence of EAD application in multiple scenarios. Further analysis is performed from two perspectives:(1) application users, i.e., EAD-equipped vehicles versus unequipped vehicles; and(2) traffic operators, i.e., overall traffic performance with and without the introduction of EAD. For each perspective, conflict statistics(e.g., frequency, time-to-collision distribution), overall and by type, are analyzed. Results indicate EAD is beneficial in improving the safety performance of equipped vehicles. The influence of EAD on overall traffic is scenario dependent, and a high penetration rate shows positive effects on network-wide safety benefits for most scenarios.

DFCluster:An efficient algorithm to mine maximal differential biclusters for single pilot operations task synthesis safety analysis

With the continuous advancement of the avionics system,crew members are correspondingly reduced,and Single Pilot Operations(SPO)has attracted widespread attention from scholars.To meet the flight requirements in SPO mode,it is necessary to further strengthen air-ground coordination system integration,but at the same time,there will be some safety issues caused by resource integration,function fusion,and task synthesis.Aimed at the safety problems caused by task synthesis,an efficient differential bicluster mining algorithm--DFCluster algorithm is proposed in this paper to discover potential hazardous elements or propagation mechanisms through mining the resource-function matrixes.To mine efficiently,several pruning techniques are designed for generating maximal biclusters without candidate maintenance.The experimental results show that the DFCluster algorithm is more efficient than the existing differential biclustering algorithms under different scales of artificial datasets and public datasets.Then,a typical flight scenario is designed based on SPO air-ground collaborative system architecture,and combined with our proposed DFCluster algorithm for task synthesis safety analysis.Based on the mining results,the SPO airground collaborative system architecture is modified,which ultimately improves the safety of the SPO system.

Safety Analysis of Flow Parameters in a Rotor-stator Cavity

In order to ensure the safety of engine life limited parts （ELLP） according to airworthiness regulations, a numerical approach integrating one-way fluid structure interaction （FSI） and probabilistic risk assessment （PRA） is developed, by which the variation of flow parameters in a rotor-stator cavity on the safety of gas turbine disks is investigated. The results indicate that the flow parameters affect the probability of fracture of a gas turbine disk since they can change the distribution of stress and temperature of the disk. The failure probability of the disk rises with increasing rotation Reynolds number and Chebyshev number, but descends with increasing inlet Reynolds number. In addition, a sampling based sensitivity analysis with finite difference method is conducted to determine the sensitivities of the safety with respect to the flow parameters. The sensitivity estimates show that the rotation Reynolds number is the dominant variable in safety analysis of a rotor-stator cavity among the flow parameters.

Conceptual design and safety characteristics of a new multi-mission high flux research reactor

Research reactors with neutron fluxes higher than 10^(14) n cm^(−2) s^(−1) are widely used in nuclear fuel and material irradiation,neutron-based scientific research,and medical and industrial isotope production.Such high flux research reactors are not only important scientific research facilities for the development of nuclear energy but also represent the national comprehensive technical capability.China has several high flux research reactors that do not satisfy the requirements of nuclear energy development.A high flux research reactor has the following features:a compact core arrangement,high power density,plate-type fuel elements,a short refueling cycle,and high coolant velocity in the core.These characteristics make it difficult to simultaneously realize high neutron flux and optimal safety margin.A new multi-mission high flux research reactor was designed by the Institute of Nuclear and New Energy Technology at Tsinghua University in China;the reactor can simul-taneously realize an average neutron flux higher than 2.0×10^(15) n cm^(−2) s^(−1) and fulfill the current safety criterion.This high flux research reactor features advanced design concepts and has sufficient safety margins according to the preliminary safety analysis.Based on the analysis of the station blackout accident,loss of coolant accident,and reactivity accident of a single-control drum rotating out accidently,the maximum temperature of the cladding surface,minimum departure from nucleate boiling ratio,and temperature difference to the onset of nucleate boiling temperature satisfy the design limits.

Using Markov Chain Based Estimation of Distribution Algorithm for Model-Based Safety Analysis of Graph Transformation

The ability to assess the reliability of safety-critical systems is one of the most crucial requirements in the design of modern safety-critical systems where even a minor failure can result in loss of life or irreparable damage to the environment.Model checking is an automatic technique that verifies or refutes system properties by exploring all reachable states(state space)of a model.In large and complex systems,it is probable that the state space explosion problem occurs.In exploring the state space of systems modeled by graph transformations,the rule applied on the current state specifies the rule that can perform on the next state.In other words,the allowed rule on the current state depends only on the applied rule on the previous state,not the ones on earlier states.This fact motivates us to use a Markov chain(MC)to capture this type of dependencies and applies the Estimation of Distribution Algorithm(EDA)to improve the quality of the MC.EDA is an evolutionary algorithm directing the search for the optimal solution by learning and sampling probabilistic models through the best individuals of a population at each generation.To show the effectiveness of the proposed approach,we implement it in GROOVE,an open source toolset for designing and model checking graph transformation systems.Experimental results confirm that the proposed approach has a high speed and accuracy in comparison with the existing meta-heuristic and evolutionary techniques in safety analysis of systems specified formally through graph transformations.

