MULTI-PRED: A Software Module for Predictive Modeling of Coupled Multi-Physics Systems

Figures & data

Fig. 1. MULTI-PRED code structure.

TABLE I MultiPredSup Super-File Format for MULTI-PRED Case 4: Two Coupled Multi-Physics Models

Category	File Name
‘dims’	‘dimensions.inp’
‘a_nom’	‘a.inp’
‘r_mea’	‘rm.inp’
‘r_com’	‘rc.inp’
‘C_aa’	‘Caa.inp’
‘C_ar’	‘Car.inp’
‘C_rr’	‘Crr.inp’
‘S_ra’	‘Sra.inp’
‘b_nom’	‘b.inp’
‘q_mea’	‘qm.inp’
‘q_com’	‘qc.inp’
‘C_bb’	‘Cbb.inp’
‘C_bq’	‘Cbq.inp’
‘C_qq’	‘Cqq.inp’
‘S_qb’	‘Sqb.inp’
‘C_ab’	‘Cab.inp’
‘C_aq’	‘Caq.inp’
‘C_br’	‘Cbr.inp’
‘C_rq’	‘Crq.inp’
‘S_rb’	‘Srb.inp’
‘S_qa’	‘Sqa.inp’
‘a_BE’	‘aBE.out’
‘r_BE’	‘rBE.out’
‘C_aaBE’	‘CaaBE.out’
‘C_rrBE’	‘CrrBE.out’
‘C_arBE’	‘CarBE.out’
‘Crr_comp’	‘Crrcomp.out’
‘b_BE’	‘bBE.out’
‘q_BE’	‘qBE.out’
‘C_bbBE’	‘CbbBE.out’
‘C_qqBE’	‘CqqBE.out’
‘C_bqBE’	‘CbqBE.out’
‘Cqq_comp’	‘Cqqcomp.out’
‘C_abBE’	‘CabBE.out’
‘C_aqBE’	‘CaqBE.out’
‘C_brBE’	‘CbrBE.out’
‘C_rqBE’	‘CrqBE.out’
‘Crq_comp’	‘Crqcomp.out’
‘chi2’	‘chi2.out’

TABLE II Summary of I/O Files for MULTI-PRED Case 4: Two Coupled Multi-Physics Models

File	Unit	I/O	Corresponding Vector/Matrix	Description
superfile.inp	5	Input		File organization
dimensions.inp	20	Input		Defines the case selection and dimensions control
a.inp	21	Input		Nominal values of Na parameters of model A
rm.inp	22	Input		Nominal values of Nr measured responses of model A
rc.inp	23	Input		Nominal values of Nr computed responses of model A
Caa.inp	24	Input		Covariance matrix of Na parameters of model A
Car.inp	25	Input		Correlations between Na parameters and Nr responses of model A
Crr.inp	26	Input		Covariance matrix of Nr responses of model A
Sra.inp	27	Input		Absolute sensitivities of Nr responses of model A with respect to Na parameters of model A
b.inp	31	Input		Nominal values of Na parameters of model B
qm.inp	32	Input		Nominal values of Nq measured responses of model B
qc.inp	33	Input		Nominal values of Nq computed responses of model B
Cbb.inp	34	Input		Covariance matrix of Nb parameters of model B
Cbq.inp	35	Input		Correlations between Nb parameters and Nq responses of model B
Cqq.inp	36	Input		Covariance matrix of Nq responses of model B
Sqb.inp	37	Input		Absolute sensitivities of Nq responses of model B with respect to Nb parameters of model B
Cab.inp	41	Input		Correlation matrix between the Na parameters of model A and the Nb parameters of model B
Caq.inp	42	Input		Correlation matrix between the Na parameters and of model A and Nq responses of model B
Cbr.inp	43	Input		Correlation matrix between the Nb parameters of model B and Nr responses of model A
Crq.inp	44	Input		Correlation matrix of between Nr responses of model A and Nq responses of model B
Srb.inp	45	Input		Absolute sensitivities of Nr responses of model A with respect to Nb parameters of model B
Sqa.inp	46	Input		Absolute sensitivities of Nq responses of model B with respect to Na parameters of model A
aBE.out	51	Output		Best-estimate nominal values of parameters of model A
rBE.out	52	Output		Best-estimate nominal values of responses of model A
CaaBE.out	53	Output		Predicted covariance matrix of Na parameters of model A
CrrBE.out	54	Output		Predicted covariance matrix of Nr responses of model A
CarBE.out	55	Output		Predicted correlation matrix between the Na parameters and Nr responses of model A
Crrcomp.out	56	Output		Covariance matrix of Nr computed responses of model A
bBE.out	61	Output		Best-estimate nominal values of parameters of model B
qBE.out	62	Output		Best-estimate nominal values of responses of model B
CbbBE.out	63	Output		Predicted covariance matrix of Nb parameters of model B
CqqBE.out	64	Output		Predicted covariance matrix of Nq responses of model B
CbqBE.out	65	Output		Predicted correlation matrix between the Nb parameters and Nq responses of model B
Cqqcomp.out	66	Output		Covariance matrix of Nq computed responses of model B
CabBE.out	71	Output		Predicted correlation matrix between the Na parameters of model A and the Nb parameters for model B
CaqBE.out	72	Output		Predicted correlation matrix between the Na parameters and of model A and Nq responses of model B
CbrBE.out	73	Output		Predicted correlation matrix between the Nb parameters of model B and Nr responses of model A
CrqBE.out	74	Output		Predicted correlation matrix of between Nr responses of model A and Nq responses of model B
Crqcomp.out	75	Output		Correlation matrix of Nr computed responses of model A and Nq computed responses of model B
chi2.out	76	Output	, scalar	Value of the consistency indicator

TABLE III Input Data Files for MULTI-PRED Case 4

Input Data Files for Model A	Input Data Files for the Coupled Matrices Between Model A and Model B	Input Data Files for Model B
a.inp	–	b.inp
rm.inp	–	qm.inp
rc.inp	–	qc.inp
Caa.inp	Cab.inp	Cbb.inp
Car.inp	Caq.inp, Cbr.inp	Cbq.inp
Crr.inp	Crq.inp	Cqq.inp
Sra.inp	Sqa.inp, Srb.inp	Sqb.inp