Structural Supportive Software Tool for Fire PSA

2014 ◽  
Author(s):  
Peter Šimurka ◽  
Ján Procháska
Keyword(s):  
Information System ◽  
Nuclear Power ◽  
Input Data ◽  
Human Error ◽  
Software Tool ◽  
General Purpose ◽  
Model Parameters ◽  
Speed Up ◽  
L1 And L2

Continually increasing requirements on nowadays full scope PSA L1 and L2 as whole, which is multiplied by importance of specific data for all modes of operation of nuclear power plant, highlight role of input data used in PSA quantification process. This fact also emphasizes the role of capability to process all necessary information to analyze all nuclear plant modes by appropriate way. Even if abovementioned aspects are relevant for all parts of nowadays PSAs, their importance is critical for internal hazards including specific fire analysis. Because internal fire analysis forms one of the most challenging PSA tasks, requiring interdisciplinary work including processing and integration of extensive amount of data in such a way that fire analysis results are fully consistent with internal PSA events and can be directly incorporated into PSA project. Application of tailored information system forms one of the ways to speed up analyzing process, enhances manageability and maintainability of particular PSA projects and provides effective reporting mean to document process of work as well as traceable and human readable documentation for customers. Such information system also allows implementing rapid changes in processing input data and reduces the risk of human error. Usage of information systems for modification of input data for Living PSA is invaluable. Transparent highly automatized processing of input data allows the analyst to obtain more accurate and better insight to evaluate aspects of particular fire and its consequences. This paper provides brief overview of VUJE approach and experience in this area. The paper introduces general purpose of database developed for PSA needs containing data for relevant PSA structure system and components as well as information relevant for flood and fire analyses. Paper explains as this basic data source is enhanced by adding several relatively independent tiers to employ all common data for fire PSA purpose. Paper also briefly introduces capability of such system to generate integrated documentation covering all stages of fire analyses, covering all screening stages of fire analysis as well as future plans to enhance this part of work in such a way to be capable to build automatic interface between PSA model and fire database to enable PSA model parameters automatic updating and expansion of fires in combinations of initiating events (for example Fire and seismic event).

The Role of Maintenance in Reducing the Risk of Technological Disasters

2021 ◽  
Vol 3 (2) ◽  
pp. 1-7
Author(s):  
Robert G Batson ◽  
Keyword(s):  
Life Cycle ◽  
Nuclear Power ◽  
Human Error ◽  
Human Errors ◽  
Commercial Aviation ◽  
Technological Disasters ◽  
Safety Barriers ◽  
Analysis Scheme ◽  
System Life

In this article, we begin with characterization of technological disasters, emphasizing that human errors in one or more phases of the system life-cycle set the stage for disaster. To counter the unexpected, designers include multiple independent safety barriers capable of preventing the occurrence or mitigating the consequences of such unexpected events. The integrity of the barriers depends on adequate levels of maintenance. Maintenance actions sometimes cause technological disasters, but are shown in large part to prevent malfunctions in technology control systems and safety barriers. We argue that well-planned and executed maintenance actions are key in the reduction of risk of technological disasters. In our research, we reviewed well-documented technological disasters in a variety of organizations such as commercial aviation, nuclear power generation, and petroleum and chemical processing. Using a three-factor cause analysis scheme (human error, equipment or process failure, safety barrier failure) we analyzed twelve disasters and found these factors present in each disaster description. In each analysis, we paid particular attention to the role of maintenance managers and technicians in reducing the risk of disaster. However, maintenance was also a direct causal factor in six of the twelve (50%) disasters analyzed. In addition, we identified the phase of the technological system life-cycle when the disaster occurred.

scholarly journals An Approach to Analyze Diagnosis Errors in Advanced Main Control Room Operations Using the Cause-Based Decision Tree Method

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3832
Author(s):  
Awwal Mohammed Arigi ◽  
Gayoung Park ◽  
Jonghyun Kim
Keyword(s):  
Decision Tree ◽  
Nuclear Power ◽  
Power Plants ◽  
Human Error ◽  
Cognitive Activity ◽  
Emergency Operation ◽  
Nuclear Industry ◽  
Working Environment ◽  
Control Rooms ◽  
Diagnosis Errors

