Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

2021 ◽  
pp. 1-1
Author(s):  
Urmila Agrawal ◽  
Pavel Etingov ◽  
Renke Huang
Keyword(s):  
Sensitivity Analysis ◽  
Model Validation ◽  
Performance Metrics

scholarly journals Advanced Performance Metrics and Sensitivity Analysis for Model Validation and Calibration

2020 ◽  
Author(s):  
Urmila Agrawal ◽  
Pavel Etingov ◽  
Renke Huang
Keyword(s):  
Sensitivity Analysis ◽  
Power Systems ◽  
Model Validation ◽  
Real World ◽  
Model Calibration ◽  
Dynamic Models ◽  
Performance Metrics ◽  
Step Response ◽  
Response Characteristics ◽  
Oscillatory Response

<pre>High quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMU measurements, measurement-based approach for model validation has gained significant prominence. Currently, the model validation results are analyzed by visually comparing real--world PMU measurements with the model-based response measurements, and parameter adjustments rely mostly on engineering experience. This paper proposes advanced performance metrics to systematically quantify the generator dynamic model validation results by separately taking into consideration slow governor response and comparatively fast oscillatory response. The performance metric for governor response is based on the step response characteristics of a system and the metric for oscillatory response is based on the response of generator to each system mode calculated using modal analysis. The proposed metrics in this paper is aimed at providing critical information to help with the selection of parameters to be tuned for model calibration by performing enhanced sensitivity analysis, and also help with rule-based model calibration. Results obtained using both simulated and real-world measurements validate the effectiveness of the proposed performance metrics and sensitivity analysis for model validation and calibration.</pre>

scholarly journals Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

2021 ◽  
Author(s):  
Urmila Agrawal ◽  
Pavel Etingov ◽  
Renke Huang
Keyword(s):  
Sensitivity Analysis ◽  
Power Systems ◽  
Model Validation ◽  
Real World ◽  
Model Calibration ◽  
Dynamic Models ◽  
Performance Metrics ◽  
Step Response ◽  
Response Characteristics ◽  
Oscillatory Response

<pre>High quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMU measurements, measurement-based approach for model validation has gained significant prominence. Currently, the model validation results are analyzed by visually comparing real--world PMU measurements with the model-based response measurements, and parameter adjustments rely mostly on engineering experience. This paper proposes advanced performance metrics to systematically quantify the generator dynamic model validation results by separately taking into consideration slow governor response and comparatively fast oscillatory response. The performance metric for governor response is based on the step response characteristics of a system and the metric for oscillatory response is based on the response of generator to each system mode calculated using modal analysis. The proposed metrics in this paper is aimed at providing critical information to help with the selection of parameters to be tuned for model calibration by performing enhanced sensitivity analysis, and also help with rule-based model calibration. Results obtained using both simulated and real-world measurements validate the effectiveness of the proposed performance metrics and sensitivity analysis for model validation and calibration.</pre>

scholarly journals Advanced Performance Metrics and Sensitivity Analysis for Model Validation and Calibration

2020 ◽  
Author(s):  
Urmila Agrawal ◽  
Pavel Etingov ◽  
Renke Huang
Keyword(s):  
Sensitivity Analysis ◽  
Power Systems ◽  
Model Validation ◽  
Real World ◽  
Model Calibration ◽  
Dynamic Models ◽  
Performance Metrics ◽  
Step Response ◽  
Response Characteristics ◽  
Oscillatory Response

<pre>High quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMU measurements, measurement-based approach for model validation has gained significant prominence. Currently, the model validation results are analyzed by visually comparing real--world PMU measurements with the model-based response measurements, and parameter adjustments rely mostly on engineering experience. This paper proposes advanced performance metrics to systematically quantify the generator dynamic model validation results by separately taking into consideration slow governor response and comparatively fast oscillatory response. The performance metric for governor response is based on the step response characteristics of a system and the metric for oscillatory response is based on the response of generator to each system mode calculated using modal analysis. The proposed metrics in this paper is aimed at providing critical information to help with the selection of parameters to be tuned for model calibration by performing enhanced sensitivity analysis, and also help with rule-based model calibration. Results obtained using both simulated and real-world measurements validate the effectiveness of the proposed performance metrics and sensitivity analysis for model validation and calibration.</pre>

Repeatability Assessment and Sensitivity Analysis of Needle Insertion Physical Experiment

2018 ◽  
Author(s):  
Murong Li ◽  
Yong Lei
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Estimation ◽  
Model Validation ◽  
Ground Truth ◽  
Needle Insertion ◽  
Physical Experiment ◽  
Future Experiment ◽  
Parameter Uncertainties ◽  
Tissue Interactions ◽  
Physical Experiments

Needle insertion physical experiments are used as the ground truth for model validation and parameter estimation by measuring the needle defection and tissue deformation during the needle-tissue interactions. Hence parameter uncertainties can contribute experiment errors. To improve the repeatability and accuracy of such experiments, one-at-a-time (OAT) sensitivity analysis is used to study the impacts of the factors, such as stirring temperature, frozen time, thawing time during the process of making hydrogels as well as repeated path insertion and different puncture plane in the planer needle insertion experiments. The results show that the puncture plane has the greatest effect on the repeatability of needle insertion physic experiments, followed by repeated path insertion, while other factors have the least effect. The results serve to guide future experiment design for greater repeatability and accuracy.

scholarly journals OPTIMALISASI ALOKASI SUMBERDAYA RUMAHTANGGA TANI MELALUI INTEGRASI USAHATANI TANAMAN DAN SAPI POTONG DI GUNUNGKIDUL YOGYAKARTA

Agro Ekonomi ◽  
2016 ◽  
Vol 9 (2) ◽  
pp. 65
Author(s):  
Rini Widiati ◽  
Krishna Agung Santosa ◽  
Sri Widodo ◽  
Masyhuri Masyhuri
Keyword(s):  
Resource Allocation ◽  
Sensitivity Analysis ◽  
Linear Programming ◽  
Confidence Interval ◽  
Model Validation ◽  
Programming Model ◽  
Farm Household ◽  
Mutual Support ◽  
Cattle Farm ◽  
Household Resources

The objective of this research is to assess the optimization of cattle farm household resources. The research was carried out by survey on samples of cattle farmers from two villages in Playen regency, Gunung Kidul district. The data collected were analyzed quantitatively using linear programming model and sensitivity analysis using BLPX 88 program. The model validation was carried out using confidence interval. The result of the research shows that most cattle farmers are poor in resources that they always combine their cattle farming activities with other activities specially crop activity to fulfill their daily need. This condition indicates that although the scale of cattle farm is small but it exist and continuous because there are mutual support and dependancy amoung activities. In general, the optimum resource allocation can increase their income over their family consumption.

Thermal Modeling And Uncertainty Quantification of Tool For Automated Garment Assembly

2021 ◽  
Author(s):  
Nicolás Castrillón ◽  
Avery Rock ◽  
Tarek I. Zohdi
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Uncertainty Quantification ◽  
Performance Metrics ◽  
Element Model ◽  
Thermal Design ◽  
Future Design ◽  
Physical Experiments ◽  
Important Design ◽  
Work Cells

Abstract In this work, a thermal Finite Element model is developed to simulate the performance of a blade-like tool for robotic work cells performing automated garment production using a novel thermoplastic stiffening layer. Uncertainty quantification and sensitivity analysis are applied to determine the most important design properties and optimize key performance metrics for swift and reliable garment assembly. Attention is focused on the geometric and thermal design properties that minimize sensitivity to environmental conditions while maximizing expected productivity. An example design is shown for illustrative purposes. This work may inform future design innovation for similar heating tools and reduce the need for physical experiments and long calibration times on the factory floor.

Global Sensitivity Analysis of a Coupled Hydro-Economic Model and Groundwater Restriction Assessment

2021 ◽  
Author(s):  
José M. Rodríguez-Flores ◽  
Jorge A. Valero-Fandiño ◽  
Spencer A. Cole ◽  
Keyvan Malek ◽  
Tina Karimi ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Economic Model ◽  
Performance Metrics ◽  
Global Sensitivity Analysis ◽  
Crop Yields ◽  
Production Model ◽  
Groundwater Pumping ◽  
Global Sensitivity ◽  
Artificial Neural Network Ann ◽  
Price Uncertainties

Abstract The modeling of coupled food-water systems to represent the effect of water supply variability as well as shocks that may emerge from changes in policies, economic drivers, and productivity requires an understanding of dominant uncertainties. These uncertainties cascade into forecasts of impacts of water management policies, such as groundwater pumping restrictions. This paper assesses how parametric, crop price, crop yields, surface water price, and electricity price uncertainties shape hydro-economic model estimates for agricultural production through a diagnostic global sensitivity analysis (GSA).The diagnostic GSA explores how the uncertainties in combination with a candidate groundwater pumping restriction influence three metrics of concern: total economic revenue, total land use and groundwater depth change. The hydro-economic model integrates a Groundwater Response Function (GRF) by integrating an Artificial Neural Network (ANN) into a calibrated Positive Mathematical Programming (PMP) production model for the Wheeler Ridge-Maricopa Water Storage District located in Kern County, California. Our results show that in addition to groundwater pumping restriction, performance metrics of the system are highly sensitive to prices and yields particularly of profitable crops. These sensitivities become salient during dry years when there is a higher reliance on groundwater.

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