Carlos Chávez-Negrete

Soil stiffness can be evaluated using various techniques, among which seismic geophysical tests stand out for their simplicity and applicability. Their fundamental principle is to determine the travel times of seismic waves between points within the soil mass using transducers. In this research, a laboratory seismic protocol was used to analyze three classic approaches to defining travel times: start-to-start, maximum peak-to-peak, and minimum peak-to-peak. The test was conducted on a well-graded gravel specimen using low-cost accelerometers and impact-generated compression waves. Thirty seismic determinations were obtained and processed by applying a low-pass filter derived from the frequency spectrum via the Fourier transform. Additionally, the envelope of the seismic signals obtained via the Hilbert transform was examined, and two alternative approaches based on this technique were proposed. The results show that the start-to-start method offers the best statistical consistency, whereas the maximum peak-to-peak approach is the least reliable, even generating negative travel times. Although the approaches derived from the Hilbert transform did not yield consistent results, their potential applicability in scenarios involving different transducers or types of seismic waves is proposed. Overall, the study contributes to the discussion of selecting interpretation criteria for laboratory seismic protocols.

Most truck stops in rural areas are located along high-demand highway corridors, consistent with current methods based on capacity and demand models. However, these models underestimate the safety aspect, failing to detect highway corridors with low traffic demand and low truck stop accessibility. This study proposes a Geographic Information System (GIS)-based planning methodology to identify highway corridors affected by atypical crash rates involving commercial trucks and truck stop shortages. The proposed methodology defines two indexes to measure commercial truck safety and truck stop supply, serving as a basis for identifying four levels of need for new truck stops using reclassification and map algebra techniques. Results reveal that the identified highway corridors exhibit atypical crash rates and largely coincide with areas of low truck stop accessibility and low to moderate truck demand. Thus, the methodology introduces an important component, truck safety, in identifying new parking locations, usually dismissed by existing models.

Rainfall-triggered debris flows are among the most destructive landslides affecting mountainous regions. On July 10, 2018, one such event occurred on the slopes of Cerro del Quinceo, Morelia, Mexico, exemplifying the devastating consequences of extreme {\color{blue} hydro-geological} conditions on settlements located on unstable, steep terrains. This paper investigates the numerical modeling of the complex geomechanical mechanisms behind the event. It shows an application of the Material Point Method (MPM) to provide insight into the simulation of these flow phenomena.

Se instrumentaron tres consolidómetros unidimensionales de suelos con un sistema virtual de bajo costo basado en sensores LVDT, Arduino® y LabVIEW®, con el objetivo de reacondicionar equipos convencionales y automatizar la adquisición de datos. Se desarrolló una interfaz gráfica que permite registrar en tiempo real la deformación del suelo, mejorando la precisión mediante lecturas en intervalos cortos y reduciendo la intervención del operador. Las pruebas comparativas con equipos tradicionales validaron la eficacia del sistema. Se concluye que esta instrumentación representa una alternativa económica, precisa y funcional frente a los equipos comerciales de alto costo.

Introduction: In many of the current geotechnical tests, there is a need to improve data acquisition protocols, in addition to optimizing test procedures. The present work proposes the evaluation of 3 convetional sensors in geotechnical tests. Methodology: The devices used were an S3C DC-DC linear variable differential transformer, the HC-SR04 ultrasonic distance sensor, and the SKU:SEN0193 capacitive soil moisture sensor. The general methodology consisted of the development of the communication protocol, interface, and display of readings for each device. Subsequently, the calibration and precision level of each sensor was obtained. Results: The precision and reliability of the sensors were expressed according to the linear fit, obtaining R2 correlation values ​​for all equipment. Discussion: The implemented systems allowed the detection of significant changes or trends in the behavior of the materials, obtaining satisfactory performances in most of the sensors, except for the moisture sensor SKU:SEN0193, which registered low precision. Conclusions: The use of sensors offers an alternative to improve some of the typical geotechnical tests. However, it is important to mention that a particular calibration must be carried out for each sensor to be used.

The common practice of measuring the water content of any soil mass involves a gravimetric methodology by obtaining the dry and wet mass of a soil-water mixture. In terms of execution, this procedure is simple but time-consuming since it requires at least 12 hours to be completed. Therefore, other measuring techniques could be applied, including devices such as sensors to obtain the water contents of soil. There are plenty of sensors in the market whose purpose is to obtain volumetric water content, which is a fundamental parameter of unsaturated soil mechanics. In the present research, three conventional low-cost volumetric water content sensors were evaluated (capacitive-based and resistive-based) in one of the most basic and common geotechnical tests: the Proctor compaction test. This test is appropriate for this assessment given the fact that its objective is to analyze how the dry density of soil varies regarding different water contents when using a specific compaction energy. The soil used in this work corresponds to sandy soil, with fair amount of gravel and fine material (SM). The interface of the sensors was done via an Arduino UNO board, and the data was processed and displayed using Python code. The findings of this research are presented in terms of calibration curves and linear correlation coefficients, and furthermore, a sensor repeatability test was performed in order to evaluate the accuracy of these types of sensors. The results obtained indicate that these low-cost sensors may not be the most recommended devices to use within the context of this specific geotechnical application.