JP2011064555A - Earthquake risk evaluation system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To easily perform earthquake risk evaluation on various evaluation objects with high reliability. <P>SOLUTION: For evaluation on the earthquake risk of a predetermined evaluation object, information on an analysis object is read from a storage part 13. A response output when a design input waveform simulating seismic vibration input to the analysis object is input to the object is calculated in accordance with a predetermined calculation formula stored in the storage part 13 (S12, S13). On the basis of the calculated response output and characteristics related to the yield strength of the analysis object, the probability a damage mode will occur in the analysis object is calculated in accordance with the predetermined calculation formula stored in the storage part 13 with at least the response output out of the response output and the yield-stress-related characteristics set to be a random variable (S14). On the basis of the calculated damage probability and information on the degree of influence stored in the storage part 13, a risk evaluation result is created. The created risk evaluation result is output through an output part 12 (S15). <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The technology disclosed herein relates to an earthquake risk assessment system.

  In recent years, there has been an increasing social demand for seismic risk assessment to assess the risk of structures when an earthquake occurs. Risk assessment methods can be broadly divided into two processes: (1) quantification of damage to structures due to earthquakes, and (2) assessment of earthquake risk using the results. As the process (1), for example, it may be possible to quantify the degree of damage to the structure by an actual test using a shaking table, but in that case, it takes enormous time and cost. End up.

  For example, in Patent Document 1, as a method of evaluating the damage situation in a building at the time of an earthquake occurrence, pre-set seismic motion data, response data of each floor of the building, specifications and conditions of installations installed in the building, etc. A system is disclosed that calculates the movement probability and fall probability of an installation based on the installation data and the like, and evaluates the damage status based on the calculated movement probability and the like.

JP 2007-109107 A

  By the way, in order to receive approval for the manufacture and sale of a new drug, it is necessary to submit to the Ministry of Health, Labor and Welfare test results data to support its “effectiveness”, “safety” and “quality”. There is a long-term stability test as one of the tests for supporting "." This long-term stability test is a test in which a pharmaceutical specimen is stored and stored for a long period in a room that maintains a predetermined constant temperature and humidity condition. In this test, if the temperature and humidity conditions are outside the allowable range even once, and it cannot be denied that the sample has been affected, the drug sample will not be usable. There is a very strict requirement that experimental data measured over a long period of time cannot be used at all. Because this is a long-term test, the person who performs the long-term stability test and the manufacturer of the stability test room should appropriately evaluate the risk at the time of the earthquake and take measures to avoid the risk, for example. There is a request to apply in advance.

  On the other hand, taking the time and cost to evaluate the risk of the stability laboratory from the viewpoint of recent lead time shortening of design / development and quick response to design change at the time of product development In practice, there is a need for risk assessment that is difficult, simple, and highly reliable.

  For example, the risk evaluation method disclosed in Patent Document 1 has an advantage that it can be easily evaluated without using a shaking table. However, the risk evaluation method disclosed in Patent Document 1 calculates a fall probability or the like assuming that the magnitude of the load acting on the structure at the time of the earthquake occurrence or the proof stress (strength) of the structure is a definite amount. . However, in reality, the magnitude of the load acting on the structure varies, and the proof stress (for example, strength) of the structure also varies. Therefore, the evaluation of Patent Document 1 that does not consider these variations The method is inferior in reliability.

  The technology disclosed herein has been made in view of such a point, and the object thereof is to perform an earthquake risk evaluation for various evaluation objects easily and with high reliability.

  In view of the above-mentioned object, the inventors of the present application use a stochastic method based on reliability engineering in order to take into account variations in loads and variations in strength, thereby causing damage to the structure. Quantification of the probability of performing high-reliability while ensuring a simple evaluation without using a shaking table.

  The earthquake risk evaluation system disclosed here is an earthquake risk evaluation system that evaluates an earthquake risk of a predetermined evaluation target. The system is configured to be operable by a user, an input unit that outputs information corresponding to the operation, an output unit that outputs various types of information so that the user can recognize, a storage unit that stores various types of information, and An arithmetic processing unit is connected to the input unit, the output unit, and the storage unit so as to be able to exchange information, and executes various types of calculations.

  The said memory | storage part has memorize | stored the information regarding the analysis target object which may affect the said evaluation object by receiving damage at the time of the occurrence of an earthquake. The arithmetic processing unit reads information related to the analysis object from the storage unit, and outputs a response when a design input waveform simulating a seismic motion input to the analysis target is input to the analysis target. Is calculated according to a predetermined response calculation formula stored in the storage unit.

  The arithmetic processing unit is also configured to perform the analysis using at least the response output as a random variable among the characteristics related to the response output and the strength based on the calculated response output and the properties related to the strength of the analysis target. A damage probability, which is a probability of occurrence of a damage mode in the object, is calculated according to a predetermined probability calculation formula stored in the storage unit. Then, the arithmetic processing unit, the calculated damage probability, the information of the influence degree representing the magnitude of the value loss when the damage mode occurs in the analysis object stored in the storage unit, The risk assessment result based on the above is created, and the created risk assessment result is output through the output unit.

  In this configuration, the response output when the design input waveform is input to the analysis object, in other words, the earthquake motion is input, is calculated, and the response output is related to the strength of the analysis object. Of the characteristics, at least the response output is used as a random variable, and the probability that a damage mode occurs in the analysis target is calculated. Here, the characteristics related to the proof stress of the analysis object include, for example, the material characteristics of the analysis object (related to shear strength and bending strength, first pass fracture described later) and the maximum static friction coefficient (related to sliding described later). Included).

  That is, the arithmetic processing unit calculates the damage probability assuming that the response output varies, or both the response output and the material characteristics and the maximum static friction coefficient vary.

  In this way, risk assessment is quantitative by performing risk assessment based on damage probability and impact information calculated by a probabilistic method that takes into account variations in response output (and characteristics related to proof stress) Can be done. This can increase the reliability of the risk assessment.

  Further, by not using a shaking table or the like, earthquake risk evaluation can be performed easily and in a short time.

  The arithmetic processing unit may calculate a probability of occurrence of at least one damage mode among first-pass destruction, sliding, and falling as a damage mode caused by a single earthquake motion.

  In this way, the occurrence of damage to the analysis object at the time of the earthquake is appropriately evaluated, and the reliability of the earthquake risk evaluation is increased. Here, the first-pass failure includes failure due to the shear force acting on the object exceeding the shear strength and failure due to the bending force acting on the object exceeding the bending strength. The phenomenon that the object moves from its original location by receiving the input seismic force) may be that the object slides when the seismic external force exceeds the maximum static frictional force. A determination condition using static acceleration may be used as a phenomenon in which an object receives an input seismic force during an earthquake and causes the object to rotate around a certain fulcrum.

  The arithmetic processing unit may calculate a probability of occurrence of cumulative damage destruction as a damage mode caused by a plurality of earthquake motions.

