This study provides a comprehensive analysis of Ground Penetrating Radar (GPR) data processing techniques for detecting water leakage in urban pavements. By examining GPR images characterized by continuous and discontinuous high-amplitude reflections, the research identifies clear indicators of water saturation caused by leaking underground pipes. Computer modeling of GPR profiles enables effective comparisons with real data and helps in calibrating key GPR attributes such as energy, amplitude variance, and RMS amplitude. These attributes allow for the precise delineation of leakage zones in both synthetic and real GPR datasets collected in the Amazon region of Brazil. The Reflector Tilt Method (RTM) significantly enhances GPR data analysis, especially for detecting subsurface water leaks. RTM utilizes changes in the relative dielectric constant and electromagnetic wave velocity induced by water saturation in unconsolidated, horizontally stratified sand layers. By analyzing the tilt of reflections in GPR profiles, RTM differentiates between dry and saturated zones, providing insights into the geometry and extent of water infiltration. Notably, this study demonstrates how increased subsurface water saturation causes underlying reflectors to tilt. Using the tilt angle, we propose a novel technique to quantify the increase in the dielectric constant due to water saturation. This technique could also be adapted to detect leaks involving other fluids, as long as there is a strong contrast between the dielectric constant and the background. The integration of RTM improves the creation of accurate three-dimensional models of affected areas, enhancing leak detection and aiding in understanding water movement dynamics within the subsurface. The study underscores the importance of combining GPR attributes with RTM to generate detailed 3D models of leakage zones, which are essential for estimating the volume of infiltrated areas. Observations indicate significant water saturation near leaking pipes at shallow depths, with saturation levels decreasing rapidly as depth increases. By identifying 2D geophysical signatures of water leaks in public distribution networks, the research highlights the effectiveness of non-invasive GPR methods in mitigating risks such as soil erosion and surface collapse. This approach demonstrates the utility of GPR attributes and RTM as essential tools for assessing urban pavement integrity, enabling early detection of leaks and precise mapping of affected zones. The findings contribute significantly to the efficient and sustainable management of urban infrastructure, enhancing maintenance strategies and reducing potential hazards associated with undetected fluid leaks.

Esse artigo aborda a discussão acerca da instrução e aprendizagem de Matemática no contexto educacional brasileiro, referente ao aprendizado dos alunos do 3° ano do Ensino Médio. A questão de pesquisa foi como se designa o ensino e aprendizagem de Matemática no ensino médio? Com base nessa questão, justificou-se diagnosticar a aprendizagem dos educandos a respeito do tema. Objetivo foi realizar um diagnóstico do processo de ensino-aprendizagem da Matemática em discentes oriundos do 2ª ano do Ensino Médio, especificamente alunos matriculados no 3º ano do Ensino Médio. Para verificar a aprendizagem dos estudantes utilizamos 1 instrumentos de pesquisa que foi um questionário. A pesquisa foi realizada com 100 alunos do ensino médio e as informações coletadas foram analisadas a partir de 3 categorias, sendo elas: o perfil social; impressões metodológicas do ensino e a avaliação da aprendizagem, as quais possibilitaram o entendimento sobre o assunto em questão sob o direcionamento que essa pesquisa seguiu. Diante dos resultados obtidos, podemos conhecer mais das características sociais dos estudantes e a metodologia de ensino usada pelos professores, que de alguma forma pode influenciar no metodologia de aprendizagem e nos resultados avaliativos dos estudantes.