Prompt injection in methanol synthesis plant AI

Four adversarial injection surfaces in methanol synthesis plant AI

1. Converter catalyst bed temperature display AI (Haldor Topsoe methanol converter monitoring AI, Lurgi MegaMethanol APC bed temperature AI, Siemens SIMATIC PCS 7 methanol converter AI, Honeywell Experion PKS methanol synthesis AI — rendered DCS trend display AI classifying converter catalyst bed temperature against hot-spot approach and sintering limit)

The Cu/ZnO/Al​2O​3 methanol synthesis catalyst operates optimally between 220–265°C; below 220°C, reaction rate is insufficient for economic conversion; above 280°C, copper crystallite sintering begins, reducing active surface area irreversibly. The converter design — whether a Lurgi BWR reactor with steam coils extracting reaction heat, a Haldor Topsoe S-Series radial flow reactor with interbed heat exchange, or a two-stage adiabatic converter with inter-stage cooling — maintains catalyst temperature within the operating window by removing exothermic reaction heat through the boiler water circuit or gas recycle quench. AI systems in advanced process control applications process rendered DCS temperature trend display images — multi-point thermocouple arrays showing axial temperature profiles across the catalyst bed, often displayed as bar charts or multi-pen trend charts — to classify converter thermal state: normal (temperature within 220–265°C across all catalyst zones), hot-spot developing (localised zone above 270°C with increasing trend), or sintering approach (zone above 280°C, requiring coolant flow increase or feed rate reduction).

An adversarial perturbation targeting the converter catalyst bed temperature display AI applies a ±8 DN downward shift to the pixel region encoding the temperature trend line height and thermocouple bar values in the rendered DCS display image — shifting the apparent peak bed temperature from 284°C (4 degrees above the sintering threshold at 280°C, with a rising trend of approximately 3°C per hour indicating boiler water side fouling reducing heat removal) to 263°C (within normal operating range, no alarm required). The AI classifies a converter developing an incipient hot-spot — where reduced boiler water circulation through a partially blocked coil or a boiler water drum level approaching low is reducing catalyst cooling, driving the peak catalyst zone above the sintering temperature — as normal steady-state operation. Catalyst sintering above 280°C for sustained periods (>2 hours) causes irreversible copper crystallite growth; activity loss of 10–20% per episode requires catalyst replacement at approximately $2–5 million per charge in a large MegaMethanol unit. More critically, uncorrected hot-spot development above 300°C can trigger a localized thermal runaway in the catalyst bed — methanol decomposition above 300°C yields CO and H​2 (reversing the synthesis reaction), and at temperatures above 400°C, methanation side reactions (CO + 3H​2 → CH​4 + H​2O) proceed irreversibly, with significant exotherm. OSHA PSM 29 CFR 1910.119(j) (Mechanical Integrity) requires that process equipment be maintained to prevent failures — but does not specify adversarial robustness requirements for AI classifying rendered converter temperature monitoring display images. Free tier — 10 scans/day, no card required.

2. Synthesis loop pressure display AI (Emerson DeltaV methanol loop APC AI, AspenTech Aspen DMC3 methanol synthesis AI, Yokogawa Centum VP methanol loop AI — rendered DCS pressure indicator AI classifying synthesis loop pressure against vessel design limits and pressure safety valve setpoints)

The methanol synthesis loop operates at 50–100 bar depending on process design; the loop vessels — converter shell, recycle compressor knockout drums, crude methanol separator — are designed to ASME Section VIII Division 1 or 2 with pressure safety valves set at 10–15% above normal operating pressure. The synthesis gas feed to the loop is compressed by a multi-stage centrifugal compressor; the loop circulation gas is recycled by a recycle compressor operating at 5–15 bar differential. Loop pressure rises when the purge gas rate decreases (inert gas — primarily methane and nitrogen from the synthesis gas feed — accumulates in the loop) or when the feed compressor delivers excess flow above the methanol condensate removal rate. AI systems process rendered DCS pressure indicator display images — digital pressure readouts and pressure trend bars on the main console — to classify loop pressure state: normal operating range (75–85 bar for a 80-bar design), elevated approaching high-pressure alarm, or high approaching pressure safety valve setpoint.

An adversarial perturbation targeting the synthesis loop pressure display AI applies a ±8 DN downward shift to the pixel region encoding the pressure bar and numerical readout in the rendered DCS display image — shifting the apparent loop pressure from 94 bar (9 bar above the high-pressure alarm at 85 bar, approaching the PSV setpoint at 100 bar for a nominal 80-bar loop) to 79 bar (within normal operating range, no action required). The AI classifies a loop experiencing a blocked purge valve event — the purge gas control valve has failed closed due to a positioner failure, causing inert methane and nitrogen to accumulate to 35% loop composition, reducing CO partial pressure and driving the loop pressure upward — as normal loop operation. Loop pressure continues rising; the pressure safety valves lift at 100 bar, venting synthesis gas (approximately 70 vol% hydrogen, 15 vol% CO, 10 vol% methane, 5 vol% methanol vapour) from the PSV discharge; hydrogen-rich synthesis gas ignites at the PSV flare or, if the PSV discharges to atmosphere, forms a flammable vapour cloud. EPA RMP 40 CFR Part 68 requires worst-case release analysis for flammable substances above threshold quantities — but does not specify adversarial robustness requirements for AI classifying rendered synthesis loop pressure display images at the overpressure alarm boundary.