  In this way, the occurrence of damage to the analysis object at the time of the earthquake is appropriately evaluated, and the reliability of the earthquake risk evaluation is increased. Here, the cumulative damage fracture may be considered as fatigue fracture, and the life evaluation may be performed using the concept of cumulative damage degree described later.

  In addition, when the calculation processing unit calculates the damage probability by dividing into a damage mode caused by a single earthquake motion and a damage mode caused by a plurality of earthquake motions, the reliability of the earthquake risk evaluation can be further improved.

  The arithmetic processing unit creates an FMEA worksheet including the probability of occurrence and the degree of influence of damage for each analysis object as a risk evaluation, and performs an event generation process that can cause damage to the evaluation object when an earthquake occurs The event tree analysis and the FMEA worksheet may be combined to calculate the event occurrence probability and the degree of influence due to the event occurrence.

  An event that may cause damage to the evaluation object may occur when one analysis object generates a damage mode and / or when a plurality of analysis object damage modes are combined. The combination of the event tree analysis and the FMEA worksheet clarifies the process until the evaluation target is damaged, and the occurrence probability of the event (in other words, the probability of damage occurrence of the evaluation target) and the degree of influence due thereto are as follows: Each is quantified.

  The arithmetic processing unit calculates the occurrence probability of the event for each seismic intensity class, and creates a risk matrix including three parameters of the event occurrence probability, the influence degree due to the event occurrence, and the seismic intensity class, It is good also as outputting through an output part.

  This risk matrix makes it possible to evaluate the risk in consideration of the two effects constituting the risk, the occurrence probability and the degree of influence.

  The storage unit stores a measurement value of time history acceleration data of stationary vibration of a floor surface on which the analysis object is installed, and a predetermined function indicating secular characteristics of seismic motion, and the arithmetic processing unit Creates a waveform that combines the measured value and the function, and amplifies the amplitude of the waveform according to the seismic intensity class that is set and input through the input unit. The corresponding input waveform for design may be created.

  By doing so, a design input waveform can be created easily and accurately.

  The evaluation target may be an environmental test apparatus for testing the storage stability of a predetermined specimen.

  As described above, the earthquake risk evaluation system described above is based on the probability of damage calculated by a probabilistic method in consideration of variations in response output (and characteristics related to proof stress) of the analysis object, and the analysis object. The risk assessment can be performed quantitatively by performing the risk assessment of the assessment target based on the information on the degree of impact that represents the magnitude of the value loss when the damage mode occurs in the Reliability can be improved. Moreover, earthquake risk assessment is simplified by not using a shaking table or the like.

It is a flowchart which shows an earthquake risk evaluation procedure roughly. It is a block diagram which shows the structure of an earthquake risk evaluation system. It is a figure which shows the functional block which an earthquake risk evaluation system has. It is a flowchart which shows the preparation procedure of the input waveform for design. It is a flowchart which shows the procedure of a time history response analysis. It is a flowchart which shows the procedure (evaluation method regarding a single scenario earthquake) which calculates the generation probability of the first passage failure. It is a flowchart which shows the procedure which calculates the generation | occurrence | production probability of sliding. It is a flowchart which shows the procedure which calculates the occurrence probability of a fall. It is a conceptual diagram of a PSN curve. It is a flowchart which shows the procedure which calculates the generation | occurrence | production probability of a cumulative damage destruction. It is a figure which shows the example of the generation probability of each event. It is a figure which shows an example of the worksheet of Seismic P-FMEA. It is an example of a risk extraction table. It is a figure which shows the relationship between SP-FMEA and ET. It is a figure which shows an example of a risk matrix.

  Hereinafter, an embodiment of an earthquake risk evaluation system will be described based on the drawings. The following description of the preferred embodiment is merely exemplary in nature. FIG. 1 is a flowchart showing a schematic procedure for earthquake risk evaluation. In this embodiment, an explanation will be given by taking as an example an earthquake risk assessment relating to a laboratory that conducts a long-term stability test of pharmaceutical products. However, risk assessment is not limited to long-term stability laboratories. The earthquake risk evaluation method disclosed here can be applied to earthquake risk evaluation of various objects.

  In the procedure of this evaluation method, in the first step S11, a function request for risk evaluation including, for example, determination of a risk evaluation target is determined. This function request includes selection of an analysis object such as equipment and piping related to the risk evaluation target based on the determined function request.

  In the subsequent step S12, a design input waveform necessary for analyzing the vibration response of the analysis target object during the earthquake is created. This design input waveform is the vibration external force that is input to the analysis object due to the earthquake motion. As will be described later, this earthquake risk assessment method adopts time history response analysis as the vibration analysis of the analysis object. Therefore, a time history waveform is created as the design input waveform. Although details will be described later, the design input waveform creation step S12 includes a step (S121) of determining the vibration of the floor surface on which the analysis target object is installed and a step of determining the earthquake motion (S122). .

  When the design input waveform is created, in a subsequent step S13, response analysis and eigenvalue analysis of the analysis object are performed. The vibration analysis here performs time history response analysis using FEM (Finite Element Method). This step S13 includes a step of creating an FEM model of the analysis object (S131) and a step of performing response analysis of the analysis object (S132).

  If the response analysis of the analysis object is completed, evaluation for each damage mode is performed based on the result (step S14). As will be described in detail later, in step S14, a plurality of damage modes are set (step S141), and the probability of occurrence of the damage mode is calculated for each analysis object according to the evaluation formula for each damage mode set in advance ( Step S142).

  If the evaluation for each damage mode is completed, the earthquake risk evaluation to be evaluated is performed based on the result (step S15). This seismic risk evaluation is performed by combining ETA (Event Tree Analysis) and FMEA (Failure Mode and Effect Analysis) and combining the evaluation of the occurrence probability of each damage mode and the impact evaluation (steps S151 and S152). ). Note that FMEA here is Seismic Probability FMEA (SP-FMEA) specialized in risk assessment during earthquakes based on general FMEA.

  FIG. 2 shows an example of the configuration of the earthquake risk evaluation system 1 (hereinafter also simply referred to as the system 1). In this system 1, measurement values measured by a keyboard, a pointing device, and / or various measuring devices that can input various types of information to the system 1 by a user's operation are stored in the system 1. An input device 11 configured to include an input interface that can be input, a display or printer that outputs various information related to risk assessment in a recognizable manner by a user (person), and / or various information An output device 12 including an output interface that can be used in the system, a storage device (storage medium) 13 that stores various information such as a hard disk drive (HDD) and a flash memory in a readable / writable manner. And input / output of signals to / from the input device 11, the output device 12 and the storage device 13, respectively. An arithmetic processing unit 14 (for example, a personal computer) that is connected so as to execute various calculations related to earthquake risk evaluation based on signals (information) from the respective units 11 to 13 is configured. ing.

