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Suggested criteria for evaluating systems engineering methodologies

Systems engineering is the application of mathematical and scientific principles to practical ends in the life-cycle of a system. A methodology for systems engineering is a carefully developed, relatively complex procedure or process for applying these mathematical and scientific principles. There are many systems engineering methodologies (or possibly many versions of a few methodologies) currently in use in government and industry. These methodologies are usually designed to meet the needs of a particular organization. It has been observed, however, that many technical and non-technical problems arise when inadequate systems engineering methodologies are applied by organizations to their systems development projects. Various criteria for evaluating systems engineering methodologies are discussed. Such criteria are developed to assist methodology-users in identifying and selecting methodologies that best fit the needs of the organization.

Gates, Audrey↗

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Moore, N. R.↗

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 2: Software documentation

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes, These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Moore, N. R.↗

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 3: Structure and listing of programs

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Moore, N. R.↗

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 1: Methodology and applications

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for designs failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

Moore, N. R.↗

Methodology for inferring reactor core power distribution from an optical fiber based gamma thermometer array

Here, a 4-step data analytic methodology has been devised for the purpose of inferring the distribution of power in a reactor core, based on the response of an array of optical fiber based gamma thermometers (OFBGTs). This data analytic methodology is crucial for the development of a system of OFBGTs for the purpose of calibrating local power range monitors in boiling water reactors. Such a system would be an improvement to the present calibration system in boiling water reactors, in terms of safety, efficiency, and permanence. The first step of this methodology is to establish an energy balance method. In this method, one uses MCNP to determine response functions, which allow one to convert from gamma thermometer response to power. The gamma thermometers and the reactor core are segmented, such that each gamma thermometer segment provides an estimate of power for each reactor core segment. The estimates of power for the reactor core segments (hereafter referred to as fuel assembly segments) are calculated based on the measured response of the gamma thermometers. The second step of the methodology is to employ a weighting scheme to combine the estimates of the power of the various fuel assembly segments, based on the response of the various OFGBT segments and the incremental dose rates of the various fuel assembly segments to the OFBGT segments. The third step is to iteratively calculate the estimates of the power of the fuel assembly segments, until a convergence criterion is met, which indicates that the calculation has converged. The fourth and final step of the methodology is to estimate the uncertainty of the power for each fuel assembly segment. The mathematical basis for this step is not the focus of this paper. We have used a 3-D homogeneous reactor model to demonstrate the data analytic methodology; and have found that the data analytic methodology operates as intended.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Using Modern Methodologies with Maintenance Software

Jet Propulsion Laboratory uses multi-mission software produced by the Mission Planning and Sequencing (MPS) team to process, simulate, translate, and package the commands that are sent to a spacecraft. MPS works under the auspices of the Multi-Mission Ground Systems and Services (MGSS). This software consists of nineteen applications that are in maintenance. The MPS software is classified as either class B (mission critical) or class C (mission important). The scheduling of tasks is difficult because mission needs must be addressed prior to performing any other tasks and those needs often spring up unexpectedly. Keeping track of the tasks that everyone is working on is also difficult because each person is working on a different software component. Recently the group adopted the Scrum methodology for planning and scheduling tasks. Scrum is one of the newer methodologies typically used in agile development. In the Scrum development environment, teams pick their tasks that are to be completed within a sprint based on priority. The team specifies the sprint length usually a month or less. Scrum is typically used for new development of one application. In the Scrum methodology there is a scrum master who is a facilitator who tries to make sure that everything moves smoothly, a product owner who represents the user(s) of the software and the team. MPS is not the traditional environment for the Scrum methodology. MPS has many software applications in maintenance, team members who are working on disparate applications, many users, and is interruptible based on mission needs, issues and requirements. In order to use scrum, the methodology needed adaptation to MPS. Scrum was chosen because it is adaptable. This paper is about the development of the process for using scrum, a new development methodology, with a team that works on disparate interruptible tasks on multiple software applications.

