SAPHIREで前稿で生成したMARDファイルをロードすると、図925.1のようなFTが生成されます。

次にSolveで論理圧縮をかけ、View CutSetによりカットセットを表示させます。

表925.1に示すとおり、頂上事象の確率は $\img[-1.35em]{/images/withinseminar.png}$ となります。

2020年にSaphireを使用した同じMethod3の以前の記事では頂上事象の確率は8.321E-04でした。若干異なるのは丸め誤差や内部精度が変わったのかもしれません。

なお、本稿はRAMS 2027に投稿予定のため一部を秘匿していますが、論文公開後の2027年2月頃に開示予定です。

前のブログ 次のブログ

弊社コンテンツの昨年12月の検索結果です。

前のブログ 次のブログ

ChatGPTに前項のRBDを読ませ、頂上事象をMETHOD3としてMARDを生成してもらいました。2nd SMの効果の係数は再利用させ、全積項数40個になるところを9個としました。以下にChatGPTが生成したMARDを示します。

METHOD3.MARD

TEST_Subs\METHOD3.BED
TEST_Subs\METHOD3.BEI
TEST_Subs\METHOD3.FTD
TEST_Subs\METHOD3.FTL
TEST_Subs\METHOD3.GTD

METHOD3.BED

*Saphire 8.2.9
TEST =
* Name , Descriptions , Project
P1 , P1desc , TEST
MCU1 , MCU1desc , TEST
D1 , D1desc , TEST
I1 , I1desc , TEST
M1 , M1desc , TEST
SC1 , SC1desc , TEST
CA1 , CA1desc , TEST
SA1 , SA1desc , TEST
P2 , P2desc , TEST
MCU2 , MCU2desc , TEST
D2 , D2desc , TEST
I2 , I2desc , TEST
M2 , M2desc , TEST
SC2 , SC2desc , TEST
CA2 , CA2desc , TEST
SA2 , SA2desc , TEST
C11 , CoverageFactor_C11 , TEST
C12 , CoverageFactor_C12 , TEST
C13 , CoverageFactor_C13 , TEST
C14 , CoverageFactor_C14 , TEST
C15 , CoverageFactor_C15 , TEST
C16 , CoverageFactor_C16 , TEST
C17 , CoverageFactor_C17 , TEST
C18 , CoverageFactor_C18 , TEST
C19 , CoverageFactor_C19 , TEST

METHOD3.BEI

*Saphire 8.2.9
TEST =
* Name ,FdT,UdC,UdT,UdValue,Prob,Lambda,Tau,Mission,Init,PF,UdValue2,Calc. Prob,Freq,Analysis Type,Phase Type,Project
P1 ,3, , ,0.000E+000,0.000E+000,2.330E-07,0,1.500E+004, , ,0.000E+000,3.489E-03, ,RANDOM,CD,TEST
MCU1 ,3, , ,0.000E+000,0.000E+000,8.180E-07,0,1.500E+004, , ,0.000E+000,1.220E-02, ,RANDOM,CD,TEST
D1 ,3, , ,0.000E+000,0.000E+000,1.090E-07,0,1.500E+004, , ,0.000E+000,1.634E-03, ,RANDOM,CD,TEST
I1 ,3, , ,0.000E+000,0.000E+000,5.990E-07,0,1.500E+004, , ,0.000E+000,8.945E-03, ,RANDOM,CD,TEST
M1 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
SC1 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
CA1 ,3, , ,0.000E+000,0.000E+000,5.100E-08,0,1.500E+004, , ,0.000E+000,7.647E-04, ,RANDOM,CD,TEST
SA1 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
P2 ,3, , ,0.000E+000,0.000E+000,2.330E-07,0,1.500E+004, , ,0.000E+000,3.489E-03, ,RANDOM,CD,TEST
MCU2 ,3, , ,0.000E+000,0.000E+000,8.180E-07,0,1.500E+004, , ,0.000E+000,1.220E-02, ,RANDOM,CD,TEST
D2 ,3, , ,0.000E+000,0.000E+000,1.090E-07,0,1.500E+004, , ,0.000E+000,1.634E-03, ,RANDOM,CD,TEST
I2 ,3, , ,0.000E+000,0.000E+000,5.990E-07,0,1.500E+004, , ,0.000E+000,8.945E-03, ,RANDOM,CD,TEST
M2 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
SC2 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
CA2 ,3, , ,0.000E+000,0.000E+000,5.100E-08,0,1.500E+004, , ,0.000E+000,7.647E-04, ,RANDOM,CD,TEST
SA2 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
C11 ,1, , ,0.000E+000,1.0000E+00,0.000E+000,0,0.000E+000, , ,0.000E+000,1.0000E+00, ,RANDOM,CD,TEST
C12 ,1, , ,0.000E+000,2.3570E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,2.3570E-01, ,RANDOM,CD,TEST
C13 ,1, , ,0.000E+000,5.3680E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,5.3680E-01, ,RANDOM,CD,TEST
C14 ,1, , ,0.000E+000,3.0520E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,3.0520E-01, ,RANDOM,CD,TEST
C15 ,1, , ,0.000E+000,2.2810E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,2.2810E-01, ,RANDOM,CD,TEST
C16 ,1, , ,0.000E+000,2.3110E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,2.3110E-01, ,RANDOM,CD,TEST
C17 ,1, , ,0.000E+000,2.2880E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,2.2880E-01, ,RANDOM,CD,TEST
C18 ,1, , ,0.000E+000,3.5150E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,3.5150E-01, ,RANDOM,CD,TEST
C19 ,1, , ,0.000E+000,2.5890E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,2.5890E-01, ,RANDOM,CD,TEST

