⚡ electrical engineering

Digital-Twin-Driven Cost-Scenario Simulation for Civil Infrastructure: A Comparative Framework from the Netherlands and Germany with an Adaptation Pathway for Peru

This study compares the digital-twin-driven cost-scenario simulation frameworks of the Netherlands and Germany to propose a hybrid, context-sensitive adaptation pathway for reducing budget overruns in Peru's civil infrastructure sector by integrating open BIM standards with life-cycle costing under existing regulatory mandates.

Original authors: PAUL RICARDO PRUDENCIO GALVEZ

Published 2026-07-01

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CC BY 4.0

Original authors: PAUL RICARDO PRUDENCIO GALVEZ

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine building a massive bridge or a highway. Usually, the budget is like a static, printed map drawn years before the construction even starts. It assumes the weather will be perfect, materials will cost exactly what was predicted, and no surprises will happen. But in reality, construction is messy. Prices change, delays occur, and the final bill often ends up much higher than the map predicted.

This paper proposes a solution: The Digital Twin.

Think of a Digital Twin not as a 3D model on a computer, but as a "living, breathing ghost" of the real construction project. Every time a truck delivers steel or a worker pours concrete in the real world, this "ghost" updates instantly. It doesn't just show what the building looks like; it constantly recalculates what the building costs in real-time.

The Big Idea: Learning from the Best

The author, Paul Ricardo Prudencio Galvez, looked at how two European countries—the Netherlands and Germany—use these "living ghosts" to manage money. He found they do it in two very different ways, like two different chefs cooking the same dish:

The Dutch Approach (The Logistics Chef):
- Focus: They treat the construction site like a busy airport or a shipping port. Their digital twin focuses on movement and flow.
- How it works: They simulate how traffic, materials, and logistics move to save money and reduce carbon emissions.
- The Secret Sauce: They use open, shared rules (like a universal language) so everyone can see the costs.
- Result: They get very accurate budgets, usually only off by about 5–8%.
The German Approach (The Structural Chef):
- Focus: They treat the building like a high-tech machine or a car engine. Their digital twin focuses on long-term health and durability.
- How it works: They connect sensors to the building to monitor how the structure wears down over time, calculating costs for repairs and maintenance decades into the future.
- The Secret Sauce: They use very strict, detailed rules for classifying costs and link them to real-time sensor data.

The Problem in Peru

The paper notes that Peru is currently struggling with construction projects that go over budget. Peru has a rule (a government decree) that says they must use a specific type of 3D modeling (BIM 5D), but they are still using old, static methods to guess the costs. It's like having a Ferrari engine but driving it with a bicycle chain.

The Proposed Solution: A "Hybrid" Recipe

The author suggests Peru shouldn't just copy one country. Instead, Peru should mix the best parts of both to create a Hybrid Framework:

Take the Dutch "Openness": Use the Dutch style of open, shared cost codes. This fits well with Peru's existing price lists and makes the budget transparent and easy to audit.
Take the German "Long-Term View": Use the German style of calculating "Life-Cycle Costs." This means planning for the cost of fixing and maintaining the building for 20 or 30 years, not just the cost to build it today.

How It Works in Practice (The "Magic" Formulas)

The paper lists specific mathematical "recipes" (formulas) that make this work. Instead of guessing a single number for the cost, these formulas use probabilities (like a weather forecast).

Instead of saying, "This bridge will cost $10 million," the system says, "There is a 50% chance it costs $10 million, a 10% chance it costs $12 million, and a 90% chance it costs under $14 million."
As the "living ghost" (Digital Twin) gets new data from the construction site, it instantly updates these probabilities, telling the managers, "Hey, we are spending faster than planned; here is the new forecast."

The Bottom Line

The paper concludes that Peru has the legal rules (the "BIM mandate") to start doing this. The technology isn't the problem; the problem is governance (how data is managed) and training (teaching people how to use it).

If Peru combines the Dutch way of organizing costs with the German way of planning for the future, and maps it onto their existing laws, they can stop the "budget overruns" that plague their infrastructure projects. It's a roadmap to turn a static, broken budget into a dynamic, living financial plan.

Technical Summary: Digital-Twin-Driven Cost-Scenario Simulation for Civil Infrastructure

Problem Statement
Civil infrastructure projects globally suffer from systematic cost overruns and schedule delays, a phenomenon attributed to the decoupling of static, document-based budgeting prepared during the design phase from the dynamic conditions encountered during execution. While Digital Twin (DT) technology—defined as a virtual representation of a physical asset continuously synchronized with real-world data—has been proposed as a mechanism to embed cost engineering into live, queryable models, comparative evidence regarding how mature DT ecosystems structure cost-scenario simulation remains fragmented. Specifically, there is a lack of systematic cross-mapping of the cost-engineering formulas embedded in distinct national ecosystems against a unified framework, and a gap in translating these findings into explicit adaptation pathways for developing contexts like Peru.

