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Detection limits in air quality and environmental measurements / / editor: Michael J. Brisson
| Detection limits in air quality and environmental measurements / / editor: Michael J. Brisson |
| Pubbl/distr/stampa | ASTM International |
| Disciplina | 628.5 |
| Soggetto topico |
Pollution - Measurement
Air - Pollution - Measurement Environmental monitoring - Statistical methods Observed confidence levels (Statistics) Sensitivity theory (Mathematics) |
| ISBN | 0-8031-7683-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910439159803321 |
| ASTM International | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Global sensitivity analysis [[electronic resource] ] : the primer / / Andrea Saltelli ... [et al.]
| Global sensitivity analysis [[electronic resource] ] : the primer / / Andrea Saltelli ... [et al.] |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley, c2008 |
| Descrizione fisica | 1 online resource (306 p.) |
| Disciplina | 003 |
| Altri autori (Persone) | SaltelliA <1953-> (Andrea) |
| Soggetto topico |
Sensitivity theory (Mathematics)
Global analysis (Mathematics) Mathematical models |
| ISBN |
1-281-32188-5
9786611321888 0-470-72518-4 0-470-72517-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Global Sensitivity Analysis. The Primer; Contents; Preface; 1 Introduction to Sensitivity Analysis; 1.1 Models and Sensitivity Analysis; 1.1.1 Definition; 1.1.2 Models; 1.1.3 Models and Uncertainty; 1.1.4 How to Set Up Uncertainty and Sensitivity Analyses; 1.1.5 Implications for Model Quality; 1.2 Methods and Settings for Sensitivity Analysis - an Introduction; 1.2.1 Local versus Global; 1.2.2 A Test Model; 1.2.3 Scatterplots versus Derivatives; 1.2.4 Sigma-normalized Derivatives; 1.2.5 Monte Carlo and Linear Regression; 1.2.6 Conditional Variances - First Path
1.2.7 Conditional Variances - Second Path1.2.8 Application to Model (1.3); 1.2.9 A First Setting: 'Factor Prioritization'; 1.2.10 Nonadditive Models; 1.2.11 Higher-order Sensitivity Indices; 1.2.12 Total Effects; 1.2.13 A Second Setting: 'Factor Fixing'; 1.2.14 Rationale for Sensitivity Analysis; 1.2.15 Treating Sets; 1.2.16 Further Methods; 1.2.17 Elementary Effect Test; 1.2.18 Monte Carlo Filtering; 1.3 Nonindependent Input Factors; 1.4 Possible Pitfalls for a Sensitivity Analysis; 1.5 Concluding Remarks; 1.6 Exercises; 1.7 Answers; 1.8 Additional Exercises 1.9 Solutions to Additional Exercises2 Experimental Designs; 2.1 Introduction; 2.2 Dependency on a Single Parameter; 2.3 Sensitivity Analysis of a Single Parameter; 2.3.1 Random Values; 2.3.2 Stratified Sampling; 2.3.3 Mean and Variance Estimates for Stratified Sampling; 2.4 Sensitivity Analysis of Multiple Parameters; 2.4.1 Linear Models; 2.4.2 One-at-a-time (OAT) Sampling; 2.4.3 Limits on the Number of Influential Parameters; 2.4.4 Fractional Factorial Sampling; 2.4.5 Latin Hypercube Sampling; 2.4.6 Multivariate Stratified Sampling; 2.4.7 Quasi-random Sampling with Low-discrepancy Sequences 2.5 Group Sampling2.6 Exercises; 2.7 Exercise Solutions; 3 Elementary Effects Method; 3.1 Introduction; 3.2 The Elementary Effects Method; 3.3 The Sampling Strategy and its Optimization; 3.4 The Computation of the Sensitivity Measures; 3.5 Working with Groups; 3.6 The EE Method Step by Step; 3.7 Conclusions; 3.8 Exercises; 3.9 Solutions; 4 Variance-based Methods; 4.1 Different Tests for Different Settings; 4.2 Why Variance?; 4.3 Variance-based Methods. A Brief History; 4.4 Interaction Effects; 4.5 Total Effects; 4.6 How to Compute the Sensitivity Indices; 4.7 FAST and Random Balance Designs 4.8 Putting the Method to Work: The Infection Dynamics Model4.9 Caveats; 4.10 Exercises; 5 Factor Mapping and Metamodelling; 5.1 Introduction; 5.2 Monte Carlo Filtering (MCF); 5.2.1 Implementation of Monte Carlo Filtering; 5.2.2 Pros and Cons; 5.2.3 Exercises; 5.2.4 Solutions; 5.2.5 Examples; 5.3 Metamodelling and the High-Dimensional Model Representation; 5.3.1 Estimating HDMRs and Metamodels; 5.3.2 A Simple Example; 5.3.3 Another Simple Example; 5.3.4 Exercises; 5.3.5 Solutions to Exercises; 5.4 Conclusions; 6 Sensitivity Analysis: From Theory to Practice 6.1 Example 1: A Composite Indicator |
| Record Nr. | UNINA-9910144716603321 |
| Chichester, England ; ; Hoboken, NJ, : John Wiley, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Global sensitivity analysis [[electronic resource] ] : the primer / / Andrea Saltelli ... [et al.]