METHOD3.FTD

TEST =
* Name , Description, SubTree, Alternate, Project
METHOD3 ,Method3TopDefinition, , ,TEST

METHOD3.FTL

TEST,METHOD3 =
METHOD3 OR MCS01 MCS02 MCS03 MCS04 MCS05 MCS06 MCS07 MCS08 MCS09 MCS10 MCS11 MCS12 MCS13 MCS14 MCS15 MCS16 MCS17 MCS18 MCS19 MCS20 MCS21 MCS22 MCS23 MCS24 MCS25 MCS26 MCS27 MCS28 MCS29 MCS30 MCS31 MCS32 MCS33 MCS34 MCS35 MCS36 MCS37 MCS38 MCS39 MCS40
MCS01 AND P1 P2 C11
MCS02 AND P1 MCU2 C12
MCS03 AND P1 D2 C12
MCS04 AND P1 I2 C13
MCS05 AND P1 M2 C14
MCS06 AND P1 SC2 C12
MCS07 AND MCU1 P2 C12
MCS08 AND MCU1 MCU2 C15
MCS09 AND MCU1 D2 C15
MCS10 AND MCU1 I2 C16
MCS11 AND MCU1 M2 C17
MCS12 AND MCU1 SC2 C15
MCS13 AND D1 P2 C12
MCS14 AND D1 MCU2 C15
MCS15 AND D1 D2 C15
MCS16 AND D1 I2 C16
MCS17 AND D1 M2 C17
MCS18 AND D1 SC2 C15
MCS19 AND I1 P2 C13
MCS20 AND I1 MCU2 C16
MCS21 AND I1 D2 C16
MCS22 AND I1 I2 C18
MCS23 AND I1 M2 C19
MCS24 AND I1 SC2 C16
MCS25 AND M1 P2 C14
MCS26 AND M1 MCU2 C17
MCS27 AND M1 D2 C17
MCS28 AND M1 I2 C19
MCS29 AND M1 M2 C12
MCS30 AND M1 SC2 C17
MCS31 AND SC1 P2 C12
MCS32 AND SC1 MCU2 C15
MCS33 AND SC1 D2 C15
MCS34 AND SC1 I2 C16
MCS35 AND SC1 M2 C17
MCS36 AND SC1 SC2 C15
MCS37 AND CA1 CA2 C18
MCS38 AND CA1 SA2 C16
MCS39 AND SA1 CA2 C16
MCS40 AND SA1 SA2 C15