Scrum↗

Physics-informed hybrid modeling methodology for building infiltration

Infiltration is responsible for one-third to one-half of the space conditioning load of a typical residential home, but the modeling of infiltration for building energy modeling is either represented by over-simplified equations or dependent on over-generalized rules of thumb. Here, this paper develops a physics-informed data-driven methodology for modeling infiltration using building-specific empirical measurements. The developed hybrid methodology combines machine-learning categorization and grey-box sub-modeling to improve the accuracy and generalization of commonly used grey-box infiltration models. The developed methodology excels at predicting infiltration by improving the ability to predict infiltration under unseen environmental conditions using machine learning algorithms with physical significance. In a case study conducted using the iUnit, a modular studio apartment experimental test facility located at the National Renewable Energy Laboratory, we use empirical airtightness measurements to fit an infiltration model using the developed methodology. We find that the developed methodology can improve the overall model accuracy by 43% and improve extrapolation by 38%, compared with the model based on the common grey-box infiltration equation. We also notice that the selected features can improve the performance of a pure machine-learning model, indicating that our methodology identifies the features with the most physical significance to infiltration modeling.

97 MATHEMATICS AND COMPUTING↗

A Risk-Informed Performance-Based Methodology to Manage Fire Protection Systems in Nuclear Facilities

Fire protection systems (FPSs) and features are installed in U.S. Department of Energy (DOE) Hazard Category 1, 2, or 3 nuclear facilities to protect property (maximum possible fire loss thresholds), life, and nuclear safety (i.e., structures, systems, and components). These FPSs and features are designed and maintained in accordance with the prescriptive guidance provided in applicable building codes and National Fire Protection Association codes and standards. Management, operations, and maintenance activities of FPSs involve significant effort. A DOE facility’s documented safety analysis or other safety basis document could also rely on FPSs to provide either a safety significant or safety class function to mitigate fire hazards and minimize radiological consequences. In some cases, the designation of safety significant or safety class may be determined to provide a layer of defense-in-depth to minimize nuclear safety risks independent of the fire risk. DOE standards allow the use of performance-based design alternatives developed by the fire industry but do not consider the defense-in-depth layers of protection provided in DOE facilities to prevent or mitigate the risks associated with unintended release of radioactive materials into the environment. Pacific Northwest National Laboratory developed a decision-making methodology tailored for DOE non-reactor nuclear facilities to manage FPSs and features by integrating nuclear safety risk insights into a performance-based analysis. This risk-informed, performance-based (RIPB) methodology can be used to provide the technical basis for classifying an FPS as safety class and safety significant, tailoring administrative controls (e.g., technical safety requirements), and ranking the importance of FPSs to prioritize maintenance, upgrades, and replacement activities. The RIPB methodology is a graded approach to inform DOE facility owners and Fire Protection Program managers of the most risk-significant FPSs and equipment, and those systems would be cost-beneficial to relax rigor if there is a need to re-design the FPS coverage or deviate from DOE and National Fire Protection Association standards for those systems that would be less significant. This paper describes the framework used to develop the RIPB methodology and the outcome of implementing this methodology in a use-case nuclear facility. This paper also discusses the impact to DOE policies and standards and the safety margins and defense-in-depth measures credited in nuclear safety assessments in a facility’s documented safety analysis and the benefits of implementing an RIPB methodology in lieu of a prescriptive method to comply with fire protection requirements.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

IMPAC: An Integrated Methodology for Propulsion and Airframe Control

The National Aeronautics and Space Administration is actively involved in the development of enabling technologies that will lead towards aircraft with new/enhanced maneuver capabilities such as Short Take-Off Vertical Landing (STOVL) and high angle of attack performance. Because of the high degree of dynamic coupling between the airframe and propulsion systems of these types of aircraft, one key technology is the integration of the flight and propulsion control. The NASA Lewis Research Center approach to developing Integrated Flight Propulsion Control (IFPC) technologies is an in-house research program referred to as IMPAC (Integrated Methodology for Propulsion and Airframe Control). The goals of IMPAC are to develop a viable alternative to the existing integrated control design methodologies that will allow for improved system performance and simplicity of control law synthesis and implementation, and to demonstrate the applicability of the methodology to a supersonic STOVL fighter aircraft. Based on some preliminary control design studies that included evaluation of the existing methodologies, the IFPC design methodology that is emerging at the Lewis Research Center consists of considering the airframe and propulsion system as one integrated system for an initial centralized controller design and then partitioning the centralized controller into separate airframe and propulsion system subcontrollers to ease implementation and to set meaningful design requirements for detailed subsystem control design and evaluation. An overview of IMPAC is provided and detailed discussion of the various important design and evaluation steps in the methodology are included.