  FIG. 3 is a diagram showing main processes executed by the system 1 regarding risk assessment as functional blocks. The system 1 includes, as functional blocks, an analysis condition setting unit 21, a damage probability calculating unit 22, a risk block At least an evaluation unit 23 and a data storage unit 24 are included. In this system 1, single scenario earthquake evaluation for determining whether or not an analysis object is damaged by a single earthquake and whether or not the analysis object is damaged by multiple earthquakes are determined. Each process is executed separately for multiple scenario earthquake evaluation.

  The analysis condition setting unit 21 is a functional block that executes processing corresponding to step S12 and step S13 in FIG.

  The damage probability calculation unit 22 is a functional block that executes processing corresponding to step S14 in FIG. As will be described in detail later, this system sets a plurality of damage modes as the damage mode of the analysis object, and the damage probability calculation unit 22 sets the calculation unit for calculating the occurrence probability of each damage mode as the damage mode. It is provided for each mode (calculation units 221 to 224).

  The risk evaluation unit 23 is a functional block that executes a process corresponding to step S15 in FIG.

  The data storage unit 24 is a functional block related to the recording device 13 in FIG. 2, stores information input based on operations of the input device 11, and the like, as well as an analysis condition setting unit 21 and a damage probability calculation unit 22. And according to the request | requirement from the risk evaluation part 23, the memorize | stored information is provided to each part 21-23. Hereinafter, each procedure of the earthquake risk evaluation executed by the system 1 having the configuration shown in FIGS. 2 and 3 will be described with reference to the drawings.

(Selection of evaluation target and analysis target)
First, the user determines an evaluation target for performing an earthquake risk evaluation. Here, as described above, the long-term stability test of a pharmaceutical specimen and its stability test room (stability test system) are evaluated.

  If the evaluation object is determined, the user selects an analysis object related to the evaluation object. The stability test chamber is configured by combining a plurality of components. Specifically, as shown in FIG. 12, the stability test chamber is roughly divided into a constant temperature and humidity test chamber (also simply referred to as a test chamber), and water is supplied to the test chamber. A water production chamber for power generation and a power generation chamber for supplying power to the test chamber. In this example, the test room is provided on the first floor of the building, and the water production room and the power generation room are provided on the second floor of the building.

  The test chamber includes a specimen storage rack, a temperature / humidity sensor, and a storage container in the chamber, and includes an upper fixing portion and a lower fixing portion for fixing the test chamber outside the chamber. In addition, the control unit for controlling the test room includes an electric conductivity meter, a reinforcing plate, a pure water device, a switchboard, a gauge pipe, a pipe (1), a pipe (2), and a pipe (3). As a measurement system for measuring various data related to the sex test, a cabinet rack, UPS (Uninterruptible Power Supply), server, alarm box, and data logger are included. The water production chamber has a pure water unit, and the pure water unit includes a pure water tank, a filtration device, and a booster. The power generation chamber includes a generator as a power generation facility.

  Thus, by selecting equipment, piping, etc. (small classification) related to the constant temperature and humidity test room to be evaluated, it is possible to select damage elements that can be damaged when an earthquake occurs. The damaged element includes a main body (for example, a storage rack and a deionized water tank), a fixing screw (for example, a screw for fixing the storage rack), and a gripping chain (for example, a deionized water tank) Gripping chain). These damage elements are analysis objects that are targets for calculating the occurrence probability of the damage mode. The information on the analysis object thus selected is input to the system 1 in response to, for example, the user operating the input device 11 and stored in the storage device 13 (and the data storage unit 24).

  Further, along with the selection of the analysis object, the user determines a damage mode in which the analysis object can be damaged. As will be described in detail later, the damage modes include first-pass failure, sliding, and overturning related to a single scenario earthquake, and cumulative damage failure related to a multi-scenario earthquake. Here, for sliding and overturning, select the object that is not fixed by bolting or welding, but just placed on the ground surface, and for destruction, the object is bolted What has fixed point or fixed surface by welding, etc. should just be selected. The information on the damage mode determined here is also input to the system 1 in response to, for example, the user operating the input device 11, and corresponds to the information on the analysis target in the storage device 13 (and the data storage unit 24). It will be stored together (see FIG. 12).

(Create input waveform for design)
Next, a procedure for creating a design input waveform executed by the analysis condition setting unit 21 will be described with reference to FIGS. The floor steady vibration data input unit 211 of the analysis condition setting unit 21 inputs and stores the vibration response data of the floor surface of the first floor or the second floor of the building where the analysis target is installed in the system 1. Although the floor vibration response data is not shown in the figure, the time history acceleration data of the floor surface steady vibration measured by an acceleration sensor installed at a predetermined location on the first and second floors of the building (floor vertical) Direction (see P41 in FIG. 4). The input device 11 inputs the measured time history acceleration data to the system 1 and the storage device 13 stores it.

  The arbitrary waveform extraction unit 212 reads out the time history acceleration data stored in the storage device 13 and arbitrarily cuts out a waveform from the time history acceleration data using a random number (see P42 in FIG. 4).

The envelope curve calculation unit 213 sets an envelope function including a rising portion of an initial motion, a steady portion, and a decay portion as a function indicating a temporal change of the ground motion in order to set secular motion characteristics over time (see P42 in FIG. 4). . More specifically, the Jennings-type envelope function E (t) shown in Equation (1) is used (“A Study on the Envelope Function of Earthquake Waveforms” Kazuo Dan, Takahide Watanabe, pp.773-774, 1989, Japanese Architecture Society (Kyushu)), using equation (2) as an estimation formula for the parameter T _i (i = ad) that determines the duration of the envelope function (“Statistical characteristics of duration of ground motion based on multipoint strong motion observation records” "Takeshi Kamada, Nobuo Fukuwa, Jun Tobita, 2003, Architectural Institute of Japan Annual Meeting Abstract (Tokai)). The period from T _{a to} T _b corresponds to the rising part of the initial movement, the period from T _{b to} T _c corresponds to the steady part, and the period from T _{c to} T _d corresponds to the attenuation part.

ここで、Ｂは減衰特性を表すパラメータ、Ｍはマグニチュード、Ｘは震源距離（ｋｍ）である。式（１）（２）において、地震のマグニチュードＭと震源距離Ｘとが、入力装置１１の操作を通じてユーザにより設定されれば、包絡関数Ｅ（ｔ）の時間に係るパラメータＴ_ｉ（ｉ＝ａ〜ｄ）及びＢが設定される。

Here, B is a parameter representing attenuation characteristics, M is a magnitude, and X is a source distance (km). In the equations (1) and (2), if the earthquake magnitude M and the epicenter distance X are set by the user through the operation of the input device 11, the parameter T _i (i = a) related to the time of the envelope function E (t) ~ D) and B are set.

  The evaluation seismic intensity input unit 214 prompts the user to set the seismic intensity class of the earthquake related to the risk evaluation through the display on the display, and accepts the seismic intensity class set by the user operating the input device 11, This is stored in the storage device 13 (and the data storage unit 24).

