Towards closed carbon loop fermentations: co-feeding of Yarrowia lipolytica with glucose and formic acid

A novel fermentation process was developed in which renewable electricity is indirectly used as a fermentation substrate, synergistically decreasing both the consumption of sugar as a first generation carbon source and emission of the greenhouse gas CO2. To achieve this, a glucose-based process is co-fed with formic acid, which can be generated by capturing CO2 from fermentation offgas followed by electrochemical reduction with renewable electricity. This ‘closed carbon loop’ concept is demonstrated by a case study in which co-feeding formic acid is shown to significantly increase the yield of biomass on glucose of the industrially relevant yeast species Yarrowia lipolytica. First, the optimal feed ratio of formic acid to glucose is established using chemostat cultivations. Subsequently, guided by a dynamic fermentation process model, a fed-batch protocol is developed and demonstrated on laboratory scale. Finally, the developed fed-batch process is proven to be scalable to pilot scale. An extension of this proven concept to also recycle the O2 that is co-generated with the formic acid to the fermentation process for intensification purposes, and a potential further application of the concept to anaerobic fermentations are discussed.

Optimal and combined control of the direct drive with the torque motor

The paper covers the problem of reaching the maximum speed performance of a direct drive based on the torque motor. The authors propose the solution to the problem by implementing optimal feed-forward control in accordance with Pontryagin’s maximum principle and Feldbaum’s theorem on the finite number of switching times. Combined control allows a transition from optimal to automatic control in the finite state stabilization zone. Results of mathematical modelling prove the efficiency of selected engineering solutions.

Optimization of Feed Components to Improve Hermetia illucens Growth and Development of Oil Extractor to Produce Biodiesel

HIL are useful in agriculture because they can be used as feed for livestock or fertilizer and can bioconvert organic wastes, such as food waste and human and animal manure to usable fertilizer. In addition, HIL are being studied as a source of biodiesel because of their high-fat content. However, their use for biodiesel production has not been fully adopted. Here, the results showed that survival, weight gains, and total dried weight were significantly enhanced when HIL were fed dried-food waste (DFW)/chicken manure (CM). Furthermore, increased weight gain was observed in HIL fed DFW containing 5 mL waste cooking oil (WCO) per 100 g and 1.2% (v/w) fermented effective microorganism (F-EM). Based on these results, we prepared experimental feeds containing DFW, CM, WCO, and F-EM to establish an optimal feed for biodiesel production. We found that FT-1-2, a feed prepared with 60 g DFW, 40 g CM, 2 mL WCO, and 0.8% F-EM (v/w), significantly enhanced fat content, weight gain, and total dried weight of HIL. Our results indicate FT-1-2 is a suitable feed to breed HIL for biodiesel production. We then developed an automatic oil extractor for biodiesel production. The yield of the oil extractor was higher than that of solvent extraction. The study shows FT-1-2 is an optimal HIL feed for biodiesel production and that the developed oil extractor is useful for the extraction of crude oil from HIL and for the harvesting of defatted HIL frass for livestock feed and fertilizer. Taken together, we established an optimized low-cost feed for HIL breeding and developed an automatic oil extractor for the production of biodiesel from HIL.

An optimal feed-forward artificial neural network model and a new empirical correlation for prediction of the relative viscosity of Al2O3-engine oil nanofluid

This study presents the design of an artificial neural network (ANN) to evaluate and predict the viscosity behavior of Al2O3/10W40 nanofluid at different temperatures, shear rates, and volume fraction of nanoparticles. Nanofluid viscosity ($${\mu }_{nf}$$ μ nf ) is evaluated at volume fractions ($$\varphi$$ φ =0.25% to 2%) and temperature range of 5 to 55 °C. For modeling by ANN, a multilayer perceptron (MLP) network with the Levenberg–Marquardt algorithm (LMA) is used. The main purpose of this study is to model and predict the $${\mu }_{nf}$$ μ nf of Al2O3/10W40 nanofluid through ANN, select the best ANN structure from the set of predicted structures and manage time and cost by predicting the ANN with the least error. To model the ANN, $$\varphi$$ φ , temperature, and shear rate are considered as input variables, and $${\mu }_{nf}$$ μ nf is considered as output variable. From 400 different ANN structures for Al2O3/10W40 nanofluid, the optimal structure consisting of two hidden layers with the optimal structure of 6 neurons in the first layer and 4 neurons in the second layer is selected. Finally, the R regression coefficient and the MSE are 0.995838 and 4.14469E−08 for the optimal structure, respectively. According to all data, the margin of deviation (MOD) is in the range of less than 2% < MOD < + 2%. Comparison of the three data sets, namely laboratory data, correlation output, and ANN output, shows that the ANN estimates laboratory data more accurately.

Correlation of yarn feeding to the dimensional and elastic parameters of tubular knitted fabric

The yarn feeding for a loop formation is a critical factor in determining the size and elasticity of highly elastic knitted fabrics. Currently, the prevalent production processes rely on experienced machine operators to set up the optimal feed rate by trial and error. To improve production efficiency and reduce the reliance on the operator’s skill, we attempt to create a structure model of tubular knitted fabric that could correlate the size as well as elasticity of fabric with the loop geometry parameters (wale spacing, course spacing) of the yarn feeding. The experimental tensile test of the elastic fabric verified that the model is able to deduce the yarn feeding parameters from the elasticity and dimensional requirements of the fabric to be knitted. It is also illustrated that the yarn feeding is a key factor in controlling the elasticity of knitted fabrics.

