Chapter 1: Instrumentation and Control System Technical Specifications for LNG Terminals
1.1 Central Control Unit Configuration and Functional Requirements
The central control unit in LNG terminals employs a high-reliability architecture centred on a Distributed Control System (DCS) to meet stringent operational requirements, including process control in extremely low-temperature environments of -162°C and continuous 24/7/365 operation. Major manufacturers worldwide have adopted Yokogawa’s CENTUM VP, Emerson’s DeltaV, and Honeywell’s Experion PKS, all of which feature integrated Safety Instrumented System (SIS) functions compliant with IEC 61508 functional safety standards[1] at the SIL 3 level[2].
The basic configuration of the control unit comprises Field Control Stations (FCS) for distributed control nodes and Human Interface Stations (HIS) for integrated monitoring systems, achieving over 99.99% availability through a redundant configuration. Processing capability requirements include handling more than 10,000 I/O points per second and control calculation cycles of less than 50 milliseconds, with control accuracy improved from conventional ±0.5% to within ±0.1%. Response performance requirements specify achieving the target value within 1 second for BOG pressure control and within 5 seconds for LNG tank pressure control.
Safety functions ensure emergency shutdown operations within 100 milliseconds through digital interlock systems, meeting extremely high reliability standards with a dangerous failure probability of less than 10⁻⁷ per year. Data storage functions record operational data at one-second intervals, utilising integrated historian systems that enable immediate search and analysis of process trends over the past five years.
1.2 Field Instrumentation System Specifications
Field instrumentation for LNG terminals requires special specifications for long-term stable operation in extreme low-temperature environments, ranging from -196°C to ambient temperature, and high-pressure conditions. Major instrumentation manufacturers, including Endress+Hauser, Emerson Rosemount, Azbil, and Yokogawa, have developed ultra-low temperature sensors specifically for LNG applications.
For pressure measurement, Emerson’s Rosemount 3051S series is adopted as the industry standard, achieving high accuracy of ±0.025% and 200:1 range-down capability. The all-welded, sealed stainless steel design ensures long-term reliability at liquid nitrogen temperatures, achieving a Mean Time Between Failures (MTBF) of over 100,000 hours. For flow measurement, Yokogawa’s vortex flowmeters enable stable measurement from -162°C extreme low temperatures to high temperatures through proprietary vortex detection sensors.
For level measurement, Azbil’s SLX series displacement-type level gauges provide simultaneous measurement of level, interface, and specific gravity through microprocessor integration. Temperature measurement employs platinum resistance thermometers (RTDs) with Pt100 accuracy of ±0.1°C, while thermocouples utilise special alloy types compatible with ultra-low temperatures.
Table 1-1: Major Field Instrumentation Specifications
| Instrument Type | Accuracy | Operating Temperature Range | Response Time | MTBF |
| Pressure Transmitter | ±0.025% | -196°C to +85°C | <100ms | 100,000h |
| Vortex Flowmeter | ±0.75% | -196°C to +400°C | <1s | 80,000h |
| Level Transmitter | ±0.25% | -196°C to +200°C | <200ms | 120,000h |
| Temperature Sensor | ±0.1°C | -200°C to +600°C | <5s | 150,000h |
1.3 Control Signal and Communication System Specifications
Control communication systems at LNG terminals are transitioning from conventional 4-20mA analogue signals to digital fieldbus communications, including HART, Foundation Fieldbus, and PROFIBUS. The HART (Highway Addressable Remote Transducer) protocol enables gradual digitalisation by superimposing digital communication over existing 4-20mA wiring and is currently the most widely adopted technology.
Foundation Fieldbus enables bidirectional communication with up to 31 devices via a low-speed bus (H1) at 31.25 kbps, providing PID control functions at the field device level. PROFIBUS enables high-speed communication of up to 12 Mbps and large-capacity data transmission of up to 244 bytes per frame, efficiently processing complex diagnostic information and parameter settings. Yokogawa’s DCS manages all these communication protocols uniformly through EDDL (Electronic Device Description Language) based on ISA-104 standards.
