86 research outputs found
How does technology pathway choice influence economic viability and environmental impacts of lignocellulosic biorefineries?
Background: The need for liquid fuels in the transportation sector is increasing, and it is essential to develop industrially sustainable processes that simultaneously address the tri-fold sustainability metrics of technological feasibility, economic viability, and environmental impacts. Biorefineries based on lignocellulosic feedstocks could yield high-value products such as ethyl acetate, dodecane, ethylene, and hexane. This work focuses on assessing biochemical and biomass to electricity platforms for conversion of Banagrass and Energycane into valuable fuels and chemicals using the tri-fold sustainability metrics. Results: The production cost of various products produced from Banagrass was 1.00/kg ethyl acetate, 2.34/kg ethylene and 1.31/kg ethanol, 3.35/kg dodecane, and $2.62/kg ethylene. The sensitivity analysis revealed that the price of the main product, feedstock cost and cost of ethanol affected the profitability the overall process. Banagrass yielded 11% higher ethanol compared to Energycane, which could be attributed to the differences in the composition of these lignocellulosic biomass sources. Acidification potential was highest when ethylene was produced at the rate of 2.56 × 10−2 and 1.71 × 10−2 kg SO2 eq. for Banagrass and Energycane, respectively. Ethanol production from Banagrass and Energycane resulted in a global warming potential of − 12.3 and − 40.0 g CO2 eq./kg ethanol. Conclusions: Utilizing hexoses and pentoses from Banagrass to produce ethyl acetate was the most economical scenario with a payback period of 11.2 years and an ROI of 8.93%, respectively. Electricity production was the most unprofitable scenario with an ROI of − 29.6% using Banagrass/Energycane as a feedstock that could be attributed to high feedstock moisture content. Producing ethylene or dodecane from either of the feedstocks was not economical. The moisture content and composition of biomasses affected overall economics of the various pathways studied. Producing ethanol and ethyl acetate from Energycane had a global warming potential of − 3.01 kg CO2 eq./kg ethyl acetate
Zero resource speech synthesis using transcripts derived from perceptual acoustic units
Zerospeech synthesis is the task of building vocabulary independent speech
synthesis systems, where transcriptions are not available for training data. It
is, therefore, necessary to convert training data into a sequence of
fundamental acoustic units that can be used for synthesis during the test. This
paper attempts to discover, and model perceptual acoustic units consisting of
steady-state, and transient regions in speech. The transients roughly
correspond to CV, VC units, while the steady-state corresponds to sonorants and
fricatives. The speech signal is first preprocessed by segmenting the same into
CVC-like units using a short-term energy-like contour. These CVC segments are
clustered using a connected components-based graph clustering technique. The
clustered CVC segments are initialized such that the onset (CV) and decays (VC)
correspond to transients, and the rhyme corresponds to steady-states. Following
this initialization, the units are allowed to re-organise on the continuous
speech into a final set of AUs in an HMM-GMM framework. AU sequences thus
obtained are used to train synthesis models. The performance of the proposed
approach is evaluated on the Zerospeech 2019 challenge database. Subjective and
objective scores show that reasonably good quality synthesis with low bit rate
encoding can be achieved using the proposed AUs
Resistance network-based thermal conductivity model for metal foams
A network model for the estimation of effective thermal conductivity of open-celled metal foams is pre-sented. A nodal network representation of three aluminum foam samples from DUOCEL – 10 ppi, 20 ppi and 40 ppi – is constructed out of X-ray microtomography data obtained by computed tomography (CT) scanning of the samples using a commercial CT scanner. Image processing and 3D skeletonization are performed with commercially available image processing software. The effective thermal conductivity is estimated through a 1D conduction model, representing individual ligaments as an effective thermal resistance using the topological information from the scan data. The effective thermal conductivity data thus obtained are compared with the Lemlich theory and other pore-based models. Further, microstruc-tural characterization of foam features – pore size, ligament thickness, ligament length and pore shapes – is performed. All the three foam samples are observed to have similar pore shapes and volumetric poros-ity, while the other features scale with the pore size. For a given porosity the computed permeability is found to scale as the square of the pore diameter, as also noted by previous researchers
A Communication-Efficient Adaptive Algorithm for Federated Learning under Cumulative Regret
We consider the problem of online stochastic optimization in a distributed
setting with clients connected through a central server. We develop a
distributed online learning algorithm that achieves order-optimal cumulative
regret with low communication cost measured in the total number of bits
transmitted over the entire learning horizon. This is in contrast to existing
studies which focus on the offline measure of simple regret for learning
efficiency. The holistic measure for communication cost also departs from the
prevailing approach that \emph{separately} tackles the communication frequency
and the number of bits in each communication round
Optimization of surfactant addition in cellulosic ethanol process using integrated techno-economic and life cycle assessment for bioprocess design
Surfactants have been demonstrated to be effective in increasing the cellulase enzyme efficacy and overall enzymatic hydrolysis efficiency. However, the impact of the surfactant addition on the economic viability and environmental impacts of the bioethanol process has not been well-investigated. The objective of this study was to determine the economic and the environmental impacts of using five surfactant types—polyethylene glycol (PEG) 3000, PEG4000, PEG6000, PEG8000, and Tween80—at various concentrations (8%, 5%, 2%, 1%, 0.75%, 0.5%, 0.25%, and 0% (w/w)) during enzymatic hydrolysis and fermentation of pretreated Banagrass. We used an integrated techno-economic and life cycle assesment to guide the selection of optimal surfactant concentration in the bioethanol process. A surfactant concentration of >2% negatively affects the profitability of ethanol, even when there is a statistically significant increase in glucose and ethanol titers. Based on the overall performance indicators for final ethanol, economic viability and environmental impacts, the addition of PEG6000 at 2% (w/w) were determined to be the optimal option. Glucose and ethanol concentrations of 119.2 ± 5.4 g/L and 55.0 ± 5.8 g/L, respectively, with an 81.5% cellulose conversion rate, were observed for 2% (w/w) PEG6000. Techno-economic and life cycle analysis indicated that 2% w/w PEG6000 addition resulted in ROI of 3.29% and had reduced the global warming potential by 6 g CO2/MJ ethanol produced
Effect of solids loading on ethanol production: Experimental, Economic and Environmental analysis
This study explores the effect of high-solids loading for a fed batch enzymatic hydrolysis and fermentation. The solids loading considered was 19%, 30% and 45% using wheat straw and corn stover as a feedstock. Based on the experimental results, techno-economic analysis and life cycle assessments were performed. The experimental results showed that 205±25.8 g/L glucose could be obtained from corn stover at 45% solids loading after 96h which when fermented yielded 115.9±6.37 g/L ethanol after 60h of fermentation. Techno-economic analysis showed that corn stover at 45% loading yielded the highest ROI at 8% with a payback period less than 12 years. Similarly, the global warming potential was lowest for corn stover at 45% loading at -37.8 gCO2 eq./MJ ethanol produced
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