Sub system & component level safety classification evaluation & identification for tank farm safety systems

Abstract The use of Dynamic Infrared (IR) Imaging is presented as a novel, valuable and non-destructive approach for the analysis and isolation of failures at a system/component level.

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Hanford tank farm safety, monitors found lacking

Chemical & Engineering News ◽

10.1021/cen-v071n009.p022 ◽

1993 ◽

Vol 71 (9) ◽

pp. 22-23

Author(s):

DEBORAH ILLMAN

Keyword(s):

Farm Safety ◽

Tank Farm

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Tank Farm Safety Programmable System Software Management Plan

10.2172/1475170 ◽

2018 ◽

Author(s):

Nicholas Houlbrook

Keyword(s):

Management Plan ◽

Software Management ◽

System Software ◽

Farm Safety ◽

Tank Farm

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DETERMINATION OF MAINTENANCE PRIORITY INDEX (MPI) FOR COMPONENTS ON RSG-GAS SAFETY SYSTEM

JURNAL TEKNOLOGI REAKTOR NUKLIR TRI DASA MEGA ◽

10.17146/tdm.2018.20.2.4283 ◽

2018 ◽

Vol 20 (2) ◽

pp. 77 ◽

Cited By ~ 1

Author(s):

Entin Hartini ◽

Sukmanto Dibyo ◽

Santosa Pujiarta

Keyword(s):

Operating System ◽

Operational Reliability ◽

Safety System ◽

System Component ◽

Priority Index ◽

Reliability Management ◽

Equipment Reliability ◽

Gas System ◽

Safety Systems

Reliability management is an activity to ensure no failure of all equipment when operated. Reliability management can be optimized to minimize costs or eliminate failures and causes. Critical equipment is the condition of a potentially damaging component affecting the operational reliability of the system. The criticality level of each equipment determines its impact on the operating system and the direction of maintenance improvement. The research was conducted on the main system/component of the operating system and performed at the level of reliability improvement. The purpose of this research is to prioritize the reliability of systems and equipment for safety systems using System Equipment Reliability Prioritization (SERP). Determination of component criticality level on reliability management based on category rankings of frequency data and duration of interference with certain criteria as well as system aspects, safety, quality and cost. From the evaluation results it can be concluded that the MPI of the RSG-GAS system/ component for the top 5 if sorted are KBE01 AP-01-02, PA01-02 / CR001, KBE02 AA-01/ AA-02, JE-01 (AP01-02 ) and JNA10 / 20/30 BC001 with MPI values 143,101, 95, 90 and 60.Keywords: Maintenance, priority, index, safety system, RSG-GAS PENENTUAN MAINTENANCE PRIORITY INDEX (MPI) UNTUK KOMPONEN PADA SISTEM KESELAMATAN RSG-GAS. Manajemen keandalan merupakan suatu kegiatan untuk menjamin tidak terjadinya suatu kegagalan pada seluruh komponen saat dioperasikan. Dengan manajemen keandalan dapat dilakukan optimasi untuk meminimumkan biaya atau menghilangkan kegagalan dan penyebabnya. komponen kritis merupakan kondisi suatu komponen yang berpotensi mengalami kerusakan yang berpengaruh pada keandalan operasional sistem. Tingkat kekritisan dari setiap komponen menentukan dampaknya terhadap sistem operasi dan arah penyempurnaan pemeliharaan. Penelitian dilakukan pada sistem/komponen yang utama dari sistem operasi dan dilakukan pada level peningkatan keandalan. Tujuan dari penelitian ini adalah menentukan indeks prioritas pemeliharaan (MPI) untuk peringkat keandalan sitem/komponen pada system keselamatan menggunakan metode System Equipment Reliability Prioritization (SERP). Penentuan tingkat kekritisan komponen pada manajemen keandalan berdasarkan peringkat kategori dari data durasi dan frekuensi gangguan dengan kriteria tertentu serta aspek sistem, keselamatan, kualitas dan biaya. Dari hasil evaluasi dapat disimpulkan bahwa MPI dari sistem/komponen RSG-GAS untuk 5 teratas jika diurutkan adalah: KBE01 AP-01-02, PA01-02 / CR001, KBE02 AA-01 / AA-02, JE-01 (AP01-02) dan JNA10 / 20/30 BC001 dengan nilai MPI berturut turut 143,101, 95, 90 dan 60.Kata kunci: Pemeliharaan, prioritas, indeks, sistem keselamatan, RSG-GAS

