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Field‐assisted processing techniques can enhance the kinetics of powder synthesis, accelerate sintering processes, and drive phase transformations at significantly lower temperatures compared to conventional methods. However, the exact nature of this nonthermal interaction between field and matter remains vastly speculative. A 2‐day workshop on “Electromagnetic Effects in Materials Synthesis” was organized at Carnegie Mellon University (Pittsburgh, USA) in June 2017, jointly sponsored by the U.S. National Science Foundation and the U.S. Office of Naval Research. This workshop gathered the scientific community working on field‐assisted techniques of materials processing. Inspired by the discussions held at the workshop, this paper summarizes the advancements to date and opens scientific questions and research opportunities in the three major field‐assisted sintering techniques (laser, microwave, and flash sintering). Significant challenges remain in (a) experimental design, measurements, and computational simulations to distinguish the nonthermal effects of the externally applied fields from conventional thermal phenomena; and (b) identifying fundamental mechanisms behind low temperature, nonthermal effects that produce phase transitions and microstructural evolution in materials under externally applied fields. We also present the recent developments in multiscale characterization techniques and the theory and modeling efforts, which aim to tackle the aforementioned grand multidisciplinary challenges facing researchers.

This paper presents laboratory tests and experiments using scale models to study the hydraulic behavior of permeable geosynthetics within unsaturated embankments subjected to rainfall infiltration. Water retention curves were measured in the laboratory in order to evaluate the unsaturated hydraulic characteristics of soil and geosynthetics. Model embankments were built using two layers of permeable geosynthetics; rainfall was simulated using an irrigation pipe. Embankments were subjected to wetting and drying processes; negative and positive pore water pressure and water contents within the model were measured. Comparison between Tempe pressure cell and hanging column test results showed that geosynthetics embedded within the soil approached saturation only when the pore water pressures of the surrounding soil were close to zero or positive. This behavior was also observed in the model tests. Local failure during the wetting processes was observed while pore water pressure increased immediately above the geosynthetic layers. In the models, where strips of geotextile were used, water could not accumulate above the geotextile, and instead drained down between strips. Strips of geotextile prevented the capillary barrier effect and allowed the free drainage of water through the embankment.

A recent meeting focused on accelerated materials design and discovery examined user requirements for a general, collaborative, integrative, and on-demand materials research platform.

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SUMMARYA multiphase coupled elasto-viscoplastic finite element analysis formulation, based on the theory of porous media, is used to describe the rainfall infiltration process into a one-dimensional soil column. Using this framework, we have numerically analyzed the generation of pore water pressure and deformations when rainfall is applied to the soil. A parametric study, including rainfall intensity, soil-water characteristic curves, and permeability, is carried out to observe their influence on the changes in pore water pressure and volumetric strain. From the numerical results, it is shown that the generation of pore water pressure and volumetric strain is mainly controlled by material parameters and n that describe the soil-water characteristic curve. A comparison with the laboratory results shows that the proposed method can describe very well the characteristics observed during the experiments of one-dimensional water infiltration into a layered unsaturated soil column.

ResumenSe propone un modelo para el pronóstico del precio de la energía eléctrica en Colombia mediante el uso de redes neuro-difusas. Se utilizan dos estructuras de redes incluyendo como entradas la serie de precios diarios en la primera y la serie de precios más el nivel medio de los embalses en la segunda. Los resultados son comparados con dos estructuras de redes neuronales y con un modelo Autoregresivo Condicional Heterocedástico Generalizado (GARCH). Los datos históricos fueron obtenidos de la Compañía XM del Grupo ISA; datos para 120 días son usados para entrenamiento y los 31 días siguientes para verificar la capacidad predictiva del modelo. Se encontró ventajas en este último dentro del periodo de muestreo para una variable de entrada, pero un mejor desempeño de las redes neuro-difusas en el periodo fuera de la muestra tanto para una como para dos variables de entrada. Palabras clave: precio de la electricidad, redes neuronales artificiales, redes neuro-difusas, modelos de series de tiempo Electricity Price Forecasting using Neurofuzzy Networks AbstractA forecasting model for the price of electricity in Colombia using neurofuzzy networks is proposed. Two network structures including the price series in the first and the price series plus the reserve water levels in the latter are used. The results are compared with two neural networks structures and a Generalized Autoregressive Conditional Heteroscedasticity model (GARCH). Historical data were supplied by the Company XM of the ISA Group; data for 120 days were used as for training the network and the following 31 days were used for testing the predictive capabilities of the model. The GARCH model shows better adjustment within the training period for the prices series as input, but the neurofuzzy networks have better forecasting performance for one and for two input variables.