  The waveform amplitude amplification unit 215 multiplies the time history acceleration data cut out by the arbitrary waveform extraction unit 212 and the envelope function set by the envelope curve calculation unit 213 to create a waveform having secular motion temporal characteristics ( (See P43 in FIG. 4). Further, the waveform amplitude is amplified according to the seismic intensity class set and stored by the evaluation seismic intensity input unit 214 (see P44 in FIG. 4), and a design input waveform is created.

  The design input waveform output unit 216 outputs the created design input waveform for the subsequent response output calculation of the analysis object.

(Calculation of response output of analysis object)
Next, the calculation procedure of the response output of the analysis target executed by the analysis condition setting unit 21 will be described with reference to FIGS. As described above, the analysis object input unit 217 reads information about the analysis object that is selected in advance by the user and stored in the storage device 13 (step S51 in FIG. 5), and the FEM model input unit 218 reads out the information. Based on the information on the analyzed object, the FEM model 57 of each analyzed object is created (step S52). Although the FEM model 57 is not shown, the FEM model 57 is interactively operated based on the output of the output device 12 (display on the display) and the input of the input device 11 (operation of the input device 11 by the user). 57 may be created, or an FEM model 57 created separately in advance may be input to the system 1 through the input device 11. The FEM model 57 of each analysis object created or input here is appropriately stored in the storage device 13 (and the data storage unit 24).

  The attenuation constant input unit 219 inputs an attenuation constant used for response analysis to the system 1 (step S53). As the attenuation constant, for example, an attenuation constant obtained by an experimental mode analysis performed in advance may be input to the system 1 at this timing through the operation of the input device 11 or may be stored in the storage device 13 in advance. The attenuation constant may be read from the storage device 13 (or the data storage unit 24).

  The design waveform input unit 2110 reads the design input waveform 58 created above (step S54), and the time history response analysis unit 2111 inputs the FEM model 57 input by the FEM model input unit 218 and the design waveform input. Based on the design input waveform read by the unit 2110, the response analysis of the analysis object is executed by the time history response analysis according to a predetermined calculation formula stored in the storage device 13 (step S55). Since time history response analysis is common, detailed description thereof is omitted here. This time history response analysis is performed for each analysis object, whereby a response output 59 of each analysis object during an earthquake is obtained. The response output unit 2112 outputs the response output 59 of each analysis object to the damage probability calculation unit 22 (and the storage device 13 and the data storage unit 24) (step S56).

(Damage probability calculation)
Structures that receive seismic inputs must maintain their functions during and after seismic motion, and safety is important in designing various machines and structures. . There are roughly two methods for evaluating safety. One is a method based on the concept of safety factor, and the other is a method based on the concept of reliability. The method based on the concept of safety factor is a determinism in which the load acting on a machine or structure and its strength are deterministic amounts, and the design load is designed to be less than the value obtained by dividing the strength by the safety factor (allowable load). It is a natural way of thinking. A machine or structure designed in this way should maintain its function without damage to loads up to twice the safety factor of the design load, provided that the load or strength is a definite amount. In practice, however, the load and strength are rarely deterministic quantities, and in most cases are uncertain quantities with some variation. In such a case, damage may occur even if the load is lower than the safety factor times the design load. As described above, the evaluation method based on the concept of the safety factor can be evaluated only based on the concept of the probability of damage.

  On the other hand, the evaluation method based on the concept of reliability is a method in which a probabilistic concept is introduced, and both the load and the strength are uncertain quantities, that is, there is variation, and the probability and statistical This is a method of considering the probability of damage. The complementary probability of damage probability is called reliability. The smaller the damage probability, the higher the reliability. The method of evaluating the safety of a structure from a probabilistic standpoint, taking into account the uncertainties of the various variations associated with it, is called the reliability theory or safety theory of the structure. In this evaluation system 1, as will be described in detail below, damage to the analysis object is evaluated using a probabilistic method based on the concept of reliability.

  In the evaluation system 1, as described above, the ground motion is classified into a single scenario earthquake and a multi-scenario earthquake, and three modes of first-pass failure, sliding and falling are set as damage modes due to the single scenario earthquake. At the same time, cumulative damage destruction is set as the damage mode due to the multi-scenario earthquake. Thus, the four different damage modes of first pass failure, sliding and falling, and cumulative damage failure are evaluated with the same criteria. Below, the evaluation is demonstrated for every damage mode.

(Evaluation method for first-pass failure)
The first-pass failure probability is calculated by the first-pass failure probability calculator 221 of the damage probability calculator 22. FIG. 6 shows a procedure for calculating the probability of occurrence of the first-pass failure. The yield strength (material property) and external force (response output 59 of the analysis object) of the analysis object are represented by random variables R and S, respectively. As shown in P61, P62 of FIG. 6, respectively the probability density function of R and _S, and _{f R (r), f S} (s), R ≦ S is destructive, R> S is intended to refer to non-destructive I think. Here, “destruction” means that the index value of the structural yield strength exceeds the index value of the external force effect, and does not mean that the structure is actually destroyed.

The probability that R ≦ S is satisfied is defined as the occurrence probability (damage probability) P _f of the damage mode of the object to be analyzed by Expression (3).

ＲとＳとを互いに独立な確率変数とすれば、Ｐ_ｆは、図６のＰ６３，Ｐ６４の図（尚、Ｐ６３は二次元イメージ、Ｐ６４は三次元イメージである）における、ｒ≦ｓの領域Ｄ_Ｆ上の同時確率密度関数ｆ_ＲＳ（ｒ，ｓ）を積分することにより得られ、式（４）で与えられる。式（４）は損傷確率の算出式として、入力装置１１を通じてシステム１に入力されて、記憶装置１３に予め記憶されることになる。

If R and S are independent random variables, P _f is a region of r ≦ s in the diagrams of P63 and P64 in FIG. 6 (where P63 is a two-dimensional image and P64 is a three-dimensional image). It is obtained by integrating the joint probability density function f _RS (r, s) on _DF , and is given by Equation (4). Equation (4) is input to the system 1 through the input device 11 as a calculation formula for damage probability, and stored in the storage device 13 in advance.

Further, assuming that the first-pass fracture includes shear fracture and bending fracture, the evaluation formula of shear fracture is expressed by α _H ≧ Aτ _B / M, and the evaluation formula of bending fracture is α _H ≧ Zσ _B / ML. Indicated by Where α _H is the horizontal acceleration (maximum response acceleration) of the object caused by the earthquake external force, A is the cross-sectional area, M is the mass, τ _B is the shear strength, Z is the cross-sectional modulus, L is the length, σ _B is bending strength. The random variables included in these evaluation formulas are α _H and τ _B or σ _B (see P61 and P62 in FIG. 6).

  The two evaluation formulas relating to the first-pass failure are also input to the system 1 through the input device 11 and stored in the storage device 13. The first-pass failure probability calculation unit 221 reads the equation (4) and each evaluation equation from the storage device 13 when necessary, and outputs the response output 59 (maximum response acceleration) of the analysis object calculated by the analysis condition setting unit 21. Based on the equation (4) and the first pass failure evaluation formula, the probability of occurrence of the first pass failure of the analysis object is calculated.