Garg, Sanjay↗

A framework for assessing the adequacy and effectiveness of software development methodologies

Tools, techniques, environments, and methodologies dominate the software engineering literature, but relatively little research in the evaluation of methodologies is evident. This work reports an initial attempt to develop a procedural approach to evaluating software development methodologies. Prominent in this approach are: (1) an explication of the role of a methodology in the software development process; (2) the development of a procedure based on linkages among objectives, principles, and attributes; and (3) the establishment of a basis for reduction of the subjective nature of the evaluation through the introduction of properties. An application of the evaluation procedure to two Navy methodologies has provided consistent results that demonstrate the utility and versatility of the evaluation procedure. Current research efforts focus on the continued refinement of the evaluation procedure through the identification and integration of product quality indicators reflective of attribute presence, and the validation of metrics supporting the measure of those indicators. The consequent refinement of the evaluation procedure offers promise of a flexible approach that admits to change as the field of knowledge matures. In conclusion, the procedural approach presented in this paper represents a promising path toward the end goal of objectively evaluating software engineering methodologies.

Arthur, James D.↗

Virtual-pulse time integral methodology: A new explicit approach for computational dynamics - Theoretical developments for general nonlinear structural dynamics

The present paper describes a new explicit virtual-pulse time integral methodology for nonlinear structural dynamics problems. The purpose of the paper is to provide the theoretical basis of the methodology and to demonstrate applicability of the proposed formulations to nonlinear dynamic structures. Different from the existing numerical methods such as direct time integrations or mode superposition techniques, the proposed methodology offers new perspectives and methodology of development, and possesses several unique and attractive computational characteristics. The methodology is tested and compared with the implicit Newmark method (trapezoidal rule) through a nonlinear softening and hardening spring dynamic models. The numerical results indicate that the proposed explicit virtual-pulse time integral methodology is an excellent alternative for solving general nonlinear dynamic problems.

Chen, Xiaoqin↗

Reference Management Methodologies for Large Structural Models at Kennedy Space Center

There have been many challenges associated with modeling some of NASA KSC's largest structures. Given the size of the welded structures here at KSC, it was critically important to properly organize model struc.ture and carefully manage references. Additionally, because of the amount of hardware to be installed on these structures, it was very important to have a means to coordinate between different design teams and organizations, check for interferences, produce consistent drawings, and allow for simple release processes. Facing these challenges, the modeling team developed a unique reference management methodology and model fidelity methodology. This presentation will describe the techniques and methodologies that were developed for these projects. The attendees will learn about KSC's reference management and model fidelity methodologies for large structures. The attendees will understand the goals of these methodologies. The attendees will appreciate the advantages of developing a reference management methodology.

Jones, Corey↗

Reliability Centered Maintenance - Methodologies

Journal article about Reliability Centered Maintenance (RCM) methodologies used by United Space Alliance, LLC (USA) in support of the Space Shuttle Program at Kennedy Space Center. The USA Reliability Centered Maintenance program differs from traditional RCM programs because various methodologies are utilized to take advantage of their respective strengths for each application. Based on operational experience, USA has customized the traditional RCM methodology into a streamlined lean logic path and has implemented the use of statistical tools to drive the process. USA RCM has integrated many of the L6S tools into both RCM methodologies. The tools utilized in the Measure, Analyze, and Improve phases of a Lean Six Sigma project lend themselves to application in the RCM process. All USA RCM methodologies meet the requirements defined in SAE JA 1011, Evaluation Criteria for Reliability-Centered Maintenance (RCM) Processes. The proposed article explores these methodologies.

