Integrating existing water and wastewater assets to reduce domestic heating emissions

A study was undertaken to explore opportunities for achieving reducing greenhouse gas emissions from UK domestic heating by using existing drinking water and wastewater assets as energy storage and recovery mechanisms, coupled with modest local renewable energy generation. The sensitivity of the solutions to future projections for domestic heating demands and climate change effects was explored. Simulations optimised the available energy supply, potential for storage, heat recovery and heat demand to minimise emissions at a scale that could be adopted in most UK towns. The approach may be able to deliver significant emissions reductions with more limited capital investment than more centralised renewable energy approaches. Results from two UK locations showed that integrated water–energy systems could theoretically reduce emissions by about 50%. Furthermore, the system could satisfy demand for about 70% of the time periods each year. Future scenarios were tested and it was found that the projected annual emissions reduction was similar across all scenarios, suggesting this would be a robust approach.

Prevalence and Amounts of Common Ingredients Found in Energy Drinks and Shots

Background: Energy drinks are one of the most popular packaged beverage products consumed within the United States (US). Energy drinks are considered a functional beverage, a category that also includes sports drinks and nutraceutical beverages. Purpose: The focus of the current study was to examine the nutrition fact panels of the top selling commercially available energy drink and energy shot products within the US to characterize common ingredient profiles to help establish a standard definition and ingredient profile of energy drinks and energy shots for consumers, health care practitioners, and researchers. Methods: The top 75 commercially available energy drinks and shots were identified and compiled from multiple commercial retail websites as of September 2021. For the purpose of this study, an energy drink must have met the following criteria: (A) marketed as an energy drink; (B) purported to improve energy, focus, or alertness; (C) not sold as a dietary supplement (no supplement fact panels); (D) manufactured as a pre-packaged and ready-to-drink beverage; and (E) contains at least three of (1) caffeine, (2) B-vitamins, (3) sugar, (4) taurine, (5) creatine, (6) quercetin, (7) guarana, (8) ginseng, (9) coenzyme Q10, or (10) branched chain amino acids. Energy shots must have met similar criteria to be included: (A) marketed as an energy shot; (B) purported to improve energy, focus, or alertness; (C) sold as a dietary supplement; (D) manufactured as a pre-packaged beverage with a small volume (<3.5 mL); and (E) contains at least three of the ingredients stated above. Results: Twenty energy shots and fifty-five energy drinks were included in this analysis. The number of ingredients per product (mean ± SD) was 18.2 ± 5.7, with 15 products containing proprietary blends with undisclosed ingredient amounts. The relative prevalence and average amounts of the top ingredients were as follows: caffeine (100%; 174.4 ± 81.1 mg), vitamin B6 (72%; 366.9 ± 648.1 percent daily value (%DV)), vitamin B3 (67%; 121.44 ± 69.9% DV), vitamin B12 (67%; 5244.5 ± 10,474.6% DV), vitamin B5 (37.3%; 113.6 ± 76.6% DV), and taurine (37.3%; amounts undisclosed). Conclusions: Our findings suggest a high prevalence of caffeine and B-vitamins in these energy products, with many of the formulations containing well above the recommended daily value of B-vitamins.

A SOE estimation method for lithium batteries considering available energy and recovered energy

State of energy (SOE) is a critical index of lithium battery. The problem of the inaccurate available energy and recovered energy of lithium battery affects the accuracy of SOE estimation. In order to solve the problem, this paper proposes a method to estimate the available discharge energy of lithium batteries based on response surface model. In this method, the energy efficiency of lithium batteries in different states is obtained by establishing the relationship model of external charge voltage and external discharge voltage, so as to estimate the actual available energy of lithium batteries in different charge states. On this basis, a correction method based on radial basis function (RBF) neural network is proposed to estimate the actual energy released by the recovered energy when the current direction of the battery is changed. The proposed energy correction method is combined with the adaptive particle filter algorithm to estimate SOE. This method is not limited to the assumption of Gaussian function and can accurately predict the noise variance, so as to improve the estimation accuracy of SOE. Simulations under urban dynamometer driving schedule (UDDS) are conducted, and the result shows that the proposed method can effectively estimate the battery energy and improve the accuracy of SOE estimation.

Energy-conserving model of hexagonal pattern in Rayleigh-Bénard convection

We have constructed an energy-conserving sixteen mode dynamical system to model hexagonal pattern in Rayleigh-Bénard convection of Boussinesq fluids with symmetric stress-free thermally conducting boundaries. The model shows stable roll pattern at the onset of convection. Hexagon is found to appear in the system via sausage and (or) stationary rhombus patterns. Both up and down hexagons arise periodically or chaotically with roll, sausage and rhombus patterns. Hexagonal patterns exist for all values of the Prandtl number, 1 ≤ Pr ≤ 5 explored here. However the pattern is more prominent for small Pr and k < kc , where k denotes the wave number. The plot of Nusselt number matches with previous theoretical result. In dissipationless limit, the total energy and the unavailable energy are constants though the kinetic energy, the potential energy and the available energy vary with time. The derived model does not diverge for large values of Rayleigh number Ra.