| Global sensitivity analysis [[electronic resource] ] : the primer / / Andrea Saltelli ... [et al.] |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley, c2008 |
| Descrizione fisica | 1 online resource (306 p.) |
| Disciplina | 003 |
| Altri autori (Persone) | SaltelliA <1953-> (Andrea) |
| Soggetto topico |
Sensitivity theory (Mathematics)
Global analysis (Mathematics) Mathematical models |
| ISBN |
1-281-32188-5
9786611321888 0-470-72518-4 0-470-72517-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Global Sensitivity Analysis. The Primer; Contents; Preface; 1 Introduction to Sensitivity Analysis; 1.1 Models and Sensitivity Analysis; 1.1.1 Definition; 1.1.2 Models; 1.1.3 Models and Uncertainty; 1.1.4 How to Set Up Uncertainty and Sensitivity Analyses; 1.1.5 Implications for Model Quality; 1.2 Methods and Settings for Sensitivity Analysis - an Introduction; 1.2.1 Local versus Global; 1.2.2 A Test Model; 1.2.3 Scatterplots versus Derivatives; 1.2.4 Sigma-normalized Derivatives; 1.2.5 Monte Carlo and Linear Regression; 1.2.6 Conditional Variances - First Path
1.2.7 Conditional Variances - Second Path1.2.8 Application to Model (1.3); 1.2.9 A First Setting: 'Factor Prioritization'; 1.2.10 Nonadditive Models; 1.2.11 Higher-order Sensitivity Indices; 1.2.12 Total Effects; 1.2.13 A Second Setting: 'Factor Fixing'; 1.2.14 Rationale for Sensitivity Analysis; 1.2.15 Treating Sets; 1.2.16 Further Methods; 1.2.17 Elementary Effect Test; 1.2.18 Monte Carlo Filtering; 1.3 Nonindependent Input Factors; 1.4 Possible Pitfalls for a Sensitivity Analysis; 1.5 Concluding Remarks; 1.6 Exercises; 1.7 Answers; 1.8 Additional Exercises 1.9 Solutions to Additional Exercises2 Experimental Designs; 2.1 Introduction; 2.2 Dependency on a Single Parameter; 2.3 Sensitivity Analysis of a Single Parameter; 2.3.1 Random Values; 2.3.2 Stratified Sampling; 2.3.3 Mean and Variance Estimates for Stratified Sampling; 2.4 Sensitivity Analysis of Multiple Parameters; 2.4.1 Linear Models; 2.4.2 One-at-a-time (OAT) Sampling; 2.4.3 Limits on the Number of Influential Parameters; 2.4.4 Fractional Factorial Sampling; 2.4.5 Latin Hypercube Sampling; 2.4.6 Multivariate Stratified Sampling; 2.4.7 Quasi-random Sampling with Low-discrepancy Sequences 2.5 Group Sampling2.6 Exercises; 2.7 Exercise Solutions; 3 Elementary Effects Method; 3.1 Introduction; 3.2 The Elementary Effects Method; 3.3 The Sampling Strategy and its Optimization; 3.4 The Computation of the Sensitivity Measures; 3.5 Working with Groups; 3.6 The EE Method Step by Step; 3.7 Conclusions; 3.8 Exercises; 3.9 Solutions; 4 Variance-based Methods; 4.1 Different Tests for Different Settings; 4.2 Why Variance?; 4.3 Variance-based Methods. A Brief History; 4.4 Interaction Effects; 4.5 Total Effects; 4.6 How to Compute the Sensitivity Indices; 4.7 FAST and Random Balance Designs 4.8 Putting the Method to Work: The Infection Dynamics Model4.9 Caveats; 4.10 Exercises; 5 Factor Mapping and Metamodelling; 5.1 Introduction; 5.2 Monte Carlo Filtering (MCF); 5.2.1 Implementation of Monte Carlo Filtering; 5.2.2 Pros and Cons; 5.2.3 Exercises; 5.2.4 Solutions; 5.2.5 Examples; 5.3 Metamodelling and the High-Dimensional Model Representation; 5.3.1 Estimating HDMRs and Metamodels; 5.3.2 A Simple Example; 5.3.3 Another Simple Example; 5.3.4 Exercises; 5.3.5 Solutions to Exercises; 5.4 Conclusions; 6 Sensitivity Analysis: From Theory to Practice 6.1 Example 1: A Composite Indicator |
| Record Nr. | UNINA-9910830220603321 |
| Chichester, England ; ; Hoboken, NJ, : John Wiley, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Global sensitivity analysis : the primer / / Andrea Saltelli ... [et al.]