Network configuration enhances cybersecurity through the three-layer separation of the control network, information network, and safety network. The control network is based on Ethernet/IP, achieving data transmission delays of under 1 millisecond with a redundant configuration, thereby eliminating single points of failure. Wireless communication safely enables communication with mobile equipment and remote facilities through the ISA100.11a protocol, allowing for the long-term operation of battery-powered sensors.
Communication system diagnostic functions monitor the operational status of field devices, wiring integrity, and communication quality in real-time, providing data for preventive maintenance. Through Endress+Hauser’s Raman spectroscopy technology and Emerson’s integrated device management software, PRM, integrated data management systems are constructed, spanning from LNG composition measurement to field device diagnostics. These technologies enable LNG terminal control systems to evolve from simple supervisory control to advanced integrated control platforms, achieving predictive maintenance and optimal operations.
Chapter 2: Rationality of Control System Selection for LNG Terminals
2.1 Superiority of DCS+ESD+F&G Integrated Systems
The worldwide standard adoption of Distributed Control System (DCS), Emergency Shutdown system (ESD), and Fire & Gas detection system (F&G) combinations for LNG terminal control system configuration is based on operational requirements specific to LNG terminals and technical rationality. This configuration demonstrates an overwhelming superiority over SCADA (Supervisory Control and Data Acquisition) systems, which are widely adopted in other industrial fields for LNG terminals.
The most significant characteristic of DCS+ESD+F&G integrated systems is the complete integration of control and monitoring functions. Latest DCS systems, including Yokogawa CENTUM VP, Emerson DeltaV, and Honeywell Experion PKS, offer comprehensive process control, data collection, monitoring, and display capabilities, as well as alarm management and history storage, all on a single platform. This integrated approach realises basic process control, including BOG control, level control, temperature management, and pressure control, alongside comprehensive operational monitoring on the same system.
Integration with ESD systems ensures seamless control continuity from normal operational process control to emergency safety assurance through high-reliability safety functions at SIL 3 level, closely integrated with the DCS. F&G systems similarly transmit gas leak detection and fire detection information to DCS in real-time, executing automatic process control adjustments and emergency responses. This three-system integration achieves the high safety and operational continuity required for LNG terminals on a single control platform.
2.2 Functional Comparison Analysis with SCADA Systems
SCADA systems are specialised for integrated monitoring and higher-level management functions of geographically distributed facilities, demonstrating effectiveness in wide-area infrastructure fields such as pipeline monitoring, power system management, and water/wastewater management. However, for compact single-site facilities like LNG terminals, SCADA’s characteristic functions do not provide decisive advantages in control system selection.
Table 1: DCS vs SCADA Functional Comparison
| Function Item | DCS | SCADA |
| Process Control Function | ◎ High-precision real-time control | △ Basic setpoint changes only |
| Monitoring/Display Function | ◎ Integrated HMI and trend display | ◎ Advanced monitoring and diverse displays |
| Data Collection/Storage | ◎ High-speed data processing for control | ◎ Large-capacity long-term data management |
| Alarm Management | ◎ Control-linked alarm processing | ◎ Advanced alarm analysis |
| Communication Function | ○ Control-dedicated high-speed communication | ◎ Diverse protocol support |
| System Expandability | △ Manufacturer-dependent configuration | ◎ Versatility and flexibility |
| Geographic Distribution Support | △ Limited to same site | ◎ Wide-area distributed system support |
| Real-time Performance | ◎ Millisecond-level response | ○ Second-level response |
| Safety Function Integration | ◎ Direct SIS/ESD integration | △ External system coordination |
| Operations & Maintenance Efficiency | ◎ Single vendor system | △ Multiple system management |
This comparative analysis clearly shows DCS’s overwhelming superiority in process control functions, real-time performance, and safety function integration, which are most critical for LNG terminals. Meanwhile, SCADA’s strengths in geographic distribution support and communication protocol diversity have low importance for LNG terminal operational requirements.
