Safety factors in aviation
A formula for calculating the safety of airplanes is given and the stresses on airplane components are calculated.
Factors of safety↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Non-disruptive error field measurement in DIII-D low safety factor plasmas and projection to ITER
Previous experiments in DIII-D (Paz-Soldan et al 2022 Nucl. Fusion 62 126007) introduced a method to identify intrinsic error fields (EFs) in tokamaks with minimal disruption risk by promptly healing driven magnetic islands during the conventional 'compass scan'. This paper presents recent experimental and numerical advancements in extending this approach to low q 95 plasmas, and projects its applicability to ITER. Non-disruptive EF measurement is achieved at q 95 = 4.5 and 3.9 without any initial EF correction (EFC) by reducing the time between the occurrence of the locked mode (LM) and control action to 10 ms and increasing the density 50%–100%. However, 50% correction of the intrinsic EF is required to achieve island healing at q 95 = 3.2 with 10 ms delay for the control action. Nonlinear two-fluid modeling with the TM1 code reproduces the DIII-D experimental observations, indicating that promptly turning off the 3D coil current reduces both magnetic island width and electromagnetic force, while raising the density increases plasma viscosity, facilitating magnetic island healing. The simulations show that for scenarios with q 95 = 3.2, lowering the control action time to 5 ms will lead to island healing without EFC. TM1 simulations are extended to future ITER scenarios with 5 MA and 7.5 MA plasma currents, predicting the dependence of required density rise on action time and EF amplitude. These simulations indicate that, benefiting from the much longer resistive time, island healing can be successfully achieved in ITER when taking control action 100–500 ms after a LM occurrence.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Toward Improved Credibility Assessment and Communication concerning Risk and Consequence—Transformation to Advisory Safety Factors on Estimated Uncertainty
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Romero, Vicente Jose↗
Aerostructural safety factor criteria using deterministic reliability
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Verderaime, Vincent↗
White Paper on Factors of Safety
Following the Columbia Accident Investigation Board (CAIB) Report, the "Diaz Team" identified CAIB Report elements with Agency-wide applicability. The "Diaz Report", A Renewed Commitment To Excellence, generated an action to "Review current policies and waivers on safety factors". This document addresses this action.
Raju, Ivatury↗
Model Development for the ACME Lab Modular Wall and A-Frame Assemblies
The structural frame used for conducting large structural tests was replaced by the ACME (Applied Combined Mechanical Environments) Lab in Building 860 of Sandia National Laboratories in Albuquerque, NM. This new design required simulation and analysis to verify maximum loads and corresponding factors of safety. Two major assemblies which are part of the ACME Lab, the Modular Wall and A-Frame, were designed to operate with a multitude of components in various configurations and with varying loads. Simulations of the Modular Wall and A-Frame structures were performed through explicit analysis to determine safety factors for numerous loading scenarios. The Modular Wall had safety factors of 1.1 for the lateral, diagonal, and gusset loading conditions. The A-Frame had safety factors of 2 for all loading conditions simulated.
42 ENGINEERING↗
Human factors and safety in emergency medicine
A model based on an input process and outcome conceptualisation is suggested to address safety-relevant factors in emergency medicine. As shown in other dynamic and demanding environments, human factors play a decisive role in attaining high quality service. Attitudes held by health-care providers, organisational shells and work-cultural parameters determine communication, conflict resolution and workload distribution within and between teams. These factors should be taken into account to improve outcomes such as operational integrity, job satisfaction and morale.
Non-NASA Center↗
Critical safety assurance factors for manned spacecraft - A fire safety perspective
Safety assurance factors for manned spacecraft are discussed with a focus on the Space Station Freedom. A hazard scenario is provided to demonstrate a process commonly used by safety engineers and other analysts to identify onboard safety risks. Fire strategies are described, including a review of fire extinguishing agents being considered for the Space Station. Lessons learned about fire safety technology in other areas are also noted. NASA and industry research on fire safety applications is discussed. NASA's approach to ensuring safety for manned spacecraft is addressed in the context of its multidiscipline program.