| Global sensitivity analysis : the primer / / Andrea Saltelli ... [et al.] |
| Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, : John Wiley, c2008 |
| Descrizione fisica | 1 online resource (306 p.) |
| Disciplina | 003 |
| Altri autori (Persone) | SaltelliA <1953-> (Andrea) |
| Soggetto topico |
Sensitivity theory (Mathematics)
Global analysis (Mathematics) Mathematical models |
| ISBN |
1-281-32188-5
9786611321888 0-470-72518-4 0-470-72517-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Global Sensitivity Analysis. The Primer; Contents; Preface; 1 Introduction to Sensitivity Analysis; 1.1 Models and Sensitivity Analysis; 1.1.1 Definition; 1.1.2 Models; 1.1.3 Models and Uncertainty; 1.1.4 How to Set Up Uncertainty and Sensitivity Analyses; 1.1.5 Implications for Model Quality; 1.2 Methods and Settings for Sensitivity Analysis - an Introduction; 1.2.1 Local versus Global; 1.2.2 A Test Model; 1.2.3 Scatterplots versus Derivatives; 1.2.4 Sigma-normalized Derivatives; 1.2.5 Monte Carlo and Linear Regression; 1.2.6 Conditional Variances - First Path
1.2.7 Conditional Variances - Second Path1.2.8 Application to Model (1.3); 1.2.9 A First Setting: 'Factor Prioritization'; 1.2.10 Nonadditive Models; 1.2.11 Higher-order Sensitivity Indices; 1.2.12 Total Effects; 1.2.13 A Second Setting: 'Factor Fixing'; 1.2.14 Rationale for Sensitivity Analysis; 1.2.15 Treating Sets; 1.2.16 Further Methods; 1.2.17 Elementary Effect Test; 1.2.18 Monte Carlo Filtering; 1.3 Nonindependent Input Factors; 1.4 Possible Pitfalls for a Sensitivity Analysis; 1.5 Concluding Remarks; 1.6 Exercises; 1.7 Answers; 1.8 Additional Exercises 1.9 Solutions to Additional Exercises2 Experimental Designs; 2.1 Introduction; 2.2 Dependency on a Single Parameter; 2.3 Sensitivity Analysis of a Single Parameter; 2.3.1 Random Values; 2.3.2 Stratified Sampling; 2.3.3 Mean and Variance Estimates for Stratified Sampling; 2.4 Sensitivity Analysis of Multiple Parameters; 2.4.1 Linear Models; 2.4.2 One-at-a-time (OAT) Sampling; 2.4.3 Limits on the Number of Influential Parameters; 2.4.4 Fractional Factorial Sampling; 2.4.5 Latin Hypercube Sampling; 2.4.6 Multivariate Stratified Sampling; 2.4.7 Quasi-random Sampling with Low-discrepancy Sequences 2.5 Group Sampling2.6 Exercises; 2.7 Exercise Solutions; 3 Elementary Effects Method; 3.1 Introduction; 3.2 The Elementary Effects Method; 3.3 The Sampling Strategy and its Optimization; 3.4 The Computation of the Sensitivity Measures; 3.5 Working with Groups; 3.6 The EE Method Step by Step; 3.7 Conclusions; 3.8 Exercises; 3.9 Solutions; 4 Variance-based Methods; 4.1 Different Tests for Different Settings; 4.2 Why Variance?; 4.3 Variance-based Methods. A Brief History; 4.4 Interaction Effects; 4.5 Total Effects; 4.6 How to Compute the Sensitivity Indices; 4.7 FAST and Random Balance Designs 4.8 Putting the Method to Work: The Infection Dynamics Model4.9 Caveats; 4.10 Exercises; 5 Factor Mapping and Metamodelling; 5.1 Introduction; 5.2 Monte Carlo Filtering (MCF); 5.2.1 Implementation of Monte Carlo Filtering; 5.2.2 Pros and Cons; 5.2.3 Exercises; 5.2.4 Solutions; 5.2.5 Examples; 5.3 Metamodelling and the High-Dimensional Model Representation; 5.3.1 Estimating HDMRs and Metamodels; 5.3.2 A Simple Example; 5.3.3 Another Simple Example; 5.3.4 Exercises; 5.3.5 Solutions to Exercises; 5.4 Conclusions; 6 Sensitivity Analysis: From Theory to Practice 6.1 Example 1: A Composite Indicator |
| Record Nr. | UNINA-9910876962603321 |
| Chichester, England ; ; Hoboken, NJ, : John Wiley, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
A method for reducing the sensitivity of optimal nonlinear systems to parameter uncertainty / / by Jarrell R. Elliott and William F. Teague
| A method for reducing the sensitivity of optimal nonlinear systems to parameter uncertainty / / by Jarrell R. Elliott and William F. Teague |
| Autore | Elliott Jarrell R. |
| Pubbl/distr/stampa | Washington, D.C. : , : National Aeronautics and Space Administration, , June 1971 |
| Descrizione fisica | 1 online resource (40 pages) : illustrations |
| Collana | NASA/TN |
| Soggetto topico |
Sensitivity
Mathematical analysis Nonlinear systems Mathematical optimization Sensitivity theory (Mathematics) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910715362103321 |
Elliott Jarrell R.
