Use when determine shielding calculation uncertainties for a spacecraft radiation analysis under ECSS-E-ST-10C §6.4: identify each uncertainty contributor as model (transport-code assumptions and dose-conversion factors), geometry (simplified mesh versus as-built structural detail), or cross-section (nuclear reaction data spread), assign a fractional uncertainty to each contributor, combine them by RSS or linear worst-case summation, apply a k-sigma margin to the nominal computed dose or flue...
Scanned 9/27/2026
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---
name: e1012-shield-unc
description: "Use when determine shielding calculation uncertainties for a spacecraft radiation analysis under ECSS-E-ST-10C §6.4: identify each uncertainty contributor as model (transport-code assumptions and dose-conversion factors), geometry (simplified mesh versus as-built structural detail), or cross-section (nuclear reaction data spread), assign a fractional uncertainty to each contributor, combine them by RSS or linear worst-case summation, apply a k-sigma margin to the nominal computed dose or fluence, and verify the margined result remains within the allowable shielding requirement. Trigger: ecss, e-st-10-system-scope, shielding-uncertainty, model-uncertainty, geometry-uncertainty, cross-section-uncertainty, radiation-margin, dose-budget."
license: Apache-2.0
compliance: STANDARDS-REF
standards:
- id: ecss
reference-only: true
gated: false
domain: space-systems
pack: space-systems
compatibility: "agentskills.io SKILL.md; any SKILL.md host (Claude Code, Hermes, OpenClaw)"
metadata:
domain: space-systems
subdomain: ecss
tags: [ecss, e-st-10-system-scope, shielding-uncertainty, model-uncertainty, geometry-uncertainty, cross-section-uncertainty, radiation-margin, dose-budget]
version: 0.1.0
author: Aero Agent Skills
---
# ECSS Space Environment — Shielding Calculation Uncertainties (space-systems/ecss/e1012-shield-unc)
Use when the task is to determine and propagate the uncertainties in a
spacecraft shielding calculation per ECSS-E-ST-10C §6.4 — covering model
errors in the transport code, geometric simplifications of the structural
model, and nuclear cross-section data spread — so that a margin-adjusted
dose or fluence can be checked against the shielding requirement.
## Domain quick reference
- §6.4 identifies three uncertainty families that affect a shielding result:
model uncertainty (approximations built into the radiation transport code and
dose-conversion methodology), geometry uncertainty (difference between the
simplified mesh used in the analysis and the actual as-built spacecraft
structure), and cross-section uncertainty (spread in the nuclear reaction
data libraries used to model particle interactions). Each contributor is
assigned to exactly one family before its magnitude is estimated.
- A fractional uncertainty is assigned to each contributor as a dimensionless
ratio (0 to 1). Contributors within or across families are combined either
by root-sum-square (RSS) for statistically independent contributors or by
linear worst-case sum for correlated or conservatively treated contributors.
RSS yields a smaller combined uncertainty; worst-case is used when
correlations between contributors cannot be ruled out.
- The combined fractional uncertainty is applied to the nominal shielded dose
or fluence via a k-sigma margin: margined value = nominal × (1 + k ×
combined_unc). k = 1 represents a one-sigma margin; k = 2 a two-sigma margin.
The margined value must not exceed the shielding requirement; if it does,
the nominal shielding thickness is insufficient or the uncertainty estimate
must be revisited.
## Workflow
1. Enumerate all contributors to shielding result uncertainty and assign each
to one of three families: model, geometry, or cross-section. Reject any
contributor whose family cannot be determined before it enters the budget.
2. For each contributor, assign a fractional uncertainty value in [0, 1] backed
by analysis, literature data, or engineering judgement. Document the
rationale for each value.
3. Select the combination method: RSS when contributors are independent, linear
worst-case when they are correlated or when a conservative bound is required
by the project's radiation design margin policy.
4. Combine the fractional uncertainties using the selected method to produce a
single combined fractional uncertainty for the calculation.
5. Apply the k-sigma margin to the nominal computed dose or fluence to obtain
the uncertainty-margined result.
6. Compare the margined result against the shielding requirement. Flag an
exceedance and identify the dominant uncertainty family to guide where
analysis effort should be focused to reduce the combined uncertainty.
## Pitfalls
- Assigning the same contributor to more than one uncertainty family — each
source of error belongs to exactly one family; double-counting inflates the
combined uncertainty and overstates the margin requirement.
- Using RSS combination when contributors share a common input (e.g., both
model and geometry uncertainty driven by the same simplified orbit model) —
correlated sources must be combined linearly to avoid underestimating the
combined effect.
- Treating a missing k value as equivalent to k = 0 — a zero margin means the
nominal result is used directly against the requirement, which may violate
the project's radiation design margin policy even if the nominal result
passes.
- Accepting a result as compliant when the fractional uncertainty for any
contributor is unsubstantiated — an engineering-judgement placeholder that
has not been reviewed and accepted by the project carries a hidden risk that
the true uncertainty exceeds the budget.
## Behavior contract (gate 3)
The uncertainty-source validation, RSS and worst-case combination, margin
application, and compliance-check logic are exercised by the gate 3 contract
test: scripts/test_e1012_shield_unc.py against
scripts/e1012_shield_unc_logic.py (stdlib unittest, offline). Run:
python3 scripts/test_e1012_shield_unc.py
## Compliance
- ECSS standards are freely downloadable (ESA); cite the source and paraphrase
per standards-map.yaml.
- compliance: STANDARDS-REF, gated: false.
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