Researchers within Idaho National Laboratory’s Risk-Informed Decisions division study the interaction between human and machines to determine how that relationship can be improved in order to enhance performance and reduce safety hazards and risks. It is comprised of researchers who study human factors, design control systems and gather and analyze statistical data. Those issues have long been studied by INL and have been melded into a single division within the laboratory to foster better collaboration. The division’s goal is to study human-machine interactions from a variety of angles and approaches to produce advanced systems that are intuitive and user friendly. The three distinct areas of technical expertise in this department (human factors, instrumentation and controls and statistics), can work collectively on projects that require a diversity of talent, including the design and empirical testing of next generation nuclear power plant control rooms, the life extension of existing commercial nuclear power plants, and the evaluation of the human contributions to risk in probabilistic assessment.
INL controls researchers provide instrumentation and control engineering, software engineering, programming, modeling, real-time computer applications/systems, and nuclear facility engineering services to organizations within the lab, DOE, and other U.S. government agencies.
Their specific areas of expertise include:
- Commercial nuclear power plant I&C design, evaluation, setpoint analysis, licensing, plant thermal performance assessment, commissioning and test programs, root-cause failure analysis, reactor engineering, and integrated plant operation evaluation and transient evaluation and analysis
- Real-time and embedded computer system design and development
- Industrial control system and data acquisition system design and development
- Database systems design and development for plant/instrument/engineering databases
- HMI design and development
- Programming in ladder logic, Fortran, C++, Java, Perl, LabVIEW and LabWindows/CVI Unix and Windows system administration
- Electrical/Electronic engineering related to instrumentation, control, data acquisition, and database systems
- Discrete-event modeling for existing and proposed facilities and processes
INL researchers have studied and developed innovative and more intuitive ways for operators to utilize machinery and control systems for more than 25 years. Preventing mishaps and accidents requires the application of knowledge of humans in system design to advance the art of technological systems. This requires a thorough understanding of human behavior, equipment functions and failures, and past events. INL’s approach has been to develop technology for humans rather than trying to mold humans to technology.The human factors group is opening a new laboratory in the Center for Advanced Energy Studies where it can conduct human-centered simulation research for the development, demonstration, and deployment activities designed to improve the performance, safety, and resilience of systems and people in complex and high-risk environments.
This group provides statistical design, statistical analysis and reliability analysis services to a variety of organizations inside the lab and several federal agencies. Researchers provide key support to major projects including the Next Generation Nuclear Plant (NGNP) by ensuring data is qualified through verification and validation and then extensively analyzing that information to model trends, predict future behavior and quantify statistical variation.They are currently building and maintaining the NGNP Data Management and Analysis System (NDMAS), which provides fuel and material data storage, qualification and delivery of analysis information for fuel and materials irradiation experiments underway or planned for the project. NDMAS allows NGNP team members to access the data by experimental information, review it, obtain analysis results and create documents and slide presentations. However, this Web-based system can also be tailored to fit other agencies’ or groups’ needs.