Reliability Modelling of an ADS Accelerator Myrrha Linac

Reliability Modelling of an ADS Accelerator - Myrrha Linac reliability model - Eu. CARD 2, GENEVA (22 -23 June 2015) CERN

Step 1. SNS Linac modeling (MAX Task 4. 2) –(Eu. CARD 2 2014) Step 2. Myrrha Linac modeling (MAX Task 4. 4) – Myrrha Linac gen. Design (Reliability oriented) – Input Data; Modeling Assumptions – Fault Tree & RS Analysis – Modeling- Rel. Design optimization Availability/Frequency – Conclusions

1. SNS Linac Modeling (MAX Task 4. 2) -(Eu. CARD 2 2014) q MAX Task 4. 2 - SNS – ORNL Linac Reliability modeling (methodology currently applied for NPPs – modeling with Risk Spectrum) q SNS Linac reliability analysis - feedback on SNS Linac reliability performance - modeling tool for Myrrha Linac (Task 4. 4). q Draft preliminary conclusions and recommendations: - Maximize the reliability/availability/safety of MYRRHA Acc. - Guidance for designing the MYRRHA Accelerator.

SNS Linac Modeling – Results evaluation; SNS Logbook data (Accelerator trip failures) q Conclusions from the SNS RS Model runs in line with the SNS Logbook data statistics: Ø RF system and electrical system failures - most frequent Ø Electrical systems failures - most contributing to accelerator downtime Accelerator downtime contribution (by system) SNS Rel. Analysis Results: q Most affected SNS Linac parts/systems : Ø SCL, Front-End systems (IS, LEBT, MEBT), Diagnostics & Controls Ø RF systems (especially the SCL RF system) Ø Power Supplies and PS Controllers q To be enforced: redundancy of systems, subsystems and components most affected by failures q Need for intelligent fail-over redundancy implementation in controllers, for compensation purposes q Enough diagnostics – for reliable functioning of the redundant solutions and compensation function. Accelerator trip failures frequency (by system)

SNS Linac Modeling – Results evaluation; SNS Logbook data (Accelerator trip failures) q In accordance with the SCL RS analysis: Most affected subsystems of the SNS Linac (by failures leading to accelerator trips): Ø SCL-HPRF (Superconducting Linac - High Power Radiofrequency) - short failures frequency Ø HVCM (High Voltage Converter Modulator - duration of trips RF System failures (no. & duration-hours)

2. Myrrha Linac Modeling (MAX Task 4. 4) 1. SNS Linac Modeling Overall approach Ø Fault Tree: SNS model (Risk Spectrum) based + Max design Ø Activities Ø Basic Events: Component / Function failures q Design & Reliability data base (Sources: SNS, Max team, suppliers, conservative assumptions / reliability targets) Ø Undeveloped Events/Systems: Reliability targets Ø Reliability model: Availability / Failure (Linac shutdown) frequency Ø Reliability Analysis: Design Optimization Myrrha linac - Reliability challenges: Ø Injector Switch magn. Ø Fault tolerance/compensation function Ø Reliability of SSAs (Solid State Amplifiers) q Myrrha Linac model - based on the SNS RS Model and analysis results/conclusions. q Reliability analysis (Availability/Frequency) performed, with due consideration of reliability challenges q Myrrha Linac Risk Spectrum reliability analysis results in accordance with and completing the previous SNS modeling results

Myrrha Linac Design MYRRHA accelerator Conceptual scheme Linac Design: Low energy section – Injector/Linac front end: Multicell cavities –Modularity & fault tolerance not applicable Parallel Redundancy -2 Injectors with fast switching Medium and High energy section Independently-phased superconducting section -Highly modular (individual, independently controlled accelerating cavities. Serial redundancy -strong tolerance to faults. LEBT Conceptual scheme MYRRHA reference injector: ECR proton source, LEBT, RFQ, CH-Booster , MEBT MYRRHA 17 Me. V Injector reference layout

Myrrha Linac Design Reference layout for the MYRRHA 17 Me. V injector; CH-DTL cavity with two triplets MEBT general layout, superimposed on a preliminary building layout (red squares: quadrupoles, blue elements: Spoke SRF cavities, purple arrows: BPMs) Reference lattices of the SCL Layout of the MYRRHA beam lines to reactor and dump