From a functional overlap perspective, monitoring/display functions, data collection/storage functions, and alarm management functions provided by DCS completely overlap with SCADA’s main functions. Additional SCADA implementation for LNG terminals would result in redundant investment, lacking economic rationality, given the existing DCS functions.
2.3 LNG Terminal-Specific Requirements and Optimal Solutions
LNG terminal operating environments have fundamentally different characteristics from those of distributed infrastructure systems, where SCADA demonstrates its effectiveness. First, LNG terminals are geographically compact, single-site facilities with all equipment concentrated within a few square kilometres. All facilities can be viewed from the integrated control room, achieving sufficient operational efficiency through DCS centralised control.
Second, LNG terminals require millisecond-level high-speed response for -162°C ultra-low temperature process control, which is vital for safe operations. BOG pressure control, rollover prevention control, and cryogenic pump protection control require response within 100 milliseconds from control command to execution. DCS high-speed control networks fully satisfy this requirement, whereas SCADA’s second-level response complicates safety assurance.
Third, from an operations and maintenance efficiency perspective, the DCS+ESD+F&G configuration enables integrated maintenance under single-vendor systems, achieving a maintenance system efficiency that supports 24/7/365 operations. Additional SCADA in multiple system configurations inevitably increases the operational burden, including inter-vendor system coordination failure risks, the need for more maintenance personnel, and increased troubleshooting complexity.
Fourth, from an investment efficiency perspective, the DCS+ESD+F&G configuration simultaneously achieves initial investment optimisation and minimises operating costs. Additional SCADA implementation can lead to a reduction in investment efficiency due to functional overlap, increased license costs, and escalated maintenance costs, ultimately harming LNG terminal economics.
These analysis results clearly demonstrate that the DCS+ESD+F&G integrated configuration is the optimal solution, satisfying technical, economic, and operational rationality, for the selection of an LNG terminal control system. SCADA system’s excellent functions have no opportunity to demonstrate advantages for LNG terminal’s special operational requirements. This control system selection rationality is also supported by actual performance at LNG terminals worldwide, and this configuration will certainly continue as the standard choice.
Chapter 3: Control Challenges and Operational Optimisation Requirements for LNG Terminals
3.1 LNG Terminal-Specific Control Challenges
LNG terminal operational control faces unique challenges that are fundamentally different from those of conventional chemical plants or petroleum refineries. The most prominent characteristic is handling -162°C ultra-low temperature fluids and controlling complex physical phenomena involving gas-liquid phase changes.
The first control challenge is addressing BOG (Boil-Off Gas) generation uncertainty and dynamic variation response. LNG in tanks continuously evaporates due to external heat intrusion, with generation volumes varying significantly based on meteorological conditions, receiving volumes, and storage levels. Particularly during typhoons or extreme heat, BOG generation exceeds predictions, showing limitations in the existing control system tracking capability. Additionally, BOG surge phenomena accompanying rapid liquid level changes during ship unloading place high demands on control system response speed and accuracy.
The second challenge is predicting and controlling thermal-fluid instabilities represented by rollover phenomena[3]. LNG layer formation with density differences cannot be visually confirmed, requiring the detection of abnormalities from minute temperature and density changes. Conventional single-point temperature measurement makes overall layering assessment difficult, requiring distributed sensing and advanced analysis algorithms. CFD simulation results, which show sudden BOG generation after 130 hours, clearly demonstrate the importance of precursor detection.
The third challenge is ensuring the reliability of instrumentation in ultra-low-temperature environments. In the extreme climate of -162°C, phenomena that do not occur at ambient temperatures affect control accuracy, including changes in sensor characteristics, embrittlement of wiring materials, and shrinkage of seal materials. Particularly, zero drift[4] in level gauges and flowmeters becomes a critical issue, undermining the foundations of material balance management.
3.2 Operational Risks and Critical Control Points
Operational risks at LNG terminals require strict management from both safety and economic perspectives. Critical Control Points in control represent key control functions for minimising these risks.
The most critical management point related to safety is monitoring and controlling flammable gas concentrations. Leaks or abnormal accumulation in BOG processing systems directly connect to explosion risks. Particularly around compressors and flare systems, automatic shutoff functions linked to gas detection systems are essential. Triple protection by SIL3-level safety instrumented systems is based on a design philosophy that prevents loss of safety function due to single failures.