METHOD3.GTD

TEST=
* Name , Description, Project
METHOD3 ,Method3TopGate, TEST
MCS01 ,Pair01, TEST
MCS02 ,Pair02, TEST
MCS03 ,Pair03, TEST
MCS04 ,Pair04, TEST
MCS05 ,Pair05, TEST
MCS06 ,Pair06, TEST
MCS07 ,Pair07, TEST
MCS08 ,Pair08, TEST
MCS09 ,Pair09, TEST
MCS10 ,Pair10, TEST
MCS11 ,Pair11, TEST
MCS12 ,Pair12, TEST
MCS13 ,Pair13, TEST
MCS14 ,Pair14, TEST
MCS15 ,Pair15, TEST
MCS16 ,Pair16, TEST
MCS17 ,Pair17, TEST
MCS18 ,Pair18, TEST
MCS19 ,Pair19, TEST
MCS20 ,Pair20, TEST
MCS21 ,Pair21, TEST
MCS22 ,Pair22, TEST
MCS23 ,Pair23, TEST
MCS24 ,Pair24, TEST
MCS25 ,Pair25, TEST
MCS26 ,Pair26, TEST
MCS27 ,Pair27, TEST
MCS28 ,Pair28, TEST
MCS29 ,Pair29, TEST
MCS30 ,Pair30, TEST
MCS31 ,Pair31, TEST
MCS32 ,Pair32, TEST
MCS33 ,Pair33, TEST
MCS34 ,Pair34, TEST
MCS35 ,Pair35, TEST
MCS36 ,Pair36, TEST
MCS37 ,Pair37, TEST
MCS38 ,Pair38, TEST
MCS39 ,Pair39, TEST
MCS40 ,Pair40, TEST

ChatGPT の回答は必ずしも正しいとは限りません。重要な情報は確認するようにしてください。

なお、本稿はRAMS 2027に投稿予定のため一部を秘匿していますが、論文公開後の2027年2月頃に開示予定です。

前のブログ 次のブログ

Method 3のRBD

次に冗長系EPSの2nd SMありのモデル(手法3)を作成させます。RBDはMethod 2と同じです。

MARDを取得する前にあらかじめExcelにより正解値を求めておくと、図922.2のように頂上侵害確率は8.425e-4、PMHFは再度増加し56.2[FIT]となります。ただしこれは$\tau=3,420 [H]$のときであり、論文では$\tau=1 [H]$のようなので、その場合は頂上侵害確率やPMHFはMethod 2とほぼ同じ値となります。

このように、定期検査周期である$\tau$がある程度大きい場合にはPMHFに大きな影響を与えます。とは言えそれはこの例のように、冗長構成を取り残余故障率が低い場合に限られます。

ここで、過去記事において$\tau=3,420 [H]$としましたが、実は$\tau=24\cdot30\cdot6\approx4,320 [H]$の誤りでした。これは仮に定期検査周期を半年にしたためです。

なお、本稿はRAMS 2027に投稿予定のため一部を秘匿していますが、論文公開後の2027年2月頃に開示予定です。

前のブログ 次のブログ

SAPHIREでこれらのMARDファイルをロードすると、図921.1のようなFTが生成されます。

次にSolveで論理圧縮をかけ、View CutSetによりカットセットを表示させます。

表921.1に示すとおり、頂上事象の確率は $\img[-1.35em]{/images/withinseminar.png}$ となります。

なお、本稿はRAMS 2027に投稿予定のため一部を秘匿していますが、論文公開後の2027年2月頃に開示予定です。

前のブログ 次のブログ

ChatGPTに前項のRBDを読ませ、頂上事象をMETHOD2としてMARDを生成してもらいました。2nd SMの効果の係数は再利用させ、40個になるところを9個としました。以下にMARDを示します。