(Evaluation method for sliding)
The occurrence probability of the sliding is calculated by the sliding probability calculating unit 222 of the damage probability calculating unit 22. FIG. 7 shows a procedure for calculating a sliding evaluation formula. Sliding generally refers to a phenomenon in which an object moves from its original location by receiving an input seismic force during an earthquake. Here, when an earthquake external force F exceeds the maximum static frictional force F _f, regarded as the object is slid (F ≧ F _f). That is, here, the start of slipping of the object when receiving an earthquake input is determined as a sliding phenomenon. The judgment of sliding at the start of sliding is the strictest condition, and from this viewpoint, the evaluation on the safe side is also performed from the viewpoint of reliability.

The maximum static friction force is expressed by F _f = μm (g−α _V ). Here, α _V is the vertical acceleration (maximum response acceleration) of the object caused by the seismic external force, μ is the maximum static frictional force, m is the mass of the structure, and g is the gravitational acceleration. Therefore, the sliding condition is α _H ≧ μ (g−α _V ). If the relational expression between vertical acceleration and horizontal acceleration, α _V = (1/2) · α _H , which is adopted for the evaluation of facilities and equipment of nuclear power plants and chemical plants, is used in this equation, the sliding condition (Evaluation formula) is finally expressed by α _H ≧ (2 gμ) / (2 + μ). The random variables included in this evaluation formula are α _H and μ (see P72 and P73 in FIG. 7). The maximum static friction coefficient necessary for this evaluation formula is obtained by, for example, performing a tensile test using only a spring in advance and storing the measured value in the storage device 13 (and the data storage unit 24) through the input device 11. Good (see P71 in FIG. 7).

  This sliding evaluation formula is also input to the system 1 through the input device 11 in advance and stored in the storage device 13, and the sliding probability calculation unit 222, when necessary, stores the sliding evaluation formula and the formula (4) from the storage device 13. ), And based on the response output 59 (maximum response acceleration) of the analysis object, the probability of occurrence of sliding of the analysis object is calculated according to the equation (4) and the sliding evaluation equation.

(Evaluation method for falls)
The fall probability calculation unit 223 of the damage probability calculation unit 22 calculates the fall occurrence probability. FIG. 8 shows a procedure for calculating a fall evaluation formula. Here, the overturn is a phenomenon in which an object undergoes a rotational motion around a fulcrum by receiving an input seismic force during an earthquake. There are some fall evaluations that consider fall as a dynamic phenomenon and obtain a more exact estimation formula. Here, judgment conditions using static acceleration, which is the strictest condition, are used. As a result, the safety side evaluation is performed in the same manner as the sliding evaluation.

As shown in P82 of FIG. 8, the seismic external force is F, the gravity is F _g , the maximum horizontal acceleration α _H and the maximum vertical acceleration α _V , the geometric center position of the object is point C, and the center of gravity position is point G. Represented by The point O ′ is an intersection on the x axis with the point G, and the point O is an intersection on the x axis with the point C, and this is the origin (0, 0). Further, a and b are distances in the x and y directions from the point C to the point G, respectively. Here, the seismic force F, the x-axis on the intersection X of the resultant force vector of gravity F _g, the size of the x-direction component | O'X | is, | O'A | when exceeded, it is determined that the fall . Based on the balance formula of moments around the point X, the overturn condition (evaluation formula) is expressed by formula (5).

βは、構造物のアスペクト比（幅に対する高さの比率）、γは重力位置による影響を表すパラメータである。ここでは寸法形状のばらつきは考慮しないとする。従って転倒評価式に含まれる確率変数はα_Ｈだけとなる（図８のＰ８１参照）ことから、転倒確率は、式（６）又は式（７）を用いて算出することが可能である（図８のＰ８３参照）。

β is an aspect ratio of the structure (ratio of height to width), and γ is a parameter that represents the influence of gravity position. Here, it is assumed that variations in dimensions and shapes are not considered. Accordingly, since the only random variable included in the fall evaluation formula is α _H (see P81 in FIG. 8), the fall probability can be calculated using the formula (6) or the formula (7) (see FIG. 8). 8 P83).

  The fall evaluation formula and the formula (6) (or formula (7)) are input to the system 1 in advance through the input device 11 and stored in the storage device 13. Then, the fall evaluation formula and formula (6) (or formula (7)) are read from the storage device 13, and based on the response output 59 (maximum response acceleration) of the analysis object, formula (6) (or formula (7) ) And the fall evaluation formula, the occurrence probability of the fall of the analysis object is calculated.

Here, FIG. 11, for part of the analysis object, (a) first pass destruction (shear fracture), (b) sliding, and the probability of occurrence of (c) falls, as a function of the maximum horizontal acceleration alpha _H An example of the calculated result is shown. As described above, the calculation units 221 to 223 can calculate the probability of occurrence of each damage mode for each analysis object for each magnitude of the maximum horizontal acceleration, in other words, for each seismic intensity class.

  In this way, for a single scenario earthquake, the occurrence probability of damage of each analysis object is calculated for each seismic intensity class, and the calculated occurrence probability of damage is associated with the analysis object and stored in a storage device. 13 is stored. As described in detail later, the occurrence probability column in the Seismic P-FMEA worksheet as shown in FIG. 12 is filled. Note that the SP-FMEA worksheet is created for each seismic intensity class.

(Evaluation method for cumulative damage destruction)
In this system 1, cumulative damage fracture that is a damage mode for a multi-scenario earthquake is considered fatigue fracture. In general, the fatigue strength characteristics are evaluated by using an SN diagram in which the vertical axis represents the stress amplitude as a logarithm or logarithm, and the horizontal axis represents the fatigue life as a logarithm. Here, since the fatigue life varies, a P-S-N diagram is obtained at each point on the S-N diagram to obtain a probability of failure at that point, that is, a probability of occurrence of fatigue failure. By using it, the variation of the SN diagram is taken into consideration (see FIG. 9). In this fracture probability curved surface, the vertical axis represents the stress amplitude σ, the horizontal axis represents the number of repetitions N _f , and the height represents the fracture probability P _f .

  It is known that the fatigue life depends on the average stress, and from this fact, the SN diagram is usually created only from the results of fatigue tests conducted with the average stress or the stress ratio kept constant. Therefore, in the SN diagram, only a fatigue life having the same average stress or stress ratio can be evaluated. Therefore, a fatigue limit diagram is used as a method for evaluating the influence of the average stress on the fatigue life. Here, a modified Goodman diagram (fatigue limit diagram) is applied to the concept of the PSN diagram. This makes it possible to express variation on the fatigue limit diagram.