Policy Assistance for Adoption of Residential Solar PV in India: A Stakeholder-centric Approach for Welfare Optimization

Background Domestic solar PV installations in India are yet to become a valuable proposition for both the prosumers and utility because of the deficiencies in the formulation of the policy parameters. This paper presents a comprehensive analysis of the consumer-centric business model for rooftop solar PV installations in India. We explore areas where potential policy interventions may be introduced to improve collective stakeholder benefits and incentivize more domestic consumers to install rooftop solar panels in their premises. We propose a policy framework that seeks optimal Feed-in Tariff (FiT) rates, PV capacities and Average Billing Rates (ABRs) towards maximizing stakeholder benefits. The stakeholders considered are the consumers/prosumers and the utility. Results Case studies with three residential prosumers of different demand and generation profiles (extracted from data provided by Indian utilities) are presented. A multi-objective problem is formulated with the FiT, generation capacity (as a function of demand) and ABR as decision variables, exploring the various welfare trade-offs. The pareto-optimal front is identified for prosumer and utility benefits and suitable points with reasonable tradeoff are selected based on sensitivity analysis of the impact of the decision variables on collective welfare. Conclusions The paper provides a workflow to fix tariff, FiT and local PV capacities in active residential distribution systems. The suitability of prevailing tariff and FiT rates of three Indian utilities namely, MSEDCL, TATA POWER (Delhi) and TANGEDCO are studied, and their impact on prosumer savings and utility profits is brought out. The paper recommends optimal installation capacities for prosumers based on their load demand so as to encourage the adoption of roof-top solar without affecting collective benefits. This provides policymakers and prosumers an effective decision-making tool.

Feeding habits and the influence of pellet diameter on the feeding responses of the flathead grey mullet (Mugil cephalus) in captivity

The feeding habits and effect of the diameter of pelleted feeds on the feeding responses of wild juvenile and adult flathead grey mullet (Mugil cephalus) in captivity were examined. Optimal pellet size for feeding was defined according to the behavioural responses and ingestion of pellets with different diameters (2, 4, 6, 8 mm) that were dropped into the tank in a random sequence. Larger pellets (6 and 8 mm) were more attractive (lower reaction time, high percentage of capture), but the small to medium-sized pellets (2 and 4 mm) were consumed the most. The optimal size was the 2- and 4-mm pellet diameter for juvenile individuals (365.50 ± 36.90 g; 28.8 ± 0.84 cm) and the 4-mm diameter pellet for adults (937.49 ± 146.54 g; 40 ± 1.12 cm). The preferred feeding area of adult mullet was also studied to estimate preference in relation to pellet characteristics such as floating or sink. Two pellet types, floating or sinking, were offered simultaneously in the water column: at the surface, mid-water column and bottom of the tank. The flathead grey mullet had a preference to feed in the mid-water column and the bottom of the tanks indicating that sinking or slow-sinking pellets would be the optimal feed type in relation to mullet feeding behaviour.

DFT and experimental studies on synthesis of bisphenol a: Determination of optimal feed profile in semi-batch reactor

Bisphenol A (BPA) is theoretically synthesized with 2 moles of phenol and 1 mol of acetone. During the reaction, a stoichiometric ratio or high acetone concentration causes the formation of by-products. This situation has been confirmed by density functional theory (DFT) calculations in addition to the literature information. In these calculations, the B3LYP method and the 6-311++G(d, p) basis set were used. DFT calculations show that by-products can be formed in the synthesis of bisphenol a. The common method used to solve this problem is to work with high molar phenol/acetone ratios. But this brings additional operating and investment costs. In this study, semi-batch reaction experiments were performed which stoichiometric acetone was fed in reactor with various pulsed modes in the presence of homogenous and heterogonous catalysts. As a result, it has been shown that high conversion and selectivity can be achieved by providing energy efficiency

Optimal feedforward torque control for nonlinear induction machines considering stator & rotor copper losses and current & voltage limits

In order to analytically solve the optimal feed-<br>forward torque control (OFTC) problem of induction machines (IMs), the unified theory for synchronous machine introduced in [1] is extended by considering relevant IM nonlinearities and incorporating stator and rotor copper losses. Instead of the well known Maximum Torque per (stator) Current (MTPC) operation strategy, Maximum Torque per (copper) Losses (MTPL Cu ) is realized and extended by the Maximum (rotor) Current (MC r, ext ) strategy due to stator and rotor current limitations. Modeling magnetic saturation and cross-coupling effects leads to a con-<br>strained nonlinear optimization problem which is solved based on the idea of sequential quadratic programming (SQP). The second order Taylor approximations are formulated in implicit form as quadrics. Applying the Lagrangian formalism to the quadratic problem leads to analytical solution for the optimal rotor currents. For a doubly-fed induction machine (DFIM), a decision tree for optimal operation management is presented and the OFTC is validated in simulations for a real nonlinear IM.

Optimal feedforward torque control for nonlinear induction machines considering stator & rotor copper losses and current & voltage limits

In order to analytically solve the optimal feed-<br>forward torque control (OFTC) problem of induction machines (IMs), the unified theory for synchronous machine introduced in [1] is extended by considering relevant IM nonlinearities and incorporating stator and rotor copper losses. Instead of the well known Maximum Torque per (stator) Current (MTPC) operation strategy, Maximum Torque per (copper) Losses (MTPL Cu ) is realized and extended by the Maximum (rotor) Current (MC r, ext ) strategy due to stator and rotor current limitations. Modeling magnetic saturation and cross-coupling effects leads to a con-<br>strained nonlinear optimization problem which is solved based on the idea of sequential quadratic programming (SQP). The second order Taylor approximations are formulated in implicit form as quadrics. Applying the Lagrangian formalism to the quadratic problem leads to analytical solution for the optimal rotor currents. For a doubly-fed induction machine (DFIM), a decision tree for optimal operation management is presented and the OFTC is validated in simulations for a real nonlinear IM.