Tracker Gas Flow Quality Control Method

• Tracker gas flow quality control is a systematic method that uses time-resolved 55Fe source measurements to detect channel blockages in high-channel-count straw tube arrays.
• The technique applies an error-function model to extract the 90% plateau rise time (Δt), flagging channels with Δt shifts beyond the median plus 5σ as potential obstructions.
• Implementation results showed a median rise time of 900–1200 s per panel and a repair success rate of approximately 75%, underscoring its value in maintaining detector precision.

The tracker gas flow quality control method is a systematic approach developed to ensure the uniformity and reliability of gas conductance through high-channel-count straw tube arrays, specifically the Mu2e experiment’s tracker. This method utilizes time-resolved measurements of gain recovery during gas exchange—with the gain determined by induced ionization from an external 55Fe source—to directly quantify the channel-by-channel integrity of the gas flow. Inefficient channels, typically due to partial or complete blockages, are identified via deviations in gas exchange time constants, enabling remedial action and maintaining the required uniformity in drift gas conditions for optimal detector performance (Bharatwaj et al., 3 Dec 2025).

1. Straw Tube Tracker Context and Gas Flow Requirements

The Mu2e tracker is constructed from thin-walled (15 μm Mylar®) straw tubes, each with an outer diameter of 5 mm and lengths ranging from 430 mm to 1200 mm. These straws are grouped into panels (typically 96 straws per panel), arranged in overlapping layers to form a low-mass, high-resolution tracking volume critical for reconstructing electron momenta with ∼100–150 μm spatial and 100 keV/c momentum resolution at p ≈ 105 MeV/c (2002.03643, Hedges, 2022, Lucà, 2017). The tracker is operated with an Ar–CO₂ (80:20) mixture at atmospheric pressure, requiring precise control of gas quality and flow in each straw to ensure uniform electron drift velocity (v_d ≃ 5 cm/μs) and consistent gain throughout its lifetime (Hedges, 2022). Local deviations in gas quality degrade time resolution and, more critically, momentum resolution, motivating stringent quality assurance of the gas system at the single-straw level.

2. Principle of Gain-Based Flow Quality Control

The core of the quality control procedure is the temporal correlation between the onset of ionization gain—and thus measured current—during a transition from a “no-gain” gas (N₂) to operational Ar–CO₂. This transition is monitored by measuring current induced by a 55Fe X-ray source sweeping across each straw doublet, while applying a fixed high voltage (HV ≈ 1450 V).

Mathematically, the time-dependent current I(t) during gas exchange is modeled as:

$I(t) = I_\infty\,[1 - \exp(-t/\tau)]$

where $I_\infty$ is the asymptotic plateau current, and $\tau = V/C$ is the gas exchange time constant ($V$ = straw volume, $C$ = conductance) (Bharatwaj et al., 3 Dec 2025). In practice, the discrete nature of the source measurement leads to fitting an error function:

$$I(t) = \frac{A}{2}\,[1 + \mathrm{erf}((t-t_0)/(\sqrt{2}\sigma))]$$

Here, $A \simeq I_\infty$, $t_0$ is the midpoint of the transition, and $\sigma$ characterizes its width. The “rise time” $\Delta t$ (from gas switch to 90% plateau gain) quantifies the effective conductance of each straw. Blocked or restricted straws exhibit prolonged $\Delta t$, allowing their unambiguous identification (Bharatwaj et al., 3 Dec 2025).

3. Experimental Implementation

Panels are equipped with two-layer, 96-straw modules with gas managed through inlet and outlet manifolds and monitored by a central Digital Mother Board (DMB). The quality control protocol proceeds by: (1) flushing with Ar–CO₂, (2) purging with N₂ to suppress gain, (3) rapidly refilling manifolds with Ar–CO₂ (bypassing straws), and (4) resuming flow through straws while recording HV-induced current response to the 55Fe source. Ganged straws (doublets) share a common HV channel and readout; thus, measurement is per doublet.

