Energy Transport In Systems Research Articles

Aberrant Energy Metabolism in Alzheimer's Disease.

To maintain energy supply to the brain, a direct energy source called adenosine triphosphate (ATP) is produced by oxidative phosphorylation and aerobic glycolysis of glucose in the mitochondria and cytoplasm. Brain glucose metabolism is reduced in many neurodegenerative diseases, including Alzheimer's disease (AD), where it appears presymptomatically in a progressive and region-specific manner. Following dysregulation of energy metabolism in AD, many cellular repair/regenerative processes are activated to conserve the energy required for cell viability. Glucose metabolism plays an important role in the pathology of AD and is closely associated with the tricarboxylic acid cycle, type 2 diabetes mellitus, and insulin resistance. The glucose intake in neurons is from endothelial cells, astrocytes, and microglia. Damage to neurocentric glucose also damages the energy transport systems in AD. Gut microbiota is necessary to modulate bidirectional communication between the gastrointestinal tract and brain. Gut microbiota may influence the process of AD by regulating the immune system and maintaining the integrity of the intestinal barrier. Furthermore, some therapeutic strategies have shown promising therapeutic effects in the treatment of AD at different stages, including the use of antidiabetic drugs, rescuing mitochondrial dysfunction, and epigenetic and dietary intervention. This review discusses the underlying mechanisms of alterations in energy metabolism in AD and provides potential therapeutic strategies in the treatment of AD.

Multilayer Dielectric Nanocomposites with Cross-Linked Dielectric Transition Interlayers for High-Temperature Applications.

In energy storage and transportation systems, polymer dielectrics are widely applied in smart grids, electric vehicles, and power conditioning owing to their incomparable power density and high reliability. However, the dielectric constant (ε) and breakdown strength (Eb) normally cannot be increased simultaneously, which results in insufficient discharged energy density especially at high temperatures. In this work, enhanced Eb and high energy density are archived in multilayer polymer nanocomposites by introducing cross-linked dielectric transition layers. Specifically, the sandwiched composite achieves a huge discharge energy density of 4.64 J cm-3 with a charged-discharged efficiency of 84% at 150 °C and 500 MV m-1. The formation of cross-linked dielectric transition layers between layers of the multilayer nanocomposite could effectively restrain the growth of the electrical tree and greatly increase the Eb. This work presents a strategy for designing high-performance multilayered dielectric polymer nanocomposites by introducing cross-linked dielectric transition layers to reduce the loss from interlayer interfaces.

Optimal design and operation of maritime energy systems based on renewable methanol and closed carbon cycles

The phasing out of fossil fuels in the shipping sector is of key importance for reducing greenhouse gas emissions. Synthetic fuels based on renewable energy are a promising option for a sustainable maritime sector, with renewable methanol being one of the most widely considered energy carriers. However, the availability of renewable methanol is still limited and the costs associated with it are significantly higher than for conventional fuels, also because fuel synthesis must rely on carbon dioxide as a resource. Through the use of onboard carbon capture, the release of carbon dioxide during combustion can be avoided, and this closed cycle reduces the need for carbon sources. This paper investigates such a scenario by analyzing overall ship energy systems that use internal combustion engines with connected pre-combustion and post-combustion carbon capture technologies. The effect of these technologies on the techno-economic performance of a fully renewable energy system is investigated by setting up a mixed-integer optimization framework for the optimal design and operation of ship propulsion systems. The propulsion demand for the chosen case study consists of a typical operational profile of a ferry operating in the Baltic Sea. Comparison of the capture cases to a system solely based on renewable methanol reveals significant cost advantages of the closed carbon cycle systems. The baseline scenario has nearly 20% lower annual costs, with total capture rates of 90% in the post-combustion case and around 40% in the pre-combustion case. An extensive sensitivity analysis shows that these cost advantages are robust against various technological and economic boundary conditions. In the pre-combustion case, process heat demand reduction in combination with increased engine heat supply might enable higher capture rates beyond 90%. The results indicate that combining renewable fuels with onboard carbon capture creates opportunities for cost-effective, sustainable shipping.

Wind-assisted, electric, and pure wind propulsion – the path towards zero-emission RoRo ships

ABSTRACT Electrical and wind propulsion, together with energy stored in batteries and renewable energies harnessed onboard, can lead the way towards zero-emission ships. This study compares wind propulsion solutions and battery storage possibilities for a RoRo ship operating in the Baltic Sea. The ship energy systems simulation model ShipCLEAN is used to predict the performance of the zero-emission ship in real-life operating conditions. The study showcases how ships can be transferred from a conventional, diesel-powered to a zero-emission ship. For the zero-emission ship, all energy needed for auxiliaries and propulsion is taken from renewable sources onboard or from batteries. Challenges and opportunities, as well as necessary adaptions of the route and logistics, are discussed. Results of the study present which wind propulsion technology is the most suitable for the example RoRo ship, and how the installation of suitably sized battery packs for zero-emission operation affects the cargo capacity of the ship.

