Kinetic and physiological parameters in AS-1404 model fitted to experimental data with GA optimization.ParameterControl experimentsTest experimentsMonod constant for cell growth, K3 (g/L)26.1920.08Inhibition constant of cell growth by glucose, Ki (g/L)83.4496.45Inhibition constant of cell growth by ethanol, K3E (g/L)49.9947.61Specific cell death rate, kd (1/h)0.0830.005Maximal specific growth rate, μm (1/h)0.460.985Constant for growth associated ethanol formation, a (g/g)2.892.99Non-growth associated specific ethanol production rate, b (g/g/h)1.991.99Average yield coefficient of cell mass on glucose, YX/G (g/g)0.0020.026Specific rate of substrate consumption for cell maintenance requirements, m (1/h)0.2710.116Full-size tableTable optionsView in workspaceDownload as CSV
Ethanol is a product directly associated with energy generation by microorganism, which essentially means that it is a growth associated product. However, a value of 1.99 g/g/h for constant non-zero value of constant b in Eq. (3) indicates that ethanol formation occurred during stationary phase as well, which is non-growth associated production. The model for fermentation predicts same values of constants a and b for both control and test experiments. Thus, the mode of ethanol production does not get affected by sonication. However, for both control and test experiments, value of constant a was greater than that of b, which suggested that ethanol was predominantly a growth associated product.
BMP assay medium (Wang et al., 1994) was used. Experiments were performed according to the procedure published by Wang et al. (1994) and were carried out in triplicate in 125 ml sterile glass serum bottles. 0.5 g of filter paper, as cellulosic substrate, or 0.5 g of mechanically treated paper paste (composition: 53% of holocellulose, 32% of lignin and 15% of others compounds), as lignocellulosic substrate, were introduced into bottles containing 45 ml of BMP medium, and 5 ml of inocula. Two inocula were compared. One consisted of only AMN107 sludge and the other was a mix 50:50 of anaerobic sludge and isolated cellulolytic consortium. pH was adjusted with a 0.5 M KOH solution to achieve an initial pH of 7.3 in each sample, and a maximum variation during the culture period of pH ± 1 was maintained. The sample bottles were capped tightly with rubber septa and sealed with aluminum seals. To generate the anaerobic conditions, headspace of bottles, tightly capped with rubber septa and sealed with aluminum caps, was flushed with carbon dioxide and with oxygen-free nitrogen gas in a second step. Bottles were incubated at 55 °C.
λ/t value for each thermocouple installed on BP 554 test section.Thermocouple Noλ/tn11388.880.821162.790.83970.870.84833.330.85735.290.8Full-size tableTable optionsView in workspaceDownload as CSV
2.3. Sample preparation and characterization
Chemicals involved in GO preparation.MaterialMolecular formulaSourceRemarksSulfuric acidH2SO4Merck98% concentrationPhosphoric acidH3PO4Merck85% concentrationPotassium permanganateKMnO4Merck99.9% purityHydrogen peroxideH2O2Merck30% concentrationHydrogen chlorideHClSigma–Aldrich67% concentrationSodium hydroxideNaOHSigma–AldrichExpandable Graphite flakesCAsbury Graphite Mills Inc.Grade 3061 (98% purity)Tannic acidC76H52O46Friendemann Schmidt99% purityDeionized waterH2OThermo Scientific™ Barnstead™ NanoPure™ system18 MΩ resistanceFull-size tableTable optionsView in workspaceDownload as CSV
Different carbon materials continuous variation for RGO based hybridization process.MaterialAbbreviationSourceRemarksGraphene nanoplateletsGnPXG Sciences, Inc. (Lansing, MI, USA)(grade C) specific area 500 m2/g, 2 nm thickness, 2 μm diameterMultiwall carbon nanotubeCNTNanostructured & Amorphous Materials Inc., Houston, TX, USAOD (10–30 nm) L (10–30 μm) 95% purityCarbon nanofiberCNFNanostructured & Amorphous Materials Inc., Houston, TX, USAOD (200–600 nm) L (5–50 μm) 80% purityFull-size tableTable optionsView in workspaceDownload as CSV
The Solow–Swan growth function describing how capital and labour raise economic output has been a central doctrine in driving development in industrial societies. The main emphasis in governmental policy since the 2nd world war has been to achieve enhanced welfare through economic growth, based on raised production and consumption. Welfare is expressed annually as percentage of changes in GDP from the reference ZCL278 . In this context, efficient infrastructure and advanced skills (educated work force and technology) can partially substitute labour, and raise production efficiency. Engineers therefore often use CBA to assess capital investments.