Methodology
This study employs a structured, criteria-based comparative analysis rather than an experimental protocol. The research relies exclusively on secondary, publicly available technical and scientific literature indexed in Scopus and Web of Science, with all sources verified via Digital Object Identifiers (DOIs).

Comparative Cases: The Netherlands and Germany were selected as comparator cases due to their institutionalized but architecturally distinct DT ecosystems. The Dutch model is driven by public-infrastructure and urban-logistics agencies (e.g., Rijkswaterstaat, TKI Dinalog), while the German model is rooted in structural health monitoring, Industry 4.0, and the DIN 276 cost-classification tradition.
Analytical Framework: A seven-dimension comparison matrix was constructed to evaluate: governing cost standard, primary DT use-case, simulation method, data interoperability protocol, reported budget variance, institutional driver, and applicability to Peru.
Formula Systematization: Modern cost and budget formulas (parametric estimating, BIM 5D quantity costing, Earned Value Management, Monte Carlo simulation, and Life-Cycle Costing) were extracted from the literature, standardized, and mapped onto a proposed four-layer digital-twin architecture (physical, data/BIM, simulation-engine, and decision layers).

Key Results
The analysis reveals distinct yet converging approaches in the two national ecosystems:

The Dutch Ecosystem: Predominantly infrastructure- and logistics-centric. It relies on open BIM/IFC mandates for public tenders and utilizes probabilistic cost-CO2 co-simulation focused on logistics and network-level externalities. Reported budget variances in digital-twin pilots range from 5% to 8%.
The German Ecosystem: Predominantly structural- and manufacturing-centric. It is anchored in DIN 276 cost classification and life-cycle costing (LCC) coupled with sensor telemetry, emphasizing structural degradation and maintenance costs.
Convergence: Both ecosystems have shifted from single-point deterministic budgeting toward probabilistic, percentile-based estimates (P10–P50–P90) that are recalculated as field data is ingested.
Divergence: The principal divergence lies in the dominant cost driver (logistics vs. structural degradation) and interoperability protocols (Open BIM/IFC in the Netherlands vs. IFC combined with proprietary OEM/Industry 4.0 protocols in Germany).

Key Contributions

Comparative Matrix: The study provides the first systematic cross-mapping of cost-engineering formulas embedded in Dutch and German DT ecosystems against a single seven-dimension matrix.
Formula Architecture: It systematizes modern cost formulas (e.g., $EAC = AC + (BAC - EV)/CPI $;$ LCC$ equations) and assigns them to specific architectural layers of a digital-twin framework.
Adaptation Pathway for Peru: The paper derives a context-sensitive, stepwise adaptation pathway for Peruvian public works. It proposes a hybrid framework that combines:
- Dutch-style open cost coding: Adaptable to Peru's national price databases (INEI, CAPECO) to ensure transparency and auditability.
- German-style life-cycle costing: Applicable to assets with significant operation-and-maintenance exposure (e.g., hospitals, schools, roads under long-term contracts).
- Regulatory Alignment: This pathway is explicitly mapped onto Peru's existing BIM 5D regulatory mandate (Decreto Supremo No. 289-2019-EF).

Significance and Claims
The paper claims that mature digital-twin cost-simulation ecosystems are not a single, transferable technology stack but a context-dependent combination of national standards, institutional drivers, and simulation methods matched to dominant project risks.

Feasibility: The study asserts that a hybrid framework is a feasible, low-cost adaptation pathway for reducing budget overruns in Peruvian public infrastructure, contingent upon addressing data governance and workforce capacity-building as preconditions.
Practical Application: It suggests that Peruvian regional and municipal governments can initiate "digital-twin-lite" pilots focusing on data and simulation-engine layers without requiring full IoT instrumentation. Furthermore, it posits that Earned Value Management indicators (CPI, SPI) can be coupled with BIM 5D quantities at marginal additional cost, and that shifting to probabilistic budgeting would materially improve contingency-fund allocation.
Limitations: The authors maintain a modest stance, acknowledging that the proposed framework is a structured literature synthesis rather than a primary empirical study. Consequently, the findings are framed as a qualitative-quantitative synthesis bounded by the cited evidence, and the authors explicitly state that the framework requires empirical validation through pilot implementation on Peruvian public-works projects before broader policy recommendations can be issued.