Rodney, George A.↗
Investigation of Structural Factors of Safety for the Space Shuttle
A study was made of the factors governing the structural design of the fully reusable space shuttle booster to establish a rational approach to select optimum structural factors of safety. The study included trade studies of structural factors of safety versus booster service life, weight, cost, and reliability. Similar trade studies can be made on other vehicles using the procedures developed. The major structural components of a selected baseline booster were studied in depth, each being examined to determine the fatigue life, safe-life, and fail-safe capabilities of the baseline design. Each component was further examined to determine its reliability and safety requirements, and the change of structural weight with factors of safety. The apparent factors of safety resulting from fatigue, safe-life, proof test, and fail-safe requirements were identified. The feasibility of reduced factors of safety for design loads such as engine thrust, which are well defined, was examined.
Source record↗
The Ultimate Factor of Safety for Aircraft and Spacecraft Its History, Applications and Misconceptions
The ultimate factor of safety (FOSULT) concept used in aircraft and spacecraft has evolved over many decades. Currently an FOSULT 1.5 is the FAR‐mandated value for aircraft while an FOSULT of 1.4 has been used in various spacecraft. This paper was motivated by the desire to concisely explain the origins, proper interpretation and application of the ultimate factor of safety concept, since the authors have seen throughout their careers many misconceptions and incorrect applications of this concept. The history of the ultimate factor of safety concept is briefly summarized, the proper application of the factor of safety in aircraft design, structural analysis and operations is covered in detail, examples of limit load exceedance in aircraft and spacecraft are discussed, the evolution of the 1.4 FOSULT for spacecraft is described and some misconceptions regarding the ultimate factor of safety concept are addressed. It is hoped that this paper can be a summary resource for engineers to understand the origin, purpose and proper application of the ultimate factor of safety.
Zipay, John J.↗
Quasi-Static Probabilistic Structural Analyses Process and Criteria
Current deterministic structural methods are easily applied to substructures and components, and analysts have built great design insights and confidence in them over the years. However, deterministic methods cannot support systems risk analyses, and it was recently reported that deterministic treatment of statistical data is inconsistent with error propagation laws that can result in unevenly conservative structural predictions. Assuming non-nal distributions and using statistical data formats throughout prevailing stress deterministic processes lead to a safety factor in statistical format, which integrated into the safety index, provides a safety factor and first order reliability relationship. The embedded safety factor in the safety index expression allows a historically based risk to be determined and verified over a variety of quasi-static metallic substructures consistent with the traditional safety factor methods and NASA Std. 5001 criteria.
Goldberg, B.↗
Calculating Factors of Safety and Margins of Safety from Interaction Equations
This report presents the derivation of the relationship between the factor of safety, the margin of safety, and a given interaction equation in two- or three-dimensional space. Factors of safety and margins of safety can be calculated from these interaction equations using either the closed-form solutions provided or the numerical methods mentioned in this report. The dual definition of the factor of safety is presented.
Factor of Safety↗
Assessing Factors of Safety, Margins of Safety, and Reliability of Thermal Protection Systems
This paper provides formally derived definitions for Thermal Protection Systems (TPS) factors of safety and margins of safety borrowing from machine design approaches. The new factors of safety and margins of safety definitions are quite simple and easy to use, and should provide improved comparison of design safety and margins of past, present and future vehicles, These definitions are then applied to several entry vehicles, including Apollo, the Space Shuttle, the Mars Viking and Pathfinder vehicles, and the Pioneer Venus entry vehicle for example and clarity, and to aid in developing a database of previous TPS design experience. In addition to the factors and margins of safety, definitions of computed reliabilities incorporation the reliability index used in machine design are also developed and presented. Adoption and use of the reliability index will hopefully considerably aid the optimization of TPS design for future vehicles.