|
||
| Washington, D.C. : , : National Aeronautics and Space Administration, , June 1971 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The nth-order comprehensive adjoint sensitivity analysis methodology . Volume II : overcoming the curse of dimensionality / / Dan Gabriel Cacuci and Ruixian Fang
| The nth-order comprehensive adjoint sensitivity analysis methodology . Volume II : overcoming the curse of dimensionality / / Dan Gabriel Cacuci and Ruixian Fang |
| Autore | Cacuci Dan Gabriel |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer Nature Switzerland AG, , [2023] |
| Descrizione fisica | 1 online resource (474 pages) |
| Disciplina | 003.5 |
| Soggetto topico |
Large scale systems
Linear systems Sensitivity theory (Mathematics) |
| ISBN |
9783031196355
9783031196348 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter1. 1st-Order Sensitivity Analysis of the OECD/NEA PERP Reactor Physics Benchmark -- Chapter2. 2nd-Order Sensitivities of the PERP Benchmark to the Microscopic Total and Capture Cross Sections -- Chapter3. 2nd-Order Sensitivities of the PERP Benchmark to the Microscopic Scattering Cross Sections -- Chapter4. 2nd-Order Sensitivities of the PERP Benchmark to the Microscopic Fission Cross Sections -- Chapter5. 2nd-Order Sensitivities of the PERP Benchmark to the Average Number of Neutrons per Fission -- Chapter6. 2nd-Order Sensitivities of the PERP Benchmark to the Spontaneous Fission Source Parameters -- Chapter7. 2nd-Order Sensitivities of the PERP Benchmark to the Isotopic Number Densities -- Chapter8. 3rd-Order Sensitivities of the PERP Benchmark -- Chapter9. 4th-Order Sensitivities of the PERP Benchmark -- Chapter10. Overall Impact of 1st-, 2nd-, 3rd-, and 4th-Order Sensitivities on the PERP Benchmark's Response Uncertainties. |
| Record Nr. | UNINA-9910720077703321 |
|
Cacuci Dan Gabriel
|
||
| Cham, Switzerland : , : Springer Nature Switzerland AG, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The nth-order comprehensive adjoint sensitivity analysis methodology . Volume III : overcoming the curse of dimensionality : nonlinear systems / / Dan Gabriel Cacuci
| The nth-order comprehensive adjoint sensitivity analysis methodology . Volume III : overcoming the curse of dimensionality : nonlinear systems / / Dan Gabriel Cacuci |
| Autore | Cacuci Dan Gabriel |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer Nature Switzerland AG, , [2023] |
| Descrizione fisica | 1 online resource (XII, 369 p. 148 illus., 20 illus. in color.) |
| Disciplina | 003.5 |
| Soggetto topico |
Large scale systems
Nonlinear systems Sensitivity theory (Mathematics) |
| ISBN | 3-031-22757-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part A: Function-Valued Responses. Chapter 1: The First- and Second-Order Comprehensive Adjoint Sensitivity Analysis Methodologies for Nonlinear Systems with Function-Valued Responses -- Chapter 2: The Third-Order Comprehensive Adjoint Sensitivity Analysis Methodology (C-ASAM-3) for Nonlinear Systems with Function-Valued Responses -- Chapter 3: The Fourth-Order Comprehensive Adjoint Sensitivity Analysis Methodology (C-ASAM-4) for Nonlinear Systems with Function-Valued Responses -- Chapter 4: The Nth-Order Adjoint Sensitivity Analysis Methodology (C-ASAM-N) for Nonlinear Systems with Function-Valued Responses -- Part B: Scalar-Valued Responses -- Part B: Scalar-Valued Responses -- Chapter 5: The Fourth-Order Comprehensive Adjoint Sensitivity Analysis Methodology (C-ASAM-4) for Nonlinear Systems with Scalar-Valued Responses -- Chapter 6: The Nth-Order Adjoint Sensitivity Analysis Methodology (C-ASAM-N) for Nonlinear Systems with Scalar-Valued Responses -- Chapter 7: Applications of C-ASAM to Uncertainty Analysis. |
| Record Nr. | UNINA-9910698641303321 |
|
Cacuci Dan Gabriel
|
||
| Cham, Switzerland : , : Springer Nature Switzerland AG, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The nth-order comprehensive adjoint sensitivity analysis methodology . Volume 1 : overcoming the curse of dimensionality : linear systems / / Dan Gabriel Cacuci
| The nth-order comprehensive adjoint sensitivity analysis methodology . Volume 1 : overcoming the curse of dimensionality : linear systems / / Dan Gabriel Cacuci |
| Autore | Cacuci Dan Gabriel |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (373 pages) |
| Disciplina | 629.8312 |
| Soggetto topico |
Sensitivity theory (Mathematics)
Linear systems - Mathematical models |
