# Methodology

Given this particular boundary around reality, this is what the evidence currently supports.

## The decision before the metric

Start with a useful service and its beneficiary. Define the service quantity and quality, place, time, duty cycle, reliability and unmet need. A functional unit is the exact amount of service compared: for example, one tonne-kilometre at a specified payload and route, or one computational task meeting fixed quality and latency limits. Examples are not selected project cases.

The question is whether usable installed-system energy density addresses the binding constraint better than feasible alternatives. Compare the current baseline, best feasible existing option, efficiency or service redesign, and infrastructure or operational change. Exclude an irrelevant alternative only with an explicit reason. A baseline with inadequate service must report that deficit.

## Keep quantities separate

Energy is an amount, commonly measured in joules or kilowatt-hours. Power is the rate of energy transfer, commonly kilowatts. Specific energy is energy per mass; volumetric energy density is energy per volume. Always state whether numbers describe a material, cell, pack or installed system, the usable rather than nameplate energy, and the duty cycle. Heat must include temperature; computation must include task quality. Efficiency is not energy density.

## Boundaries and burden shifting

Account for extraction, manufacture, transport, conversion, storage, delivery, use, maintenance, replacement and end of life. Declare geography, time horizon, marginal supply assumptions, allocation choices, embodied impacts, excluded processes and missing data. Show effects per functional unit and in total. Name who receives benefits and who bears costs or risk.

“Where did the entropy go?” asks a useful question, but entropy has a precise thermodynamic meaning. Track energy flows and, where needed, exergy (available work relative to specified surroundings). Separately audit emissions, toxicity, heat, water, land, minerals, cost, safety, reliability, supply concentration and infrastructure. Do not convert these into a fictitious common entropy unit.

## Tradeoffs and uncertainty

Register the minimum relevant improvement and non-negotiable safety, environmental and service constraints before reviewing comparison outcomes. Affected stakeholders and domain practitioners choose thresholds and explain why; the project imposes no universal numerical threshold. Record capital and operating cost, currency year, discount rate and lifetime before comparing economics.

Keep the Pareto set: an option is dominated only if a feasible comparator is no worse on every declared objective and better on at least one, on matching service and boundary. Do not apply this rule across incompatible cases. Consider measurement uncertainty, correlations, source dependence and model assumptions. If ordering changes across defensible assumptions, report it as unresolved and show the sensitivity. Do not replace missing values with zero or collapse the objectives to an arbitrary score. A Pareto option is not automatically safe, scalable or desirable.

## Test and update

Record hypothesis, mechanism, assumptions, measurable prediction, cheapest discriminating test, equipment, uncertainty, safety, falsifier and replication procedure. Preregister before analysis or data collection, disclose deviations and preserve the original. Prefer information that can reverse a decision over an expensive demonstration that cannot distinguish alternatives.

Allowed hypothesis states are UNRESOLVED, PLAUSIBLE — EXPERIMENT REQUIRED, FALSIFIED, and SUPPORTED WITHIN TESTED CONDITIONS. Falsified is scoped to the registered claim; missing data is unresolved. Support requires documented independent replication within named tested conditions, including qualifying result records. Simulations and desk analyses cannot be relabeled as physical replication. Report reasons, dates and limitations in confidence history. The launch probability is null because it is not calibrated.

## Rebound and total demand

An efficiency gain reduces energy per service. More use can offset that reduction. Causal rebound means demand induced by the efficiency-related change; unrelated population, income or workload growth is not automatically rebound. Jevons-type backfire describes cases in which the induced increase more than offsets savings; do not assume it always occurs.

The website calculator is a dimensionless accounting illustration: new operational energy / baseline operational energy = (1 − fractional energy saving per task) × (1 + fractional task growth). Tasks have equal quality. It omits embodied energy, cooling changes, hardware turnover, prices, elasticity and other sectors. It neither estimates causal rebound nor predicts demand or total lifecycle outcomes.

## First framing audit

EDC-E-0001 is proposed, with its service and thresholds deliberately unregistered. The first decision is to select the case with a practitioner. An audit may retain density for this case, narrow its relevance, replace it with another constraint, or remain unresolved. It cannot establish that energy density is humanity's most important problem.