Skip Nav Destination
Close Modal
Update search
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
NARROW
Date
Availability
1-20 of 2597
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
1
Sort by
Journal Articles
Accepted Manuscript
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert.
Paper No: VVUQ-23-1047
Published Online: August 28, 2024
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. June 2024, 9(2): 021009.
Paper No: VVUQ-24-1002
Published Online: August 2, 2024
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. June 2024, 9(2): 021007.
Paper No: VVUQ-23-1055
Published Online: August 2, 2024
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. June 2024, 9(2): 021010.
Paper No: VVUQ-24-1009
Published Online: August 2, 2024
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. June 2024, 9(2): 021008.
Paper No: VVUQ-23-1056
Published Online: August 2, 2024
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Verif. Valid. Uncert. June 2024, 9(2): 021006.
Paper No: VVUQ-23-1053
Published Online: August 2, 2024
Image
in Machine Learning-Based Resilience Modeling and Assessment of High Consequence Systems Under Uncertainty
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 1 Resilience composition More about this image found in Resilience composition
Image
in Machine Learning-Based Resilience Modeling and Assessment of High Consequence Systems Under Uncertainty
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 2 Schematic diagram of the impact of spent fuel transport packaging container More about this image found in Schematic diagram of the impact of spent fuel transport packaging container...
Image
in Machine Learning-Based Resilience Modeling and Assessment of High Consequence Systems Under Uncertainty
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 3 The relative compression distance of point C ranges with time t More about this image found in The relative compression distance of point C ranges with time t
Image
in Machine Learning-Based Resilience Modeling and Assessment of High Consequence Systems Under Uncertainty
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 4 Resilience assessment procedure More about this image found in Resilience assessment procedure
Image
in Machine Learning-Based Resilience Modeling and Assessment of High Consequence Systems Under Uncertainty
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 5 Stress of seal ring aging More about this image found in Stress of seal ring aging
Image
in Machine Learning-Based Resilience Modeling and Assessment of High Consequence Systems Under Uncertainty
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 6 Distribution of the yield stress of the buffer material More about this image found in Distribution of the yield stress of the buffer material
Image
in Machine Learning-Based Resilience Modeling and Assessment of High Consequence Systems Under Uncertainty
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 7 Distribution of d under impact speed 18.995 m/s, H = 5 mm More about this image found in Distribution of d under impact speed 18.995 m/s, H = 5 mm
Image
in Sparse Identification of Nonlinear Dynamics-Based Feature Extraction for Data Driven Model Predictive Control of a Buck Boost Switch Mode Power Supply
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 1 Equivalent circuit diagrams of a buck SMPS. The three different possible “conduction modes” of the circuit are shown which depend on state of the MOSFET and diode state as well as the inductor current. More about this image found in Equivalent circuit diagrams of a buck SMPS. The three different possible “c...
Image
in Sparse Identification of Nonlinear Dynamics-Based Feature Extraction for Data Driven Model Predictive Control of a Buck Boost Switch Mode Power Supply
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 2 Critical inductance values in terms of input voltage and purely resistive load. This value is the inductance which would place an ideal buck converter on the boundary of the DCM and CCM and the inductor current reaches zero directly in line with the switch period. More about this image found in Critical inductance values in terms of input voltage and purely resistive l...
Image
in Sparse Identification of Nonlinear Dynamics-Based Feature Extraction for Data Driven Model Predictive Control of a Buck Boost Switch Mode Power Supply
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 3 Diagram of the LTSPICE model used to generate the training data for the data driven techniques. Piece-wise linear variable assignments were used to vary the input voltage, Vi , output load, R , and a behavioral voltage component was used to modulate the duty cycle, DC. More about this image found in Diagram of the LTSPICE model used to generate the training data for the dat...
Image
in Sparse Identification of Nonlinear Dynamics-Based Feature Extraction for Data Driven Model Predictive Control of a Buck Boost Switch Mode Power Supply
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 4 Coefficient values for the standardized extended features. Values were generated by including noise with the LTSPICE training data and standardizing the signals to use as inputs into the SINDy algorithm. Standardizations allow for determinations to be made for which terms are most dominant ... More about this image found in Coefficient values for the standardized extended features. Values were gene...
Image
in Sparse Identification of Nonlinear Dynamics-Based Feature Extraction for Data Driven Model Predictive Control of a Buck Boost Switch Mode Power Supply
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 5 Time-series response for the different CCM SSA models, TS model created using the critical inductance relationship, the nonlinear model derived from the SINDy method, the eDMDc method using the truncated extended features to solve the data-driven controls problem, and the LTSPICE model show... More about this image found in Time-series response for the different CCM SSA models, TS model created usi...
Image
in Sparse Identification of Nonlinear Dynamics-Based Feature Extraction for Data Driven Model Predictive Control of a Buck Boost Switch Mode Power Supply
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 6 Open loop time-series response, using parameters in Table 1 , for the DCM SSA models, TS model created using the critical inductance relationship, the nonlinear model derived from the SINDy method, the eDMDc method using the truncated extended features to solve the data-driven controls pro... More about this image found in Open loop time-series response, using parameters in Table 1 , for the DCM ...
Image
in Sparse Identification of Nonlinear Dynamics-Based Feature Extraction for Data Driven Model Predictive Control of a Buck Boost Switch Mode Power Supply
> Journal of Verification, Validation and Uncertainty Quantification
Published Online: August 2, 2024
Fig. 7 Closed loop time-series response of the output voltage error for the DCM SSA models, TS model and the PID compensation method applied to incremental LTSPICE simulations using the circuit found in Fig. 3 More about this image found in Closed loop time-series response of the output voltage error for the DCM SS...
1