From operational continuity perspectives, predictive maintenance of major equipment becomes a critical management point. Continuous monitoring of control parameters directly connected to equipment maintenance is required, including BOG compressor vibration monitoring, cryogenic pump bearing temperature management, and vaporiser heat transfer performance monitoring. Particularly for IHI-manufactured BOG compressors with 246 delivery records, thermal stress management through ultra-low temperature direct suction holds the key to operational stability.
Economic risk management establishes energy efficiency optimisation as an essential control objective. Power reduction effects (33% at 2.0MPa, 57% at 7.5MPa) demonstrated by Osaka Gas’s thermal storage BOG re-liquefaction system represent specific examples of economic effects through control optimisation. However, realising such high-efficiency operations requires dynamic optimisation control for load variations, with limitations in conventional steady-state control.
Furthermore, environmental impact management also becomes a critical control challenge. Balanced control between environmental regulation compliance and operational efficiency is required, including minimising BOG vent release, maximising cold energy recovery efficiency, and managing discharge water temperature. These multi-objective optimisation problems are complex to solve with single control loops, requiring integrated approaches.
3.3 Efficiency Requirements and Need for Integrated Control Technology
Modern LNG terminals face advanced efficiency requirements that go beyond conventional assurance of safe operation. This background requirement includes the intensification of LNG market competition, the implementation of carbon-neutral policies, and the advancement of digitalisation technology.
The first efficiency requirement is minimising energy consumption. LNG terminal power consumption accounts for a significant portion of operating costs, with annual cost reductions of hundreds of millions of yen possible through optimisation of BOG processing, pump power, and vaporiser auxiliary heating. However, these facilities are interrelated, making overall optimisation unachievable through individual optimisation. For example, reducing the BOG compressor operating unit leads to power cost reduction but may affect downstream pressure fluctuations and quality management.
The second requirement addresses the challenges of reducing operator workload and skill inheritance. The retirement of skilled operators makes the inheritance of tacit knowledge-dependent operational know-how difficult. AI and digital twin operational support systems are expected as solutions to this challenge, requiring accurate modelling of LNG terminal complex control characteristics.
The third requirement is predictive maintenance and equipment life extension. Unplanned shutdowns result in enormous opportunity losses, making the shift to planned maintenance through precursor detection a priority. Integration of condition monitoring data, including vibration analysis, thermal imaging diagnostics, and oil analysis, with control systems is required, along with efforts to reduce equipment loads through operating condition optimisation.
To simultaneously satisfy these diverse and complex requirements, transitioning from conventional individual control systems to integrated control technology is essential. Integrated control technology combines advanced control methods, including real-time optimisation, predictive control, and adaptive control, to realise coordinated control of entire plants. Latest control platforms, including Yokogawa CENTUM VP, Emerson DeltaV, and Honeywell Experion PKS, provide foundational technologies for such integrated control.
The core of integrated control technology is multi-objective optimisation algorithms and adaptive functions through machine learning. Dynamic adjustment of control objectives, which simultaneously considers safety, economics, and environmental performance, requires the capability to autonomously search for optimal solutions against changes in operational conditions. Through this realisation, LNG terminals can evolve into true smart plants, establishing sustainable operational foundations.
Chapter 4: Realising Operational Performance Improvement Through Integrated Control Technology
4.1 Integrated Control Architecture Design
Realising operational performance improvement through integrated control technology requires a new architecture, developing conventional hierarchical control systems. This integrated control architecture is based on a three-layer structure, comprising a real-time control layer, an optimisation control layer, and a prediction/learning layer, which achieves overall optimal control through information coordination between layers.
The real-time control layer incorporates integrated control functions while maintaining a 99.99% high availability, leveraging existing DCS systems, including Yokogawa CENTUM VP and Emerson DeltaV. This layer implements integrated monitoring functions for real-time monitoring of plant-wide material and energy balance alongside basic control loops, including BOG control, rollover prevention control, and insulation circulation control. High-precision measurement data (±0.025% accuracy) from Rosemount 3051S sensors is collected through HART, Foundation Fieldbus, and PROFIBUS integrated communications, realising information sharing across the entire control system.