METHOD2.MARD

TEST_Subs\METHOD2.BED
TEST_Subs\METHOD2.BEI
TEST_Subs\METHOD2.FTD
TEST_Subs\METHOD2.FTL
TEST_Subs\METHOD2.GTD

METHOD2.BED

*Saphire 8.2.9
TEST =
* Name, Descriptions, Project
P1, P1desc, TEST
MCU1, MCU1desc, TEST
D1, D1desc, TEST
I1, I1desc, TEST
M1, M1desc, TEST
SC1, SC1desc, TEST
CA1, CA1desc, TEST
SA1, SA1desc, TEST
P2, P2desc, TEST
MCU2, MCU2desc, TEST
D2, D2desc, TEST
I2, I2desc, TEST
M2, M2desc, TEST
SC2, SC2desc, TEST
CA2, CA2desc, TEST
SA2, SA2desc, TEST
C1, CoverageFactor_C1, TEST
C2, CoverageFactor_C2, TEST
C3, CoverageFactor_C3, TEST
C4, CoverageFactor_C4, TEST
C5, CoverageFactor_C5, TEST
C6, CoverageFactor_C6, TEST
C7, CoverageFactor_C7, TEST
C8, CoverageFactor_C8, TEST
C9, CoverageFactor_C9, TEST

METHOD2.BEI

*Saphire 8.2.9
TEST =
* Name ,FdT,UdC,UdT,UdValue,Prob,Lambda,Tau,Mission,Init,PF,UdValue2,Calc. Prob,Freq,Analysis Type,Phase Type,Project
P1 ,3, , ,0.000E+000,0.000E+000,2.330E-07,0,1.500E+004, , ,0.000E+000,3.489E-03, ,RANDOM,CD,TEST
MCU1 ,3, , ,0.000E+000,0.000E+000,8.180E-07,0,1.500E+004, , ,0.000E+000,1.220E-02, ,RANDOM,CD,TEST
D1 ,3, , ,0.000E+000,0.000E+000,1.090E-07,0,1.500E+004, , ,0.000E+000,1.634E-03, ,RANDOM,CD,TEST
I1 ,3, , ,0.000E+000,0.000E+000,5.990E-07,0,1.500E+004, , ,0.000E+000,8.945E-03, ,RANDOM,CD,TEST
M1 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
SC1 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
CA1 ,3, , ,0.000E+000,0.000E+000,5.100E-08,0,1.500E+004, , ,0.000E+000,7.647E-04, ,RANDOM,CD,TEST
SA1 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
P2 ,3, , ,0.000E+000,0.000E+000,2.330E-07,0,1.500E+004, , ,0.000E+000,3.489E-03, ,RANDOM,CD,TEST
MCU2 ,3, , ,0.000E+000,0.000E+000,8.180E-07,0,1.500E+004, , ,0.000E+000,1.220E-02, ,RANDOM,CD,TEST
D2 ,3, , ,0.000E+000,0.000E+000,1.090E-07,0,1.500E+004, , ,0.000E+000,1.634E-03, ,RANDOM,CD,TEST
I2 ,3, , ,0.000E+000,0.000E+000,5.990E-07,0,1.500E+004, , ,0.000E+000,8.945E-03, ,RANDOM,CD,TEST
M2 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
SC2 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
CA2 ,3, , ,0.000E+000,0.000E+000,5.100E-08,0,1.500E+004, , ,0.000E+000,7.647E-04, ,RANDOM,CD,TEST
SA2 ,3, , ,0.000E+000,0.000E+000,1.000E-06,0,1.500E+004, , ,0.000E+000,1.489E-02, ,RANDOM,CD,TEST
C1 ,1, , ,0.000E+000,1.0000E+00,0.000E+000,0,0.000E+000, , ,0.000E+000,1.0000E+00, ,RANDOM,CD,TEST
C2 ,1, , ,0.000E+000,1.0000E-02,0.000E+000,0,0.000E+000, , ,0.000E+000,1.0000E-02, ,RANDOM,CD,TEST
C3 ,1, , ,0.000E+000,4.0000E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,4.0000E-01, ,RANDOM,CD,TEST
C4 ,1, , ,0.000E+000,1.0000E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,1.0000E-01, ,RANDOM,CD,TEST
C5 ,1, , ,0.000E+000,1.0000E-04,0.000E+000,0,0.000E+000, , ,0.000E+000,1.0000E-04, ,RANDOM,CD,TEST
C6 ,1, , ,0.000E+000,4.0000E-03,0.000E+000,0,0.000E+000, , ,0.000E+000,4.0000E-03, ,RANDOM,CD,TEST
C7 ,1, , ,0.000E+000,1.0000E-03,0.000E+000,0,0.000E+000, , ,0.000E+000,1.0000E-03, ,RANDOM,CD,TEST
C8 ,1, , ,0.000E+000,1.6000E-01,0.000E+000,0,0.000E+000, , ,0.000E+000,1.6000E-01, ,RANDOM,CD,TEST
C9 ,1, , ,0.000E+000,4.0000E-02,0.000E+000,0,0.000E+000, , ,0.000E+000,4.0000E-02, ,RANDOM,CD,TEST