Current readout electronics, sampling at 10 Hz, capture the time evolution of the current as Ar–CO₂ returns. Peak-finding and Gaussian fitting are performed on each X-ray sweep, forming a time series that is fitted to the error-function model above. The time to reach 90% of the plateau (relative to the refill trigger) is computed per channel. Channels exceeding a specified threshold ($\Delta t$ > median + 5σ of the panel) or with artificially depressed gain are flagged.

4. Statistical Performance and Repair Outcomes

Application of this procedure to 11 280 straw-doublet channels yielded a median fill time $\Delta t$ of 900–1200 s per panel, with the expected systematic dependence on straw length and panel topology. A total of 1.94% of channels were initially flagged, of which 74.9% were repaired successfully (primarily by re-drilling the epoxy gas seals), while the remainder were lost, typically due to wire breakage during intervention. At the single-straw level, 0.95% had one blocked end; 76.3% of such cases were successfully remedied (Bharatwaj et al., 3 Dec 2025). No large-scale spatial pattern of failures was observed, consistent with the expectation that blockages are stochastic and manufacturing-related rather than systemic.

Metric	Value	Comments
Median rise time ($\Delta t$)	900–1200 s	Panel-dependent, length-correlated
Total flagged channels	1.94% of 11,280	$\Delta t$ > median + 5σ or low plateau
Repair success rate	74.9%	Post-drilling repair
Single-straw blockage	0.95%	Fraction with one blocked end

5. Technique Limitations and Generalization

The method’s principal strengths are scalability, quantitative flagging criteria, and its agnosticism to underlying flow obstruction mechanisms (end-epoxy, crimp deformation, etc.). However, only restrictions causing significant flow loss ($\Delta t$ shifts > typical dispersion) are detectable; partial blockages may escape detection, and the procedure is time-consuming (≈1–2 hours per panel). Mechanical access for source placement and intervention tooling is essential. Further, per-straw absolute conductance extraction is only approximate; panel-to-panel normalization and relative comparisons are more robust than absolute channel characterization.

The QC protocol is generically applicable to any gaseous detector system with segmented, accessible flow channels and compatible drift gas/ionization source combinations. This includes drift tube arrays and multiwire proportional chambers, provided per-channel current monitoring is available. Potential future improvements include real-time gas-composition sensing, segmented manifold designs for faster and more uniform gas exchange, and machine learning-based thresholding for subtle defect identification (Bharatwaj et al., 3 Dec 2025).

6. Significance for Detector Operations and Physics Goals

By ensuring uniform and reproducible gas flow characteristics across all tracking channels, the method safeguards the constant drift-velocity regime and stable gain required for the Mu2e experiment’s stringent momentum resolution. Uniformity in gain and timing calibration underpins the tracker’s ability to discriminate 104.97 MeV/c conversion electrons against the tail of decay-in-orbit backgrounds, a requirement for achieving the ambitious single-event sensitivity goal of $\mathcal{O}(10^{-17})$ (Hedges, 2022). The empirical procedures and repair data from panel production establish a standard for high-reliability, high-channel-count drift-based tracking systems in future lepton flavor violation and other precision physics experiments.

7. Comparison to Conventional Quality Assurance Approaches

Traditional QA for gaseous trackers focuses on leak rate testing, wire tension verification (by resonance), dimensional survey, and electrical connectivity (Lucà, 2017, 2002.03643). Leak rate thresholds (≤0.03 cm³/min/panel) demonstrate panel integrity but cannot resolve intra-panel heterogeneity or single-straw blockages below the aggregate leak rate resolution. The gain-based gas flow QC outlined here adds a uniquely quantitative, per-channel metric sensitive to small-volume blockages, yielding a level of operational assurance otherwise inaccessible through conventional tests. A plausible implication is that future tracker designs may integrate continuous or periodic gain-based flow quality checks as part of the standard preventive maintenance and calibration cycle.