Reliability oriented design Myrrha Linac reliability objectives: Beam interruptions: Reliability goal principles: 1) Use of components far from limits: SC RF cavities perform. – Limit: 10 beam interruptions/3 -month operating cycle; allow adopting comfortable margins. < (3) seconds each 2) Fault-tolerance (serial redundancy): SC linac sequence modular Global accelerator MTBF: 250 hours. RF cavities. Interruptions in the range 0. 1 ms – 3 s: theoretically unlimited, but proposed Individual cavity control (phase/amplitude); RF/LLRF layout so to limit in practice to less than 100 per day as to: switch time < 3 s Tolerant beam dynamics - inactive cavity with subsequent retuning of adjacent cavities 3) Repairability (engineering design) + redundant schemes for continued availability. Trip frequency vs. trip Modularity of SC linac duration for high power Early fault detection and fault diagnostic proton accelerators, and ADS specifications. MTTR Retuning strategy used in the Trace. Win code for compensation optimization (case where Spokecryomodule #18 is off-line Reliability oriented design: MTBF of 250 hours could be achieved by providing significant RF power and gradient overhead throughout the three (3) SC sections Single failure criteria application

Input Data & Gen. Assumptions INPUT Data Linac design - General hypotheses & assumptions Modeling Assumptions (Risk Spectrum) ¨Continuously monitored repairable component¨ - Risk Spectrum Type 1 reliability model – Linac components ¨Constant Frequency¨ - Risk Spectrum Type 5 reliability model – accelerator trip frequency ¨Mean Unavailability¨ and ¨Frequency¨ types of calculation unavailability/frequency values (basic events). The long-term average unavailability (Q) and frequency (F), the expected number of failures per unit time) were calculated (A 1) Radiofrequency (RF) System - similar to SNS (excepting Klystron and Modulator subsystems and related). All MYRRHA Linac amplifiers are solid-state type. (A 2) ¨Transmitter ¨subsyst. (SNS model) - equipment to run the SSA for RF cavity control. Generally, the transmitters consist of a low level RF system, amplifier water-cooling, AC distribution, etc. (A 3) Auxiliary systems (AUX) -based on SNS (reference), modified to MYRRHA Acc. Design, adjusted to a lower level of detail. No glycol cooling -not applicable to the MYRRHA Linac case. (A 4) Relevant Beam Diagnostics -those related to possible beam failures and/or linked to the Machine Protection System (MPS). Diagnostics for monitoring and tuning -not relevant to normal operation. (A 5) MTBF=10 e 5 h (SNS) SC Cavs -cavity failures due connected systems failures (other than cav. Mechanical failure) (A 6 -7) Comps. Missing data – SNS similitude, assumptions Impact on global reliability: - Injector Switch magnet - Fault tolerance and compensation system/function -high reliability objectives for detection and control systems. Assumptions -reliability targets (failure probability), so as to reach general reliability objectives.

Input Data & detailed Assumptions 50% of SNS RFQ Vacuum Syst. capacity

Table 4. 5 - MAIN SUPERCONDUCTING LINAC modeling data Input Data & detailed Assumptions Ø MAIN SUPERCONDUCTING LINAC modeling data Model code Part/System SCL (YYYUUUvv) SCL No. MTBF MTTR Manufacturer/Ref. Design Model/ Type Details; Obs. Section 1 Spoke CAVs 48 100000 3 SNS RF SCL cavity SNS Spoke 2 -gap (β=0. 37); (included in SCLsect 2+3 fault tree) 34 100000 3 SNS RF SCL cavity SNS Elliptical 1 -5 cell (β=0. 51); SNS modified for 142/2=71 Cavs 100000 3 SNS RF SCL cavity SNS Elliptical 2 -5 cell (β=0. 7) ); SNS modified for 142/2=71 Cavs Section 2 SNS tree Elliptical-1 CAVs SNS tree Elliptical-2 CAVs 60 SNS tree SCL cavities-total (spoke+ellipt. ) 142 (2 x 71) SNS tree Cryostats (cryomodules) 56 (2 x 28) Section 3 SCL-SSAS SNS SCL: 81 cavities (33 mb + 48 hb) => 1. 75 -2 multiplication factor for SCL AUX systems capacity MAX SS Amplifier 2 x 71 50000 4 Soleil technology - SNS tree RF Feedthroughs 2 x 71 100000 24 SNS SCL-RF SNS tree SCL Cavity 142 SNS RF SCL Cavity SNS SCL Circulator 2 x 71 50000 3 SNS scl SNS SCL Load 2 x 71 75019 3 SNS scl SNS SCL Waveguide 2 x 71 100000 3 SNS scl SNS SCL Window 2 x 71 100000 3 SNS scl SNS SCL Cavity 2 x 71 100000 3 SNS scl SNS 24+17+15 (configuration in Figure 2. 10)

