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At least 199 records · Page 11

Rancor-HUNTER: Using a Simulator Engine for Realistic Human Performance Modeling of Nuclear Power Operations

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a software system to simulate human performance in support of human reliability analysis (HRA) in nuclear power plants. This paper summarizes recent work to integrate HUNTER with a plant simulator, namely the Rancor Microworld Simulator. Rancor is an offshoot of earlier work at Idaho National Laboratory (INL) to support plant modernization. The graphical software tools used to mimic digital human-system interface upgrades at INL’s Human Systems Simulation Laboratory were linked to the Rancor Microworld Simulator, an INL-developed simplified plant model. HUNTER becomes a “virtual operator” coupled to the Rancor simulator, thereby allowing a tight coupling between a digital human twin and a digital twin of the plant. Rancor-HUNTER may be run through Monte Carlo iterations across a dynamic range of performance shaping factors, thereby producing distributions of human performance in terms of procedure paths, errors instantiations, and task durations. This paper overviews the various unique features of Rancor-HUNTER and presents an example run of Rancor-HUNTER for a startup scenario.

99 - GENERAL AND MISCELLANEOUS↗

1-G Human Factors for Optimal Processing and Operability of Ground Systems up to CxP GOP PDR

During the mid stages of design development, up to Constellation Program (CxP) Preliminary Design Review (PDR), the requirements for leveraging I-G human factors for optimizing ground processing of Flight Hardware were mature for levels - 2, 3, 4, and 5. This paper gives an overview of the accomplishments achieved during that time. The main focus of this paper will be on the CxP Ground Operations Project human factors engineering analysis process using a Human Factors Engineering Analysis Tool (HFEAT) for developing the level- 5 requirements effecting the design development of the subsystems for Ground Support System (GSS), and Ground Support Equipment (GSE).

Stambolian, Damon B.↗

Three-Dimensional Engineered High Fidelity Normal Human Lung Tissue-Like Assemblies (TLA) as Targets for Human Respiratory Virus Infections

Unlike traditional two-dimensional (2D) cell cultures, three-dimensional (3D) tissue-like assemblies (TLA) (Goodwin et aI, 1992, 1993, 2000 and Nickerson et aI. , 2001,2002) offer high organ fidelity with the potential to emulate the infective dynamics of viruses and bacteria in vivo. Thus, utilizing NASA micro gravity Rotating Wall Vessel (RWV) technology, in vitro human broncho-epithelial (HBE) TLAs were engineered to mimic in vivo tissue for study of human respiratory viruses. These 3D HBE TLAs were propagated from a human broncho-tracheal cell line with a mesenchymal component (HBTC) as the foundation matrix and either an adult human broncho-epithelial cell (BEAS-2B) or human neonatal epithelial cell (16HBE140-) as the overlying element. Resulting TLAs share several characteristic features with in vivo human respiratory epithelium including tight junctions, desmosomes and cilia (SEM, TEM). The presence of epithelium and specific lung epithelium markers furthers the contention that these HBE cells differentiate into TLAs paralleling in vivo tissues. A time course of infection of these 3D HBE TLAs with human respiratory syncytial virus (hRSV) wild type A2 strain, indicates that virus replication and virus budding are supported and manifested by increasing virus titer and detection of membrane-bound F and G glycoproteins. Infected 3D HBE TLAs remain intact for up to 12 days compared to infected 2D cultures that are destroyed in 2-3 days. Infected cells show an increased vacuolation and cellular destruction (by transmission electron microscopy) by day 9; whereas, uninfected cells remain robust and morphologically intact. Therefore, the 3D HBE TLAs mimic aspects of human respiratory epithelium providing a unique opportunity to analyze, for the first time, simulated in vivo viral infection independent of host immune response.

Goodwin, T. J.↗

Digital Human Modeling

The development of models to represent human characteristics and behaviors in human factors is broad and general. The term "model" can refer to any metaphor to represent any aspect of the human; it is generally used in research to mean a mathematical tool for the simulation (often in software, which makes the simulation digital) of some aspect of human performance and for the prediction of future outcomes. This section is restricted to the application of human models in physical design, e.g., in human factors engineering. This design effort is typically human interface design, and the digital models used are anthropometric. That is, they are visual models that are the physical shape of humans and that have the capabilities and constraints of humans of a selected population. They are distinct from the avatars used in the entertainment industry (movies, video games, and the like) in precisely that regard: as models, they are created through the application of data on humans, and they are used to predict human response; body stresses workspaces. DHM enable iterative evaluation of a large number of concepts and support rapid analysis, as compared with use of physical mockups. They can be used to evaluate feasibility of escape of a suited astronaut from a damaged vehicle, before launch or after an abort (England, et al., 2012). Throughout most of human spaceflight, little attention has been paid to worksite design for ground workers. As a result of repeated damage to the Space Shuttle which adversely affected flight safety, DHM analyses of ground assembly and maintenance have been developed over the last five years for the design of new flight systems (Stambolian, 2012, Dischinger and Dunn Jackson, 2014). The intent of these analyses is to assure the design supports the work of the ground crew personnel and thereby protect the launch vehicle. They help the analyst address basic human factors engineering questions: can a worker reach the task site from the work platform provided; can she or he see the task site; can she or he control tools, which, if dropped, might damage the system? Figure 7.3.1 provides an example of such analysis for a future NASA launch vehicle. [figure 7.3.1 here] In-space systems for operation by astronauts have long been targets for DHM analysis, given the focus on mission success and concerns for astronaut safety. Figure 7.3.2 illustrates the analysis of the design to support astronaut tasks for an International Space Station glovebox. [Figure 7.3.2 here] Use by