A scheduling strategy for a new energy highway integrated network with clean green energy synergy

Purpose Green energy as a transportation supply trend is irreversible. In this paper, a highway energy supply system (HESS) evolution model is proposed to provide highway transportation vehicles and service facilities with a clean electricity supply and form a new model of a source-grid-load-storage-charge synergistic highway-PV-WT integrated system (HPWIS). This paper aims to improve the flexibility index of highways and increase CO2 emission reduction of highways. Design/methodology/approach To maximize the integration potential, a new energy-generation, storage and information-integration station is established with a dynamic master–slave game model. The flexibility index is defined to evaluate the system ability to manage random fluctuations in power generation and load levels. Moreover, CO2 emission reduction is also quantified. Finally, the Lianhuo Expressway is taken as an example to calculate emission reduction and flexibility. Findings The results show that through the application of the scheduling strategy to the HPWIS, the flexibility index of the Lianhuo Expressway increased by 29.17%, promoting a corresponding decrease in CO2 emissions. Originality/value This paper proposed a new model to capture the evolution of the HESS, which provides highway transportation vehicles and service facilities with a clean electricity supply and achieves energy transfer aided by an energy storage system, thus forming a new model of a transportation energy system with source-grid-load-storage-charge synergy. An evaluation method is proposed to improve the air quality index through the coordination of new energy generation and environmental conditions, and dynamic configuration and dispatch are achieved with the master–slave game model.

Quantum simulation of the Lindblad equation using a unitary decomposition of operators

Accurate simulation of the time evolution of a quantum system under the influence of an environment is critical to making accurate predictions in chemistry, condensed-matter physics, and materials sciences. Whereas there has been a recent surge in interest in quantum algorithms for the prediction of nonunitary time evolution in quantum systems, few studies offer a direct quantum analog to the Lindblad equation. Here, we present a quantum algorithm---utilizing a decomposition of nonunitary operators approach---that models dynamic processes via the unraveled Lindblad equation. This algorithm is employed to probe both a two-level system in an amplitude damping channel as well as the transverse field Ising model in a variety of parameter regimes; the resulting population dynamics demonstrate excellent agreement with classical simulation, showing the promise of predicting population dynamics utilizing quantum devices for a variety of important systems in molecular energy transport, quantum optics, and other open quantum systems.

Eliminating Radiative Losses in Long-Range Exciton Transport

We demonstrate that it is possible to effectively eliminate radiative losses during excitonic energy transport in systems with an intrinsic energy gradient. By considering chain-like systems of repeating `unit' cells which can each consist of multiple sites, we show that tuning a single system parameter (the intra-unit-cell coupling) leads to efficient and highly robust transport over relatively long distances. This remarkable transport performance is shown to originate from a partitioning of the system's eigenstates into energetically-separated bright and dark subspaces, allowing long range transport to proceed efficiently through a `dark chain' of eigenstates. Finally, we discuss the effects of intrinsic dipole moments, which are of particular relevance to molecular architectures, and demonstrate that appropriately-aligned dipoles can lead to additional protection against other (non-radiative) loss processes. Our dimensionless open quantum systems model is designed to be broadly applicable to a range of experimental platforms.

Heat Flow Characteristics of Ferrofluid in Magnetic Field Patterns for Electric Vehicle Power Electronics Cooling

The ferrofluid is a kind of nanofluid that has magnetization properties in addition to excellent thermophysical properties, which has resulted in an effective performance trend in cooling applications. In the present study, experiments are conducted to investigate the heat flow characteristics of ferrofluid based on thermomagnetic convection under the influence of different magnetic field patterns. The temperature and heat dissipation characteristics are compared for ferrofluid under the influence of no-magnet, I, L, and T magnetic field patterns. The results reveal that the heat gets accumulated within ferrofluid near the heating part in the case of no magnet, whereas the heat flows through ferrofluid under the influence of different magnetic field patterns without any external force. Owing to the thermomagnetic convection characteristic of ferrofluid, the heat dissipates from the heating block and reaches the cooling block by following the path of the I magnetic field pattern. However, in the case of the L and T magnetic field patterns, the thermomagnetic convection characteristic of ferrofluid drives the heat from the heating block to the endpoint location of the pattern instead of the cooling block. The asymmetrical heat dissipation in the case of the L magnetic field pattern and the symmetrical heat dissipation in the case of the T magnetic field pattern are observed following the magnetization path of ferrofluid in the respective cases. The results confirm that the direction of heat flow could be controlled based on the type of magnetic field pattern and its path by utilizing the thermomagnetic behavior of ferrofluid. The proposed lab-scale experimental set-up and results database could be utilized to design an automatic energy transport system for the cooling of power conversion devices in electric vehicles.