| ISBN |
9783030963644
9783030963637 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Chapter 1: Motivation: Overcoming the Curse of Dimensionality in Sensitivity Analysis, Uncertainty Quantification, and Predict... -- 1.1 Introduction -- 1.2 Need for Computation of High-Order Response Sensitivities: An Illustrative Example -- 1.2.1 Sensitivity Analysis -- 1.2.2 Uncertainty Quantification: Moments of the Response Distribution -- 1.3 The Curse of Dimensionality in Sensitivity Analysis: Computation of High-Order Response Sensitivities to Model Parameters -- 1.4 The Curse of Dimensionality in Uncertainty Quantification: Moments of the Response Distribution in Parameter Phase-Space -- 1.4.1 Expectation Value of a Response -- 1.4.2 Response-Parameter Covariances -- 1.4.3 Covariance of Two Responses -- 1.4.4 Triple Correlations Among Responses and Parameters -- 1.4.5 Quadruple Correlations Among Responses and Parameters -- 1.5 Chapter Summary -- Chapter 2: The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Sy... -- 2.1 Introduction -- 2.2 Mathematical Modeling of Response-Coupled Linear Forward and Adjoint Systems -- 2.3 The First-Order Comprehensive Sensitivity Analysis Methodology for Response-Coupled Linear Forward and Adjoint Systems (1s... -- 2.4 The Second-Order Comprehensive Sensitivity Analysis Methodology for Response-Coupled Linear Forward and Adjoint Systems (2... -- 2.5 The Third-Order Comprehensive Sensitivity Analysis Methodology for Response-Coupled Linear Forward and Adjoint Systems (3r... -- 2.6 The Fourth-Order Comprehensive Sensitivity Analysis Methodology for Response-Coupled Linear Forward and Adjoint Systems (4... -- 2.7 The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (... -- 2.7.1 The Pattern Underlying the nth-CASAM-L for n = 1, 2, 3, 4.
2.7.2 The Pattern Underlying the nth-CASAM-L: Arbitrarily High-Order n -- 2.7.3 Proving That the Framework for the nth-CASAM-L also Holds for the (n + 1)th-CASAM-L -- 2.8 The Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Coupled Forward/Adjoint Linear Systems (5th-CAS... -- 2.9 Chapter Summary -- Chapter 3: Illustrative Applications of the nth-CASAM-L to Paradigm Physical Systems with Imprecisely Known Properties, Intern... -- 3.1 Introduction -- 3.2 Transmission of Particles Through Media -- 3.2.1 Point-Detector Response -- 3.2.2 Particle Leakage Response -- 3.2.3 Reaction Rate Response -- 3.2.4 Contribution-Response Flux -- 3.3 Application of the 1st-CASAM-L to Compute First-Order Response Sensitivities to Imprecisely Known Parameters -- 3.3.1 Point-Detector Response -- 3.3.2 Particle Leakage Response -- 3.3.3 Reaction Rate Response -- 3.3.4 Contribution-Response -- 3.4 Application of the 2nd-CASAM-L to Compute Second-Order Response Sensitivities to Imprecisely Known Parameters -- 3.4.1 Determination of the Second-Order Sensitivities of the Form 2ρ(φ,ψ -- α)/αiμ(α), i = 1, , TP -- 3.4.2 Determination of the Second-Order Sensitivities of the Form 2ρ(φ,ψ -- α)/αib2, i = 1, , TP -- 3.4.3 Summary of Main Features Underlying the Computation of the Second-Order Sensitivities 2ρ(φ,ψ -- α)/αiαj, i, j = 1, , TP -- 3.5 Application of the 3rd-CASAM-L to Compute Third-Order Response Sensitivities to Imprecisely Known Parameters -- 3.5.1 Determination of the Third-Order Sensitivities of the Form 3ρ(φ,ψ -- α)/αiμ(α)μ(α), i = 1, , TP -- 3.5.2 Determination of the Third-Order Sensitivities of the Form 3ρ(φ,ψ -- α)/αib1b2, i = 1, , TP -- 3.6 Illustrative Application of the 4th-CASAM-L to a Paradigm Time-Evolution Model. 3.6.1 Applying the 1st-CASAM-L to Compute the first-Order Sensitivities to Model Parameters, Including Imprecisely Known Initi... -- 3.6.2 Applying the 2nd-CASAM-L to Compute the Second-Order Response Sensitivities to Model Parameters, Including Imprecisely K... -- 3.6.2.1 Second-Order Sensitivities Corresponding to R1(ρ -- α)/σi, i = 1, , N -- 3.6.2.2 Second-Order Sensitivities Corresponding to R1(ρ -- α)/ni, i = 1, , N -- 3.6.2.3 Second-Order Sensitivities Corresponding to R1(ρ -- α)/ρin -- 3.6.2.4 Second-Order Sensitivities Corresponding to R1(ρ -- α)/td -- 3.6.2.5 Second-Order Sensitivities Corresponding to R1(ρ -- α)/β -- 3.6.2.6 Independent Mutual Verification of Adjoint Sensitivity Functions -- 3.6.2.7 Aggregating Model Parameters to Reduce the Number of Large-Scale Adjoint Computations for Determining the Second-Order... -- 3.6.2.8 Illustrative Computation of Third- and