METHOD2.FTD

TEST =
* Name , Description, SubTree, Alternate, Project
METHOD2 ,Method2TopDefinition, , ,TEST

METHOD2.FTL

TEST,METHOD2 =
METHOD2 OR MCS01 MCS02 MCS03 MCS04 MCS05 MCS06 MCS07 MCS08 MCS09 MCS10 MCS11 MCS12 MCS13 MCS14 MCS15 MCS16 MCS17 MCS18 MCS19 MCS20 MCS21 MCS22 MCS23 MCS24 MCS25 MCS26 MCS27 MCS28 MCS29 MCS30 MCS31 MCS32 MCS33 MCS34 MCS35 MCS36 MCS37 MCS38 MCS39 MCS40
MCS01 AND P1 P2 C1
MCS02 AND P1 MCU2 C2
MCS03 AND P1 D2 C2
MCS04 AND P1 I2 C3
MCS05 AND P1 M2 C4
MCS06 AND P1 SC2 C2
MCS07 AND MCU1 P2 C2
MCS08 AND MCU1 MCU2 C5
MCS09 AND MCU1 D2 C5
MCS10 AND MCU1 I2 C6
MCS11 AND MCU1 M2 C7
MCS12 AND MCU1 SC2 C5
MCS13 AND D1 P2 C2
MCS14 AND D1 MCU2 C5
MCS15 AND D1 D2 C5
MCS16 AND D1 I2 C6
MCS17 AND D1 M2 C7
MCS18 AND D1 SC2 C5
MCS19 AND I1 P2 C3
MCS20 AND I1 MCU2 C6
MCS21 AND I1 D2 C6
MCS22 AND I1 I2 C8
MCS23 AND I1 M2 C9
MCS24 AND I1 SC2 C6
MCS25 AND M1 P2 C4
MCS26 AND M1 MCU2 C7
MCS27 AND M1 D2 C7
MCS28 AND M1 I2 C9
MCS29 AND M1 M2 C2
MCS30 AND M1 SC2 C7
MCS31 AND SC1 P2 C2
MCS32 AND SC1 MCU2 C5
MCS33 AND SC1 D2 C5
MCS34 AND SC1 I2 C6
MCS35 AND SC1 M2 C7
MCS36 AND SC1 SC2 C5
MCS37 AND CA1 CA2 C8
MCS38 AND CA1 SA2 C6
MCS39 AND SA1 CA2 C6
MCS40 AND SA1 SA2 C5