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Thermodynamic Modeling and Performance Simulation of Combined Cycle Power Plant Under Design and Off-Design Condition

10.1115/gtindia2021-75827 ◽

2021 ◽

Author(s):

Lalatendu Pattanayak ◽

Biranchi Narayana Padhi ◽

Hemant Gajjar

Keyword(s):

Power Plants ◽

Model Simulation ◽

Performance Comparison ◽

Combined Cycle ◽

System Component ◽

Air Cooling ◽

Component Level ◽

Performance Simulation ◽

Design Performance ◽

And Performance

Abstract Combined cycle power plants (CCPP) are increasingly important for safer and cleaner electricity generation. In this context it is imperative to explore options to enhance its thermal performance for its design and off-design condition. This study presents the performance comparison of two heavy-duty gas turbined (GT) based CCPP with triple pressure steam bottoming cycle. The CCPP system component is modeled using a commercial software Ebsilon and the off-design performance prediction is made using necessary component correlations. The correlations make use of normalized curves that are generated from model runs and apply the factors received from such curve to design performance to estimate the off-design performance. The model simulation is validated against literatures. Furthermore, inlet air cooling technique (IAC) is introduced in this study to enhance the CCPP power production without compromising component performance. The performance comparison of both the CCPP units are presented in an integrated manner by considering interaction of bottoming cycle on GT operation. The results are established as a function of ambient temperature based on energy and exergy principle and the power boosting and economic profit. The results also demonstrate the benefit of IAC on part-load performance. The component level exergy analysis proved that IAC improves the system exergy efficiency.

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Application of Fractional Scaling Analysis to Loss of Coolant Accidents: Component Level Scaling for Peak Clad Temperature

Journal of Fluids Engineering ◽

10.1115/1.4000370 ◽

2009 ◽

Vol 131 (12) ◽

Cited By ~ 2

Author(s):

Ivan Catton ◽

Wolfgang Wulff ◽

Novak Zuber ◽

Upendra Rohatgi

Keyword(s):

Computational Effort ◽

System Level ◽

System Component ◽

Scaling Analysis ◽

Primary System ◽

Component Level ◽

Single Experiment ◽

Pressurized Water ◽

Loss Of Coolant Accident ◽

Loss Of Coolant

Fractional scaling analysis (FSA) is demonstrated here at the component level for depressurization of nuclear reactor primary systems undergoing a large-break loss of coolant accident. This paper is the third of a three-part sequence. The first paper by Zuber et al. (2005, “Application of Fractional Scaling Analysis (FSA) to Loss of Coolant Accidents (LOCA), Part 1. Methodology Development,” Nucl. Eng. Des., 237, pp. 1593–1607) introduces the FSA method; the second by Wulff et al. (2005, “Application of Fractional Scaling Methodology (FSM) to Loss of Coolant Accidents (LOCA), Part 2. System Level Scaling for System Depressurization,” ASME J. Fluid Eng., to be published) demonstrates FSA at the system level. This paper demonstrates that a single experiment or trustworthy computer simulation, when properly scaled, suffices for large break loss of coolant accident (LBOCAs) in the primary system of a pressurized water reactor and of all related test facilities. FSA, when applied at the system, component, and process levels, serves to synthesize the world-wide wealth of results from analyses and experiments into compact form for efficient storage, transfer, and retrieval of information. This is demonstrated at the component level. It is shown that during LBOCAs, the fuel rod stored energy is the dominant agent of change and that FSA can rank processes quantitatively and thereby objectively in the order of their importance. FSA readily identifies scale distortions. FSA is shown to supercede use of the subjectively implemented phenomena identification and ranking table and to minimize the number of experiments, analyses and computational effort by reducing the evaluation of peak clad temperature (PCT) to a single parameter problem, thus, greatly simplifying uncertainty analysis.

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