Kammerer, Catherine C.↗

Implementation of J-A Methodology Elastic-Plastic Crack Instability Analysis Capability into the WARP-3D Code

Characterization of the near crack-tip stress/strain fields is the foundation of fracture mechanics. The description of the near tip stress field and the prediction of when fracture occurs is well established for brittle materials that exhibit linear elastic behavior. However, in ductile materials or conditions that violate linear elastic assumptions (Aluminum alloys, Al 2024-T3, Al 2024- T351 etc.), the elastic-plastic crack-tip stress fields are characterized by the Hutchison-Rice-Rosengren (HRR) field. The J-integral is commonly used to characterize amplitude of the HRR field under elastic-plastic conditions. The J-integral has been demonstrated for crack-tip fields that are under high constraint conditions (i.e., small-scale plasticity where the J-dominance is maintained). However, as the external load increases, yielding changes from small- to largescale plasticity and usually a loss of constraint (i.e., reduction in the triaxial stress field along the crack front). The loss of constraint leads to the deviation of the crack-tip stress fields from that given by the HRR field. Hence, the J-dominance will be gradually lost and additional parameter(s) are required to quantify the crack-tip stress fields and predict fracture behavior. The assessment objectives were to: 1) implement a two-parameter (i.e., J-A) fracture criterion into an elastic-plastic three-dimensional (3D) finite element analysis (FEA), 2) validate the implementation by comparison with the A parameter from literature data, 3) conduct material characterization tests to quantify the material behavior and provide fracture data for validation of the J-A fracture criteria, and (4) perform evaluations to establish if the J-A criteria can be used to predict fracture in a ductile metallic material (e.g., aluminum alloys). The A parameter in these criteria is the second parameter in a three-term elastic-plastic asymptotic expansion of the neartip stress behavior. A series of extensive FEAs were performed using WARP3D software package to obtain solutions for the A parameter for different specimen configurations. The methodology needed for the estimation of the A parameter in the asymptotic expansion was developed and implemented using Matlab®. A user material (UMAT) routine was used to model the material stress-strain response using a Ramberg-Osgood power law with a hardening exponent (n) and a material coefficient (alpha). This UMAT routine was successfully implemented in WARP3D software and validated through comparison with the experimental data. Three configurations were extracted from published results: 1) center cracked plate (CCP), 2) single edge-cracked plate (SECP), and 3) double edge-cracked plate (DECP). These configurations and four other configurations (three-hole tension (THT)), three-point bend (3PTB), three-hole compact tension (3PCT), and compact tension (CT)) were analyzed to verify the methodology that was developed and implemented into WARP3D. Solutions of the A parameter were obtained for remote tension loading conditions that started with small-scale yielding and continued into the large-scale plasticity regime. The results indicate that the methodology developed can be used to calculate the elastic-plastic J-A parameters for test specimens with a range of crack geometries, material strain hardening behaviors, and loading conditions. The J-A parameters were implemented as fracture criteria and used to predict the test results. For comparison, other fracture criteria were used to predict the same test results. Major findings include: The A constraint parameter A varies with specimen type and applied load thus accurate determination is crucial in predicting the failure load, and the A parameter is asymptotic as the failure load is approached, making an accurate determination difficult (i.e., small differences in the A parameter can cause large variations in failure load) for materials exhibiting elastic-plastic behavior. The failure predictions from J-A methodology were more accurate than the traditionally used KC and J methods, and have comparable scatter to that observed when using the crack-tip opening angle (CTOA) method. However, the J-A methodology requires considerable effort (expertise level and labor) to implement and to evaluate the A parameter for different specimen types and materials, or to apply this methodology to part-through crack (e.g., 3D problems) structural applications.

