Surrogate models to predict maximum dry unit weight, optimum moisture content and California bearing ratio form grain size distribution curve

This study evaluates the applicability of using a robust, novel, data-driven method in proposing surrogate models to predict the maximum dry unit weight, optimum moisture content, and California bearing ratio of coarse-grained soils using only the results of the grain size distribution analysis. The data-driven analysis has been conducted using evolutionary polynomial regression analysis (MOGA-EPR), employing a comprehensive database. The database included the particle diameter corresponding to a percentage of the passing of 10%, 30%, 50%, and 60%, coefficient of uniformity, coefficient of curvature, dry unit weight, optimum moisture content, and California bearing ratio. The statistical assessment results illustrated that the MOGA-EPR provides robust models to predict the maximum dry unit weight, optimum moisture content, and California bearing ratio. The new models’ performance has also been compared with the empirical models proposed by different researchers. It was found from the comparisons that the new models provide enhanced accuracy in predictions as these models scored lower mean absolute error and root mean square error, mean values closer to one, and higher a20−index and coefficient of correlation. Therefore, the new models can be used to ensure more optimised and robust design calculations

Importancia de las redes neuronales artificiales en la ingeniería civil: una revisión sistemática de la literatura

Las redes neuronales artificiales (RNA) tienen un papel relevante en la actualidad, diversas áreas aplican esta técnica por las ventajas que presentan para resolver problemas complejos con muchas restricciones en comparación con los métodos tradicionales, que están quedando desfasados. Se conoce muy poco acerca de esta técnica y su aplicación en distintas ramas de la Ingeniería Civil. Por tal motivo, la presente investigación tiene por objetivo realizar una revisión sistemática de la literatura para identificar el uso de esta técnica y determinar los resultados de la aplicación de modelos de RNA en la ingeniería civil. Se incluyeron un total de 41 artículos científicos que se distribuyen de la siguiente forma: 6 en Scopus, 1 en ScienceDirect, 23 en ProQuest, 7 en Google Académico, 2 en Dialnet, 2 en SciELO. Se encontró que las RNA son utilizadas para predecir o pronosticar variables asociadas a los campos de estudio de la ingeniería civil, se hallaron 8 aplicaciones de RNA para propiedades del concreto, 11 para propiedades del suelo, 5 para análisis sísmico, 9 para hidráulica, 7 para valorización de inmuebles y 1 para diseño de puentes. Así mismo se encontró que el Perceptrón Multicapa es el modelo de RNA más utilizada, logrando en promedio un R2 de 0.99, lo que demuestra ventajas para resolver problemas con precisión, en tiempos más cortos, con datos faltantes en los conjuntos de datos, así como la reducción del factor de error.Artificial neural networks (ANN) have a relevant role nowadays; several areas apply this technique due to the advantages they have to solve complex problems with many constraints compared to traditional methods, which are becoming outdated. Very little is known about this technique and its application in different branches of Civil Engineering. For this reason, the present research aims to conduct a systematic review of the literature to identify the use of this technique and to determine the results of the application of ANN models in civil engineering. A total of 41 scientific articles were included, distributed as follows: 6 in Scopus, 1 in ScienceDirect, 23 in ProQuest, 7 in Google Scholar, 2 in DialNet, 2 in SciELO. It was found that ANNs are used to predict or forecast variables associated with the fields of study in civil engineering; 8 applications of ANN were found for concrete properties, 11 for soil properties, 5 for seismic analysis, 9 for hydraulics, 7 for real estate valuation and 1 for bridge design. Likewise, it was found that the multilayer Perceptron is the most used ANN model, achieving an average R2 of 0.99, which shows advantages to solve problems with precision, in shorter times, with missing data in the data sets, as well as the reduction of the error factor

On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils

The California Bearing Ratio (CBR) is an important index for evaluating the bearing capacity of pavement subgrade materials. In this research, random subspace optimization-based hybrid computing models were trained and developed for the prediction of the CBR of soil. Three models were developed, namely reduced error pruning trees (REPTs), random subsurface-based REPT (RSS-REPT), and RSS-based extra tree (RSS-ET). An experimental database was compiled from a total of 214 soil samples, which were classified according to AASHTO M 145, and included 26 samples of A-2-6 (clayey gravel and sand soil), 3 samples of A-4 (silty soil), 89 samples of A-6 (clayey soil), and 96 samples of A-7-6 (clayey soil). All CBR tests were performed in soaked conditions. The input parameters of the models included the particle size distribution, gravel content (G), coarse sand content (CS), fine sand content (FS), silt clay content (SC), organic content (O), liquid limit (LL), plastic limit (PL), plasticity index (PI), optimum moisture content (OMC), and maximum dry density (MDD). The accuracy of the developed models was assessed using numerous performance indexes, such as the coefficient of determination, relative error, MAE, and RMSE. The results show that the highest prediction accuracy was obtained using the RSS-based extra tree optimization technique