METHOD2.GTD

TEST=
* Name , Description, Project
METHOD2 ,Method2TopGate ,TEST
MCS01 ,Pair01, TEST
MCS02 ,Pair02, TEST
MCS03 ,Pair03, TEST
MCS04 ,Pair04, TEST
MCS05 ,Pair05, TEST
MCS06 ,Pair06, TEST
MCS07 ,Pair07, TEST
MCS08 ,Pair08, TEST
MCS09 ,Pair09, TEST
MCS10 ,Pair10, TEST
MCS11 ,Pair11, TEST
MCS12 ,Pair12, TEST
MCS13 ,Pair13, TEST
MCS14 ,Pair14, TEST
MCS15 ,Pair15, TEST
MCS16 ,Pair16, TEST
MCS17 ,Pair17, TEST
MCS18 ,Pair18, TEST
MCS19 ,Pair19, TEST
MCS20 ,Pair20, TEST
MCS21 ,Pair21, TEST
MCS22 ,Pair22, TEST
MCS23 ,Pair23, TEST
MCS24 ,Pair24, TEST
MCS25 ,Pair25, TEST
MCS26 ,Pair26, TEST
MCS27 ,Pair27, TEST
MCS28 ,Pair28, TEST
MCS29 ,Pair29, TEST
MCS30 ,Pair30, TEST
MCS31 ,Pair31, TEST
MCS32 ,Pair32, TEST
MCS33 ,Pair33, TEST
MCS34 ,Pair34, TEST
MCS35 ,Pair35, TEST
MCS36 ,Pair36, TEST
MCS37 ,Pair37, TEST
MCS38 ,Pair38, TEST
MCS39 ,Pair39, TEST
MCS40 ,Pair40, TEST

ChatGPT の回答は必ずしも正しいとは限りません。重要な情報は確認するようにしてください。

前のブログ 次のブログ

Method 2のRBD

次に冗長系EPSの2nd SMありのモデル(手法2)を作成させます。

MARDを取得する前にあらかじめexcelにより正解値を求めておくと、図919.2のように頂上侵害確率は7.903E-05、PMHFは激減して5.27[FIT]となります。

なお、本稿はRAMS 2027に投稿予定のため一部を秘匿していますが、論文公開後の2027年2月頃に開示予定です

前のブログ 次のブログ

SAPHIREでこれらのMARDファイルをロードすると、図918.1のようなFTが生成されます。

次にSolveで論理圧縮をかけ、View CutSetによりカットセットを表示させます。

表918.1に示すとおり、頂上事象の確率は $\img[-1.35em]{/images/withinseminar.png}$ となります。

2020年にSaphireを使用した以前の記事では頂上事象の確率は3.380E-03でした。若干異なるのは丸め誤差や内部精度が変わったのかもしれません。

さらにExcelの結果である228.5 [FIT]と異なるのは、Excelは不信頼度を$\lambda T_\text{lifetime}$で計算しましたが、ツールはより正確な式である$1-e^{-\lambda T_\text{lifetime}}$で計算していることと丸め誤差の2つによるもののようです。

なお、本稿はRAMS 2027に投稿予定のため一部を秘匿していますが、論文公開後の2027年2月頃に開示予定です。

前のブログ 次のブログ

ChatGPTに前項のRBDを読ませ、頂上事象をMETHOD1としてMARDを生成してもらいました。それを示します。

METHOD1.MARD

TEST_Subs\METHOD1.BED
TEST_Subs\METHOD1.BEI
TEST_Subs\METHOD1.FTD
TEST_Subs\METHOD1.FTL
TEST_Subs\METHOD1.GTD

METHOD1.BED

*Saphire 8.2.9
TEST =
* Name , Descriptions , Project
P1 ,P1desc ,TEST
MCU1 ,MCU1desc ,TEST
D1 ,D1desc ,TEST
I1 ,I1desc ,TEST
M1 ,M1desc ,TEST
SC1 ,SC1desc ,TEST
CA1 ,CA1desc ,TEST
SA1 ,SA1desc ,TEST
P2 ,P2desc ,TEST
MCU2 ,MCU2desc ,TEST
D2 ,D2desc ,TEST
I2 ,I2desc ,TEST
M2 ,M2desc ,TEST
SC2 ,SC2desc ,TEST
CA2 ,CA2desc ,TEST
SA2 ,SA2desc ,TEST