Rasky, Daniel J.↗
Design of a unidirectional composite momentum wheel rim
A preliminary study comparing twelve unidirectional-fiber composite systems to five metal materials conventionally used in momentum wheels is presented. Six different fibers are considered in the study: E-Glass, S-Glass, Boron, AS, T300, and Kevlar. Because of the possibility of high momentum requirements, and thus high stresses, only two matrix materials are considered: a high-modulus (HM) and a intermediate-modulus-high-strength (IMHS) matrix. Each of the six fibers are coupled with each of the two matrix materials. In an effort to optimize the composite system, each composite is considered while varying the fiber volume ratio from 0.0 to 0.7 in increments of 0.1. For fiber volume ratios above 0.2, all twelve unidirectional-fiber composite systems meet the study's requirements with higher factors of safety and less mass than the five conventional isotropic (metal) materials. For example, at a fiber volume ratio of 0.6, the Kevlar/IMHS composite system has a safety factor 4.5 times greater than that of a steel (maraging) system and an approximately 10 percent reduction in weight.
Shogrin, Bradley↗
Design of Critical Components
Critical component design is based on minimizing product failures that results in loss of life. Potential catastrophic failures are reduced to secondary failures where components removed for cause or operating time in the system. Issues of liability and cost of component removal become of paramount importance. Deterministic design with factors of safety and probabilistic design address but lack the essential characteristics for the design of critical components. In deterministic design and fabrication there are heuristic rules and safety factors developed over time for large sets of structural/material components. These factors did not come without cost. Many designs failed and many rules (codes) have standing committees to oversee their proper usage and enforcement. In probabilistic design, not only are failures a given, the failures are calculated; an element of risk is assumed based on empirical failure data for large classes of component operations. Failure of a class of components can be predicted, yet one can not predict when a specific component will fail. The analogy is to the life insurance industry where very careful statistics are book-kept on classes of individuals. For a specific class, life span can be predicted within statistical limits, yet life-span of a specific element of that class can not be predicted.
Hendricks, Robert C.↗
Conservative buffering of approximate nonlinear constraints
In engineering design practice behavior is usually predicted based on some known nominal design. However, when the design is fabricated it will differ from the nominal design because of manufacturing tolerances. In order to generate nominal designs that will still satisfy behavior constraints in the presence of manufacturing tolerances, engineers resort to the use of safety factors, over and above those introduced to account for other uncertainties (e.g., in load conditions, material properties, analysis modeling). The accurate selection of the values of these manufacturing tolerances safety factors is dependent on the capability of the engineer to determine the sensitivity of the critical constraints to changes in the design variables. This process usually leads to overly conservative designs. The task of choosing safety factors is much more difficult in structural synthesis because: (1) it is not known which constraints will be active at the final design, (2) as the design changes during the synthesis process the sensitivities of the constraints with respect to the design variables also change, and (3) the imposition of the safety factors themselves may change the set of critical constraints. These difficulties can be overcome with the approximation concepts approach to structural synthesis by buffering the approximate constraints with quantities that are related to the design variable tolerances and the accurate sensitivities of the constraints with respect to the design variable. Designs generated by this approach tend to be feasible but not overly conservative.
Thomas, H. L.↗
Space station crew safety: Human factors interaction model
A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this space station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.
Cohen, M. M.↗
Space Station crew safety - Human factors model
A model of the various human factors issues and interactions that might affect crew safety is developed. The first step addressed systematically the central question: How is this Space Station different from all other spacecraft? A wide range of possible issue was identified and researched. Five major topics of human factors issues that interacted with crew safety resulted: Protocols, Critical Habitability, Work Related Issues, Crew Incapacitation and Personal Choice. Second, an interaction model was developed that would show some degree of cause and effect between objective environmental or operational conditions and the creation of potential safety hazards. The intermediary steps between these two extremes of causality were the effects on human performance and the results of degraded performance. The model contains three milestones: stressor, human performance (degraded) and safety hazard threshold. Between these milestones are two countermeasure intervention points. The first opportunity for intervention is the countermeasure against stress. If this countermeasure fails, performance degrades. The second opportunity for intervention is the countermeasure against error. If this second countermeasure fails, the threshold of a potential safety hazard may be crossed.
Cohen, M. M.↗