Fourth-Order Sensitivities Using Aggregated Model Parameters -- 3.6.3 Applying the nth-CASAM-L to Compute Sensitivities of the Average Concentration Response to Model Parameters, Including I... -- 3.6.3.1 First-Order Sensitivities -- 3.6.3.2 Second-Order Sensitivities -- 3.7 Chapter Summary -- Chapter 4: Sensitivity Analysis of Neutron Transport Modeled by the Forward and Adjoint Linear Boltzmann Equations -- 4.1 Introduction -- 4.2 Paradigm Physical System: Neutron Transport in a Multiplying Medium with Source -- 4.3 Application of the 1st-CASAM-L to Determine the First-Order Sensitivities of R(φ,φ+ -- α) -- 4.4 Application of the 2nd-CASAM-L to Determine the Second-Order Sensitivities of R(φ,φ+ -- α) -- 4.4.1 Determination of the Second-Order Sensitivities of the Form -- 4.4.2 Determination of the Second-Order Sensitivities of the Form -- 4.4.3 Determination of the Second-Order Sensitivities of the Form -- 4.4.4 Determination of the Second-Order Sensitivities of the Form. 4.4.5 Determination of the Second-Order Sensitivities of the Form -- 4.4.6 Determination of the Second-Order Sensitivities of the Form -- 4.4.7 Determination of the Second-Order Sensitivities of the Form -- 4.5 Second-Order Sensitivity Analysis of the Schwinger and Roussopoulos Functionals -- 4.5.1 Application of the 1st-CASAM-L to Determine the First-Order Sensitivities of the Roussopoulos and Schwinger Functionals ... -- 4.5.2 Application of the 2nd-CASAM-L to Determine the Second-Order Sensitivities of the Schwinger and Roussopoulos Functionals... -- 4.5.2.1 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.2 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.3 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.4 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.5 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.6 Determination of the Second-Order Sensitivities of the Form -- 4.6 Chapter Summary -- Chapter 5: Concluding Remarks -- References -- Index. |
| Record Nr. | UNINA-9910585793103321 |
|
Cacuci Dan Gabriel
|
||
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The nth-order comprehensive adjoint sensitivity analysis methodology . Volume 1 : overcoming the curse of dimensionality : linear systems / / Dan Gabriel Cacuci
| The nth-order comprehensive adjoint sensitivity analysis methodology . Volume 1 : overcoming the curse of dimensionality : linear systems / / Dan Gabriel Cacuci |
| Autore | Cacuci Dan Gabriel |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (373 pages) |
| Disciplina | 629.8312 |
| Soggetto topico |
Sensitivity theory (Mathematics)
Linear systems - Mathematical models |
| ISBN |
9783030963644
9783030963637 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Chapter 1: Motivation: Overcoming the Curse of Dimensionality in Sensitivity Analysis, Uncertainty Quantification, and Predict... -- 1.1 Introduction -- 1.2 Need for Computation of High-Order Response Sensitivities: An Illustrative Example -- 1.2.1 Sensitivity Analysis -- 1.2.2 Uncertainty Quantification: Moments of the Response Distribution -- 1.3 The Curse of Dimensionality in Sensitivity Analysis: Computation of High-Order Response Sensitivities to Model Parameters -- 1.4 The Curse of Dimensionality in Uncertainty Quantification: Moments of the Response Distribution in Parameter Phase-Space -- 1.4.1 Expectation Value of a Response -- 1.4.2 Response-Parameter Covariances -- 1.4.3 Covariance of Two Responses -- 1.4.4 Triple Correlations Among Responses and Parameters -- 1.4.5 Quadruple Correlations Among Responses and Parameters -- 1.5 Chapter Summary -- Chapter 2: The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Sy... -- 2.1 Introduction -- 2.2 Mathematical Modeling of Response-Coupled Linear Forward and Adjoint Systems -- 2.3 The First-Order Comprehensive Sensitivity Analysis Methodology for Response-Coupled Linear Forward and Adjoint Systems (1s... -- 2.4 The Second-Order Comprehensive Sensitivity Analysis Methodology for Response-Coupled Linear Forward and Adjoint Systems (2... -- 2.5 The Third-Order Comprehensive Sensitivity Analysis Methodology for Response-Coupled Linear Forward and Adjoint Systems (3r... -- 2.6 The Fourth-Order Comprehensive Sensitivity Analysis Methodology for Response-Coupled Linear Forward and Adjoint Systems (4... -- 2.7 The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (... -- 2.7.1 The Pattern Underlying the nth-CASAM-L for n = 1, 2, 3, 4.
