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At least 19 records

A framework to implement human reliability analysis during early design stages of advanced reactors

Nuclear power plants require human actions throughout their lifecycle from design, construction, operation, and decommissioning. However, for advanced reactors (e.g., Generation IV), the reliance on human intervention in safety-related actions is expected to be reduced or completely replaced by automated actions. The Probabilistic Risk Assessment (PRA) Standard for Advanced Non-LWR Nuclear Power Plants requires that the impacts of all operator actions are captured and incorporated in the risk of the modeled plant. Moreover, the Modernization of Technical Requirements for Licensing Advanced Reactors requires human reliability analysis (HRA) to be included throughout all design and PRA development stages. However, due to the lack of details during the early design stages, HRA is often postponed until the design is mature enough. Conducting HRA in later design stages, though it may be adequate in capturing pre-, at-, and post-initiators comes short of informing the design itself in the iterative design lifecycle. Hence, this paper presents a framework to include HRA during the design's early stages, pre-conceptual or conceptual. The proposed framework provides a process for the removal of operator actions that do not contribute to the risk and the identification of all key operator actions that are critical to the safety of the design. The results of this framework are then used to inform the design of those safety-related operator actions to update the design further. Then, using information from the updated design, this framework can be reapplied to investigate the impact of the design update on human reliability. The PRA model of the X-energy's pre-conceptual Xe-100 high-temperature gas-cooled pebble-bed reactor (HTGR-PB) design is used to demonstrate the approach. In the pre-conceptual Xe-100 PRA model, also called Phase 0 PRA model, human actions were considered an integral part of analyzing the plant response to different initiating events. Hence, in this paper, all possible human actions in the Xe-100 PRA model are identified, analyzed, and removed to emulate a design relying only on the available automated control systems. The preliminary results of this assessment show how safe the Xe-100 design is even without crediting any human actions. The results also list necessary sequences in which operator actions are critical to the risk profile of the design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Can Resilience Assessments Inform Early Design Human Factors Decision-making?

There is a growing call among researchers for tighter coupling between human factors and human reliability assessments. In this research, we explore if early design stage resilience assessments can help bridge some of the gaps between human factors and human reliability assessments. Resilience in systems is their ability to recover reasonably and operate within acceptable bounds during failures and unexpected events. The fmdtools toolkit allows designers to assess the resilience of a system by modeling the human error and machine-related failure propagation in both nominal and faulty scenarios during the early design stages. As a result, the fmdtools toolkit has a low-fidelity dynamic human reliability assessment component built into it. In this paper, we study if the results from the fmdtools simulations can help inform and prioritize human factors design decision-making, resulting in tighter coupling between human factors and human reliability assessments during the design process. Specifically, we explore the results from a rover design example to understand the types of information that can help guide human factor-related decision-making.

Resilience-based Design↗

The Impact of Early Design Phase Risk Identification Biases on Space System Project Performance

Risk identification during the early design phases of complex systems is commonly implemented but often fails to result in the identification of events and circumstances that truly challenge project performance. Inefficiencies in cost and schedule estimation are usually held accountable for cost and schedule overruns, but the true root cause is often the realization of programmatic risks. A deeper understanding of frequent risk identification trends and biases pervasive during space system design and development is needed, for it would lead to improved execution of existing identification processes and methods.

Reeves, John D., Jr.↗

A Framework of Working Across Disciplines in Early Design and R&D of Large Complex Engineered Systems

This paper examines four primary methods of working across disciplines during R&D and early design of large-scale complex engineered systems such as aerospace systems. A conceptualized framework, called the Combining System Elements framework, is presented to delineate several aspects of cross-discipline and system integration practice. The framework is derived from a theoretical and empirical analysis of current work practices in actual operational settings and is informed by theories from organization science and engineering. The explanatory framework may be used by teams to clarify assumptions and associated work practices, which may reduce ambiguity in understanding diverse approaches to early systems research, development and design. The framework also highlights that very different engineering results may be obtained depending on work practices, even when the goals for the engineered system are the same.

McGowan, Anna-Maria Rivas↗

Formal Verification Toolkit for Requirements and Early Design Stages

Efficient flight software development from natural language requirements needs an effective way to test designs earlier in the software design cycle. A method to automatically derive logical safety constraints and the design state space from natural language requirements is described. The constraints can then be checked using a logical consistency checker and also be used in a symbolic model checker to verify the early design of the system. This method was used to verify a hybrid control design for the suit ports on NASA Johnson Space Center's Space Exploration Vehicle against safety requirements.

Badger, Julia M.↗

A Computational Framework for Making Early Design Decisions in Deep Space Habitats

The dynamics of systems of systems often involve complex interactions among the individual systems, making the implications of design choices challenging to predict. Design features in such systems may trigger unexpected behaviors or result in large variations in safety, performance or resilience. To provide a means of simulating such systems for aiding in these decisions, we have developed a prototype tool, the control-oriented dynamic computational modeling tool (CDCM). The CDCM provides rapid simulation capabilities to perform trade studies in systems of systems. The general class of systems of systems that we aim to examine involve multiple hazards, damage, cascading consequences, repair and recovery. We especially focus on systems-of-systems that incorporate a health management system (HMS) that can monitor the state of the habitat and make decisions about actions to take. In this paper we describe the features of the CDCM, the architecture we devised for simulation of systems-of-systems, the unique functionalities of this tool, and we provide a demonstration of the capabilities by performing two illustrative examples. We articulate the use of this tool for making early design decisions and demonstrate its use for trade studies that consider a model of a deep space habitat. We also share some experiences and lessons that may be useful for others seeking to address similar problems.