Table 4. 5 - MAIN SUPERCONDUCTING LINAC modeling data Input Data & detailed Assumptions Ø MAIN SUPERCONDUCTING LINAC modeling data SCL Cavity Vacuum 2 x 71 100000 3 SNS scl SNS Compensation failure probability 2 x 71 Failure p=10 -1 no data - SNS tree SCL Transmitters 2 x 12 SNS scl SNS tree SCL LLRF 12 x 1 SNS scl SNS SCL LLRF Reference 12 x 1 100000 8 SNS scl SNS SCL HPM 12 x 1 100000 3 SNS scl SNS SCL FCM 12 x 1 100000 3 SNS scl SNS SCL HPRF 12 x 1 SNS scl SNS SCL Magnet Power Supply 12 x 1 10743 4 SNS scl SNS SCL Solid State Amp 12 x 1 10743 4 SNS scl SNS SCL Filament Power Supply 12 x 1 10743 4 SNS scl SNS SCL TCU 12 x 1 30000 4 SNS scl SNS SCL Klystron Window Airflow 12 x 1 30000 3 SNS scl SNS SCL Klystron Waterflow 12 x 1 30000 3 SNS scl SNS SCL Interface 12 x 1 68634 4 SNS scl SNS SCL AC Distribution Chassis 12 x 1 34843 4 SNS scl SNS SCL HV Enclosure 12 x 1 114811 4 SNS scl SNS SCL PPS Chassis 12 x 1 34843 4 SNS scl SNS SCL Water cooling 12 x 1 196850 4 SNS scl SNS Assumed

Table 4. 5 - MAIN SUPERCONDUCTING LINAC modeling data Input Data & detailed Assumptions Ø MAIN SUPERCONDUCTING LINAC modeling data SCL Cryomodules SNS tree SNS MB/HB scl cryom SNS JT Valves 2 x 28 28 x(5 series) 87719 2 SNS MB/HB chl SNS Window Heaters 28 x(3 series) 500000 2 SNS MB/HB chl SNS Heater 1 -3 28 x(2 of 3)) 500000 2 SNS MB/HB chl SNS RF Cavities 28 x(3 series) 876000000 2880 SNS MB/HB chl SNS Tuner Assemblies 28 x(3 series) 175439 120 SNS MB/HB chl SNS Cryostat Structure 28 x 1 5000000 24 SNS MB/HB chl SNS Feedthrough Leak 28 x(24 series) 13000000 2 SNS MB/HB chl SNS RF Coupler 28 x(3 series) 500000 4 SNS MB/HB chl SNS SCL Magnets 112 qds-65 ps/psc + 66 corr(steerers) -configuration in Fig. 2. 10 MAX (SNS: 67 qds-39 ps/psc + 32 corr 32 ps/psc) Quads doublets (24) 48 10000000 4 SNS scl-quads SNS Room temp. Quads (Magnet Assembly) Quads doublets (17) 34 10000000 4 SNS scl-quads SNS Room temp. Quads (Magnet Assembly) Quads doublets (15) 30 10000000 4 SNS scl-quads SNS Room temp. Quads (Magnet Assembly) SCL Steerers 66 10000000 4 SNS scl-correctors SNS Compensation failure probability 112 Failure p=10 -1 no data - Assumed Magnet Supplies SNS Magnet Supplies Quads PS 65 100000 2 SNS SCL Power supplies (SNS quads) Quads PSC 65 50000 2 SNS SCL Power supply controllers (SNS quads) Steerers PS 66 100000 2 SNS SCL Power supplies (SNS correctors) Steerers PSC 66 50000 2 SNS SCL Power supply controllers (SNS correctors) Magnet Supplies SCL AUX 2 x(SNS) SNS SCL-aux syst SNS Correctors -Magnet Assembly Assumed: SCL Auxiliary Systems approx. double capacity - 142 Cavs vs. 81 Cavs (SNS)

