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The presentation reviews the dependability and safety effort of NASA's Independent Verification and Validation Facility. Topics include: safety engineering process, applications to non-space environment, Phase I overview, process creation, sample SRM artifact, Phase I end result, Phase II model transformation, fault management, and applying Phase II to individual projects.
As world-wide air traffic continues to grow even at a modest pace, the overall complexity of the system will increase significantly. This increased complexity can lead to a larger number of fatalities per year even if the extremely low fatality rate that we currently enjoy is maintained. One important source of information about the safety of the aviation system is in Aviation Safety Text Reports which are written by members of the flight crew, air traffic controllers, and other parties involved with the aviation system. These anonymized narrative reports contain fixed-field contextual information about the flight but also contain free-form narratives that describe, in the author s own words, the nature of the safety incident and, in many cases, the contributing factors that led to the safety incident. Several thousand such reports are filed each month, each of which is read and analyzed by highly trained experts. However, it is possible that there are emerging safety issues due to the fact that they may be reported very infrequently and in different contexts with different descriptions. The goal of this research paper is to develop correlated topic models which uncover correlations in the subspaces defined by the intersection of numerous fixed fields and discovered correlated topics. This task requires the discovery of latent topics in the text reports and the creation of a topic cube. Furthermore, because the number of potential cells in the topic cube is very large, we discuss novel methods of pruning the search space in the topic cells, thereby making the analysis feasible. We demonstrate the new algorithms on an analysis of pilot fatigue and its contributing factors, as well as the safety incidents that are correlated with this phenomenon.
International Atomic Energy Agency (IAEA) works, together with Member States (MS), to provide a strong, sustainable and visible global nuclear safety and security framework, protecting people and the environment from the harmful effects of ionizing radiation. In the announcement of this IAEA Conference it is underlined that 'nuclear safety and security are to a great extent scientific in nature, a regulatory body with responsibilities for nuclear facilities and other licensed activities involving radioactive material needs to have permanent access to supporting expertise'. This can be provided internally to the regulatory body or through an external entity such as a TSO in order to provide a competent and timely response to regulatory needs, and the development and maintenance of an appropriate knowledge base and associated tools and services, including training and tutoring services, are the main areas on which the conference will focus. This paper presents certain results obtained during carrying out the IAEA-Romanian Scientific Research Contract entitled: 'Romanian Contribution to the Development of Methodology for Risk Assessment and State Management of Nuclear Security Regime (Risk and Radiological Consequences)' where the author served as CSI (Chief Scientific Investigator) a part of the IAEA CRP-(Coordinated Research Project) on the: 'Development of Methodology for Risk Assessment and State Management of Nuclear Security Regime'. Also, potential risks and their possible radiological consequences to peoples and environment must not be underestimated. However, the assessment of risk must be realistic and quantified, and the requirements placed on the appropriate. The IAEA regulations for the Safe Transport of Radioactive Material, 2012 Edition, Specific Safety Requirements, SSR-6, are applicable to the national and international carriage of radioactive material by all modes of transport- by road, by rail, by air, by sea or by inland waters. The Radioactive Material to be transported must be categorized on the basis of its activity concentration, total activity, fissile characteristics (if any) and other relevant subsidiary characteristics. Packaging and package requirements are then specified on the basis of the hazard of the contents and range from normal commercial packaging (for low hazard contents) to strict design and performance requirements (for higher hazard contents). (authors)
Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.
The world-wide aviation system is one of the most complex dynamical systems ever developed and is generating data at an extremely rapid rate. Most modern commercial aircraft record several hundred flight parameters including information from the guidance, navigation, and control systems, the avionics and propulsion systems, and the pilot inputs into the aircraft. These parameters may be continuous measurements or binary or categorical measurements recorded in one second intervals for the duration of the flight. Currently, most approaches to aviation safety are reactive, meaning that they are designed to react to an aviation safety incident or accident. In this paper, we discuss a novel approach based on the theory of multiple kernel learning to detect potential safety anomalies in very large data bases of discrete and continuous data from world-wide operations of commercial fleets. We pose a general anomaly detection problem which includes both discrete and continuous data streams, where we assume that the discrete streams have a causal influence on the continuous streams. We also assume that atypical sequence of events in the discrete streams can lead to off-nominal system performance. We discuss the application domain, novel algorithms, and also discuss results on real-world data sets. Our algorithm uncovers operationally significant events in high dimensional data streams in the aviation industry which are not detectable using state of the art methods
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A systematic approach is presented to constructing a radiation assurance case using Goal Structured Notation (GSN) for spacecraft containing COTS parts. The GSN paradigm is applied to an SRAM single-event upset experiment board designed to fly on a CubeSat November 2016. Construction of a radiation assurance case without use of hardened parts or extensive radiation testing is discussed.
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