Amir Behjat↗

Interdisciplinary Interactions During R&D and Early Design of Large Engineered Systems

Designing Large-Scale Complex Engineered Systems (LaCES) such as aircraft and submarines requires the input of thousands of engineers and scientists whose work is proximate in neither time nor space. Comprehensive knowledge of the system is dispersed among specialists whose expertise is in typically one system component or discipline. This study examined the interactive work practices among such specialists seeking to improve engineering practice through a rigorous and theoretical understanding of current practice. This research explored current interdisciplinary practices and perspectives during R&D and early LaCES design and identified why these practices and perspectives prevail and persist. The research design consisted of a three-fold, integrative approach that combined an open-ended survey, semi-structured interviews, and ethnography. Significant empirical data from experienced engineers and scientists in a large engineering organization were obtained and integrated with theories from organization science and engineering. Qualitative analysis was used to obtain a holistic, contextualized understanding. The over-arching finding is that issues related to cognition, organization, and social interrelations mostly dominate interactions across disciplines. Engineering issues, such as the integration of hardware or physics-based models, are not as significant. For example, organization culture is an important underlying factor that guided researchers more toward individual sovereignty over cross-disciplinarity. The organization structure and the engineered system architecture also serve as constraints to the engineering work. Many differences in work practices were observed, including frequency and depth of interactions, definition or co-construction of requirements, clarity or creation of the system architecture, work group proximity, and cognitive challenges. Practitioners are often unaware of these differences resulting in confusion and incorrect assumptions regarding work expectations. Cognitively, the enactment and coconstruction of knowledge are the fundamental tasks of the interdisciplinary interactions. Distributed and collective cognition represent most of the efforts. Argument, ignorance, learning, and creativity are interrelated aspects of the interactions that cause discomfort but yield benefits such as problem mitigation, broader understanding, and improved system design and performance. The quality and quantity of social interrelations are central to all work across disciplines with reciprocity, respectful engagement, and heedful interrelations being significant to the effectiveness of the engineering and scientific work.

McGowan, Anna-Maria Rivas↗

Early Design Choices: Capture, Model, Integrate, Analyze, Simulate

I. Designs are constructed incrementally to meet requirements and solve problems: a) Requirements types: objectives, scenarios, constraints, ilities. etc. b) Problem/issue types: risk/safety, cost/difficulty, interaction, conflict, etc. II. Capture requirements, problems and solutions: a) Collect design and analysis products and make them accessible for integration and analysis; b) Link changes in design requirements, problems and solutions; and c) Harvest design data for design models and choice structures. III. System designs are constructed by multiple groups designing interacting subsystems a) Diverse problems, choice criteria, analysis methods and point solutions. IV. Support integration and global analysis of repercussions: a) System implications of point solutions; b) Broad analysis of interactions beyond totals of mass, cost, etc.

Malin, Jane T.↗

VARED: Verification and Analysis of Requirements and Early Designs

Requirements are a part of every project life cycle; everything going forward in a project depends on them. Good requirements are hard to write, there are few useful tools to test, verify, or check them, and it is difficult to properly marry them to the subsequent design, especially if the requirements are written in natural language. In fact, the inconsistencies and errors in the requirements along with the difficulty in finding these errors contribute greatly to the cost of the testing and verification stage of flight software projects [1]. Large projects tend to have several thousand requirements written at various levels by different groups of people. The design process is distributed and a lack of widely accepted standards for requirements often results in a product that varies widely in style and quality. A simple way to improve this would be to standardize the design process using a set of tools and widely accepted requirements design constraints. The difficulty with this approach is finding the appropriate constraints and tools. Common complaints against the tools available include ease of use, functionality, and available features. Also, although preferable, it is rare that these tools are capable of testing the quality of the requirements.

Badger, Julia↗

Approach for energy efficient building design during early phase of design process

Energy consumption in the building sector is about 40% of total energy consumed globally and is trending upwards, along with its contribution to greenhouse gas (GHG) emissions. Given the adverse impacts of GHG emissions, it is crucial to integrate energy efficiency into building designs. The most significant opportunities for enhancing energy performance are present during the initial phases of building design, when there is less impact of other design constraints. Various tools exist for simulating different design options and providing feedback in terms of energy consumption and comfort parameters. These simulation outputs must then be analyzed to derive design solutions. This paper presents an innovative approach that utilizes user input parameters, processes them through cloud computing, and outputs easily understandable strategies for energy-efficient building design. The methodology employs Asynchronous Distributed Task Queues (DTQ) - a more scalable and reliable alternative to conventional speedup techniques-for conducting parametric energy simulations in the cloud. The goal of this approach is to assist design teams in identifying, visualizing, and prioritizing energy-saving design strategies from a range of possible solutions for each project. Furthermore, a tool ‘eDOT’ has been developed utilizing the discussed methodology. Unlike existing tools, eDOT leverages artificial intelligence to dynamically generate and provide design strategies during the early phases of design process. By simplifying the simulation process, eDOT enables design teams to make informed, data-driven decisions without needing to interpret complex simulation outputs. A case study simulated for two locations is provided in this paper to demonstrate the effectiveness of eDOT, further underscoring its practical impact on energy-efficient building design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Computerized Preliminary Design at the Early Stages of Vehicle Definition

