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首页> 外文期刊>Journal of Applied Phycology >In silico optimization for production of biomass and biofuel feedstocks from microalgae
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In silico optimization for production of biomass and biofuel feedstocks from microalgae

机译:在计算机上优化微藻生产生物质和生物燃料原料

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Optimization of the production rate of biomass rich in N (e.g. for protein) or C (e.g. for biofuels) is key to making algae-based technology commercially viable. Creating the appropriate conditions to achieve this is a challenge; operational permutations are extensive, while geographical variations localise effective methods of cultivation when utilising natural illumination. As an aid to identifying suitable operational envelopes, a mechanistic acclimative model of microalgae growth is used for the first time to simulate production in virtual systems over a broad latitudinal range. Optimization of production is achieved through selection of strain characteristics, system optical depth, nutrient supply, and dilution regimes for different geographic and seasonal illumination profiles. Results reveal contrasting requirements for optimising biomass vs biofuels production. Trade-offs between maximising areal and volumetric production while conserving resources, plus hydrodynamic limits on reactor design, lead to quantifiable constraints for optimal operational permutations. Simulations show how selection of strains with a high maximum growth rate, U (m) , remains the prime factor enabling high productivity. Use of an f/2 growth medium with a culture dilution rate set at similar to 25 % of U (m) delivers sufficient nutrition for optimal biomass production. Further, sensitivity to the balance between areal and volumetric productivity leads to a well-defined critical depth at similar to 0.1 m at which areal biofuel production peaks with use of a low concentration f/4 growth medium combined with a dilution rate similar to 15 % of U (m) . Such analyses, and developments thereof, will aid in developing a decision support tool to enable more productive methods of cultivation.
机译:富含N(例如用于蛋白质)或C(例如用于生物燃料)的生物质生产率的优化是使基于藻类的技术在商业上可行的关键。为实现这一目标创造适当的条件是一个挑战;操作排列是广泛的,而地理变化在利用自然光照时会定位有效的栽培方法。为了帮助确定合适的运行范围,首次使用了微藻生长的机械适应模型来模拟在宽纬度范围内的虚拟系统中的生产。通过选择应变特性,系统光学深度,养分供应以及针对不同地理和季节光照分布的稀释方案,可以实现生产的优化。结果揭示了在优化生物质与生物燃料生产方面的不同要求。在节省资源的同时最大化面积和体积产量之间的权衡,再加上反应堆设计的水动力限制,导致可量化的约束,以实现最佳的运行排列。模拟表明如何选择具有最大最大生长率U(m)的菌株仍然是实现高生产率的主要因素。将f / 2生长培养基的稀释度设定为U(m)的25%,可以提供充足的营养,以实现最佳的生物量生产。此外,对面积生产率和容积生产率之间的平衡的敏感性会导致在大约0.1 m处有一个明确定义的临界深度,在该深度处,使用低浓度的f / 4生长培养基以及稀释率类似于15%时,区域生物燃料的产量达到峰值。的U(m)。这样的分析及其发展将有助于开发决策支持工具,以实现更具生产力的耕作方法。

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