Dischinger, H. Charles, Jr.↗

Integration of MSFC Usability Lab with Usability Testing

As part of the Stage Analysis Branch, human factors engineering plays an important role in relating humans to the systems of hardware and structure designs of the new launch vehicle. While many branches are involved in the technical aspects of creating a launch vehicle, human factors connects humans to the scientific systems with the goal of improving operational performance and safety while reducing operational error and damage to the hardware. Human factors engineers use physical and computerized models to visualize possible areas for improvements to ensure human accessibility to components requiring maintenance and that the necessary maintenance activities can be accomplished with minimal risks to human and hardware. Many methods of testing are used to fulfill this goal, such as physical mockups, computerized visualization, and usability testing. In this analysis, a usability test is conducted to test how usable a website is to users who are and are not familiar with it. The testing is performed using participants and Morae software to record and analyze the results. This analysis will be a preliminary test of the usability lab in preparation for use in new spacecraft programs, NASA Enterprise, or other NASA websites. The usability lab project is divided into two parts: integration of the usability lab and a preliminary test of the usability lab.

Cheng, Yiwei↗

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

Data Assessment↗

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

Data Assessment↗

GN&C Engineering Best Practices For Human-Rated Spacecraft Systems

The NASA Engineering and Safety Center (NESC) recently completed an in-depth assessment to identify a comprehensive set of engineering considerations for the Design, Development, Test and Evaluation (DDT&E) of safe and reliable human-rated spacecraft systems. Reliability subject matter experts, discipline experts, and systems engineering experts were brought together to synthesize the current "best practices" both at the spacecraft system and subsystems levels. The objective of this paper is to summarize, for the larger Community of Practice, the initial set of Guidance, Navigation and Control (GN&C) engineering Best Practices as identified by this NESC assessment process.

Dennehy, Cornelius J.↗

GN&C Engineering Best Practices for Human-Rated Spacecraft Systems

The NASA Engineering and Safety Center (NESC) recently completed an in-depth assessment to identify a comprehensive set of engineering considerations for the Design, Development, Test and Evaluation (DDT&E) of safe and reliable human-rated spacecraft systems. Reliability subject matter experts, discipline experts, and systems engineering experts were brought together to synthesize the current "best practices" both at the spacecraft system and subsystems levels. The objective of this paper is to summarize, for the larger Community of Practice, the initial set of Guidance, Navigation and Control (GN&C) engineering Best Practices as identified by this NESC assessment process.

Dennehy, Cornelius J.↗

GN&C Engineering Best Practices for Human-Rated Spacecraft System

The NASA Engineering and Safety Center (NESC) recently completed an in-depth assessment to identify a comprehensive set of engineering considerations for the Design, Development, Test and Evaluation (DDT&E) of safe and reliable human-rated spacecraft systems. Reliability subject matter experts, discipline experts, and systems engineering experts were brought together to synthesize the current "best practices" both at the spacecraft system and subsystems levels. The objective of this paper is to summarize, for the larger Community of Practice, the initial set of Guidance, Navigation and Control (GN&C) engineering Best Practices as identified by this NESC assessment process.

Dennehy, Cornelius J.↗

Postures and Motions Library Development for Verification of Ground Crew Human Factors Requirements

Spacecraft and launch vehicle ground processing activities require a variety of unique human activities. These activities are being documented in a primitive motion capture library. The library will be used by human factors engineering analysts to infuse real to life human activities into the CAD models to verify ground systems human factors requirements. As the primitive models are being developed for the library, the project has selected several current human factors issues to be addressed for the Space Launch System (SLS) and Orion launch systems. This paper explains how the motion capture of unique ground systems activities is being used to verify the human factors engineering requirements for ground systems used to process the SLS and Orion vehicles, and how the primitive models will be applied to future spacecraft and launch vehicle processing.