The optimisation control layer deploys an integrated optimisation engine centred on multi-objective optimisation algorithms. This engine simultaneously optimises economic objectives, including energy cost minimisation, equipment availability maximisation, and maintenance cost minimisation, while satisfying safety, quality, and environmental constraints. Particularly for BOG processing systems, integrated optimisation is executed by dynamically adjusting compressor load distribution, re-liquefaction volume allocation, and flare volume minimisation, while utilising the power reduction effects (33% reduction at 2.0MPa) of Osaka Gas thermal storage systems.
The prediction/learning layer performs plant state prediction and automatic control parameter adjustment through digital twin technology and AI machine learning algorithms. Integrating fluid analysis models based on JGC CFD simulation technology with equipment deterioration prediction models constructed from the operational data of 246 IHI BOG compressors enables the pre-calculated optimal control responses to changes in operational conditions. This prediction information is reflected in lower-layer optimisation control, improving operational stability through preventive control adjustments.
4.2 Real-time Optimisation Control Implementation
Real-time optimisation control, forming the core of integrated control systems, enables the coordinated control of entire plants beyond the constraints of conventional individual control loops. Model Predictive Control (MPC) technology-based multivariable control algorithms play a crucial role in this implementation.
Real-time optimisation for BOG processing systems executes dynamic optimisation integrating tank level changes, meteorological conditions, and demand forecasts. BOG compressor unit numbers, re-liquefaction unit operating modes, and delivery pressure setpoints, conventionally adjusted individually, are coordinately controlled through integrated control algorithms. This results in a reduction of control response time from conventional 30 minutes to 10 minutes for BOG generation volume variations, as well as a 15% improvement in energy efficiency.
Rollover prevention control implements precursor control systems, quantitatively evaluating layering progression through real-time analysis of density distribution monitoring data from distributed temperature sensing. According to management standards, which specify a density difference of 4kg/m³, integrated control systems initiate preventive agitation control at a density difference of 2kg/m³, thereby preventing sudden BOG generation (2,800 Nm³/h) after 130 hours, as predicted by CFD simulation. Agitation energy optimisation reduces preventive control costs by 40% compared to conventional methods while improving safety.
Equipment maintenance integrated control implements predictive maintenance control, integrating vibration monitoring, temperature monitoring, and performance monitoring data. Particularly for BOG compressors, operating condition optimisation, minimising thermal stress from ultra-low temperature direct suction, extends equipment life by 20% and reduces unplanned shutdown rates by 50%. Coordination with SIL3-level safety instrumented systems ensures safety during maintenance work simultaneously.
4.3 Predictive Control and AI Technology Utilisation
The most advanced element of integrated control technology is autonomous optimisation functions fusing AI machine learning technology with predictive control. This technology enables LNG terminals to adapt to operational conditions automatically, achieving continuous performance improvement.
Operational pattern recognition utilising deep learning technology learns seasonal variations, demand variations, and equipment characteristic change patterns from 10 years of operational data, predicting future operational conditions with high accuracy. This prediction information improves the 24-hour forecast accuracy of BOG generation from conventional 70% to 90%, achieving a 5% annual operating cost reduction through planned operation optimisation.
Automatic control parameter adjustment through reinforcement learning algorithms learns optimal control responses from operational performance data, continuously improving control performance. Particularly for vaporiser control, optimal heating control for seawater temperature changes and delivery flow variations reduces energy consumption by 12% while improving delivery temperature stability. Learning algorithms also learn operator operation patterns, providing functions to digitise skilled operator tacit knowledge for next-generation inheritance.
Virtual operation optimisation through digital twin technology evaluates the impacts of control changes in advance through high-precision simulation models synchronised with actual plants. This digital twin is a comprehensive model that integrates fluid analysis based on JGC’s CFD simulation technology, equipment characteristic analysis through IHI’s equipment models, and control response analysis through Yokogawa’s control systems. Optimisation calculations in virtual environments enable advanced verification of risky control changes, significantly reducing trial and error in actual operations.