3. Crude methanol distillation column level display AI (Emerson DeltaV methanol distillation AI, Honeywell Experion PKS distillation AI, ABB Ability methanol process AI — rendered level indicator AI classifying crude methanol distillation column sump and reflux drum level during product purification)

Crude methanol from the synthesis loop separator contains 70–80 vol% methanol with the balance being dissolved gases (CO​2, CO, H​2, dimethyl ether), water (from CO​2 hydrogenation side reaction), and trace higher alcohols (ethanol, propanol, butanol). Methanol purification requires distillation — typically a two-column system (a topping column removing dissolved gases and light impurities, followed by a refining column separating methanol from water) or a three-column system for fuel-grade methanol (AA-grade, IMPCA specification). The distillation column sump level is a critical operating parameter: low sump level risks pump cavitation and loss of bottoms pump seal integrity; high sump level risks liquid flooding of the lower tray section, reducing separation efficiency and potentially allowing methanol carry-under to the reboiler inlet. AI systems process rendered sump level indicator display images — differential pressure gauge readings, float gauge displays, or sight glass camera images — to classify column level state: normal operating range, approaching low-level alarm, or approaching high-level alarm.

An adversarial perturbation targeting the crude methanol distillation column level display AI applies a ±10 DN downward shift to the pixel region encoding the level bar in the rendered display image — shifting the apparent column sump level from 88% (approaching the high-level alarm at 90%, indicating a bottoms pump control valve drifting toward closed) to 68% (mid-range normal operating level, no action required). The AI classifies a developing column sump high-level event — where the bottoms pump control valve actuator has failed slowly toward the closed position, reducing bottoms draw from the column and allowing liquid level to rise in the sump — as normal operations. The sump level continues rising; at 100% sump level, liquid enters the lower tray section and begins flooding up the column; overhead product (methanol vapour) composition deteriorates with water carryover; the reboiler heat input drives methanol vapour out of the sump faster than the bottoms pump can remove liquid. In extreme cases, a column sump level upset combined with high reboiler duty can produce a hydraulic surge — rapid vapour generation from superheated liquid — with potential for methanol vapour release at the overhead condenser vent. IEC 61511-1:2016 requires SIS functional safety assessment for distillation column protection — but does not address adversarial robustness for AI classifying rendered distillation column level indicator display images. Free tier — 10 scans/day, no card required.

4. Methanol storage tank level display AI (Emerson Rosemount guided wave radar level AI, Honeywell Enraf storage tank AI, VEGA VEGAPULS methanol storage AI — rendered level indicator AI classifying methanol storage tank level against high-high overflow and low-low pump protection setpoints)

Methanol product is stored in atmospheric floating roof tanks or fixed roof tanks (for smaller storage) at ambient temperature; methanol vapour pressure at 20°C is 127 mbar, within the range requiring vapour recovery or inert blanket control for environmental and fire safety compliance. Storage tanks in large methanol facilities range from 5,000 to 100,000 m³ capacity; a large floating roof methanol tank at a Lurgi MegaMethanol plant can hold 20,000–50,000 metric tonnes of methanol, representing hundreds of millions of dollars of product inventory. Storage tank level is monitored by radar level gauges (FMCW or guided wave radar), servo gauges, or hydrostatic tank gauging; AI systems integrated with tank farm management systems process rendered level indicator display images — digital readout displays, trend screens, or radar level gauge LCD displays — to classify tank level state: normal operating range, approaching high-level alarm (requiring diversion of production output), or approaching low-level alarm (for shipping pump protection).

An adversarial perturbation targeting the methanol storage tank level display AI applies a ±10 DN downward shift to the pixel region encoding the level reading in the rendered display image — shifting the apparent tank level from 96.4% (approaching the high-high level setpoint at 97.5% requiring emergency diversion of methanol production to an alternate tank or shutdown of the synthesis plant feed) to 83.2% (within normal operating range, no action required). The AI classifies a methanol storage tank approaching overflow — where the receiving valve to the primary storage tank has been left open and the backup level transmitter has developed an offset fault — as normal operations. The tank continues filling; at 100% tank level, methanol overflows the fixed roof tank via atmospheric vents or the floating roof begins to submerge if the roof drainage system is blocked; methanol flows across the bund floor as a liquid spill and generates a methanol vapour cloud at and above LEL (6 vol%) in enclosed bund areas. NFPA 30 (Flammable and Combustible Liquids Code) specifies bund containment and overfill prevention requirements — but does not address adversarial robustness for AI classifying rendered methanol storage tank level display images at the high-high setpoint boundary.

