Sanitary and industrial wastewater discharged into rivers, is a general problem that occurs in most of the world and Mexico is not the exception, the main goal of this research is to determine based on simulations of pollutants concentrations, the assimilation capacity of the Gallinas River against discharges of agricultural and industrial wastewater from the cultivation and processing of sugar cane under two different hypothetical simulation scenarios, based on reproducing two well know scenarios. In sugarcane cultivation, large quantities of fertilizers are used whose main active components are based on nitrogen or phosphorus compounds, therefore, the wastewater resulting from sugarcane processing contains a high organic content from 20 to 40% of inorganic compounds, such as nitrogenous substances, organic acids, and phosphorous sulfates. For this reason, the physical–chemical variables of interest analyzed in this work are the PO $$_4$$4 (phosphate), NO $$_3$$3 (nitrate), and DO (dissolved oxygen). With the simulation results according to each scenery, it can be determined, that despite the continuous discharge of polluting elements, the Gallinas River has a good assimilation capacity thanks to reaeration processes that permit efficient recovery of the dissolved oxygen in the water column. Gallinas River is located in the region known as the Huasteca Potosina, this investigation is relevant for the region due to the River is of vital importance being the main tributary that allows socioeconomic development activities in this zone. To carry out the simulations, was used the Explorer Modeling System 8.4 (EFCD) model and was performed two samplings campaign along 15 km in the water body to calibrate the numerical model to represent the dry and wet seasons during May and September respectively named as calibration scenarios.

This work focuses on the effects of vegetation on a fluid flow pattern. In this numerical research, we verify the applicability of a simpler turbulence model than the commonly used k-" model to predict the mean flow through vegetation. The novel characteristic of this turbulence model is that the horizontal mixing-length is explicitly calculated and coupled with a multi-layer approach for the vertical mixing-length, within a general three-dimensional eddy-viscosity formulation. This mixing-length turbulence model has been validated in previous works for different kinds of non-vegetated flows. The hydrodynamic numerical model used for simulations is based on the Reynolds-averaged Navier–Stokes equations for shallow water flows, where a vegetation shear stress term is considered to reproduce the effects of drag forces on flow. A second-order approximation is used for spatial discretization and a semi-implicit Lagrangian–Eulerian scheme is used for time discretization. In order to validate the numerical results, we compare them against experimental data reported in the literature. The comparisons are carried out for two cases of study: submerged vegetation and submerged and emergent vegetation, both within an open channel flow.

Deployable mechanisms in CubeSat satellites have many problems with the system that provides the anchor position. The main defect of the traditional deployment mechanisms for solar panels in CubeSats is the lack of position system to block the back-driving of the panel when it reaches the final phase of the deployment. This generates spurious oscillations in the panel, affecting the photovoltaic process as well as generating fatigue in the mechanical elements of the mechanism (hinge or pin). In this work, the design, analysis and manufacture of a deployment mechanism for CubeSat solar panels is shown. A finite element method analysis was carried out in a hinge with an integrated blocking system as well as a double torsion spring, which can be used on CubeSats. The outcome shows the layout of the described anchor hinge and the used double-torsion spring, which provides a positive direction torque transfer. Likewise, the performed numerical analyses on the designed system, reduce the weight and optimise the geometry of the mechanism, showing its feasibility as well as the potential applications and further research in the area.

This paper describes the development of a two‐dimensional water quality model that solves hydrodynamic equations tied to transport equations with reactions mechanisms inherent in the processes. This enables us to perform an accurate assessment of the pollution in a coastal ecosystem. The model was developed with data drawn from the ecosystem found in Mexico’s southeast state of Tabasco. The coastal ecosystem consists of the interaction of El Yucateco lagoon with Chicozapote and Tonalá rivers that connect the lagoon with the Gulf of Mexico. The results of pollutants transport simulation in the coastal ecosystem are presented, focusing on toxic parameters for two hydrodynamic scenarios: wet and dry seasons. As it is of interest in the zone, the transport of four metals is studied: Cadmium, Chromium, Nickel, and Lead. In order to address these objectives, a self‐posed mathematical problem is solved numerically, which is based on the measured data. The performed simulations show how to characterise metals transport with an acceptable accuracy, agreeing well with measured data in total concentrations in four control points along the water body. Although for the accurate implementation of the hydrodynamic‐based water quality model herein presented boundary (geometry, tides, wind, etc.) and initial (concentrations measurements) conditions are required, it poses an excellent option when the distribution of solutes with high accuracy is required, easing environmental, economic, and social management of coastal ecosystems. It ought to be remarked that this constitutes a robust differential equation‐based water quality model for the transport of heavy metals. Models with these characteristics are not common to be found elsewhere.

The analytic solution of the gravimetric tensor components, making use of the gravitational potential equation for a three-dimensional volumetric assembly composed of unit prisms of constant density, demands a high computational cost. This is due to the gravitational potential of each one of these prisms must be calculated for all of the points of a previously defined observation grid, which turns out in a large scale computational cost. In this work we introduce a hybrid design and its parallel implementation, based on OpenMP and MPI, for the calculation of the vectorial components of the gravimetric field and the components of the gravimetric tensor. Since the computing time is drastically reduced, the obtained performance leads close to optimal speed-up ratios. The applied parallelization technique consists of decomposing the problem into groups of prisms and using different memory allocations per processing core to avoid bottleneck issues when accessing the main memory in one cluster node, which are generally produced when using too many execution threads over the same region in OpenMP. Due OpenMP can be only used on shared memory systems is necessary to use MPI for the calculation distribution among cluster nodes, giving as a result a hybrid code (OpenMP+MPI) highly efficient and with a nearly perfect speed-up. Additionally the numerical results were validated with respect to its sequential counterpart

Rapid and uncontrolled urban growth and land use changes in watersheds worldwide have led to increased surface runoff within metropolitan areas, coupled with climate change, creating a risk for residents during the rainy season. The city of San Luis Potosí is no exception to this phenomenon. One affected watercourse is the Garita Stream, which flows inside the city near urbanization. It is essential to analyze the effects of urban sprawl on this stream based on historical precipitation data for the town. Hydrological and topographical information were required to conduct this research. The hydrological study of the basin involved analyzing the region’s geomorphology and historical climatological data. For the stream’s topography, aerial photogrammetry using an unmanned aerial Vehicle (UAV) and Global Navigation Satellite System (GNSS) equipment was employed to conduct topographic surveys in the area. To find out when the Garita stream would overflow and which areas are most likely to flood, numerical modeling was done using 1D, 2D, and 3D programs like SWMM5 (Storm Water Management Model), HEC-RAS (Hydrologic Engineering Center’s River Analysis System), and EDFC Explorer (Environmental Fluid Dynamics Code). These models simulated different return periods and their correlation with current flooding events recorded in the area, thereby further proposing solutions to mitigate overflow issues. By conducting these simulations and analyzing the results, solutions can be suggested to address the overflow problems in the area based on historical flood events at various return periods caused by the Garita Stream.