The effect of communication quality on team performance in digital main control room operations

A team of operators is required for nuclear power plant operation, and communication between the operators is an important aspect of the team's ability to successfully carry out tasks. It has been difficult to evaluate the quality of this communication though, and as the relationship between communication quality and team performance has yet to be clarified, it has not been applied to most human reliability analysis (HRA) methodologies. This study investigates the relationship between the quality of communication and team performance using data from a full-scope training simulator of a digital main control room (MCR). Two important characteristics of communication were considered to determine quality: each operator's ability to self-confirm the status of a given task in a digital MCR, and the type of communication, as divided into 1-way, 2-way, and 3-way between operators. To measure team performance, the concept of an unsafe act was employed, which is defined as a human error that has the potential to negatively affect plant safety. Analysis results showed that the communication quality and team performance were related to each other. With this more clearly defined relationship, the results of this study can be applied to related performance shaping factors to improve HRA. (C) 2019 Korean Nuclear Society, Published by Elsevier Korea LLC

Use of a big data analysis technique for extracting HRA data from event investigation reports based on the Safety-II concept

The safe operation of complex socio-technical systems including NPPs (Nuclear Power Plants) is a determinant for ensuring their sustainability. From this concern, it should be emphasized that a large portion of safety significant events were directly and/or indirectly caused by human errors. This means that the role of an HRA (Human Reliability Analysis) is critical because one of its applications is to systematically distinguish error-prone tasks triggering safety significant events. To this end, it is very important for HRA practitioners to access diverse HRA data which are helpful for understanding how and why human errors have occurred. In this study, a novel approach is suggested based on the Safety-II concept, which allows us to collect HRA data by considering failure and success cases in parallel. In addition, since huge amount of information can be gathered if the failure and success cases are simultaneously involved, a big data analysis technique called the CART (Classification And Regression Tree) is applied to deal with this problem. As a result, it seems that the novel approach proposed by combining the Safety-II concept with the CART technique is useful because HRA practitioners are able to get HRA data with respect to diverse task contexts

Transient Diagnosis and Prognosis for Secondary System in Nuclear Power Plants

This paper introduces the development of a transient monitoring system to detect the early stage of a transient, to identify the type of the transient scenario, and to inform an operator with the remaining time to turbine trip when there is no operator's relevant control. This study focused on the transients originating from a secondary system in nuclear power plants (NPPs), because the secondary system was recognized to be a more dominant factor to make unplanned turbine-generator trips which can ultimately result in reactor trips. In order to make the proposed methodology practical forward, all the transient scenarios registered in a simulator of a 1,000 MWe pressurized water reactor were archived in the transient pattern database. The transient patterns show plant behavior until turbine-generator trip when there is no operator's intervention. Meanwhile, the operating data periodically captured from a plant computer is compared with an individual transient pattern in the database and a highly matched section among the transient patterns enables isolation of the type of transient and prediction of the expected remaining time to trip. The transient pattern database consists of hundreds of variables, so it is difficult to speedily compare patterns and to draw a conclusion in a timely manner. The transient pattern database and the operating data are, therefore, converted into a smaller dimension using the principal component analysis (PCA). This paper describes the process of constructing the transient pattern database, dealing with principal components, and optimizing similarity measures

Numerical and experimental study of air containment systems in legacy data centers focusing on thermal performance and air leakage

With the increasing awareness of data center cooling and its impact on energy costs, hot-aisle containment (HAC) and cold-aisle containment (CAC) are considered vital techniques for IT environment control. Common data center cooling problems, which include air bypass and recirculation, are crucial to airtightness. The air leakage in an air containment is typically 10% or less. However, in practice, containment systems cannot guarantee complete airtightness, and do not function in the intended manner. In this study, both numerical and experimental studies were conducted to investigate the thermal performance of two systems. We found that there are operational differences that are significant factors influencing the amount of air leakage within the air containment systems. With an air leakage rate of 15%, the numerical simulation results show that selecting HAC, over CAC, can improve the thermal performance by 24.9%, corresponding to a 5.2% reduction in the return temperature index. The field measurements also show that HAC is more effective in cooling IT equipment. The supply air temperature of HAC can be raised by 2.0 °C; however, the IT operation environment will be similar to that of CAC. With an operational condition of high air leakage rate, HAC exhibits better thermal performance than CAC

Development of zero energy flexible unit with no Infrastructure for disaster and disaster response

In this paper a new kind of unit-prefabricated building is shown. The unit-prefabricated buildings are made up living unit, energy unit, water unit. The each unit was adapted new combine structure function as a high flexible design type. Moreover the design trend implemented the energy insulation, Solar PV panels, Energy storage system which are maintained for zero energy buildings. We made a prototype for zero energy flexible residential unit. The first step, we was evaluated physical performance and living environment, insulation, airtightness, thermal environmental, acoustic performance. The second step we was evaluated energy performance building to design heating and cooling system to combined PV, ESS system in the different plan type, and climate. As a results, The insulation performance wall was 0.18 W/(m2•K). The results of air-tightness was 12.13 ACH@50 (1/h). Further research we develop the structure and construction technology for zero energy flexible unit. To designed the high performance energy performance for zero energy building in the natural disaster

MEASURING THE INFLUENCE OF TASK COMPLEXITY ON HUMAN ERROR PROBABILITY: AN EMPIRICAL EVALUATION

A key input for the assessment of Human Error Probabilities (HEPs) with Human Reliability Analysis (HRA) methods is the evaluation of the factors influencing the human performance (often referred to as Performance Shaping Factors, PSFs). In general, the definition of these factors and the supporting guidance are such that their evaluation involves significant subjectivity. This affects the repeatability of HRA results as well as the collection of HRA data for model construction and verification. In this context, the present paper considers the TAsk COMplexity (TACOM) measure, developed by one of the authors to quantify the complexity of procedure-guided tasks (by the operating crew of nuclear power plants in emergency situations), and evaluates its use to represent (objectively and quantitatively) task complexity issues relevant to HRA methods. In particular, TACOM scores are calculated for five Human Failure Events (HFEs) for which empirical evidence on the HEPs (albeit with large uncertainty) and influencing factors are available – from the International HRA Empirical Study. The empirical evaluation has shown promising results. The TACOM score increases as the empirical HEP of the selected HFEs increases. Except for one case, TACOM scores are well distinguished if related to different difficulty categories (e.g., “easy” vs. “somewhat difficult”), while values corresponding to tasks within the same category are very close. Despite some important limitations related to the small number of HFEs investigated and the large uncertainty in their HEPs, this paper presents one of few attempts to empirically study the effect of a performance shaping factor on the human error probability. This type of study is important to enhance the empirical basis of HRA methods, to make sure that 1) the definitions of the PSFs cover the influences important for HRA (i.e., influencing the error probability), and 2) the quantitative relationships among PSFs and error probability are adequately represented

Investigation on the energy and air distribution efficiency with improved data centre cooling to support high-density servers

Cooling has become a key issue in data centers where cooling accounts for about 40% of total energy usage. This study evaluated the energy and thermal performance of two data center cooling approaches: row-based cooling and room-based cooling. This research examines the temperature and humidity distribution and air distribution efficiency of an IT environment using field measurements and six performance indices. According to the observations and index evaluation results, we suggest that a row-based cooling strategy is more efficient for server cooling. Air management helps to reduce cooling energy by enhancing optimal operation and improving cooling system efficiency