  Further, when performing fatigue life evaluation, it is important to determine the life guarantee rather than the estimation of the value. When fatigue life evaluation is performed using an SN diagram, a method of plotting and organizing only test results with a constant average stress or stress ratio is common. However, the actual working load actually applied to the member is often an irregular load whose average stress or stress amplitude varies with time. For this reason, if an attempt is made to evaluate the fatigue life under actual working load using the SN diagram, an SN diagram for the average stress or stress ratio corresponding to the fatigue stress is required. I need. Therefore, here, the concept of cumulative damage degree for individually obtaining damage to a fluctuating stress waveform is used. Life evaluation using the concept of cumulative damage is extremely effective for evaluating the life of actual loads. Hereinafter, a procedure for creating a fatigue limit diagram in consideration of the fracture probability and fatigue life estimation using a linear cumulative damage law will be described in order with reference to FIG.

  First, as a fatigue limit diagram, a fatigue test is performed at a constant stress ratio (predetermined stress ratio) to create an SN diagram, and a fatigue strength distribution in the fatigue limit diagram is created (see P101 in FIG. 10). ). In this case, the fatigue strength distribution is a straight line distribution with a constant stress ratio. Fatigue strength distribution may be obtained by conducting fatigue tests with various stress ratios, and a fatigue limit diagram may be created. In that case, however, it takes a lot of time, so there are only one or two stress ratios. A fatigue test may be performed.

  Based on the obtained fatigue strength distribution, a PSN diagram is created with an arbitrary fracture probability. Next, the fatigue strength at an arbitrary number of repetitions is calculated from the created PSN diagram and plotted on the fatigue strength diagram. At this time, if an SN diagram at another stress ratio is obtained, the fatigue strength is also plotted. Here, the fatigue strength distribution obtained from the SN diagram represents the failure probability in a state where a certain number of repetitions is fixed as a stress amplitude distribution. The fatigue strength distribution in the fatigue limit diagram is the stress amplitude distribution. And the average stress distribution. Therefore, the fatigue strength distribution in the fatigue limit diagram is obtained by tilting the fatigue strength distribution obtained from the SN curve on a straight line with a constant stress ratio.

In addition, from the strength distribution obtained from the results of a separate tensile test (static strength test), a value corresponding to the fracture probability of the previously plotted fatigue strength distribution is calculated and plotted on the x-axis of the fatigue limit diagram. To do. Then, by connecting a point of a certain probability of fracture obtained from a straight line with a constant stress ratio in the fatigue limit diagram and a point of the same probability of fracture obtained from the result of the tensile test, the relevant fracture probability is obtained. The fatigue limit line (corrected Goodman diagram) is obtained (see P103 in FIG. 10). By considering such a distribution, it is possible to express variations on the fatigue limit diagram. Is what is meant by this fatigue limit diagram, the stress amplitude which is located on the diagram the fatigue limit line, cyclic loading of the average stress, repetition number N _i which is set when creating the fatigue limit _diagram, and the failure probability P _f It represents the equivalent. In other words, consider the degree of damage of n _{i /} N _i are accumulated by repeating number n _i of mean stress and stress amplitude plotted repeated stress. Incidentally, damage degree obtained by accumulating this time, since a result of failure probability P _f, which accumulated damage degree D is calculated by can also be considered as having a failure probability P _f.

In creating this fatigue limit distribution, it is preferable that there are three or more data per stress level at three stress levels, but Zako et al. Proposed to obtain the fatigue strength distribution from less data. The definition of converted stress and converted life may be used ("Study on Fracture Probability Evaluation Method Considering Uncertainty of Average Stress and Stress Amplitude" Masaru Zako, Tetsuo Kurashiki, Hiroaki Nakai, pp.845-846 , 2003, JSME 16th Computational Mechanics Lecture Proceedings, No.03-26, and "Structural Reliability Evaluation for Actual Load Fatigue Using Rainflow Method and Fatigue Limit Diagram" Masaru Zako Tetsuo Kurashiki, Hiroaki Nakai, pp.8-12, 2005, Japan Society of Materials Science, Vol.54, No.1). Here, the converted stress is based on the assumption that the fatigue strength distribution is equal in each fatigue life of the SN diagram, and the acquired data is converted into the strength at the fatigue life _Nc as shown in P102 of FIG. It is a converted value. By using this converted stress, data of different fatigue lives can be considered as a fatigue strength distribution instead of the converted stress. Similarly, the converted life is a value obtained by converting the data into the life at a certain stress amplitude based on the assumption that the fatigue life distribution is equal in each fatigue strength of the SN diagram. By using these concepts, it is possible to estimate the fatigue strength distribution and fatigue life distribution from all test results.

  Furthermore, in the fatigue test, when the upper limit of the number of repetitions in the test is set and the test is terminated when the number is reached, the aborted test data is handled as the abort data. In this case, the Jonson method may be used to estimate the fatigue test distribution.

Next, fatigue life estimation using the cumulative damage law will be described. The fatigue life due to the combination of different stress amplitude loads can be obtained by estimating the fatigue damage due to each stress amplitude load from the SN diagram and calculating the linear cumulative damage law based on the fatigue life. Here, the fatigue life when the stress amplitudes σ ₁ , σ ₂ ,..., Σ _i are repeatedly given independently is defined as N ₁ , N ₂ ,..., _Ni , and the respective stress amplitudes are n ₁ , n _2, ..., if repeated _{n i} times, fatigue damage of the respective _{stresses, n 1 / n 1, n} 1 / n 1, ..., considered n i / _{n i.} Thus, the cumulative damage degree when each stress acts in combination is considered as D = Σ (n _i / N _i ). When this cumulative damage degree D becomes 1 (D = Σ (n _i / N _i ) = 1), it is considered that it is a fatigue life (linear cumulative damage law or minor law). Since the Miner's law, the stress amplitude is less fatigue limit is N _i is considered infinite fatigue life may have a variation, also it is dangerous to completely ignore the stress amplitude below the fatigue limit, By extending the slope of the SN curve below the fatigue limit, the life evaluation is performed according to the modified minor rule in consideration of the stress amplitude below the fatigue limit.

In order to evaluate the fatigue damage given to the member by the actual load, it is necessary to determine the frequency of the stress value acting. Here, the rain flow method having good correspondence with the stress-strain behavior of the material is used for the stress frequency analysis of the actual load (see P104 in FIG. 10). As a result, a combination of average stress and stress amplitude and the number of repetitions of the stress are obtained. The thus calculated combination of average stress and stress amplitude is plotted on a fatigue limit diagram (see P105 in FIG. 10), and this is combined with a fatigue limit diagram in consideration of the fracture probability (see P106 in FIG. 10). . P106 shows a schematic diagram depicting a fatigue limit diagram by changing the fatigue life with respect to various repeated stresses. For each repeated stress obtained by the rainflow analysis, the damage degree is determined at the same failure probability. By calculating and accumulating the degree of damage, the cumulative damage degree D _pf by one cycle of the actual load is calculated. In other words, when the production load is repeated 1 / D _pf cycles, leading to fatigue fracture in fracture probability P _f. Thus, while incrementing the failure probability P _f, by repeatedly calculating a lifetime for production load, the relationship between the production time and the fracture probability is obtained. When this method is applied to earthquake motion, the failure probability is obtained for each single earthquake, and the failure probability with respect to the number of occurrences of the expected earthquake motion is illustrated by, for example, P107 in FIG. 10 by accumulating the failure probability of each earthquake. As such, it can be calculated. Here, T is the number of earthquakes that have occurred, and the probability of destruction increases as the number of occurrences increases.