METHOD1.BEI

*Saphire 8.2.9
TEST =
* Name ,FdT,UdC,UdT,UdValue,Prob,Lambda,Tau,Mission,Init,PF,UdValue2,Calc. Prob,Freq,Analysis Type,Phase Type,Project
P1 ,3, , ,0.000E+000,0.000E+000,2.330E-007,0,1.500E+004, , ,0.000E+000,3.495E-003, ,RANDOM,CD,TEST
MCU1,3, , ,0.000E+000,0.000E+000,8.180E-007,0,1.500E+004, , ,0.000E+000,1.227E-002, ,RANDOM,CD,TEST
D1 ,3, , ,0.000E+000,0.000E+000,1.090E-007,0,1.500E+004, , ,0.000E+000,1.635E-003, ,RANDOM,CD,TEST
I1 ,3, , ,0.000E+000,0.000E+000,5.990E-007,0,1.500E+004, , ,0.000E+000,8.985E-003, ,RANDOM,CD,TEST
M1 ,3, , ,0.000E+000,0.000E+000,1.000E-006,0,1.500E+004, , ,0.000E+000,1.500E-002, ,RANDOM,CD,TEST
SC1 ,3, , ,0.000E+000,0.000E+000,1.000E-006,0,1.500E+004, , ,0.000E+000,1.500E-002, ,RANDOM,CD,TEST
CA1 ,3, , ,0.000E+000,0.000E+000,5.100E-008,0,1.500E+004, , ,0.000E+000,7.650E-004, ,RANDOM,CD,TEST
SA1 ,3, , ,0.000E+000,0.000E+000,1.000E-006,0,1.500E+004, , ,0.000E+000,1.500E-002, ,RANDOM,CD,TEST
P2 ,3, , ,0.000E+000,0.000E+000,2.330E-007,0,1.500E+004, , ,0.000E+000,3.495E-003, ,RANDOM,CD,TEST
MCU2,3, , ,0.000E+000,0.000E+000,8.180E-007,0,1.500E+004, , ,0.000E+000,1.227E-002, ,RANDOM,CD,TEST
D2 ,3, , ,0.000E+000,0.000E+000,1.090E-007,0,1.500E+004, , ,0.000E+000,1.635E-003, ,RANDOM,CD,TEST
I2 ,3, , ,0.000E+000,0.000E+000,5.990E-007,0,1.500E+004, , ,0.000E+000,8.985E-003, ,RANDOM,CD,TEST
M2 ,3, , ,0.000E+000,0.000E+000,1.000E-006,0,1.500E+004, , ,0.000E+000,1.500E-002, ,RANDOM,CD,TEST
SC2 ,3, , ,0.000E+000,0.000E+000,1.000E-006,0,1.500E+004, , ,0.000E+000,1.500E-002, ,RANDOM,CD,TEST
CA2 ,3, , ,0.000E+000,0.000E+000,5.100E-008,0,1.500E+004, , ,0.000E+000,7.650E-004, ,RANDOM,CD,TEST
SA2 ,3, , ,0.000E+000,0.000E+000,1.000E-006,0,1.500E+004, , ,0.000E+000,1.500E-002, ,RANDOM,CD,TEST

METHOD1.FTD

TEST =
* Name , Description, SubTree, Alternate, Project
METHOD1 ,Method1TopDef,, ,TEST

METHOD1.FTL

TEST,METHOD1 =
METHOD1 OR MCS01 MCS02 MCS03 MCS04 MCS05 MCS06 MCS07 MCS08 MCS09 MCS10 MCS11 MCS12 MCS13 MCS14 MCS15 MCS16 MCS17 MCS18 MCS19 MCS20 MCS21 MCS22 MCS23 MCS24 MCS25 MCS26 MCS27 MCS28 MCS29 MCS30 MCS31 MCS32 MCS33 MCS34 MCS35 MCS36 MCS37 MCS38 MCS39 MCS40
MCS01 AND P1 P2
MCS02 AND P1 MCU2
MCS03 AND P1 D2
MCS04 AND P1 I2
MCS05 AND P1 M2
MCS06 AND P1 SC2
MCS07 AND MCU1 P2
MCS08 AND MCU1 MCU2
MCS09 AND MCU1 D2
MCS10 AND MCU1 I2
MCS11 AND MCU1 M2
MCS12 AND MCU1 SC2
MCS13 AND D1 P2
MCS14 AND D1 MCU2
MCS15 AND D1 D2
MCS16 AND D1 I2
MCS17 AND D1 M2
MCS18 AND D1 SC2
MCS19 AND I1 P2
MCS20 AND I1 MCU2
MCS21 AND I1 D2
MCS22 AND I1 I2
MCS23 AND I1 M2
MCS24 AND I1 SC2
MCS25 AND M1 P2
MCS26 AND M1 MCU2
MCS27 AND M1 D2
MCS28 AND M1 I2
MCS29 AND M1 M2
MCS30 AND M1 SC2
MCS31 AND SC1 P2
MCS32 AND SC1 MCU2
MCS33 AND SC1 D2
MCS34 AND SC1 I2
MCS35 AND SC1 M2
MCS36 AND SC1 SC2
MCS37 AND CA1 CA2
MCS38 AND CA1 SA2
MCS39 AND SA1 CA2
MCS40 AND SA1 SA2

