Disastrous building collapses often occur due to the propagation of local-initial failures. Although effective for small initial failures, current design approaches addressing this issue can inadvertently increase the risk of catastrophic collapse propagation after large initial failures. The ERC Consolidator Grant Endure has introduced a novel fuse-based segmentation design approach to overcome this alarming limitation, successfully testing a full-scale precast building to validate its effectiveness. While this approach can be advantageous for different types of structures, its implementation in precast concrete buildings is key to maximizing its impact. Due to several advantages in terms of efficiency and sustainability, precast structures are being increasingly used for high-occupancy and critical buildings. Incorporating fuse-based segmentation in these structural systems would thus provide a new last line of defence against catastrophic failures in the buildings for which the consequences of such an occurrence are most severe. However, at this stage of development, the design of a fuse-based segmented precast building requires advanced computational analysis and several iterative procedures that are unfeasible for most building projects. Such complexity can hinder the adoption of fuse-based segmentation in practice. Therefore, truly unlocking the market penetration potential of fuse-based segmentation solutions for precast buildings requires cost-effective implementation tools and validation across a broader range of precast systems. Encast aims to bridge these gaps by simplifying design procedures, developing user-friendly software, performing experimental demonstrations, and crafting a tailored exploitation strategy for fuse-based segmentation solutions for precast buildings. The project’s success will lead to wider adoption of robust precast systems, helping deliver more affordable and sustainable buildings that contribute to improving societal resilience.

Contaminant events disrupt stability and resilience of increasingly vulnerable soil and groundwater. Identifying where, when and how much contaminant spill is released into aquifers is critical for strengthening the competitiveness of EU in risk-reduction management, and Forensic Hydrogeology, a growing discipline that applies scientific knowledge in legal resolutions. Existing model solutions estimate the origin and affected area, but numerical challenges impose too restrictive assumptions to properly account for multiple sources or suitable aquifer characterization. The scientific goal of FORENSHYD is to develop a novel, flexible and reliable ensemble Kalman filter data assimilation method (EnKF) for the optimal identification of contaminant sources and occurrence of reactive pollutants in near-actual conditions. Latest assessed developments of Dr. Gómez-Hernández set EnKF as an excellent optimization tool for the simultaneous identification of the spatial variability of conductivities, the location, and the release function of polluting sources. A step toward coupling the algorithm with machine learning techniques may overcome ill-posed solutions, stemmed from nonlinearities between parameters and variables in the state equation, to solve kinetic-controlled reactive transport problems and to optimize data collection in groundwater observation network systems, a topic of renewal interest in administration and industrial sector. We test spurious effects of aquifer heterogeneity, reactive parameters, and initial/boundary conditions in synthetic scenarios, sandbox experiments and two demonstration sites. Transfer of this novel technology in well-reported, practical and universal open source packages will reinforce the leadership and employability in the global market of intersectorial and interdisciplinary European stakeholders. The societal value of FORENSHYD is to improve mitigation strategies, and clarify environmental liability, in liaises with Horizon 2020.

For over 5 decades, digital electronics has covered the increasing demand for computing power thanks to a periodic doubling of transistor density in integrated circuits. Currently, such scaling law is reaching its fundamental limit, leading to the emergence of a large gamut of applications that cannot be supported by digital electronics, specifically, those that involve real-time analog multi-data processing, e.g., medical diagnostic imaging, drug design and robotic control, among others. Here, an analog computing approach implemented in a reconfigurable non-electronic technology such as programmable integrated photonics (PIP) can be more efficient than digital electronics to perform these emerging applications. However, actual computing models were not conceived to extract the benefits of PIP. The aim of ANBIT is to develop an entirely new class of computation theory – termed Analog Photonic Computation (APC) – specifically designed to unleash the full potential of PIP technology. The core concept revolves around the idea of performing analog operations on a new unit of information, the analog bit or anbit, conceived as a two-dimensional analog function and matched to the building block of PIP circuits. ANBIT will reach its objectives by: 1) developing the theory of APC based on operations (gates) of anbits, 2) translating the principles of APC to the design of PIP circuits by concatenating single- and multi-anbit gates, 3) fabricating, packaging, testing and validating silicon PIP chips capable of implementing complex APC architectures, 4) designing, coordinating, setting and performing experiments that will prove the unique potential of APC in computational and signal processing applications with huge takeover. ANBIT will deliver a new computing paradigm that extracts the full potential of PIP technology, which in turn will have a crucial impact on fundamental and applied research and on our information society.

Programmable integrated photonics (PIP) is an emerging new paradigm that aims at designing common integrated optical hardware resource configurations, capable of implementing an unconstrained variety of functionalities by suitable programming. The work carried out within the Advanced Grant ERC-ADG-2016-741415 UMWPCHIP of which I was the Principal Investigator, allowed me to lay the foundation for the first technical stages of a novel revolutionary concept, the Field Programmable Photonic Gate Array (FPPGA), developed in the context of a Proof-of-concept Grant ERC-POC-2019-859927-FPPAs. Currently, the core of the processor is a uniform 2D programmable photonic waveguide mesh, formed by replicating hexagonal unit cells. This layout suffers from limited flexibility in the spectral period and sampling time values. The challenge is to develop and demonstrate solutions that overcome these limitations and which can be easily incorporated into existing mesh designs. In NP-Mesh I aim to demonstrate and validate the concept of non-periodic programmable photonic integrated waveguide meshes formed by embedding defect cells into the otherwise uniform 2D hexagonal mesh. Including defect cells solves the problem of spectral period limitation through the exploitation of the Vernier effect as well as the as the sampling time resolution limitation of the uniform waveguide mesh. My working roadmap will include: 1) carrying out the required research activities linked to the development of the proposed technical concepts, 2) validating them through outsourced chip fabrication in an external foundry followed by measurement and characterization experiments carried out in my lab at UPV, 3) generating the new intellectual property rights (IPRs) for the new results via patent writing and application and transferring the new IPR to the spinoff company iPronics, which I co-founded three years ago with the help of ERC-POC-2019-859927-FPPAs.