  The multi-scenario earthquake relating to the cumulative damage destruction is set and input by the user, for example, through the input device 11. As a multi-scenario earthquake, for example, three earthquakes with different seismic intensity classes are generated. “Measured seismic intensity I of the first earthquake I = 6.25, seismic intensity class 6 strong, second seismic intensity I = 7 The multi-scenario earthquake is specifically set as appropriate, such as “0.0, seismic intensity class 7 and measured earthquake intensity I = 5.25 of the third earthquake, and seismic intensity class 5”. Further, for example, the arithmetic processing unit 14 may automatically set a plurality of scenario earthquakes using random number generation or the like.

  As described above, the cumulative damage probability calculation unit 224 calculates the damage degree (D value) of the analysis object for one scenario earthquake based on the information on the multiple scenario earthquakes stored in the storage unit 24 or the like. By accumulating them, the failure probability for a plurality of earthquakes (number of earthquakes) is calculated.

  In this way, regarding the multi-scenario earthquake, the occurrence probability of damage of each analysis object is calculated for each scenario, and the calculated occurrence probability of damage is associated with the analysis object, and the storage device 13 The occurrence probability column in the Seismic P-FMEA worksheet as shown in FIG. 12 is filled in. Note that the SP-FMEA worksheet is created for each scenario for multiple scenario earthquakes.

  As described above, in this system 1, the occurrence probability of each damage mode of first-pass failure, sliding and falling associated with a single scenario earthquake, taking into account variations in the structural strength and the external force of the earthquake, and The probability of occurrence of cumulative damage destruction related to a multi-scenario earthquake is calculated as a numerical value, and this quantification increases the reliability of the earthquake risk evaluation of the system 1.

(Risk assessment department)
The risk evaluation unit 23 is set and input to the system 1 through the input device 11 by the user in advance and the occurrence probability of each damage mode calculated by the calculation units 221 to 224 in the damage probability calculation unit 22, and the storage unit 13. The risk is calculated based on the degree of influence stored in. Specifically, in the system 1, as described above, SP-FMEA specialized for earthquake risk is defined based on FMEA. In this SP-FMEA, the product of the occurrence probability of the damage mode of each analysis object (corresponding to a failure mode in a general FMEA) and the degree of influence representing the magnitude of value loss of the analysis object, It is defined as an earthquake risk and is used as a quantitative index of earthquake risk. SP-FMEA is characterized in that it includes the probability of occurrence of a damage mode when compared with general FMEA.

  FIG. 12 shows an example of an SP-FMEA worksheet. As described above, the SP-FMEA worksheet is stored in the storage device 13 (and the data storage unit 24). In the SP-FMEA worksheet, the damage mode occurrence probability column is filled with the occurrence probability calculated by the damage probability calculation unit, as described above. On the other hand, the user makes a setting input for the influence level column in the SP-FMEA worksheet. That is, for example, the user selects the analysis object and determines the damage mode, and appropriately sets the influence degree of each analysis object as a numerical value, and inputs this to the system 1 through the input device 11. The degree of influence of each input analysis object is stored in the storage device 13 in association with the analysis object. Here, “impact level” includes the time and cost required for recovery from trouble caused by an earthquake. In particular, in this example, the long-term stability test stops, This includes losses due to delayed application for approval for manufacturing and sales.

  When performing risk assessment for individual damaged elements (analysis objects), the assessment can be performed by calculating the product of the probability of occurrence and the degree of influence. However, in SP-FMEA, the damage to the purpose of considering the risk, that is, the process up to the damage of the evaluation target is not specified, and therefore the target evaluation target risk cannot be calculated as it is. Therefore, in this system 1, a process up to damage is clarified using ETA which is a risk analysis technique, and a risk is calculated by a combination of SP-FMEA and ETA. FIG. 13 shows an example of the risk extraction table. Here, there are two assessment targets for risk: specimen breakage and data loss. Sample breakage includes falling from the shelf (event (I)), device shutdown due to power loss (event (II)), Water supply stop due to missing water supply (event (III)), temperature / humidity deviation due to missing refrigerant pipe (event (IV)), sensor drop (event (V)), board fall (event (VI)), and ignition due to short circuit ( Event (VII)), data loss includes PC rack overturning (event (VIII)), PC power line disconnection (event (IX)), and device damage (event (X)) Yes. This risk extraction table may be input to the system 1 through operation of the input device 11 by the user and stored in the storage device 13.

  The risk evaluation unit 23 first creates an ET (Event Tree). ET is a schematic representation of the logical sequence of event occurrence, which clarifies the process leading to the top event (in this case, specimen corruption and data corruption), and the probability of damage mode occurrence in each process. It becomes possible to calculate. The ET is created by the user operating the input device 11 while reading the risk extraction table and the SP-FMEA worksheet from the storage device 13 and displaying them on the display (output by the output device 12). You may make it do. For example, FIG. 14 is an ET corresponding to the event (I) in the risk extraction table of FIG. In this way, ETs are created for all the events included in the preset risk extraction table. In some cases, there is no process from the occurrence of an earthquake to the top event (that is, the damage mode of the damaged element in FIG. 12 may directly become the occurrence probability of the top event). The created ET is associated with the event and stored in the storage device 13 (or data storage unit 24).

The risk evaluation unit 23 also calculates the occurrence probability of each event using the created ET (see 231 in FIG. 3). Specifically, as shown in FIG. 14, the risk evaluation unit 23 reads the created ET from the storage device 13 (or the data storage unit 24), and the occurrence probability P _i (i = A to Z) of each process there. The value of the occurrence probability of the SP-FMEA workflow read out from the storage device 13 (or the data storage unit 24) is also substituted. Then, the occurrence probability _Pfx is calculated by multiplying the probabilities of the respective processes, and the maximum value P (MAX) is set as the occurrence probability of the event. As described above, the occurrence probability of the damage mode is calculated for each seismic intensity class, and the SP-FMEA workflow is created for each seismic intensity class (for example, FIG. 14 is an example when the seismic intensity class is less than 6). Correspondingly, the occurrence probability of this event is calculated for each seismic intensity class.

On the other hand, the degree of influence of each event is calculated by summing the degree of influence of the process included in each event in the ET (see 232 in FIG. 3). In the example of FIG. 14, the influence degree is α _A + α _B + α _D. The influence degree of each process may be set for each seismic intensity class, and the influence degree of each event may be calculated for each seismic intensity class.

