Browse Topic: Risk assessments
This document provides guidance for oxygen cylinder installation on commerical aircraft based on airworthiness requirements, and methods practiced within aerospace industry. It covers considerations for oxygen systems from beginning of project phase up to production, maintenance, and servicing. The document is related to requirements of DOT-approved oxygen cylinders, as well to those designed and manufactured to standards of ISO 11119. However, its basic rules may also be applicable to new development pertaining to use of such equipment in an oxygen environment. For information regarding oxygen cylinders itself, also refer to AIR825/12.
In the increasingly connected and digital world, businesses are sprinting to integrate technological advancements into their corporate fabric. This is evident with the emerging concept of “digital twinning.” Digital twins are virtual representations of real-world objects or systems used to digitally model performance, identify inefficiencies, and design solutions. This helps improve the “real world” product, reduces costs, and increases efficiency. However, this replication of a physical entity in the digital space is not without its challenges. One of the challenges that will become increasingly prevalent is the processing, storing, and transmitting of Controlled Unclassified Information (CUI). If CUI is not protected properly, an idea to save time, money, and effort could result in the loss of critical data. The Department of Defense's (DoD) CUI Program website defines CUI as “government-created or owned unclassified information that allows for, or requires, safeguarding and
This SAE Recommended Practice presents a method and example results for determining the Automotive Safety Integrity Level (ASIL) for automotive motion control electrical and/or electronic (E/E) systems. The ASIL determination activity is required by ISO 26262-3, and it is intended that the process and results herein are consistent with ISO 26262. The technical focus of this document is on vehicle motion control systems. The scope of this SAE Recommended Practice is limited to collision-related hazards associated with motion control systems. This SAE Recommended Practice focuses on motion control systems since the hazards they can create generally have higher ASIL ratings, as compared to the hazards non-motion control systems can create. Because of this, the Functional Safety Committee decided to give motion control systems a higher priority and focus exclusively on them in this SAE Recommended Practice. ISO 26262 has a wider scope than SAE J2980, covering other functions and accidents
This SAE Aerospace Recommended Practice (ARP) is a tool that organizations may use to evaluate a non-authorized supplier’s processes for the prevention, detection, containment, adjudication, and reporting of suspect counterfeit and counterfeit EEE parts. See 3.1.1 and 3.1.2, which reference the use of AS6081 when performing pre-visit self-assessment and on-site assessment of non-authorized suppliers. This ARP is applicable for all organizations that procure EEE parts from suppliers other than authorized sources (e.g., independent distributors).
Vehicle Acoustic Prototyping in the mid to high frequency range is challenging with numerical models only. To overcome this challenge, over the past decade, experimental techniques were developed that allow the engineer to incorporate Test-Based models in their (numerical) simulation as well. Using Virtual Point Technology these Test-Based models serve well to describe, for example, the complex dynamics of the vehicle body Noise Transfer Functions. Here the high modal density and damping characteristics are simply measured on a mule or prototype vehicle and coupled to numerical models of the drivetrain using Dynamic Substructuring. As such accurate predictions and/or risk assessments can be made much earlier in the mid and high frequency range during the vehicle development stage. While test-based models serve well to describe the coupled vehicle dynamics, loads to compute actual vehicle responses are needed as well. Here, so-called Equivalent or Blocked Forces are ideal as they are
Contemporary cutting-edge technologies, such as automated driving brought up vital questions about safety and relativized the safety assurance and acceptance criterion on different aspects. New risk assessment, evaluation, and acceptance justifications are required to assure that the assumptions and benchmarking are made on a reasonable basis. While there are some existing risk evaluation methods, most of them are qualitative in nature and are subjective. Moreover, information such as the safety performance indicators (SPIs) of the sensors, algorithms, and actuators are often not utilized well in these methods. To overcome these limitations, in this paper we propose a risk quantification methodology that uses Bayesian Networks to assess if the residual risk is reasonable under a given scenario. Our scenario-based methodology utilizes the SPIs and uncertainty estimates of sensors, algorithms, and actuators as well as their characteristics to quantify risk using the conditional
Recent researches in autonomous driving mainly consider the uncertainty in perception and prediction modules for safety enhancement. However, obstacles which block the field-of-view (FOV) of sensors could generate blind areas and leaves environmental uncertainty a remaining challenge for autonomous vehicles. Current solutions mainly rely on passive obstacles avoidance in path planning instead of active perception to deal with unexplored high-risky areas. In view of the problem, this paper introduces the concept of information entropy, which quantifies uncertain information in the blind area, into the motion planning module of autonomous vehicles. Based on model predictive control (MPC) scheme, the proposed algorithm can plan collision-free trajectories while actively explore unknown areas to minimize environmental uncertainty. Simulation results under various challenging scenarios demonstrate the improvement in safety and comfort with the proposed perception-aware planning scheme.
Letter from the Guest Editors
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