Official Scientific Output — THEK Research Institute
Scientific papers, peer-reviewed journal articles, Zenodo records, Figshare deposits, and technical reports
produced by the THEK Research Institute and its affiliated research centers, including SERRA, NFF, FGET, VRR, SPOT, and SSM.
Research portfolio of M.Sc. (TUM) Marcelo Moncayo Theurer.
16Indexed Scientific Outputs
9Zenodo Records (DOI)
22ResearchGate Publications
25+Years Research Background
Featured Research
Original Frameworks & Systems
Flagship scientific outputs developed at the THEK Research Institute — original complex-systems frameworks, empirical validations, and automated AI systems for scientific knowledge generation.
Novel Complex Systems Frameworks
WP-001EN
Seismic Energy Release Risk Assessment (SERRA) — A Physical Energy-Based Framework for Seismic Behavior Characterization, Reactivation Stage Identification, and Seismic Risk Mapping
An original energy-based framework for seismic risk assessment. SERRA introduces a physically grounded methodology that characterizes seismic behavior, identifies reactivation stages, and constructs risk maps from released seismic energy data — a foundational THEK contribution to earthquake engineering science.
Empirical Validation of the Seismic Energy Release Method SERRA / MEL
Empirical validation study confirming the predictive and characterization capabilities of the SERRA / MEL seismic energy release framework against historical seismic records. Establishes the scientific rigor of the THEK energy-based approach to earthquake engineering and risk assessment.
Formula Genomics and Evolution Theory (FGET) — Teoría Genómica y Evolutiva de las Fórmulas
A foundational theoretical framework proposing that formulas behave as evolving mathematical entities with genomes, phenotypes, mutation, recombination, selection, and evolutionary fitness. FGET positions NFF as its operational instrument for genomic reverse engineering of patterns.
An original recursive coefficient-nesting framework for interpretable formula generation, mathematical modeling, and explainable AI. NFF operates as the methodological engine connecting observable patterns with structured, traceable mathematical equations.
Original THEK methodological framework for systematic variable screening, reduction, and ranking prior to mathematical model construction. VRR supports structured selection of influential variables and is used in conjunction with NFF and related THEK modeling workflows.
Original THEK method for estimating the natural period of structures through a compact empirical formulation, developed for rapid engineering assessment and comparison with conventional period-estimation approaches.
Soil Spring Model (SSM): Validated Empirical Correlations for Soil Spring Coefficient Estimation in Clay Soils Derived Through the Nested Formula Framework (NFF)
Validated empirical correlations for estimating soil spring coefficients in clay soils for soil–structure interaction modeling. The published record documents the SSM methodology, its engineering scope, verification, and its connection with NFF and the Elastic Spring Point Protocol.
Advanced Automated LLM-Based AI Models for Seismic and Scientific Information Systems
WP-008EN
AI-Driven Automated Scientific News Generation and Dissemination System Using Large Language Models and Telegram Integration
A fully autonomous AI pipeline that integrates large language models with RSS aggregation, automated editorial processing, and multi-channel dissemination via Telegram. The system underpins the THEK Press Engine and constitutes one of the first applied LLM journalism architectures in scientific communication.
ProfeBot: A Low-Cost Generative AI Assistant for Earthquake Engineering Education in Latin America
Development and deployment of ProfeBot, an educational AI assistant built on generative language models, designed to democratize advanced earthquake engineering concepts for students and professionals in resource-constrained academic environments across Latin America.
All scientific outputs indexed by THEK Research Institute. White papers (WP) carry Zenodo DOI registration, with original complex-systems frameworks listed first. Journal papers (JP) are published in peer-reviewed and indexed repositories.
Interaction = repository views + downloads. Zenodo values are requested live when this page opens; ResearchGate does not expose reliable per-publication reads publicly in the profile view, so those values are not fabricated.
ID
Publication Title
Lang
Status
DOI
Interactions
Links
WP-001
Seismic Energy Release Risk Assessment (SERRA) — A Physical Energy-Based Framework for Seismic Behavior Characterization, Reactivation Stage Identification, and Seismic Risk Mapping
Soil Spring Model (SSM): Validated Empirical Correlations for Soil Spring Coefficient Estimation in Clay Soils Derived Through the Nested Formula Framework (NFF)
The THEK publication portfolio spans six interconnected scientific domains developed over more than 25 years of independent research.
01
Seismic Energy Release
Original SERRA / MEL energy-based frameworks for seismic behavior characterization, reactivation stage identification, and seismic risk mapping — the core contribution of THEK to earthquake science.
02
Earthquake Engineering
Seismic-resistant structural design, ground motion characterization, spectral analysis, attenuation laws, and accelerogram recovery for engineering applications.
03
AI & Scientific Systems
AI-driven scientific journalism, LLM integration pipelines, generative AI education systems, and autonomous knowledge dissemination architectures for scientific research.
04
Structural Dynamics
Advanced structural response analysis, carbon fiber reinforcement, reduction factors, response spectra, and seismic performance frameworks for built infrastructure.
05
Scientific Education
AI-assisted engineering education, low-cost pedagogical AI tools, interdisciplinary learning systems, and knowledge democratization for engineering students in developing regions.
06
Computational Methods
Numerical simulation, mathematical modeling, finite element methods, and computational frameworks applied to seismic and Earth-system science.
How to Cite
Citation Guidelines
To cite any THEK Research Institute publication, use the following format. For Zenodo-registered works, always include the DOI for persistent reference.
APA Format
Moncayo Theurer, M. (2025). [Title of publication]. THEK Research Institute.
Zenodo. https://doi.org/10.5281/zenodo.[record_id]
Institutional Attribution
M.Sc. (TUM) Marcelo Moncayo Theurer — Director & Lead Researcher
THEK Research Institute — Advanced Scientific, Engineering & Technological Think Tank
Technical University Munich (TU München) · BRI-IISEE · University of Tokyo
Full Professor with Tenure (Profesor Titular) — Universidad de Guayaquil
Verified research presence
Marcelo Moncayo Theurer — Research Profiles
Cross-platform access to current repository records, publications, and research dissemination.
Verified Amazon titles by M.Sc. (TUM) Marcelo Moncayo Theurer. The Amazon author/search pages may contain additional editions or titles; this section lists only titles that could be independently located in the current public index.
AMAZON BOOK 01
TECTONICA DE PLACAS
Ingeniería de Terremotos y Energía Liberada · Book 1 of 4