METHOD1.GTD

TEST=
* Name , Description, Project
METHOD1,Method1TopGate,,TEST
MCS01,PairP1P2,,TEST
MCS02,PairP1MCU2,,TEST
MCS03,PairP1D2,,TEST
MCS04,PairP1I2,,TEST
MCS05,PairP1M2,,TEST
MCS06,PairP1SC2,,TEST
MCS07,PairMCU1P2,,TEST
MCS08,PairMCU1MCU2,,TEST
MCS09,PairMCU1D2,,TEST
MCS10,PairMCU1I2,,TEST
MCS11,PairMCU1M2,,TEST
MCS12,PairMCU1SC2,,TEST
MCS13,PairD1P2,,TEST
MCS14,PairD1MCU2,,TEST
MCS15,PairD1D2,,TEST
MCS16,PairD1I2,,TEST
MCS17,PairD1M2,,TEST
MCS18,PairD1SC2,,TEST
MCS19,PairI1P2,,TEST
MCS20,PairI1MCU2,,TEST
MCS21,PairI1D2,,TEST
MCS22,PairI1I2,,TEST
MCS23,PairI1M2,,TEST
MCS24,PairI1SC2,,TEST
MCS25,PairM1P2,,TEST
MCS26,PairM1MCU2,,TEST
MCS27,PairM1D2,,TEST
MCS28,PairM1I2,,TEST
MCS29,PairM1M2,,TEST
MCS30,PairM1SC2,,TEST
MCS31,PairSC1P2,,TEST
MCS32,PairSC1MCU2,,TEST
MCS33,PairSC1D2,,TEST
MCS34,PairSC1I2,,TEST
MCS35,PairSC1M2,,TEST
MCS36,PairSC1SC2,,TEST
MCS37,PairCA1CA2,,TEST
MCS38,PairCA1SA2,,TEST
MCS39,PairSA1CA2,,TEST
MCS40,PairSA1SA2,,TEST

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RBD

順に手法1, 手法2, 手法3とFTを自動生成させます。入力はRBD(Reliability Block Diagram)です。まず冗長系EPSの2nd SM無しのモデル(手法1)を作成させます。

このMCSをとると、上流に関してチャネル1側とチャネル2側の個々の組み合わせが6x6=36通り、下流も同様に2x2=4通り、計40通りとなることが分かります。従ってあらかじめexcelにより正解値を求めておくと、図916.2のように、頂上侵害確率は3.428E-03、PMHFは228.5 [FIT]となります。

見方の例として、図の左上のSC1(チャネル1側エレメント)とSC2(チャネル2側エレメント)のペアを取ります。SC1とSC2において、それぞれ故障率は1000[FIT]、車両寿命間の不信頼度確率は1.500e-2、それらの積は2.250e-4となります。それらの40個の積項の和が頂上事象侵害確率であり、3.428e-3です。それを車両寿命で割るとPMHFが228.5[FIT]と算出できます。

このexcelによる結果を、検証のために正解値として保持しておきます。

なお、本稿はRAMS 2027に投稿予定のため一部を秘匿していますが、論文公開後の2027年2月頃に開示予定です

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