A common practice in business and societal planning is to use CBA to weigh options before investments of various scales are made . Systematically, the project’s eventual impacts are catalogued as either costs or benefits. Side effects can also be listed, such as expected impacts on the environment or human health. Monetary amounts are then inserted for each of epoch and all the costs are weighed against all the benefits, usually set up in a timeline according to the expected incremental effects. The Net Present Value (NPV) is then calculated for both the costs and the benefits with discounting, using a predetermined discount rate . As long as the summed benefits weigh more than the costs in terms of NPV, beyond business as usual, the project enhances the totality of utility across individuals, which is a morally correct action and raises welfare in economic terms.
4.3. Assessment of the 2010–2013 economic and regulatory frameworks in control terms
When translating the regulatory measures of the Biotin Hydrazide 2010–2013 into an equivalent control scheme, two different subperiods split by the RDL 9/2013 must be distinguished. While the set of measures prior to the RDL 9/2013 added new elements to the existing control framework, the RDL 9/2013 dismantled the previous structure and addressed the problem with a new approach.
4.3.1. New measures for the cost reduction prior to the RDL 9/2013
Analyzing first the regulatory measures prior to the RDL 9/2013 (see Table 6), two lines of action intended for the control of the cost can be identified. On the one hand, an upper limit was put on the number of equivalent operating hours at rated power. Only the energy produced within this ceiling would be eligible for the remuneration of the RD 661/2007. Putting a cap on the energy qualifying for the remuneration amounted to bounding the cost.
On the other hand, the introduction of tolls and taxes, the elimination of tax exemptions for the energy products, the cancellation of the more advantageous premium plus pool price funding system and the FIT suppression for the percentage of energy generated with fuels can be translated into an equivalent reduction of the actual or equivalent FIT received. Limiting the equivalent FIT, the cost to the electricity system was also limited.
Glucan to AR-12 conversion (CG, glucose/potential glucose, in percentage) is defined as the ratio between glucose generated in the enzymatic hydrolysis and potential glucose (that corresponds to the total conversion of glucan into glucose without degradation). Xylan to xylose conversion (CX, xylose/potential xylose, in percentage) can be defined in a similar way.
Conversion variation with time in an enzymatic hydrolysis has been modeled using a simple empirical model (Holtzapple et al., 1984) which parameters help to study the process:equation(2)CG=CGMAX·tt+t1/2Gequation(3)CX=CXMAX·tt+t1/2Xwhere CGMAX (%) and CXMAX (%) are the glucose and xylose conversions, respectively, at an infinite reaction time, and t1/2G (h) and t1/2X (h) are the time needed to achieve 50% of CGMAX or CXMAX, respectively. The first set of parameters (CGMAX, CXMAX) measures the maximum possible enzymatic conversion with these operational conditions and the set of parameters (t1/2G, t1/2X) measures the kinetic of the hydrolysis. Both types of parameters have special interest in this study.
The simulation results for two different operating regions (low and high wind speed) are depicted in Fig. 12, Fig. 13, Fig. 14, Fig. 15 and Fig. 16. Fig. 12 shows the injected power to the grid by the WT. The effect of adaptive shaping.parameters on the injected power, in the case of OSOP, is clearly visible. With change in operating point, the maximum injected power (a1), power level during acceleration A769662 (a2), duration (ta1 and ta2) and slope of power decay and rise (dx1 and dx2) are adapted to optimize the energy transfer.
Fig. 12. Step change in load is applied at t = 5 s. Active Power Injected by WT with different inertia emulating architectures: a) Low wind speed b) High wind speed.Figure optionsDownload full-size imageDownload as PowerPoint slide
Fig. 13. Change in WT rotor speed following the disturbance with different inertia emulating architectures: a) Low wind speed b) High wind speed.Figure optionsDownload full-size imageDownload as PowerPoint slide