**4. Conclusions**

An OFS network was successfully developed and embedded during the 3D printing by AM of a PLA matrix reinforced by NiTi wire. Real-time monitoring of characteristic parameters, such as internal temperature and displacement shifts in the matrix and temperature variations in different treated zones of the wire allowed to use the OFS network as an NDT.

Joule heating experiments of NiTi wires were performed to assess changes to the sample temperature. The moments in which different currents were injected on the sample can be clearly proved and measured by all integrated fiber sensors. During the natural cooling, a thermal perturbation (structural transformation of R-phase to austenite) can be observed near 33.0 ◦C, and at the end of the cycling tests, a sample contraction of ~100 μm was detected on the PLA sample.

Regarding the tensile tests, the higher increase of temperature (exothermic behavior) arises when the applied force is between the 0.7 and 1.1 kN, on the heat-treated zone. During the unload step, a slope variation in the temperature behavior associated with the thermal-induced transformation in the heat-treated region (R-phase to austenite) was detected.

The embedded optical sensing methodology presented proved to be an effective, minimally invasive, and precise tool to identify materials' structural transformations, revealing to be a suitable solution to be applied as an NDT for Additive Manufacturing.

**Author Contributions:** Conceptualization and methodology, M.N., P.I., T.P., E.C., S.N., T.G.S. and F.M.B.F.; validation, M.N., P.I., T.G.S., F.M.B.F. and J.L.P.; data curation, M.N., P.I., T.P., E.C., S.N.; sensors fabrication, M.N., T.P. and S.N. Polymeric and NiTi wire fabrication, P.I., E.C., T.G.S. and F.M.B.F.; Software, M.N., P.I. and E.C.; Supervision, T.G.S., F.M.B.F. and J.L.P.; data analysis, M.N., S.N., P.I., T.G.S., F.M.B.F.; writing—original draft preparation, M.N.; writing—review and editing, all authors; funding acquisition, T.G.S., F.M.B.F. and J.L.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** Authors gratefully acknowledge the funding of Project POCI-01-0145-FEDER-016414 (FIBR3D), cofinanced by Programa Operacional Competitividade e Internacionalização and Programa Operacional Regional de Lisboa, through Fundo Europeu de Desenvolvimento Regional (FEDER) and by National Funds through FCT—Fundação para a Ciência e a Tecnologia, Grant numbers BI/UI96/6642/2018, BI/UI96/6643/2018, PD/BD/128265/2016 (DAEPHYS), respectively. E. Camacho and F.M. Braz Fernandes acknowledge the funding of CENIMAT/I3N by National Funds through FCT, references UID/CTM/50025/2019 and FCT/MCTES. T. G. Santos and P. Inácio acknowledge FCT—MCTES for its financial support via the project UIDB/00667/2020 (UNIDEMI). P. Inácio acknowledge FCT—MCTES for its financial support via the PhD scholarship FCT-SFRH/BD/146885/2019. This work was also developed within the scope of the project i3N, UIDB/50025/2020 & UIDP/50025/2020, financed by national funds through the FCT/MEC.

**Conflicts of Interest:** The authors declare no conflict of interest.