Hamm, Kenneth R., Jr.↗

The Method of Finite Averages: A rigorous upscaling methodology for heterogeneous porous media

Rigorous upscaling techniques offer accurate and computationally-efficient strategies for modeling the average behaviors of multi-physical, multiscale phenomena in geological porous media. However, such techniques often rely on a variety of methodological assumptions that prohibit their rigorous application to practical systems (e.g., systems involving heterogeneous porous media, system-scale boundary conditions, and fine-scale dynamics that are not diffusion-dominant). In this work, we aim to formulate an upscaling methodology with few methodological assumptions to provide high levels of model generality and foster the utilization of rigorously-derived upscaled models in practice. In particular, we introduce the Method of Finite Averages (MoFA), a novel upscaling methodology for rigorously modeling heterogeneous porous media and system-scale boundary conditions. We then detail MoFA’s implementation for the advective–diffusive transport of a single species and compare the methodology with classic numerical techniques, as well as other rigorous upscaling techniques, to highlight MoFA’s unique combination of rigor and generality. We then validate the derived model while demonstrating its benefits in three numerical experiments. The results suggest that (1.) the applicability and a priori error guarantees of MoFA models do not directly depend on system geometry, (2.) a model’s applicability and error guarantees can be can arbitrarily expanded and reduced, respectively, with further computational expense, and (3.) downscaling with MoFA provides an efficient strategy for generating accurate pore-scale solutions from upscaled results. Ultimately, the results evidence that upscaled models can be rigorously derived for heterogeneous porous media systems and resolved in a fraction of the time it takes to perform the equivalent pore-scale simulations.

58 GEOSCIENCES↗

Multicriterion benefit evaluation methodology for safety enhancements in nuclear power plants and application for FLEX strategies

Here we propose a multicriterion benefit evaluation (MCBE) methodology for evaluating costs and benefits of implementing safety enhancements in nuclear power plants. The MCBE methodology establishes a comprehensive evaluation scope using multiple evaluation criteria (including public risk, occupational risk, plant revenue, and plant cost) and multiple contexts (including plant normal operations, incidents, and accidents). The MCBE methodology formulates a benefit or cost element as the product of a monetary consequence and its occurrence-likelihood change. The MCBE methodology also incorporates a decision maker’ preferences toward occurrence likelihood and monetary consequence into cost and benefit estimations through a modified usage of cumulative prospect theory. This paper applies the MCBE methodology to the implementation of diverse and flexible coping strategy (FLEX) in a generic nuclear power plant as an illustrative example. The FLEX benefits are evaluated through three types of influence paths: plant safety enhancement, risk-informed activities, and potential additional credit of FLEX in supporting plant operation and maintenance-efficiency improvement. The benefit-to-cost ratio (BCR) of FLEX implementation is calculated. Sensitivity analyses are conducted to examine the impacts of modeling assumptions and input parameter values on the BCR.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Utility Sector Impacts of Reduced Electricity Demand: Updates to Methodology and Results

This report presents revisions to the methodology for estimating the utility sector impacts associated with electricity demand reductions, first published in our 2014 study. The earlier report described how to calculate utility impact factors based on data from the Energy Information Agency's Annual Energy Outlook (AEO) projections of electricity supply and demand. The 2014 methodology relied on data from the AEO Reference case, and side cases implementing demand-side policies with a substantial impact on total demand. Beginning in 2015, the AEO publication schedule was revised to limit the number of side cases published with each AEO, and no suitable demand-focused side cases have been released since 2014. Hence, this paper presents a generalization of the methodology that allows a uniform approach irrespective of the nature of the side cases published with the AEO. The impact factors we calculate represent coeffcients of variation between a unit reduction to site electricity demand and corresponding supply-side changes, including reductions to electric power generation and primary fuel consumption by fuel type, emissions of criteria pollutants (Hg, NO x and SO 2 ) and greenhouse gases (CO 2 , N 2 O and CH 4 ), and total installed capacity by plant type. The impact factors are time-dependent, and also depend on the demand sector and end use. In this report, we apply the methodology to all AEO publications from 2014-2019, and all scenarios. We quantify the variation in factors across different side cases within each AEO, and across different AEO publications, and compare this to the variation due to changes in methodology.

24 POWER TRANSMISSION AND DISTRIBUTION↗