Advancements in the nuclear industry have led to the development of fully digitized main control rooms (MCRs)—often termed advanced MCRs—for newly built nuclear power plants (NPPs). Diagnosis is a major part of the cognitive activity in NPP MCRs. Advanced MCRs are expected to improve the working environment and reduce human error, especially during the diagnosis of unexpected scenarios. However, with the introduction of new types of tasks and errors by digital MCRs, a new method to analyze the diagnosis errors in these new types of MCRs is required. Task analysis for operator diagnosis in an advanced MCR based on emergency operation was performed to determine the error modes. The cause-based decision tree (CBDT) method—originally developed for analog control rooms—was then revised to a modified CBDT (MCBDT) based on the error mode categorizations. This work examines the possible adoption of the MCBDT method for the evaluation of diagnosis errors in advanced MCRs. We have also provided examples of the application of the proposed method to some common human failure events in emergency operations. The results show that with some modifications of the CBDT method, the human reliability in advanced MCRs can be reasonably estimated.

scholarly journals Balanced Sparsity for Efficient DNN Inference on GPU

2019 ◽  
Vol 33 ◽  
pp. 5676-5683 ◽  
Author(s):  
Zhuliang Yao ◽  
Shijie Cao ◽  
Wencong Xiao ◽  
Chen Zhang ◽  
Lanshun Nie
Keyword(s):  
Deep Neural Networks ◽  
General Purpose ◽  
Coarse Grained ◽  
Efficient Computation ◽  
Model Accuracy ◽  
Sparse Model ◽  
Model Inference ◽  
Fine Grained ◽  
Practical Inference ◽  
Speed Up

In trained deep neural networks, unstructured pruning can reduce redundant weights to lower storage cost. However, it requires the customization of hardwares to speed up practical inference. Another trend accelerates sparse model inference on general-purpose hardwares by adopting coarse-grained sparsity to prune or regularize consecutive weights for efficient computation. But this method often sacrifices model accuracy. In this paper, we propose a novel fine-grained sparsity approach, Balanced Sparsity, to achieve high model accuracy with commercial hardwares efficiently. Our approach adapts to high parallelism property of GPU, showing incredible potential for sparsity in the widely deployment of deep learning services. Experiment results show that Balanced Sparsity achieves up to 3.1x practical speedup for model inference on GPU, while retains the same high model accuracy as finegrained sparsity.

scholarly journals Online Simulation of Nuclear Power Plant Primary Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hongyun Xie ◽  
Haixia Gu ◽  
Chao Lu ◽  
Jialin Ping
Keyword(s):  
Information System ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Real Time ◽  
Nuclear Power ◽  
Measurement Data ◽  
Reactor Core ◽  
Power Industry ◽  
Nuclear Power Industry ◽  
Online Simulation

Real-time Simulation (RTS) has long been used in the nuclear power industry for operator training and engineering purposes. And, online simulation (OLS) is based on RTS and with connection to the plant information system to acquire the measurement data in real time for calibrating the simulation models and following plant operation, for the purpose of analyzing plant events and providing indicative signs of malfunctioning. OLS has been applied in certain industries to improve safety and efficiency. However, it is new to the nuclear power industry. A research project was initiated to implement OLS to assist operators in certain critical nuclear power plant (NPP) operations to avoid faulty conditions. OLS models were developed to simulate the reactor core physics and reactor/steam generator thermal hydraulics in real time, with boundary conditions acquired from plant information system, synchronized in real time. The OLS models then were running in parallel with recorded plant events to validate the models, and the results are presented.

scholarly journals The role of renewables in the Japanese power sector: implications from the EMF35 JMIP

2021 ◽  
Vol 16 (2) ◽  
pp. 375-392 ◽  
Author(s):  
Hiroto Shiraki ◽  
Masahiro Sugiyama ◽  
Yuhji Matsuo ◽  
Ryoichi Komiyama ◽  
Shinichiro Fujimori ◽  
...  
Keyword(s):  
Emission Reduction ◽  
Nuclear Power ◽  
Renewable Energies ◽  
Model Intercomparison ◽  
Power Sector ◽  
Capital Costs ◽  
Free Hydrogen ◽  
Intercomparison Project ◽  
Policy Cost