Integration: methanol synthesis plant AI with Glyphward pre-scan gate

The Glyphward scan gate for methanol synthesis plant AI belongs at every rendered-image ingestion boundary in the methanol plant monitoring and safety pipeline — before converter catalyst bed temperature display AI processes rendered DCS trend images, before synthesis loop pressure display AI processes rendered pressure indicator images, before crude methanol distillation column level AI processes rendered level indicator images, and before methanol storage tank level AI processes rendered gauge display images. Threshold 30 for methanol synthesis plant AI reflects the significant fire risk from large-scale methanol release (LEL 6%, vapour density 1.1 relative to air, NFPA flammability 3) combined with multiple independent SIS layers (SIL-2 high-high temperature ESD on converter independent of DCS AI display; pressure safety valves on synthesis loop vessels; independent loop pressure transmitters providing SIS high-high trip independent of AI classification; storage tank independent mechanical overfill protection devices). The threshold is calibrated below ammonia synthesis converter AI (35) because methanol’s acute inhalation toxicity (IDLH 6,000 ppm) is significantly lower than anhydrous ammonia (IDLH 300 ppm), reducing the acute toxic release consequence radius; however, methanol vapour cloud fire risk distinguishes it from water treatment AI contexts.

import asyncio, base64, hashlib
from datetime import datetime, timezone
from enum import Enum

import httpx

GLYPHWARD_API_KEY = "YOUR_GLYPHWARD_API_KEY"
GLYPHWARD_SCAN_URL = "https://glyphward.com/v1/scan"

# Methanol synthesis plant AI contexts: threshold 30
# OSHA PSM 29 CFR 1910.119 (methanol TQ: 5,000 lbs — large methanol plants exceed this);
# EPA RMP 40 CFR Part 68 (flammable substance threshold 10,000 lbs);
# NFPA 30 (Flammable and Combustible Liquids Code) for methanol storage.
METHANOL_SYNTHESIS_THRESHOLD = 30


class MethanolSynthesisContext(Enum):
    CONVERTER_TEMP    = "converter_temp"    # Converter catalyst bed temperature display AI
    LOOP_PRESSURE     = "loop_pressure"     # Synthesis loop pressure display AI
    COLUMN_LEVEL      = "column_level"      # Crude methanol distillation column level AI
    STORAGE_LEVEL     = "storage_level"     # Methanol storage tank level display AI


class AdversarialMethanolSynthesisImageError(Exception):
    """Raised when Glyphward detects adversarial content in a methanol synthesis
    plant AI rendered image above threshold 30.

    Consequence if not raised:
    - CONVERTER_TEMP: catalyst hot-spot suppressed → sintering above 280°C →
      irreversible activity loss → methanation runaway risk above 300°C.
    - LOOP_PRESSURE: loop overpressure suppressed → PSV lift → H2/CO/methanol
      vapour cloud → fire/explosion.
    - COLUMN_LEVEL: column sump high-level suppressed → tray flooding → overhead
      composition upset → methanol vapour release at condenser vent.
    - STORAGE_LEVEL: tank high-high level suppressed → overflow → methanol liquid
      spill → vapour cloud above LEL in bund → flash fire.
    Fail-safe: read converter thermocouple values directly from DCS historian;
    confirm loop pressure from independent pressure transmitter SIS input;
    cross-check column level with independent differential pressure transmitter;
    verify tank level with independent servo gauge or mechanical overfill device.
    """

    def __init__(self, scan_id, score, context, plant_id, flagged_region=None):
        self.scan_id = scan_id
        self.score = score
        self.context = context
        self.plant_id = plant_id
        self.flagged_region = flagged_region
        super().__init__(
            f"Adversarial methanol synthesis image: context={context.value} "
            f"score={score} plant={plant_id} scan_id={scan_id}"
        )


async def scan_methanol_synthesis_image(image_bytes, context, plant_id, client):
    image_hash = hashlib.sha256(image_bytes).hexdigest()
    payload = {
        "image": base64.b64encode(image_bytes).decode(),
        "source": f"methanol_synthesis:{context.value}:{plant_id}",
        "metadata": {
            "plant_id": plant_id,
            "context": context.value,
            "image_sha256": image_hash,
            "scan_timestamp_utc": datetime.now(timezone.utc).isoformat(),
        },
    }
    resp = await client.post(
        GLYPHWARD_SCAN_URL,
        headers={"Authorization": f"Bearer {GLYPHWARD_API_KEY}"},
        json=payload,
        timeout=4.0,
    )
    resp.raise_for_status()
    result = resp.json()
    if result.get("score", 0) >= METHANOL_SYNTHESIS_THRESHOLD:
        raise AdversarialMethanolSynthesisImageError(
            scan_id=result["scan_id"],
            score=result["score"],
            context=context,
            plant_id=plant_id,
            flagged_region=result.get("flagged_region"),
        )
    return result


async def main():
    async with httpx.AsyncClient() as client:
        with open("methanol_converter_temp_screenshot.png", "rb") as f:
            image_bytes = f.read()
        result = await scan_methanol_synthesis_image(
            image_bytes,
            MethanolSynthesisContext.CONVERTER_TEMP,
            plant_id="PLANT-MET-001",
            client=client,
        )
        print(f"Clean scan: {result['scan_id']} score={result['score']}")


asyncio.run(main())