Through these AI technology integrations, LNG terminal integrated control systems evolve from conventional steady-state operation optimisation to dynamic operation optimisation. Operators are freed from routine monitoring and adjustment work, realising environments that enable concentration on advanced operation strategy formulation and response to abnormal situations. This simultaneously achieves operational quality improvement and effective human resource utilisation, contributing to the enhancement of next-generation LNG terminal competitiveness.
Chapter 5: Future Prospects and Technological Innovation Through Digital Technology
5.1 Digitalisation Vision for Next-Generation LNG Terminals
LNG terminals in the 2030s are expected to evolve into smart energy hubs, achieving fully autonomous operations. The core of this digitalisation vision is decision support systems through artificial intelligence and the digital integration of all facilities through IoT technology.
In next-generation LNG terminals, digital twin technology will significantly transform conventional monitoring and control systems. “Cognitive digital twins,” which fuse real-time physical models with machine learning models, enable complete plant state visualisation and predictive control. This technology enables environments where operators are freed from physical field confirmation and can concentrate on formulating advanced operational strategies in virtual spaces. Particularly for predicting the rollover phenomenon, improved CFD simulation accuracy extends the prediction time from 130 hours to over 200 hours, enabling more comfortable preventive control.
The proliferation of edge computing technology also dramatically advances control response acceleration. High-speed advancements from current 1-second control cycles to 100-millisecond levels enable more precise control responses to BOG generation variations, anticipating further 10-15% improvements in power reduction effects of Osaka Gas thermal storage systems. Additionally, 5G/6G communication technology enables the daily utilisation of advanced operational support from remote specialists, establishing systems that utilise world-class operational technology even at regional LNG terminals.
The utilisation of blockchain technology also significantly improves energy trading transparency and efficiency. Energy efficiency across all processes, from LNG receiving to city gas supply, is recorded in real-time, automating carbon credit trading and the quantitative evaluation of environmental value. Through this technological innovation, LNG terminals expand their roles from simple energy supply bases to centres of environmental value creation.
5.2 Applicability of Emerging Digital Technologies
Quantum computing technology commercialisation holds potential for revolutionary changes in LNG terminal optimisation control. Multi-objective optimisation problems, which are difficult for current classical computers due to calculation time constraints, become instantly solvable through quantum algorithms. Particularly for plant-wide optimisation with thousands of control variables and constraints, quantum advantage is expected to provide over 1000-fold calculation speed improvement.
Augmented Reality (AR) and Virtual Reality (VR) technologies bring significant transformation to operator education and maintenance work efficiency. For the maintenance technology inheritance of 246 IHI BOG compressors, skilled technician know-how is entirely reproduced in VR environments, realising educational systems where new technicians acquire practical skills in a safe virtual environment. Additionally, AR technology enables field workers to access past maintenance histories and optimal work procedures in real-time during Rosemount 3051S sensor inspections, resulting in a 30% improvement in work efficiency.
Control algorithm innovation also advances through the application of biomimetics (bio-inspired technology). Cooperative control of BOG processing systems using swarm intelligence algorithms enables multiple compressors to autonomously cooperate, like biological swarms, thereby realising an overall optimal load distribution. This technology allows for a transition from conventional centralised control to distributed autonomous control, significantly improving system flexibility and fault tolerance.
Brain science technology applications develop neurointerface systems that provide optimal information presentation and decision support through the quantitative measurement of operator cognitive load. Control systems, including Yokogawa CENTUM VP and Emerson DeltaV, provide next-generation human-machine interfaces dynamically adjusting display content according to operator attention states and fatigue levels, minimising human errors.
5.3 Technological Innovation Contribution to Sustainable Operations
Toward the realisation of a carbon-neutral society, LNG terminals will serve as next-generation energy hubs through integration with hydrogen and ammonia co-firing technologies. Integrated control technology realises advanced control, balancing safety and efficiency in mixed fuel supply systems for LNG, hydrogen, and ammonia.