Smart Design of Green Hydrogen Facilities: A Digital Twin-driven approach

This work studies the potentials of Digital Twin solutions for the design of competitive and reliable green hydrogen facilities. A digital twin based on stochastic simulations is proposed to address the uncertainties associated with investment and operating costs, to increase confidence and stimulate investments. Several input assumptions are involved (i.e., capital and operational costs, energy consumption, available energy, among others) to analyse their influence on financial indicators. A set of facility designs with equipment redundancy, and thus different system availabilities, was proposed. Monte Carlo simulation method is chosen to propagate uncertainties onto the project bankability assessment. By applying the proposed methodology, the opportunity index and internal rate of return (IRR) are calculated. A sensibility analysis is also carried out. The simulations illustrate that the design of a facility can be optimized to achieve higher profits, based on a trade-off between investment and availability. This study concludes that digital twin solutions are an opportunity for reducing the uncertainties associated with green hydrogen facility design. Improvements to the proposed model can be achieved by performing a refined simulation, in relation to the calculation of system availability and maintenance costs.

Energy-Saving Technology Opportunities and Investments of the Italian Foundry Industry

The foundry industry is regarded as one of the most energy-intensive industrial sector due to its energy consumption up to 9 MWh/ton of produced metal. As a result, many companies are trying to increase the energy efficiency of their foundry plants. Since many energy-saving technologies are proposed by manufacturers and the literature, choosing the most appropriate one is a difficult task. Moreover, being updated with the available energy-saving solutions is complicated because of the quick technology advances. Consequently, this paper aims at investigating the recent and future opportunities and investments for reducing the energy consumptions of the technologies of Italian foundry companies. Additionally, it aims at presenting a list of available technological solutions validated by Italian experts. To this end, the Energy Audits developed by 231 plants were analyzed to extract the implemented and planned interventions. Furthermore, the economic data available within the Energy Audits were studied to determine the advantages of a given technological solutions compared to the others. It emerged that the companies are strongly investing in increasing the efficiency of the auxiliary systems such as compressors and motors. The outcomes of this study can assist both researchers and energy managers in choosing the most appropriate energy-saving solutions.

Evaluation of Multi-Objective Optimization Techniques for Resilience Enhancement of Electric Vehicles

The pervasiveness of electric vehicles (EVs) has increased recently, which results in the interdependence of power and transport networks. Power outages may adversely impact the transportation sector, and the available energy may not be sufficient to meet the needs of all EVs during such events. In addition, EVs will be used for diverse purposes in the future, ranging from personal usage to emergency response. Therefore, the allocation of energy to different EVs may have different degrees of societal-, community-, and individual-level benefits. To capture these diverse aspects, the energy allocation problem to EVs during outages is modeled as a multiobjective optimization (MOO) problem in this study. Three indices are formulated to quantify the value of different EVs for societies, communities, and individuals during outages, and, correspondingly, three objective functions are formulated. The formulated MOO problem is solved using the five most widely used MOO solution methods, and their performance is evaluated. These methods include the weighted-sum method, lexicographic method, normal boundary intersection method, min–max method, and nondominated sorting genetic algorithm II. To compare the performance of these methods, two indices are proposed in this study, which include the demand fulfillment index and total demand fulfillment index. The former is for analyzing the demand fulfillment ratio of different priority EVs, while the latter is for the demand fulfillment analysis of the whole EV fleet requiring a recharge. In addition, the computational complexity, variance, and additional constraints required by each method are also analyzed. The simulation results have shown that the lexicographic method has the best performance when the relative priorities are known, while the min–max method is the most suitable method if the priorities are not known.

Unexpected spotlight on two unusual substances

Acute liver failure (ALF) is a rare and unexpected condition, which is commonly related to drug ingestion and viral infections. Here, two ALF fatalities are presented, which showed a rapid progression between the onset of symptoms and death. Both cases gained attention as unusual substances were suspected to be the reason for the fatal ALF, namely the prescription-free natural remedy Iberogast® (Bayer Vital GmbH, Leverkusen, Germany) and freely available energy drinks. Autopsy findings revealed that the fatal ALFs were unrelated to the ingestion of these two substances.

Fabrication of nano battery from CdS quantum dots and organic polymer

Efficient energy storage systems are recharged from the nano batteries; however, the available energy of present nanomaterial batteries remains capable for many applications due to the limited basic charging capacity of the electrode materials. A cadmium sulfide (CdS) nanocrystal (NCs) or quantum dots (QDs) that was prepared by chemical reaction and were fabricated nano battery device using the PVV / Li: graphite / CdS / Al. The optical properties of the CdS QDs were described by the spectrometers of ultraviolet-visible (UV-Vis.) and photoluminescence (PL), the results are indicating that the CdS QDs prepared where nanocrystalline structures are formed. The energy gap (Eg) of CdS QDs measured from PL was found to be about 2.69 eV. The CdS QDs led to improving the performs of the nano battery in terms of enhancing the mobility of the carrier's charging and consequently the processes of recombination between CdS QDs and Li-ions. The characteristics of the current-voltage (I-V) indicate acceptable conditions for the generation of light at (3 Volt). The structures can be designed to determine the fundamentals of ion and electron transport for energy storage in nanostructures and to test the limits of three-dimensional nano battery technologies. The nano battery device from semiconductor substance (CdS QDs) with (Li) has been successful in operating the nano battery with a few voltages giving a good current. Fabrication of CdS QDs and Li nano battery devices was involved in enhancing the efficiency of the nano battery devices.