Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty are rendered obsolete since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods.This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper shows how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

NASA Probabilistic Risk Assessment (PRA) has the task of estimating the aleatory (randomness) and epistemic (lack of knowledge) uncertainty of launch vehicle loss of mission and crew risk, and communicating the results. Launch vehicles are complex engineered systems designed with sophisticated subsystems that are built to work together to accomplish mission success. Some of these systems or subsystems are in the form of heritage equipment, while some have never been previously launched. For these cases, characterizing the epistemic uncertainty is of foremost importance, and it is anticipated that the epistemic uncertainty of a modified launch vehicle design versus a design of well understood heritage equipment would be greater. For reasons that will be discussed, standard uncertainty propagation methods using Monte Carlo simulation produce counter intuitive results, and significantly underestimate epistemic uncertainty for launch vehicle models. Furthermore, standard PRA methods, such as Uncertainty-Importance analyses used to identify components that are significant contributors to uncertainty, are rendered obsolete, since sensitivity to uncertainty changes are not reflected in propagation of uncertainty using Monte Carlo methods. This paper provides a basis of the uncertainty underestimation for complex systems and especially, due to nuances of launch vehicle logic, for launch vehicles. It then suggests several alternative methods for estimating uncertainty and provides examples of estimation results. Lastly, the paper describes how to implement an Uncertainty-Importance analysis using one alternative approach, describes the results, and suggests ways to reduce epistemic uncertainty by focusing on additional data or testing of selected components

Use of TRACE best estimate code to analyze spent fuel storage pools safety

Nuclear policies have experienced an important change since Fukushima Daiichi nuclear plant accident and the safety of spent fuels has been in the spot issue among all the safety concerns. At many countries, the spent fuel of nuclear power plants is not reprocessed so it has to be stored inside the facilities, normally in pools. As nuclear power plants use best estimate codes to perform safety analysis, it is interesting to assess the capacity of such codes to simulate spent fuel pools behavior. This paper uses TRACE thermal-hydraulic code to simulate steady state and transient conditions of spent fuel pools. The steady state results are compared with plant measurements of Maine Yankee with a good agreement between the calculations and the measurements. The transient simulated is a loss of cooling together with a loss of coolant through the transfer channel. TRACE heat transfer radiation model has been activated using the parameters obtained from COBRA thermal-hydraulic code.This work has been supported by the Consejo de Seguridad Nuclear under the contract with reference STN/2369/08/640.Carlos Alberola, S.; Sánchez Sáez, F.; Martorell Alsina, SS. (2014). Use of TRACE best estimate code to analyze spent fuel storage pools safety. Progress in Nuclear Energy. 77:224-238. https://doi.org/10.1016/j.pnucene.2014.07.008S2242387

A Composite Resilience Index for Road Transport Networks

This paper is concerned with the development of a composite index for the resilience of road transport networks under disruptive events. The index employs three resilience characteristics, namely redundancy, vulnerability and mobility. Two different approaches, i.e. equal weighting and principal component analysis, are adopted to conduct the aggregation. In addition, the impact of the availability of real-time travel information for travellers on the three resilience characteristics and the composite resilience index is described. The application of the index on a synthetic road transport network of Delft city (Netherlands) shows that it responds well to traffic load changes and supply variations. The composite resilience index could be of use in various ways including supporting decision makers in understanding the dynamic nature of resilience under different disruptive events, highlighting weaknesses in the network and in assisting future planning to mitigate the impacts of disruptive events

Characterizing Epistemic Uncertainty for Space Launch Designs

No abstract availabl

X-ray absorption tomography employing a conical shell beam

We demonstrate depth-resolved absorption imaging by scanning an object through a conical shell of X-rays. We measure ring shaped projections and apply tomosynthesis to extract optical sections at different axial focal plane positions. Three-dimensional objects have been imaged to validate our theoretical treatment. The novel principle of our method is scalable with respect to both scan size and X-ray energy. A driver for this work is to complement previously reported methods concerning the measurement of diffracted X-rays for structural analysis. The prospect of employing conical shell beams to combine both absorption and diffraction modalities would provide enhanced analytical utility and has many potential applications in security screening, process control and diagnostic imaging

Vacuolization of hematopoietic precursors: an enigma with multiple etiologies

Cytoplasmic vacuoles in precursors can be seen in a number of clinical settings, including copper deficiency, zinc toxicity, alcohol abuse, antibiotic treatment, myelodysplasia, and VEXAS syndrome. Gurnari et al asked how common VEXAS syndrome is in patients whose bone marrow aspirates show this distinctive feature, finding 2 diagnoses of VEXAS among 24 cases with vacuoles

The ELF Honest Data Broker:Informatics enabling public-private collaboration in a precompetitive arena

New precompetitive ways of working in the pharmaceutical industry are driving the development of new informatics systems to enable their execution and management. The European Lead Factory (ELF) is a precompetitive, 30-partner collaboration between academic groups, small–medium enterprises and pharmaceutical companies created to discover small molecule hits against novel biological targets. A unique HTS screening and triage workflow has been developed to balance the intellectual property and scientific requirements of all the partners. Here, we describe the ELF Honest Data Broker, a cloud-based informatics system providing the scientific triage tools, fine-grained permissions and management tools required to implement the workflow