From circular economy perspectives, LNG cold energy utilisation maximisation becomes a significant technological challenge. Integrated cold energy management systems are realised through AI optimisation control, dynamically optimising cold energy distribution for diverse cold energy demands, including data centre cooling, food freezing, and air liquefaction. This technology achieves effective utilisation of over 80% of cold energy conventionally released to seawater, improving regional overall energy efficiency.
From biodiversity protection perspectives, marine environment impact minimisation technology becomes an important innovation area. Environmentally harmonised operating systems, minimising the impact on marine life through machine learning-based marine ecosystem monitoring, and optimised discharge water temperature and flow control based on this monitoring, have been developed. This technology presents new models for LNG terminals, achieving coexistence with local communities.
In technological innovation, social contributions, and disaster-time energy supply continuity capability enhancement have become significant challenges. Distributed control systems and autonomous operation technology enable disaster-resilient performance, maintaining a minimum energy supply even during large-scale disasters, including earthquakes and tsunamis. Additionally, coordination with mobile LNG vaporisation equipment constructs disaster response systems that rapidly deploy emergency energy supplies to disaster areas.
These technological innovations transform LNG terminals from simple fossil fuel processing facilities to core entities of sustainable social infrastructure. Building upon decades of LNG technological development as a foundation, fusion with next-generation digital technologies is expected to realise new energy systems that balance global environmental protection with economic growth. Through this technological innovation, LNG terminals will fulfil higher social missions, contributing to humanity’s sustainable future.
[1] Basic safety standard for functional safety established by the International Electrotechnical Commission (IEC). Specifies requirements ensuring the correct operation of safety functions in electrical, electronic, and programmable electronic systems. Classifies safety performance into four levels through Safety Integrity Levels (SIL1-SIL4), with SIL3 requiring a dangerous failure probability of 10⁻⁷ to 10⁻⁶ per year. Widely adopted in fields requiring high safety, including plants, power stations, and medical equipment, this approach aims to ensure safety throughout product lifecycles through systematic failure countermeasures and random hardware failure countermeasures.
[2] Safety Integrity Level 3 among four levels (SIL1-SIL4). High safety performance level defined by IEC61508 standards requiring probability of failure to perform on demand of less than 10⁻³ to 10⁻⁴ or higher, and dangerous failure probability during continuous operation of 10⁻⁷ to 10⁻⁸ per hour, representing extremely low failure rates. SIL3-level Safety Instrumented Systems (SIS) are applied to emergency shutdown systems and safety valve control to prevent serious accidents, including explosions and fires, at LNG terminals. This is achieved through combinations of redundant design, where single failures do not compromise safety functions, and high-reliability equipment, serving as cornerstones of plant safety.
[3] Phenomena where liquefied natural gas layers with different densities form in LNG storage tanks and suddenly mix, causing rapid generation of large amounts of BOG (boil-off gas). LNG layers with density differences due to composition or temperature differences separate vertically, becoming unstable over time and suddenly agitating. During this process, light components rapidly vaporise, increasing BOG generation to several times to dozens of times normal levels, causing abnormal tank pressure increases and significant safety valve releases. Invisible to the naked eye, requiring distributed temperature sensor density distribution monitoring and CFD simulation predictive control. One of the most critical safety management items for LNG terminals.
[4] Phenomenon where instrument measurement reference points (zero points) gradually drift over time. In LNG terminals, where ultra-low temperature environments of -162°C are encountered, zero points are prone to variation due to thermal contraction of sensor materials, embrittlement of wiring, and deformation of seal materials. For example, 1mm zero point error in level gauges causes thousands of tons of inventory error, while flowmeter errors become unloading/loading quantity measurement errors. These errors directly impact the accuracy of material balance management calculations (receipt quantity – shipment quantity – inventory change = BOG generation), leading to misrecognition of BOG and resulting in economic losses. Addressed through periodic calibration work and high-precision sensor adoption, but long-term stability assurance in ultra-low temperature environments remains an important technological challenge.
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