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<p><span>This paper presents a study about electrical performance of ceramic and polymeric insulators bio-contaminated with alga <span><em>Chlorella </em><span><em>vulgaris</em><span>. The performed tests involve ANSI 55-2 and ANSI 52-1 ceramic insulators and ANSI DS-15 polymeric insulators, all of them <span>used in distribution systems of Colombia. Biological contamination of insulators is realized using a controlled environment chamber <span>that adjusts the temperature, humidity and light radiation. The laboratory tests include measurements of flashover voltages and leakage currents and they were performed to determine how insulators are affected by biological contamination. After a series of laboratory tests, it was concluded that the presence of <span><em>Chlorella vulgaris </em><span>on the contaminated ceramic insulators reduces the wet flashover <span>voltage up to 12% and increases their leakage currents up to 80%. On the other hand, for polymeric insulators the effect of algae <span>growth on flashover voltages was not to strong, although the leakage currents increase up to 60%.</span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span></span></span></span></span></p>

Context: Anaerobic Digestion (AD) is a well-established process and widely used for wastewater treatment and power generation worldwide. In engineering, the Anaerobic Digestion Model number 1 (ADM1) is the preferred tool for predicting the behavior of AD. However, this model requires a detailed characterization of the input substrate, which is often a difficult and expensive process. This paper presents an analysis of the input waste variables in the ADM1 and its effects on the biogas production, in order to identify on which variables the characterization should be centered. Method: A sensitivity analysis was performed using a simple methodology that consisted of establishing a reference case and change the value of each input concentrations one at a time leaving the other parameters equal. For this a specific range of variation was defined using the values of parameter extracted from several references. Simulations were done in MATLAB/Simulink R using a routine developed by the authors based on the ADM1 implementation proposed in the Lund University, Sweden. Results: The analysis reveals that most critical variables involved in the methane production are temperature, volumetric flow rate of substrates and the concentrations of proteins, lipids and carbohydrates. For the case analyzed, variations in concentrations of lipids and carbohydrates increase the production of methane by more than 500 %. Conclusions: In the concentrations of proteins, lipids and carbohydrates should focus the characterization of waste input when the ADM1 is implemented. Also, simulations shows that the input concentrations should be carefully estimated because oversizing of these can cause erroneous results. Keywords: ADM1; anaerobic digestion; biogas production; sensitivity analysis. ResumenContexto: La digestión anaeróbica (DA) es un proceso bien establecido y ampliamente utilizado para el tratamiento de aguas residuales y generación de energía en todo el mundo. En ingeniería, el modelo de digestión anaeróbica número 1 (ADM1) es la herramienta preferida para predecir el comportamiento de la DA. Sin embargo, este modelo requiere una caracterización detallada del sustrato de entrada, que a menudo es un proceso difícil y costoso. En este trabajo se presenta un análisis de las variables que caracterizan el residuo de entrada en el ADM1 y sus efectos en la producción de biogás, con el fin de identificar cuáles son las variables en las que la caracterización debería centrarse. Método: Se realizó un análisis de sensibilidad utilizando una metodología simple que consistió en establecer un caso de referencia y cambiar el valor de cada una de las concentraciones de entrada una a la vez dejando los otros parámetros iguales. Para ello se definió un rango específico de variación utilizando los valores de parámetros extraídos de varias referencias. Las simulaciones se realizaron en MATLAB / Simulink R mediante una rutina desarrollada por los autores y basada en la implementación de ADM1 propuesta en la Universidad de Lund, Suecia. Resultad...

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