2026
Journal article
Sensor informativeness, identifiability and uncertainty in Bayesian inverse problems for structural health monitoring
Mechanical Systems and Signal Processing 257, 114606
Dr.-Ing. habil. · Dresden, Germany
Tammam Bakeer
Computational structural mechanics · uncertainty and information · digital assessment of structures
Decisions about real structures have to be made before the evidence is complete. My work asks when what we already know is enough.
I develop computational, reliability-based and data-informed methods for the analysis and assessment of complex structural systems, and for decision-making under uncertainty. The work runs across structural mechanics, reliability theory, numerical modelling and complexity science — and deliberately on both sides of the line between science and engineering practice.
01
A short introduction
What holds my attention is how structures behave as systems rather than as collections of individual parts — and how difficult it is to reduce that behaviour to a single quantity without losing what matters. My work seeks to keep that complexity in view while still arriving at conclusions that support engineering decisions.
This work brings together structural engineering, computational mechanics, reliability theory, numerical modelling, physics and complexity science. The methods I develop are intended to support structural assessment and engineering practice, inform design standards and advance scientific research.
Over the past twenty years, this has involved nonlinear analysis, finite element modelling, reliability-based assessment and contributions to European standardization. My recent research focuses more specifically on the information contained in structural measurements: what they reveal, what remains uncertain and when the available evidence is sufficient to support a decision.
Beyond engineering, I remain interested in physics and mathematics, the history of scientific ideas and the people behind them, and portrait drawing — different ways of examining how complex systems and forms hold together.
02
The question I keep returning to
Monitoring and testing now produce more data about existing structures than engineers know what to do with. Bayesian methods can estimate stiffness, damage or remaining capacity from it — but a structural decision almost never requires those quantities to be known precisely. It requires one decision: accept the structure as it is, or intervene.
Those are different questions, and the second is often settled long before the first. A prediction can be wildly uncertain and the decision still obvious, because every future the data still allow points the same way. And a very precise prediction can leave the decision wide open, if the remaining uncertainty concerns exactly what the limit state depends on.
Determining which case applies — and how long it persists — is the more useful problem, and the one I am working on now.
03
What I work on
01
Nonlinear computational structural mechanics
Finite element and finite–discrete element formulations, constitutive and interface models, stability, damage and collapse. The numerical machinery needed to follow a structure past its peak load — and the computational capability needed to apply these methods at the scale of real structures.
02
Structural reliability and safety concepts
Reliability of nonlinear systems, where the failure domain is curved and several modes compete. The general partial safety factor theory that extends the classical format to them, together with quality control, conformity assessment and code calibration.
03
Information, identifiability and inverse problems
What observations actually reveal about a structure: Bayesian inversion, sensor informativeness, spatially distributed parameter fields — and decision identifiability, the question of when the available evidence already settles the decision that has to be made.
04
Monitoring, digital twins and predictive assessment
Coupling measurements with continuously calibrated models so that the estimated condition of a structure can be updated continuously: data assimilation, service-life prediction and the case for extending service life on the basis of evidence rather than assumption.
05
Scientific machine learning and complexity
Mechanics-informed operator learning and structure-preserving surrogates — fast, mesh-independent solvers that stay physically admissible — and measures of complexity for systems too large to reason about one member at a time.
06
Engineering practice and standardization
Where the methods are tested: assessment of existing structures and infrastructure, earthquake resilience and retrofitting, and the translation of research into European and German design rules — the point at which a method’s practical value is established.
04
Recent
Aug 2026
Conference paper — Information-guided Bayesian modelling for structural health monitoring, with Max Herbers and Steffen Marx, presented at SMAR 2026 in Dresden, in the session on intelligent digital methods for extending the service life of structures beyond 100 years.
2026
Journal article — Sensor informativeness, identifiability and uncertainty in Bayesian inverse problems for structural health monitoring, in Mechanical Systems and Signal Processing. DOI
2026
New preprint — Local information operators for spatial identifiability in distributed-parameter inverse problems in computational mechanics. arXiv
2025
Invited lecture at the JCSS workshop Global Reliability of Structures & Code Calibration, Tongji University, Shanghai — on complexity, modelling and the global reliability of structural systems.
2024
Contributing author to Reliability background of the Eurocodes, published by the Publications Office of the European Union. Read it
05
Selected publications
2026
Preprint
Local information operators for spatial identifiability in distributed-parameter inverse problems in computational mechanics
Preprint, arXiv:2605.28601
2023
Journal article
General partial safety factor theory for the assessment of the reliability of nonlinear structural systems
Reliability Engineering & System Safety 234, 109150
2024
Book / chapter
Reliability background of the Eurocodes: support to the implementation, harmonisation and further development of the Eurocodes
Publications Office of the European Union, Luxembourg
06
Where this is going
I am developing an independent research programme on information sufficiency for structural decisions — what measurements must establish before a structure can be accepted, and when the available evidence already settles the decision. The theory, algorithms and first publications are in place, and I have prepared a funding proposal. The programme now needs an institutional home.
That can take several forms: a professorship in structural mechanics, numerical methods or structural reliability; a hosted research project or a visiting appointment; or a research-lead role in industry, where the same questions are asked about real assets.
If this aligns with the work of your group or company, I would be glad to discuss it.