2.7.2 The Pattern Underlying the nth-CASAM-L: Arbitrarily High-Order n -- 2.7.3 Proving That the Framework for the nth-CASAM-L also Holds for the (n + 1)th-CASAM-L -- 2.8 The Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Coupled Forward/Adjoint Linear Systems (5th-CAS... -- 2.9 Chapter Summary -- Chapter 3: Illustrative Applications of the nth-CASAM-L to Paradigm Physical Systems with Imprecisely Known Properties, Intern... -- 3.1 Introduction -- 3.2 Transmission of Particles Through Media -- 3.2.1 Point-Detector Response -- 3.2.2 Particle Leakage Response -- 3.2.3 Reaction Rate Response -- 3.2.4 Contribution-Response Flux -- 3.3 Application of the 1st-CASAM-L to Compute First-Order Response Sensitivities to Imprecisely Known Parameters -- 3.3.1 Point-Detector Response -- 3.3.2 Particle Leakage Response -- 3.3.3 Reaction Rate Response -- 3.3.4 Contribution-Response -- 3.4 Application of the 2nd-CASAM-L to Compute Second-Order Response Sensitivities to Imprecisely Known Parameters -- 3.4.1 Determination of the Second-Order Sensitivities of the Form 2ρ(φ,ψ -- α)/αiμ(α), i = 1, , TP -- 3.4.2 Determination of the Second-Order Sensitivities of the Form 2ρ(φ,ψ -- α)/αib2, i = 1, , TP -- 3.4.3 Summary of Main Features Underlying the Computation of the Second-Order Sensitivities 2ρ(φ,ψ -- α)/αiαj, i, j = 1, , TP -- 3.5 Application of the 3rd-CASAM-L to Compute Third-Order Response Sensitivities to Imprecisely Known Parameters -- 3.5.1 Determination of the Third-Order Sensitivities of the Form 3ρ(φ,ψ -- α)/αiμ(α)μ(α), i = 1, , TP -- 3.5.2 Determination of the Third-Order Sensitivities of the Form 3ρ(φ,ψ -- α)/αib1b2, i = 1, , TP -- 3.6 Illustrative Application of the 4th-CASAM-L to a Paradigm Time-Evolution Model. 3.6.1 Applying the 1st-CASAM-L to Compute the first-Order Sensitivities to Model Parameters, Including Imprecisely Known Initi... -- 3.6.2 Applying the 2nd-CASAM-L to Compute the Second-Order Response Sensitivities to Model Parameters, Including Imprecisely K... -- 3.6.2.1 Second-Order Sensitivities Corresponding to R1(ρ -- α)/σi, i = 1, , N -- 3.6.2.2 Second-Order Sensitivities Corresponding to R1(ρ -- α)/ni, i = 1, , N -- 3.6.2.3 Second-Order Sensitivities Corresponding to R1(ρ -- α)/ρin -- 3.6.2.4 Second-Order Sensitivities Corresponding to R1(ρ -- α)/td -- 3.6.2.5 Second-Order Sensitivities Corresponding to R1(ρ -- α)/β -- 3.6.2.6 Independent Mutual Verification of Adjoint Sensitivity Functions -- 3.6.2.7 Aggregating Model Parameters to Reduce the Number of Large-Scale Adjoint Computations for Determining the Second-Order... -- 3.6.2.8 Illustrative Computation of Third- and Fourth-Order Sensitivities Using Aggregated Model Parameters -- 3.6.3 Applying the nth-CASAM-L to Compute Sensitivities of the Average Concentration Response to Model Parameters, Including I... -- 3.6.3.1 First-Order Sensitivities -- 3.6.3.2 Second-Order Sensitivities -- 3.7 Chapter Summary -- Chapter 4: Sensitivity Analysis of Neutron Transport Modeled by the Forward and Adjoint Linear Boltzmann Equations -- 4.1 Introduction -- 4.2 Paradigm Physical System: Neutron Transport in a Multiplying Medium with Source -- 4.3 Application of the 1st-CASAM-L to Determine the First-Order Sensitivities of R(φ,φ+ -- α) -- 4.4 Application of the 2nd-CASAM-L to Determine the Second-Order Sensitivities of R(φ,φ+ -- α) -- 4.4.1 Determination of the Second-Order Sensitivities of the Form -- 4.4.2 Determination of the Second-Order Sensitivities of the Form -- 4.4.3 Determination of the Second-Order Sensitivities of the Form -- 4.4.4 Determination of the Second-Order Sensitivities of the Form. 4.4.5 Determination of the Second-Order Sensitivities of the Form -- 4.4.6 Determination of the Second-Order Sensitivities of the Form -- 4.4.7 Determination of the Second-Order Sensitivities of the Form -- 4.5 Second-Order Sensitivity Analysis of the Schwinger and Roussopoulos Functionals -- 4.5.1 Application of the 1st-CASAM-L to Determine the First-Order Sensitivities of the Roussopoulos and Schwinger Functionals ... -- 4.5.2 Application of the 2nd-CASAM-L to Determine the Second-Order Sensitivities of the Schwinger and Roussopoulos Functionals... -- 4.5.2.1 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.2 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.3 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.4 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.5 Determination of the Second-Order Sensitivities of the Form -- 4.5.2.6 Determination of the Second-Order Sensitivities of the Form -- 4.6 Chapter Summary -- Chapter 5: Concluding Remarks -- References -- Index. |
| Record Nr. | UNISA-996483071503316 |
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Cacuci Dan Gabriel