AbstractThe Japanese power system has unique characteristics with regard to variable renewable energies (VREs), such as higher costs, lower potentials, and less flexibility with the grid connection compared to other major greenhouse-gas-emitting countries. We analyzed the role of renewable energies (REs) in the future Japanese power sector using the results from the model intercomparison project Energy Modeling Forum (EMF) 35 Japan Model Intercomparison Project (JMIP) using varying emission reduction targets and key technological conditions across scenarios. We considered the uncertainties for future capital costs of solar photovoltaics, wind turbines, and batteries in addition to the availability of nuclear and carbon dioxide capture and storage. The results show that REs supply more than 40% of electricity in most of the technology sensitivity scenarios (median 51.0%) when assuming an 80% emission reduction in 2050. The results (excluding scenarios that assume the continuous growth of nuclear power and/or the abundant availability of domestic biomass and carbon-free hydrogen) show that the median VRE shares reach 52.2% in 2050 in the 80% emission reduction scenario. On the contrary, the availability of newly constructed nuclear power, affordable biomass, and carbon-free hydrogen can reduce dependence on VREs to less than 20%. The policy costs were much more sensitive to the capital costs and resource potential of VREs than the battery cost uncertainties. Specifically, while the doubled capital costs of VRE resulted in a 13.0% (inter-model median) increase in the policy cost, the halved capital costs of VREs reduced 8.7% (inter-model median) of the total policy cost. These results imply that lowering the capital costs of VREs would be effective in achieving a long-term emission reduction target considering the current high Japanese VRE costs.

scholarly journals USING PROSODY TO PREDICT UPCOMING REFERENTS IN THE L1 AND THE L2

2020 ◽  
pp. 1-28
Author(s):  
Anouschka Foltz
Keyword(s):  
Language Learners ◽  
Second Language Learners ◽  
Exposure Period ◽  
Predictive Processing ◽  
Bilingual Speakers ◽  
Prosodic Cues ◽  
Resource Deficit ◽  
L1 And L2 ◽  
Pitch Accents

Abstract While monolingual speakers can use contrastive pitch accents to predict upcoming referents, bilingual speakers do not always use this cue predictively in their L2. The current study examines the role of recent exposure for predictive processing in native German (L1) second language learners of English (L2). In Experiment 1, participants followed instructions to click on two successive objects, for example, Click on the red carrot/duck. Click on the green/GREEN carrot (where CAPS indicate a contrastive L + H* accent). Participants predicted a repeated noun following a L + H* accent in the L1, but not in the L2, where processing was delayed. Experiment 2 shows that after an exposure period with highly consistent prosodic cues, bilinguals engaged in predictive processing in both their L1 and L2. However, inconsistent prosodic cues showed different effects on bilinguals’ L1 and L2 predictive processing. The results are discussed in terms of exposure-based and resource-deficit models of processing.

scholarly journals The Unusual Role of Pro in Cu(II) Binding by His2-Cyclopentapeptide

2021 ◽  
Vol 22 (12) ◽  
pp. 6628
Author(s):  
Aleksandra Pieniężna ◽  
Aleksandra Kotynia ◽  
Justyna Brasuń
Keyword(s):  
Amino Acid ◽  
Potentiometric Titration ◽  
Amino Acid Residue ◽  
Strong Impact ◽  
Mononuclear Complexes ◽  
Study Results ◽  
Metal Ratio ◽  
Ph Range ◽  
L1 And L2

In this paper, we present findings from studying the interaction of copper(II) ions with the His2-cyclopentapeptide and the role of proline used for the purpose of potentiometric titration and UV-Vis, CD and EPR spectroscopic measurements. Experiments of two homodetic peptides differing by one amino acid residue were conducted for a ligand to metal ratio of 1:1 in the pH range 2.5–11.0. The presented studies reveal that peptides form only mononuclear complexes, and the CuH2L complex appears in the system first (for both L1 and L2). Study results show that the presence of Pro influences the structure of formed complexes and their stabilities and has a strong impact on the efficiency of copper(II) coordination.

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