  Then, for each event, the occurrence probability (maximum occurrence probability) is calculated for each seismic intensity class, and if the influence degree is calculated, the risk evaluation unit 23 creates a risk matrix based on that. FIG. 15 shows an example of the risk matrix. In this risk matrix, the vertical axis indicates the probability of occurrence and the horizontal axis indicates the degree of influence. The values of each event ((I) to (VIII) in the example, (I) to (VIII) correspond to FIG. Are plotted for each seismic intensity class. The higher the probability of occurrence, the more likely damage will occur at the time of the earthquake, and the greater the degree of impact, the greater the damage caused by the damage at the time of the earthquake, so the lower left area in this risk matrix is an acceptable area. The relatively upper right area is an unacceptable area. Further, when the occurrence probability is relatively high and / or the influence degree is relatively high, it can be determined that some countermeasure is necessary. As measures, for example, in the case of evaluation of an existing stability test system, measures such as reinforcing a predetermined part of the existing stability test system can be cited. Measures such as design changes. In this way, the risk matrix can be evaluated for each seismic intensity class in consideration of the effects of the occurrence probability and the degree of influence constituting the risk.

  Instead of this risk matrix or together with the risk matrix, the occurrence probability and risk for each event (risk = occurrence probability × influence degree) may be calculated.

  The created risk matrix and risk values are displayed on a display, output to a printer (output of the output device 12), or stored in the storage device 13.

  As described above, this earthquake risk evaluation system 1 employs an evaluation using a probabilistic method based on reliability engineering as an evaluation of the occurrence of damage to each analysis object constituting the evaluation object of the earthquake risk. is doing. Specifically, the occurrence probability of the damage mode is calculated by using the characteristics related to the proof stress of the analysis object and the seismic external force as random variables. As a result, the variation in the yield strength of the analysis object, specifically the variation in the material physical properties, etc. and the variation in the external force of the earthquake are taken into account. Can be quantified. This realizes the quantification of the risk assessment of the earthquake risk assessment system 1 and the high reliability of the assessment associated therewith.

  Moreover, the damage mode can be appropriately evaluated by considering the damage mode of the analysis object separately into the damage mode due to the single scenario earthquake and the damage mode due to the multiple scenario earthquake. In addition, as damage modes caused by a single scenario earthquake, three damage modes of first-pass failure, sliding and falling are set, while predetermined probability formulas (Equations (4), (6), (7)) and By calculating the probability of occurrence of these damage modes based on the evaluation formula, different damage modes can be evaluated based on the same standard. Similarly, cumulative damage fractures resulting from multi-scenario earthquakes can be evaluated using the same criteria as other damage modes.

  In addition, by defining SP-FMEA as risk assessment, FMEA can be specialized in earthquake risk assessment, and by combining the SP-FMEA and ETA, the risk assessment can be quantified High reliability of risk assessment can be secured.

  Furthermore, as a result of risk assessment, by creating a risk matrix based on the three parameters of damage mode occurrence probability, impact level, and seismic intensity, the risk can be evaluated in consideration of both the occurrence probability and impact level. It becomes possible.

  Therefore, in this earthquake risk evaluation system 1, for example, it is possible to perform earthquake risk evaluation with high reliability without relying on the earthquake resistance characteristic evaluation of an actual machine using a shaking table, and the earthquake risk evaluation can be easily performed. This is extremely effective in reducing the time and cost required for earthquake risk assessment.

  As described above, the evaluation target of the earthquake risk evaluation system 1 does not have to be a constant temperature and humidity chamber, and is applicable to a test system that performs other environmental tests, for example. In addition, it is not limited to such a test system, and can be used for earthquake risk assessment of various other systems (for example, data centers including various server devices installed in a predetermined building). is there.

  As explained above, the earthquake risk evaluation system disclosed herein can perform quantitative earthquake risk evaluation without using a shaking table, etc., and can provide a highly reliable earthquake risk in a short time and at a low cost. It is useful for seismic risk assessment of various systems because it can be evaluated.

1 Earthquake risk assessment system 11 Input device (input unit)
12 Output device (output unit)
13 Storage device (storage unit)
14 Arithmetic processing device (arithmetic processing unit)

Claims (7)

An earthquake risk evaluation system for evaluating an earthquake risk of a predetermined evaluation object,
An input unit configured to be operable by the user and outputting information corresponding to the operation;
An output unit that outputs various types of information so that the user can recognize the information,
A storage unit for storing various information; and
An arithmetic processing unit that is connected to the input unit, the output unit, and the storage unit so as to be able to exchange information, and executes various types of calculations.
The storage unit stores information on an analysis target that may affect the evaluation target by being damaged when an earthquake occurs,
The arithmetic processing unit
Read information about the analysis object from the storage unit,
A response output when a design input waveform simulating the earthquake motion input to the analysis target is input to the analysis target is calculated according to a predetermined response calculation formula stored in the storage unit,
Based on the calculated response output and the characteristics related to the strength of the analysis object, a damage mode occurs in the analysis object using at least the response output as a random variable among the characteristics related to the response output and the strength. A damage probability that is a probability of performing according to a predetermined probability calculation formula stored in the storage unit,
Create a risk assessment result based on the calculated damage probability and information on the degree of influence representing the magnitude of value loss when a damage mode occurs in the analysis object stored in the storage unit,
An earthquake risk evaluation system for outputting the created risk evaluation result through the output unit. In the earthquake risk evaluation system according to claim 1,
The said arithmetic processing part is an earthquake risk evaluation system which calculates the probability of occurrence of at least one damage mode among first-pass failure, sliding, and falling as a damage mode caused by a single earthquake motion. In the earthquake risk evaluation system according to claim 1 or 2,
The arithmetic processing unit is an earthquake risk evaluation system that calculates an occurrence probability of cumulative damage destruction as a damage mode caused by a plurality of earthquake motions. In the earthquake risk evaluation system according to any one of claims 1 to 3,
The arithmetic processing unit, as risk assessment,
Create an FMEA worksheet containing the probability and impact of damage for each analysis object,
An earthquake in which an occurrence process of an event that may cause damage to the evaluation object is analyzed by a combination of an event tree analysis and the FMEA worksheet, and an occurrence probability of the event and an influence degree due to the occurrence of the event are calculated. Risk assessment system. In the earthquake risk evaluation system according to claim 4,
The arithmetic processing unit
An earthquake in which the occurrence probability of the event is calculated for each seismic intensity class, and a risk matrix including three parameters of the occurrence probability of the event, the influence degree due to the event occurrence, and the seismic intensity class is generated and output through the output unit Risk assessment system. In the earthquake risk evaluation system according to any one of claims 1 to 5,
The storage unit stores a measurement value of time history acceleration data of stationary vibration of a floor surface on which the analysis object is installed, and a predetermined function indicating a temporal characteristic of seismic motion,
The arithmetic processing unit creates the waveform that combines the measurement value and the function, and amplifies the amplitude of the waveform according to the seismic intensity class that is set and input through the input unit. An earthquake risk evaluation system for creating the design input waveform corresponding to a seismic intensity class. In the earthquake risk evaluation system according to any one of claims 1 to 6,
The evaluation object is an earthquake risk evaluation system which is an environmental test apparatus for testing the storage stability of a predetermined specimen.

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