Criteria for acceptance of early design information, modern methods of providing it, and suggestions for defining adequate levels of resources to accomplish the objectives of the activity are described. Specific examples of the most difficult type of early design studies, those requiring significant undeveloped technology, are used to discuss these points. The examples include design studies and cost estimates of liquid hydrogen fueled aircraft, oblique winged aircraft and remotely piloted vehicles.

Gregory, T. J.↗

Evaluation Methodologies for Early Conceptual Design Using Virtual Reality and Physical Test Environments

In this study, human factor design engineers wanted to know, by using subject matter experts (SMEs), if there would be any differences in testing low-fidelity conceptual designs in a physical environment compared to a digital/virtual one. Results indicated that when testing a design concept at this early stage, a high correlation between the two environments exists, meaning SMEs found little to no difference when evaluating a design in either a physical or a digital/virtual environment. There are advantages and limitations to both environments. The virtual world gave the experts a better sense of the microgravity space environment and the relationships of space and human presence that are difficult to simulate in a 1-g physical environment. However, the interaction between human and mechanics is better enhanced in the physical world compared to the virtual world. These advantages and limitations of each environment are important; however, cost is also an important consideration when early design concepts are being used. With the cost analysis of materials, hardware, and labor conducting for this study, virtual reality showed a 68% decrease in cost over the physical mock-up build. Thus, taking all aspects of the study into consideration, at this early design life cycle phase, virtual reality shows great promise as an evaluation environment for testing early design concepts that will cost less, give more options, and increase designer’s time to design.

Harry L. Litaker Jr↗

An Analysis of Risk and Function Information in Early Stage Design

The concept of function offers a high potential for thinking and reasoning about designs as well as providing a common thread for relating together other design information. This paper focuses specifically on the relation between function and risk by examining how this information is addressed for a design team conducting early stage design for space missions. Risk information is decomposed into a set of key attributes which are then used to scrutinize the risk information using three approaches from the pragmatics sub-field of linguistics: i) Gricean, ii) Relevance Theory, and Functional Analysis. Results of this linguistics-based approach descriptively account for the context of designer communication with respect to function and risk, and offer prescriptive guidelines for improving designer communication.

Barrientos, Francesca↗

Modeling Temporal Processes in Early Spacecraft Design: Application of Discrete-Event Simulations for Darpa's F6 Program

While the ability to model the state of a space system over time is essential during spacecraft operations, the use of time-based simulations remains rare in preliminary design. The absence of the time dimension in most traditional early design tools can however become a hurdle when designing complex systems whose development and operations can be disrupted by various events, such as delays or failures. As the value delivered by a space system is highly affected by such events, exploring the trade space for designs that yield the maximum value calls for the explicit modeling of time.This paper discusses the use of discrete-event models to simulate spacecraft development schedule as well as operational scenarios and on-orbit resources in the presence of uncertainty. It illustrates how such simulations can be utilized to support trade studies, through the example of a tool developed for DARPA's F6 program to assist the design of "fractionated spacecraft".

trade space exploration↗

Use of Probabilistic Engineering Methods in the Detailed Design and Development Phases of the NASA Ares Launch Vehicle

The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program called Constellation to send crew and cargo to the international Space Station, to the moon, and beyond. As part of the Constellation program, a new launch vehicle, Ares I, is being developed by NASA Marshall Space Flight Center. Designing a launch vehicle with high reliability and increased safety requires a significant effort in understanding design variability and design uncertainty at the various levels of the design (system, element, subsystem, component, etc.) and throughout the various design phases (conceptual, preliminary design, etc.). In a previous paper [1] we discussed a probabilistic functional failure analysis approach intended mainly to support system requirements definition, system design, and element design during the early design phases. This paper provides an overview of the application of probabilistic engineering methods to support the detailed subsystem/component design and development as part of the "Design for Reliability and Safety" approach for the new Ares I Launch Vehicle. Specifically, the paper discusses probabilistic engineering design analysis cases that had major impact on the design and manufacturing of the Space Shuttle hardware. The cases represent important lessons learned from the Space Shuttle Program and clearly demonstrate the significance of probabilistic engineering analysis in better understanding design deficiencies and identifying potential design improvement for Ares I. The paper also discusses the probabilistic functional failure analysis approach applied during the early design phases of Ares I and the forward plans for probabilistic design analysis in the detailed design and development phases.

Fayssal, Safie↗