Systematic Safety Analysis Method for Power Generating Equipment

A systematic safety analysis method is presented to guide the whole analysis process starting with safety analysis requirement and ending with technical and economical evaluation of the knowledge model and the arrangement of sensors. The method consists of five phases, including data acquisition on factual evidence and collecting design, manufacturing, and installation data of equipment; establishing knowledge model; measurable analysis and selection of sensors as well cost evaluation; knowledge description; and overall evaluation. The proposed method is used for safety analysis of hydraulic power generating units and the analysis results validate the method very well.

Bivariate macro-level safety analysis of non-motorized vehicle crashes and crash-involved road users

The high risk of injury resulting from non-motorized vehicle(NMV)crashes has created the goal of using the 3E strategy to comprehensively improve NMV safety.Traditional safety improvement methods identify hot zones generally by crash frequency or density,which is effective for roadway engineering improvements but neglects characteristics related to other improvements such as safety education.As safety education would be more effective if targeted at the residences of crash-involved road users,the traditional approach to hot zones may therefore provide biased results for such alternative countermeasures.After confirming that 77.17%of NMV crashes occurred outside the involved riders’areas of residence,this study compared the differences between the locations of crashes and the residences of NMV crash-involved riders in safety influencing factors and hot zone identification.A Poisson lognormal bivariate conditional autoregressive(PLN-BCAR)model was developed to account for potential correlations between crashes and involved riders.The model was compared with the univariate Poisson lognormal conditional autoregressive(UPLN-CAR)model and the bivariate Poisson lognormal conditional autoregressive(BPLNCAR)model;the PLN-BCAR model outperformed the other two models in its better interpretation of the influencing factors and its more efficient parameter estimation.Model results indicated that crashes were mainly associated with roadway and land use characteristics,while involved road users were mainly associated with socioeconomic and land use characteristics.The potential for safety improvement method was adopted to identify hot zones for countermeasure implementation.Results showed over 60%of the identified hot zones were inconsistent:they needed improvement in either engineering or education but not both.These findings can help target the type of improvement to better utilize resources for NMV safety.

A Logic-Based Safety Analysis Algorithm for Discretionary Access Control

For the issue of the discretionary access control（DAC） model safety analysis,a logic method is proposed.This method takes the GD model as the classic DAC model and Prolog as the basic language to describe system states and state transfer rules.A general program based on this logic method is proposed for DAC safety analysis,but this program may never be terminal for some safety analysis goal.The safety analysis algorithm is achieved by simplifying the general program according to the property of the DAC model state transfer rules.This safety analysis algorithm is easier to understand and implement than the previous algorithms and its time complexity is O（N＋M＋T）,in which N,M,and T are the numbers of the rights with copy flag,the policies for right transferring,and the policies for right permitting,respectively.

Safety Analysis of Accident Scenarios for the HTR-10

HTR-10 is a 10MW high temperature gas-cooled test reactor (HTR-10). It has inherent safety features common to the new generation of advanced reactors, i. e. the reactor automatically shuts down because of the negative temperature reactivity coefficients and the decay heat is passively removed from the reactor to the environment. A thorough accident safety analysis of HTR-10 was carried out, after establishing safety criteria and classifying the accident scenarios. Analysis results of the design basis accidents and the beyond design basis accidents are provided in this paper. It is demonstrated that HTR-10 has excellent inherent safety features.

Drug Usage Safety from Drug Reviews with Hybrid Machine Learning Approach

With the increasing usage of drugs to remedy different diseases,drug safety has become crucial over the past few years.Often medicine from several companies is offered for a single disease that involves the same/similar substances with slightly different formulae.Such diversification is both helpful and danger-ous as such medicine proves to be more effective or shows side effects to different patients.Despite clinical trials,side effects are reported when the medicine is used by the mass public,of which several such experiences are shared on social media platforms.A system capable of analyzing such reviews could be very helpful to assist healthcare professionals and companies for evaluating the safety of drugs after it has been marketed.Sentiment analysis of drug reviews has a large poten-tial for providing valuable insights into these cases.Therefore,this study proposes an approach to perform analysis on the drug safety reviews using lexicon-based and deep learning techniques.A dataset acquired from the‘Drugs.Com’contain-ing reviews of drug-related side effects and reactions,is used for experiments.A lexicon-based approach,Textblob is used to extract the positive,negative or neu-tral sentiment from the review text.Review classification is achieved using a novel hybrid deep learning model of convolutional neural networks and long short-term memory(CNN-LSTM)network.The CNN is used at thefirst level to extract the appropriate features while LSTM is used at the second level.Several well-known machine learning models including logistic regression,random for-est,decision tree,and AdaBoost are evaluated using term frequency-inverse docu-ment frequency(TF-IDF),a bag of words(BoW),feature union of(TF-IDF+BoW),and lexicon-based methods.Performance analysis with machine learning models,long short term memory and convolutional neural network models,and state-of-the-art approaches indicate that the proposed CNN-LSTM model shows superior performance with an 0.96 accuracy.We also performed a statistical sig-nificance T-test to show the significance of the proposed CNN-LSTM model in comparison with other approaches.