http://hdl.handle.net/10174/29524 2026-04-10T16:43:29Z 2026-04-10T16:43:29Z Garção, José Barbosa, Joaquim http://hdl.handle.net/10174/41404 2026-02-23T11:43:20Z 2023-03-29T23:00:00Z

Title: An extended piecewise functions formalism for computing the internal forces and deflections of beams Authors: Garção, José; Barbosa, Joaquim Abstract: Beams are slender bodies vastly used to build many kinds of structures. In sit- uations where a beam can be accurately modeled using a set of governing equations given by linear differential equations, the solution for a loading case that is the combination of sev- eral loading cases, is given by the superposition of the solutions for each particular loading case. In structural mechanics this result is called the superposition principle. The most usual loading cases appearing in practice impose discontinuities in the derivatives of the internal forces and the deflection (displacements) of a beam. Therefore, when solving the governing equations, the domain must be partitioned in regions where all the derivatives are defined, then a solution is found in each region, and finally the boundary conditions and a set of compatibility conditions at the points of discontinuity are applied. Conse- quently the solutions are piecewise functions and the solution process becomes lengthy. Several techniques have been proposed to abbreviate this procedure, all supported in the validity of the superposition of solutions. One very straightforward technique involving a compact and intuitive notation, sometimes designated Macaulay’s method, is the use of the so called ”singularity functions” [1], ”step functions” [2] or Macaulay brackets, a sort of generalization of the Heaviside function, an idea introduced by Macaulay in 1919 [3], and further refined by other authors, as explained in [4]. This technique considers loadings involving only point forces, point couples or distributed forces of polynomial type which are active from some starting point until de end of the beam. When a distributed force is nonzero in only an interior segment of the beam, it must be modeled as two dis- tributed loads that are nonzero until the end of the beam, but which cancel each other in the portion of the beam where the original loading is zero. Besides possible mistakes with finding the fictitious cancellation load, this extra load doubles the computations when evaluating the solution. We consider that this technique can be extended to any loading case and avoid the need for fictitious loads, using therefore less computations, by adding another piecewise term to the formalism, at the expense of an arguably less expressive notation. Basically the superposition of solutions given by piecewise functions, with each function representing the complete solution for a single load, is generated and applied in a very systematic way. This communication is devoted to present this extension, as well as the corresponding au- tomation of the solution procedure using symbolic computation. Several illustrative exam- ples of application, which can appear in a context of teaching as well as in real structural design, are considered. With the availability of free computer algebraic systems, a few lines of code can provide solutions for any beam and frame problem that are accurately modeled by linear differential equations. Therefore symbolic computational tools should be introduced in the curricula and used when teaching these subjects.

2023-03-29T23:00:00Z José, D.F. Janeiro, Fernando M. Pires, V.F. Pires, A.J. Martins, J.F. http://hdl.handle.net/10174/38975 2025-07-09T13:56:56Z 2025-04-30T23:00:00Z

Title: Artificial Intelligence for Fault Detection in Photovoltaic Panels Authors: José, D.F.; Janeiro, Fernando M.; Pires, V.F.; Pires, A.J.; Martins, J.F. Abstract: This paper presents an Artificial Intelligence solution for fault detection and classification in photovoltaic systems. The proposed tool integrates electrical and visual analysis methods, including I-V curve analysis, direct difference measurement, infrared thermography, electroluminescence imaging, and visual inspection. These methods are enhanced by deep learning models, which achieve high accuracy in identifying and diagnosing faults. A Python-based web application provides users with an intuitive interface for real-time data processing and fault classification. Experimental results demonstrate the tool’s effectiveness, with neural network models achieving accuracy levels exceeding 98% in electrical methods and over 90% in visual methods. By optimizing fault detection processes, the tool reduces maintenance costs, minimizes downtime, and enhances the operational reliability of photovoltaic systems. This research represents a significant step toward scalable, automated maintenance solutions, ensuring photovoltaic systems’ sustainability and efficiency in the transition to renewable energy.

2025-04-30T23:00:00Z Luz, V. S. Faria, P. Rosado, L. S. Janeiro, Fernando M. Ramos, P. M. Angelis, A. D. Moschitta, A. Carbone, P. Meniconi, S. Capponi, C. Brunone, B. Cerlini, P. B. http://hdl.handle.net/10174/38971 2025-07-09T13:26:12Z 2025-04-30T23:00:00Z

Title: Design and Implementation of a Wireless Sensor Network for Water Resource Management Authors: Luz, V. S.; Faria, P.; Rosado, L. S.; Janeiro, Fernando M.; Ramos, P. M.; Angelis, A. D.; Moschitta, A.; Carbone, P.; Meniconi, S.; Capponi, C.; Brunone, B.; Cerlini, P. B. Abstract: Water resource management is a crucial aspect to achieve efficient usage of resources and sustainable development. This paper presents research activities within the More4Water project, which aims to address the issues faced in the water resource management field by developing dedicated sensor networks and investigating novel modeling approaches. In particular, this paper focuses on the description of the early stages of development related to the design of a wireless sensor network for monitoring water resources, water supply networks, and irrigation systems. One of the main elements of the employed system development methodology is the development of prototypes and testbeds. These allow for validating the requirements and mitigating the risk of incorrect requirement definition. The architecture of the main testbed is presented, together with experimental results obtained from a dedicated prototype. This prototype is used to confirm the feasibility of integrating Long Range (LoRa) low-power radio communication technology into the wireless sensor network architecture, thus leveraging the Internet-of-Things paradigm for the water resource management application and validating the methodology employed for system design.

2025-04-30T23:00:00Z Silva, Goncalo Semiao, Viriato http://hdl.handle.net/10174/37618 2024-12-19T17:02:51Z 2023-03-29T23:00:00Z

Title: Lattice Boltzmann Modeling of Rotating Channel Flows Authors: Silva, Goncalo; Semiao, Viriato Abstract: The lattice Boltzmann method (LBM) is recognised as a well-established numerical technique, capable of solving a wide variety of fluid flow problems [1]. This study will focus on a very specific application: the LBM modeling of rotating channel flows [2]. Despite the apparent simplicity of this problem, current CFD commercial codes still show difficulties in solving it [3], and LBM is no exception [2]. This study will tackle this problem, starting from a standard LBM-BGK model [4] subject to a popular force scheme [5] on a cubic lattice [6]. Then, by taking a step-by-step analysis, based on simple numerical examples, we will progressively unfold which difficulties the method is expected to face and which strategies can be adopted to overcome them. The points under analysis will cover almost every element of the LBM algorithm, namely: 1. LBM collision model: Is a single-relaxation-time model (LBM-BGK) able to support physically consistent numerical solutions? Should a two-relaxation-time model (LBM-TRT) [7] be preferred? 2. LBM forcing model: Is the popular Guo et al. [5] force scheme able to reproduce consistent external body forces in incompressible hydrodynamics [8]? Should we be expecting the inevitable presence of LBM force errors? What are their consequences? Is there any strategy to correct/mitigate them? 3. LBM lattice and equilibrium models: Do all cubic lattices (D3Q15, D3Q19 and D3Q27) perform identically, when the same equilibrium [6] is adopted? What might explain their differences? Can we correct them by tailoring the equilibrium according to the lattice [9]? This work will address each of these questions and, at the same time, provide an improved LBM scheme, capable of competing with (or even outperforming) traditional CFD strategies for this problem class.

2023-03-29T23:00:00Z