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| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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The Second-Order Adjoint Sensitivity Analysis Methodology / / by Dan Gabriel Cacuci
| The Second-Order Adjoint Sensitivity Analysis Methodology / / by Dan Gabriel Cacuci |
| Autore | Cacuci Dan Gabriel |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Boca Raton, FL : , : Chapman and Hall/CRC, , 2018 |
| Descrizione fisica | 1 online resource (327 pages) |
| Disciplina | 003/.71 |
| Collana | Advances in Applied Mathematics |
| Soggetto topico |
Sensitivity theory (Mathematics)
Large scale systems Nonlinear systems |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-351-64658-3
1-315-12027-5 1-4987-2649-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | MOTIVATION FOR COMPUTING FIRST- AND SECOND-ORDER SENSITIVITIES OF SYSTEM RESPONSES TO THE SYSTEMS PARAMETERS -- The Fundamental Role of Response Sensitivities for Uncertainty Quantification -- The Fundamental Role of Response Sensitivities for Predictive Modeling -- Advantages and Disadvantages of Statistical and Deterministic Methods for Computing Response Sensitivities -- ILLUSTRATIVE APPLICATION OF THE SECOND-ORDER ADJOINT SENSITIVITY ANALYSIS METHODOLOGY (2nd-ASAM) TO A LINEAR EVOLUTION PROBLEM -- Exact Computation of the 1st-Order Response Sensitivities -- Exact Computation of the 2nd-Order Response Sensitivities -- Computing the 2nd-Order Response Sensitivities Corresponding to the 1st-Order Sensitivities -- Discussion of the Essential Features of the 2nd-ASAM -- Illustrative Use of Response Sensitivities for Predictive Modeling -- THE SECOND-ORDER ADJOINT SENSITIVITY ANALYSIS METHODOLOGY (2nd-ASAM) FOR LINEAR SYSTEMS -- Mathematical Modeling of a General Linear System -- The 1st-Level Adjoint Sensitivity System (1st-LASS) for Computing Exactly and Efficiently 1st-Order Sensitivities of Scalar-Valued Responses for Linear Systems -- The 2nd-Level Adjoint Sensitivity System (2nd-LASS) for Computing Exactly and Efficiently 1st-Order Sensitivities of Scalar-Valued Responses for Linear Systems -- APPLICATION OF THE 2nd-ASAM TO A LINEAR HEAT CONDUCTION AND CONVECTION BENCHMARK PROBLEM -- Heat Transport Benchmark Problem: Mathematical Modeling -- Computation of First-Order Sensitivities Using the 2nd-ASAM -- Computation of first-order sensitivities of the heated rod temperature -- Computation of first-order sensitivities of the coolant temperature -- Verification of the "ANSYS/FLUENT Adjoint Solver" -- Applying the 2nd-ASAM to Compute the Second-Order Sensitivities and Uncertainties for the Heat Transport Benchmark Problem -- APPLICATION OF THE 2nd-ASAM TO A LINEAR PARTICLE DIFFUSION PROBLEM -- Paradigm Diffusion Problem Description -- Applying the 2nd-ASAM to Compute the First-Order Response Sensitivities to Model Parameters -- Applying the 2nd-ASAM to Compute the Second-Order Response Sensitivities to Model Parameters -- Role of Second-Order Response Sensitivities for Quantifying Non-Gaussian Features of the Response Uncertainty Distribution -- Illustrative Application of First-Order Response Sensitivities for Predictive Modeling -- APPLICATION OF THE 2nd-ASAM FOR COMPUTING SENSITIVITIES OF DETECTOR RESPONSES TO UNCOLLIDED RADIATION TRANSPORT -- The Ray-Tracing Form of the Forward and Adjoint Boltzmann Transport Equation -- Application of the 2nd-ASAM to Compute the First-Order Response Sensitivities to Variations in Model Parameters -- Application of the 2nd-ASAM to Compute the Second-Order Response Sensitivities to Variations in Model Parameters -- THE SECOND-ORDER ADJOINT SENSITIVITY ANALYSIS METHODOLOGY (2nd-ASAM) FOR NONLINEAR SYSTEMS -- Mathematical Modeling of a General Nonlinear System -- The 1st-Level Adjoint Sensitivity System (1st-LASS) for Computing Exactly and Efficiently the 1st-Order Sensitivities of Scalar-Valued Responses -- The 2nd-Level Adjoint Sensitivity System (2nd-LASS) for Computing Exactly and Efficiently the 2nd-Order Sensitivities of Scalar-Valued Responses for Nonlinear Systems -- APPLICATION OF THE 2nd-ASAM TO A NONLINEAR HEAT CONDUCTION PROBLEM -- Mathematical Modeling of Heated Cylindrical Test Section -- Application of the 2nd-ASAM for Computing the 1st-Order Sensitivities -- Application of the 2nd-ASAM for Computing the 2nd-Order Sensitivities. |
| Record Nr. | UNINA-9910468033803321 |
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Cacuci Dan Gabriel
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| Boca Raton, FL : , : Chapman and Hall/CRC, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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