Myrrha Linac Modeling – Fault Tree q Myrrha Linac Fault Tree – main level

Myrrha Linac Modeling – Fault Tree q Myrrha Linac Fault Tree – SCL

Myrrha Linac Modeling – Quantification & Analysis Ø Risk Spectrum basic events quantification window Ø MCS analysis – initial point-estimate (case 1. 1) quantification of the top event (MYRRHA ACC DOWN)

Myrrha Linac Modeling –optimization (Availability) Ø Myrrha Linac Design optimization - Availability Ø MYRRHA Linac analysis Case 1. 4 (DG&C systems – SNS fault tree); DG&C failures

Myrrha Linac Modeling –optimization (Availability) Ø Myrrha Linac Design optimization - Availability Ø MYRRHA Linac systems analysis (Case: DG&C f. p 10 -3; Cmp/Switch f. p 10 -2)

Myrrha Linac Modeling –optimization (Availability) Ø Myrrha Linac Design optimization - Availability Ø MYRRHA Linac systems analysis Case 1. 4 + [DG&C f. p 10 -3; Cmp/Switch f. p 10 -2; CONV f. p 10 -3]

Myrrha Linac Modeling –optimization (Availability) Ø Myrrha Linac Design optimization - Availability Ø MYRRHA Linac systems analysis Case 1. 4 + [DG&C f. p 10 -3; Comp/Switch f. p 10 -2; CONV f. p 10 -3] + Optimization (new reliability values proposed in table 6. 4)

Myrrha Linac Modeling –optimization (Frequency) Ø Myrrha Linac Design optimization - Frequency Ø Frequency results for case 1. 5. 1 (Redundant FE/INJ + Compensation)

Myrrha Linac Modeling –optimization (Frequency) Ø Frequency results for case 1. 5. 1 + DG&C p = 10 e-3: 117 trips/year – 29. 25 trips/3 mths Ø Frequency results for case 1. 5. 1 + DG&C p = 10 e-3 + CONV p = 10 e-3: 103 trips/year – 25. 75 trips/3 mths

Myrrha Linac Modeling –optimization (Frequency) Ø Frequency results for case 1. 5. 1 + DG&C p = 10 e-3 + CONV p = 10 e-3 + optimized reliability values in Table 6. 4: 60 trips/year – 15 trips/3 mths

Myrrha Linac Modeling –optimization (Frequency) Ø MYRRHA Linac systems analysis Case 1. 4 + [DG&C f. p 10 -3; Cmp/Switch f. p 10 -2; CONV f. p 10 -3] + Optimization (Table 6. 4) + new reliability values proposed in Table 6. 7) Ø final optimised Frequency results

Myrrha Linac Modeling – CONCLUSIONS Ø Compensation (fault-tolerance) function – SSAs, cavities compensation to minimize RF failures (significant failures contribution to Acc. trips) - helps performing global fine-tuning and contributes to the machine stability during functioning, by - automatically adjusting deviations from the optimal field parameters (limited to the reserve (margins) power range foreseen for the amplifiers, supplies, etc…) Ø Doubled injector improves the overall reliability significantly - to avoid trips caused by components in the front-end (usual failures) Ø Identification of ¨critical¨ failures (Comp. failures directly leading to an accelerator trip - i. e. cooling control valves, common cause failures, etc. ) Prevention of ¨critical¨ failures ¨ - classical¨ parallel redundancy -significantly improving reliability. Parallel redundancy should be implemented for PS/PSCs and other components in the SCL and HEBT Ø Main SCL/HEBT weak parts (reliability issues) to be improved: - Large number of Quadrupoles/Corrector magnets power supplies - Large number of Quadrupoles/Corrector magnets power supply controllers (PSC) - Tuners, ion pumps: large number of components in series configuration Ø Special attention - design of advanced Diagnostics and Control systems

1. SNS Linac Modeling Thank you A. E. PITIGOI – EA (aph@empre. es) P. FERNANDEZ RAMOS – EA (pfr@empre. es)