Desarrollo de un modelo de redes neuronales artificiales para predecir las propiedades mecánicas del suelo

En este estudio se desarrollan modelos de redes neuronales artificiales para la predecir las propiedades mecánicas del suelo de la región Lambayeque. La tesis se realizó para facilitar la obtención de resultados precisos y se calculen en el menor tiempo posible. Se reunieron un total de 285 resultados de pruebas de proyectos de carreteras realizados en la región Lambayeque. Asimismo, las variables de entrada utilizadas fueron de los ensayos de contenido de humedad, contenido de sales, análisis granulométrico y límites de consistencia. Los modelos alcanzaron un error cuadrático medio favorable cuando estimaron la máxima densidad seca (0.003 g/cm3 ), el óptimo contenido de humedad (2.42%), la relación de soporte de California al 95 % de la máxima densidad seca (6.35 %) y la relación de soporte de California al 100 % de la máxima densidad seca (21.80 %). En cuanto al error absoluto medio, se obtuvieron resultados favorables al predecir la máxima densidad seca (0.035 g/cm3 ), el óptimo contenido de humedad (1.13 %), la relación de soporte de California al 95 % de la máxima densidad seca (1.65 %) y la relación de soporte de California al 100 % de la máxima densidad seca (2.79 %). Aunque son numerosos los elementos que influyen en el comportamiento del suelo, los resultados recogidos revelaron el rendimiento y las capacidades de las redes neuronales artificiales para predecir los atributos del suelo. Los modelos propuestos pueden utilizarse en proyectos reales como ayuda si se quiere obtener estas propiedades de manera rápida.TesisInfraestructura, Tecnología y Medio Ambient

Counter Unmanned Aircraft Systems Technologies and Operations

As the quarter-century mark in the 21st Century nears, new aviation-related equipment has come to the forefront, both to help us and to haunt us. (Coutu, 2020) This is particularly the case with unmanned aerial vehicles (UAVs). These vehicles have grown in popularity and accessible to everyone. Of different shapes and sizes, they are widely available for purchase at relatively low prices. They have moved from the backyard recreation status to important tools for the military, intelligence agencies, and corporate organizations. New practical applications such as military equipment and weaponry are announced on a regular basis – globally. (Coutu, 2020) Every country seems to be announcing steps forward in this bludgeoning field. In our successful 2nd edition of Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets (Nichols, et al., 2019), the authors addressed three factors influencing UAS phenomena. First, unmanned aircraft technology has seen an economic explosion in production, sales, testing, specialized designs, and friendly / hostile usages of deployed UAS / UAVs / Drones. There is a huge global growing market and entrepreneurs know it. Second, hostile use of UAS is on the forefront of DoD defense and offensive planners. They are especially concerned with SWARM behavior. Movies like “Angel has Fallen,” where drones in a SWARM use facial recognition technology to kill USSS agents protecting POTUS, have built the lore of UAS and brought the problem forefront to DHS. Third, UAS technology was exploding. UAS and Counter- UAS developments in navigation, weapons, surveillance, data transfer, fuel cells, stealth, weight distribution, tactics, GPS / GNSS elements, SCADA protections, privacy invasions, terrorist uses, specialized software, and security protocols has exploded. (Nichols, et al., 2019) Our team has followed / tracked joint ventures between military and corporate entities and specialized labs to build UAS countermeasures. As authors, we felt compelled to address at least the edge of some of the new C-UAS developments. It was clear that we would be lucky if we could cover a few of – the more interesting and priority technology updates – all in the UNCLASSIFIED and OPEN sphere. Counter Unmanned Aircraft Systems: Technologies and Operations is the companion textbook to our 2nd edition. The civilian market is interesting and entrepreneurial, but the military and intelligence markets are of concern because the US does NOT lead the pack in C-UAS technologies. China does. China continues to execute its UAS proliferation along the New Silk Road Sea / Land routes (NSRL). It has maintained a 7% growth in military spending each year to support its buildup. (Nichols, et al., 2019) [Chapter 21]. They continue to innovate and have recently improved a solution for UAS flight endurance issues with the development of advanced hydrogen fuel cell. (Nichols, et al., 2019) Reed and Trubetskoy presented a terrifying map of countries in the Middle East with armed drones and their manufacturing origin. Guess who? China. (A.B. Tabriski & Justin, 2018, December) Our C-UAS textbook has as its primary mission to educate and train resources who will enter the UAS / C-UAS field and trust it will act as a call to arms for military and DHS planners.https://newprairiepress.org/ebooks/1031/thumbnail.jp

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

XXXV Congress of the International Association of Hydrogeologists, Groundwater and Ecosystems – Abstract Book

Resumos das comunicações do XXXV Congresso da Associação Internacional de Hidrogeólogos (IAH

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen