Computer Program for Multimodel Reliability and Optimization Analysis

Mahsuli, Mojtaba; Haukaas, Terje

doi:10.1061/(asce)cp.1943-5487.0000204

Cited by 136 publications

(37 citation statements)

References 6 publications

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“…The FORM analysis was performed using RT software (Mashuli and Haukaas 2013) to evaluate the probability of non-compliance and the sensitivity of the sight distance variables for permitted left-turn movements. Importance sampling analysis was afterwards conducted using the same software to raise the accuracy of the probability of non-compliance results.…”

Section: Analysis and Mitigationmentioning

confidence: 99%

Framework for evaluating risk of limited sight distance for permitted left-turn movements: case study

2016

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A reliability analysis framework is used to evaluate the risk of limited Sight Distance for permitted left-turn movements due to the presence of opposing left-turn vehicles. Two signalized intersection approaches in the city of Surrey were used as case studies for the framework.Geometric and traffic video data was collected and analyzed using a computer vision tool to extract the input variables probability distributions. The data was used in the reliability analysis where first-order and importance sampling methods were performed. The analysis showed that the probability of non-compliance was considerable at one approach due to its large left-turn lane offset. The analysis also showed that the probability of non-compliance increased substantially when the obstacle vehicle was a bus rather than a passenger car. Moreover, the time gap had a higher impact on the probability of non-compliance compared to speed. Strategies were suggested to overcome the high probability of non-compliance.

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Section: Analysis and Mitigationmentioning

confidence: 99%

Framework for evaluating risk of limited sight distance for permitted left-turn movements: case study

2016

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“…In an Rt analysis, each of these programs may serve as a model amongst many other probabilistic models. Further information on Rt is available in [30].…”

Section: Softwarementioning

confidence: 99%

“…The probabilities are computed by e cient reliability methods, rather than a multifold integral, which may be cumbersome to evaluate; 8. It is possible to include time-varying phenomena, such as long-term deterioration and discounting, in the analysis; see Mahsuli and Haukaas [30,37] for numerical examples; 9. It is possible to distinguish between reducible and irreducible uncertainties, which are termed epistemic and aleatory uncertainties, respectively.…”

Section: Conclusion Remarksmentioning

confidence: 99%

Resilience of Civil Infrastructure by Optimal Risk Mitigation

Mahsuli

2016

Scientia Iranica

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Abstract. This paper puts forward a framework for optimal mitigation of regional risk to enhance the resilience of civil infrastructure. To meet this objective, probabilistic models, methods, and software are developed and applied. The work is conducted within a new reliability-based approach, in which reliability methods compute risk. This contrasts several contemporary approaches for risk analysis. Risk, in this context, denotes the probability of exceeding monetary loss. Evaluating such probabilities requires probabilistic models for hazards, response, damage, and loss. This motivates the following contributions in this paper. First, a new computer program is developed that is tailored to conduct reliability analysis with many interconnected probabilistic models. It orchestrates the interaction of models through an object-oriented architecture. Second, a library of probabilistic models for regional seismic risk analysis is developed. The library includes new models for earthquake location and magnitude and building response, damage, and loss. Third, probabilistic methods for multi-hazard risk analysis are developed and applied in a largescale regional analysis. The results are cost exceedance probabilities and insights into the seismic risk of the region. Finally, sensitivity measures are developed to identify the buildings whose retro t yields the most reduction in regional risk, i.e. the most resilience of the region.

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“…Using the calibrated model, a reliability analysis will be performed to study the theoretical safety of the different wall configurations. OpenSees integrates with the reliability package Rt (Mahsuli and Haukaas, 2013), which will be used in the reliability analyses. Data CASHEW reciprocal of the total R-value (called the U-value) is the sum of the individual Uvalues.…”

Section: Figure 3: Cashew Model Compared To Representative Test Datamentioning

confidence: 99%

Laboratory Testing of Energy-Efficient Wood-Framed Shear Walls

Rodríguez-Nikl¹,

Gupta

2014

Structures Congress 2014

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Residential energy use is a significant contributor to greenhouse gas emissions and climate change. In conventional wood-framed construction, the wood framing creates thermal bridges that allow heat to bypass insulation. One suggestion for reducing thermal bridging is the staggered stud (SS) wall. SS walls use 2×6 bottom and top plates with 2×4 studs alternating between sides of the wall. A literature review revealed a lack of laboratory test data for staggered stud walls used as shear walls, raising concerns about their safety under lateral loading from earthquakes. We tested the seismic performance of typical SS and conventional walls. The SS specimens performed similarly to conventional walls. Some minor differences emerged, but the data raised no immediate concerns with use of SS walls in areas of seismic hazard. Additional work is proposed for laboratory testing and computational modeling of mechanical and thermal behavior for walls with innovative framing arrangements.

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Computer Program for Multimodel Reliability and Optimization Analysis

Cited by 136 publications

References 6 publications

Framework for evaluating risk of limited sight distance for permitted left-turn movements: case study

Framework for evaluating risk of limited sight distance for permitted left-turn movements: case study

Resilience of Civil Infrastructure by Optimal Risk Mitigation

Laboratory Testing of Energy-Efficient Wood-Framed Shear Walls

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