predictive self-healing for pneumatic actuated systems
TRANSCRIPT
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Predictive Self-Healing for Pneumatic Actuated Systems
Michael W. KellerA, Rami YounisB, Cem SaricaB, Mahfujul KhanA, Anna WilliamsA, and Nnozuba SomtoB
ADepartment of Mechanical EngineeringBSchool of Petroleum EngineeringThe University of Tulsa
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Project Number FE0031876
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Methane Release from Damaged Systems
• Allen et al.* observed a significant number of anomalous methane releases in pneumatic actuators.
• This project targets 80% reduction of leak rate in those damaged systems.
• Release from damaged systems in the Allen study accounted for 14 million cubic feet of methane/year.
• Milestone goal would reflect a reduction in release by 11 million cubic feet/year for the systems in Allen paper.
2* Allen, Pasci, Sullivan, et al. Environ. Sci. Technol. 49 (2015)
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Pneumatic Controllers/Actuators
• Various models, but diaphragms are in large number of devices
• Damage can lead to direct venting of natural gas
• Proposed approach is intended to be direct retrofit
• Approach allows for “active” repair– Increases healing approach scope– Enables repair of large scale damage
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Self-Healing Diaphragm
Demonstrate automatic detection and repair of a pneumatic actuator in a pilot scale facility
• Synthesize self-healing system• Develop detection model• Build and validate pilot scale test stand
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Synthesize Self-Healing Membrane
• Synthesize self-healing membrane material
• Confirm self-repair in laboratory setting
• Integrate system into commercial pneumatic actuator (PA)
• Confirm self-repair in commercial PA.
Initiator chemical Resin chemical
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Membrane Processing/Synthesis
• Two approaches– Capsule-based repair– Microvascular networks
• Initial focus is polyurethane membrane systems
• Siloxane or acrylic-based healing chemistries are initial targets
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Microvascular Systems
• Based on depolymerization of PLA or other lost-wax approaches
• Channel positive is printed via rapid prototype
• Membrane is cast around positive• Channels are evacuated to provide
circulatory system• Healing chemistry is circulated in channels• Monolithic and multilayered systems will
be investigated
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Capsule-based approaches
• Based on reactive monomer encapsulation
• Effective for small-scale damage• Could be combined with
microvascular approach for multi-scale repair
• Monolithic and multi-layer systems will be perused
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Microvascular Manufacturing
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Design and print
channels
Mold samples
Create hollow
channels
Inject with healing chemistries and
damage
Test and collect data
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Initial Microvascular Material
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Injecting Dye (Air trapped) Cut on surfaceBeginning Specimen
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Preliminary healing demonstration
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Cut on surface Injecting Healing chemistry Healing completed
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Healing Assessment
• Pressure test for leak
• Go/no-go healing determination
• Pre-damaged and pre-healed specimens
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Test Results
• Leak initiation indicates failure of healed damage
• Healing effectiveness currently based on 100% repair
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Inlet Pressure Effect on Healing
• Low inlet pressure improves healing
• 60% of specimens healed when exposed to max inlet pressure
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Data & computation detection system
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CH4
supply & vent
Process flow
Data and controls• Inlet pressure and rate vs time• Level meter setting• Process flow
Idealized Model
Data: 𝑷𝒊𝒏𝒍𝒆𝒕 𝒕Control: 𝑣𝑖𝑛𝑙𝑒𝑡 𝑡
Elastic diaphragm
Data: 𝐲 𝑡
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Numerical simulation system
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𝜌𝜕𝒖
𝜕𝑡− ∇ ⋅ −𝑝𝑰 + 𝜇 ∇𝒖 + ∇T𝒖 + 𝜌 𝒖 − 𝒖𝑚 ⋅ ∇𝒖 = 𝑭 in 𝛺𝑓 × (0, 𝑇)
−∇ ⋅ 𝒖 = 0 in 𝛺𝑓 × (0, 𝑇) 𝒖 𝒙, 0 = 𝒖0 on 𝛺𝑓 × {0}
𝒖 𝒙, 𝑡 = 𝒖𝐷 𝒙, 𝑡 on Γ𝐷𝑓
× (0, 𝑇)
𝝈𝑓 ⋅ 𝒏𝑓 = 𝒕𝑓 on Γ𝑁𝑓
× (0, 𝑇)
𝜌𝑠
𝜕2𝒗
𝜕𝑡2= ∇ ⋅ (𝑭𝑺𝒔) + 𝜌𝑠𝒃
𝑠 in Ωs × (0, 𝑇)
𝒗 𝒙, 0 = 𝒗0 in 𝛺𝑠 × 0 𝜕𝒗
𝜕𝑡= 𝒗 0 𝑖𝑛 Ω𝑠 × 0
𝒗 = 𝒗𝐷 𝑖𝑛 Γ𝐷𝑠 × (0, 𝑇)
𝝈𝑠 ⋅ 𝒏𝑠 = 𝒕𝑠 𝑜𝑛 Γ𝑁𝑠 × (0, 𝑇)
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Validation & robustness
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Applied extreme valve cycling to a prototypical case. Introduced rupture at 1 sec.
Ruptured
Normal
0.1 sec 1 sec 2 sec
Pressure field solutions
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Simulated sampling of dimensionless parameter space
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Scaling analysis produces:• 3 dimensionless groups with design parameters• 2 groups pertaining to controls and state variables
Ongoing work:• Sample parameter space• Identify statistically reliable correlation indicating damage• Apply to test-stand• Apply to flow-loop
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Accomplisments/Summary
• Demonstrated the ability to heal diaphragm materials with microvascular networks
• Initial physical model developed to inform health monitoring
• Moving toward implementation in commercial system
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Lessons Learned
• Research gaps/Challenges– None at this time
• Unanticipated Research Difficulties– Removal of the PLA preform from elastomers was
more complicated than in epoxies.
• Technical Disappointments– None at this time
• Changes that should be made next time– None at this time
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Appendix
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Benefit to the Program
• Reduction of methane release by at least 80%.
• Currently there is no automated repair approach for that is available for pneumatically actuated valves. Additionally, the integrated leak detection approaches are also not well developed and represent a significant advancement in current SCADA technology in its own right. Furthermore, the large-volume self-healing approaches have not been demonstrated in a system that would allow for autonomous or automatic initiation of the healing. Successful demonstration of this integrated system would also represent a forward advancement in the general area of self-healing materials and structures. Finally, the successful demonstration of an integrated self-healing valve system would advance the goal of reduced methane emissions due to damaged or malfunctioning pneumatically actuated valve and control systems.
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Project Overview Goals and Objectives
• Demonstrate the ability to automatically repair pneumatic controllers from a wide range of damage.
• Develop appropriate SCADA-based real-time monitoring tools to identify a damaged pneumatic controller
• Develop appropriate SCADA-based tools to determine if self-repair was effective.
• Provide technoeconomic analysis of the proposed system.
• Demonstrate the system in a pilot scale flow loop.
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Project Organizational Chart
The University of Tulsa
Principal Investigator:
Michael W. Keller
Task 1
Project management, Planning and Reporting
Lead:
Michael Keller
Task 2
Synthesis and Characterization of Self-healing Membrane
Lead:
Michael Keller
Task 3
Development and Validation of physics-based Model
Lead:
Rami Younis
Task 4
Pilot Scale testing
Leads:
Michael Keller/Cem Sarica
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Gantt Chart
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Bibliography
– List peer reviewed publications generated from the project per
the format of the examples below.
• None to report
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