Stambolian, Damon↗

Performance Support Tools for Space Medical Operations

Early Constellation space missions are expected to have medical capabilities similar to those currently on board the Space Shuttle and International Space Station (ISS). Flight surgeons on the ground in Mission Control will direct the Crew Medical Officer (CMO) during medical situations. If the crew is unable to communicate with the ground, the CMO will carry out medical procedures without the aid of a flight surgeon. In these situations, use of performance support tools can reduce errors and time to perform emergency medical tasks. The research presented here is part of the Human Factors in Training Directed Research Project of the Space Human Factors Engineering Project under the Space Human Factors and Habitability Element of the Human Research Program. This is a joint project consisting of human factors teams from the Johnson Space Center (JSC) and the Ames Research Center (ARC). Work on medical training has been conducted in collaboration with the Medical Training Group at JSC and with Wyle that provides medical training to crew members, biomedical engineers (BMEs), and flight surgeons under the Bioastronautics contract. Human factors personnel at Johnson Space Center have investigated medical performance support tools for CMOs and flight surgeons.

Byrne, Vicky↗

Resilience Modeling in Complex Engineered Systems with Human-Machine Interactions

In recent times, there has been a growing interest in resilience-based design. Resilience-based design operates on the concept that failures and unexpected events will happen, and when they occur, complex engineered systems should be able to operate within acceptable bounds and recover reasonably. Humans can contribute to the resilience of a system by quickly detecting unforeseen events and taking corrective measures. To this effect, researchers have proposed guidelines and design approaches that can help promote human-system resilience. However, there is no early design stage tool to validate if a system is indeed resilient after applying these guidelines and design methods. In this research, we integrate the Human Error and Functional Failure Reasoning (HEFFR) framework into the fmdtools toolkit to enable designers to model the combined (machine, human, and joint) failures, including their propagation and dynamic effects, during early design stages. This integrated tool also allows designers to model the effects of performance shaping factors, team dynamics, and human-machine interactions in systems of systems. A demonstrative example of a remotely operated rover is explored to demonstrate how this approach can be applied to understand resilience in complex engineered systems with human interactions.

Lukman Irshad↗

Establishing Trust in NASA’s Artemis Campaign Computer-Human Interface (CHI) Implementation

The NASA Artemis program will return humans to the Moon. This time, with the help of commercial and international partners, the program's objective is a permanent moon base. The moon base infrastructure, including an orbiting moon station and moon surface assets, will be developed for astronauts to stay for the long haul to learn to live and work on another planet in preparation for an eventual Humans-to-Mars mission. As the roundtrip communication delays increase in deep space exploration, the crew will need more onboard systems autonomy and functionality to maintain and control the vehicle or habitat. These mission constraints will change the current Earth-based spacecraft to ground control support approach that will demand more safe, efficient, and effective Computer-Human Interface (CHI) control. For Artemis, CHI is defined as the elements that the crew interfaces with: audio, video, lighting, and crew controls subsystems. Understanding how CHI will need to evolve to support deep space missions will be critical for the Artemis program--especially crew controls, which is the focus of this paper. How does NASA ensure crew controls are reliable enough to control complex systems and prevent a catastrophic event due to human error--especially when the astronauts could be physiologically and/or psychologically impaired? NASA's approach to mitigating catastrophic hazards in human spaceflight system development such as crew controls, is through a holistic system engineering and Human System Integration methodology that focuses on incorporating NASA's Human-Rating Requirements-that ensures human performance characteristics to control/safely recover the crew from hazardous situations within the human interface design are considered. This paper discusses, at a high level, CHI for the Artemis program. Next, a discussion of what it means to human-rate a space system crew controls and how trust in the human-computer interface begins with the NASA human rating requirements. Finally, a discussion on how systems engineering and the human system integration process ensures that crew control implementation incorporates the NASA human-rating requirements.

artemis↗

How Systems Engineering and Risk Management Defend Against Murphy's Law and Human Error

Systems Engineering and Risk Management processes can work synergistically to defend against the causes of many mission ending failures. Defending against mission ending failures is facilitated by fostering a team that has a healthy respect for Murphy's Law and a team with a of curiosity for how things work, how they can fail, and what they need to know. This curiosity is channeled into making the unknowns known or what is uncertain more certain. Efforts to assure mission success require the expenditure of energy in the following areas: 1. Understanding what defines Mission Success as guided by the customer's needs, objectives and constraints. 2. Understanding how the system is supposed to work and how the system is to be produced, fueled by the curiosity of how the system should work and how it should be produced. 3. Understanding how the system can fail and how the system might not be produced on time and within cost, fueled by the curiosity of how the system might fail and how production might be difficult. 4. Understanding what we need to know and what we need learn for proper completion of the above three items, fueled by the curiosity of what we might not know in order to make the best decisions.

Bay, Michael↗