Assessing Land Use Efficiencies and Land Quality Impacts of Renewable Transportation Energy Systems for Passenger Cars Using the LANCA® Method

Targets to reduce global warming impacts of the transportation sector may lead to increased land use and negative land quality changes. The aim of this paper is to implement the Land Use Indicator Calculation in Life Cycle Assessment (LANCA®) model to assess land quality impacts and land use efficiencies (concerning occupation and transformation) of different example renewable transport energy systems for passenger cars. In addition, the land use impacts are normalized according to the Soil Quality Index building on LANCA® and included in the environmental footprint. The assessment is based on information from GaBi life cycle assessment software databases and on literature. Functional unit of the model is to provide annual drive of 18,600 km for a passenger car in the EU. The analysis includes examples of biomass, electricity, electricity to fuels and fossil-based energy systems. Our findings confirm previous research that biomass-based transport energy systems have risks to lead to significantly higher land occupation and transformation impacts than do fossil oil or electricity-based ones. According to the LANCA® model, methane from Finnish wood and German corn has the highest impacts on filtration and the physicochemical filtration reduction potential. Sugarcane ethanol and palm oil diesel systems, on the other hand, lead to the highest erosion potential. Electricity-based transportation energy systems appear to be superior to biomass-based ones from the perspectives of land occupation, land transformation, and soil quality impacts for the selected examples. Land quality impacts should be taken into account when developing and expanding renewable transportation energy systems. The paper shows that the LANCA® method is applicable for the assessment of transport systems in order to provide extended information on environmental sustainability, which should be included more often in future analysis. However, it can be challenging to interpret underlaying assumptions, especially when aggregated information is used from databases.

“Rich Fields in Persia”: Parsi Capital and the Origins of Economic Development in Pahlavi Iran, 1925–1941

AbstractThis article investigates the history of economic relations between Iran and the Parsi community of India during the Reza Shah period. Encouraged by the policies of the new Pahlavi state, Parsi entrepreneurs began a serious effort to investigate the possibilities of economic investment in Iran. The article details three Parsi economic missions that were conducted in Iran during this period, and analyzes their assessments of Iran's potential for development in fields such as energy, textile manufacturing, commercial agriculture, and modern transportation systems. As the article argues, while these Parsi-led initiatives were part of a larger history of renewed engagement between Parsis and Iranians, for a variety of political and economic reasons, by the outbreak of World War II few of the Parsi plans for investment in Iran had come to fruition. While remaining largely forestalled in the interwar period, the article also suggests that Parsi economic assessments foreshadowed many of the planning strategies carried out in Iran's post–World War II history of economic development.

Smart Energy and Intelligent Transportation Systems

With the Internet of things and various information and communication technologies, a city can manage its assets in a smarter way, constituting the urban development vision of a smart city [...]

Effect of bagasse drying on thermal energy storage utilizing zeolite water vapor ad/desorption at a sugar mill

Recently, polygeneration in the sugarcane industry, which produces not only raw sugar but also other products (ethanol and electricity), has been attracting attention for green economy via the utilization of local natural resources. We focus on “heat” as a polygeneration method for the sugarcane industry. This study describes a thermal energy storage and transport system that can eliminate the spatio-temporal mismatch between the heat source, the sugar mill, and the fossil fuel consumption. The polygeneration system connects the thermal energy storage system with the sugar mill plant, such that the additional power generated by drying sugarcane bagasse, a fuel with a high moisture content, is used as the auxiliary power for thermal energy storage. Here, assuming the bagasse drying process at a sugar mill, we studied the bagasse drying rate, the bagasse drying in the bagasse elevator, simulations of a sugar mill with bagasse drying, and the thermal energy storage system utilizing the water vapor ad/desorption cycle of zeolite; a sugar mill in Tanegashima, Japan, was used as an example. A fixed-bed test packed with sugarcane bagasse was conducted, and a numerical model was developed for simulating the temperature distribution and the evolution of the outlet vapor pressure in the fixed-bed reactor. Subsequently, the bagasse drying process using a covered bagasse elevator was numerically simulated, and a moisture reduction of 2% was expected. This result was incorporated into the process simulation, to evaluate the relationship between additional power generation and temperature as well as the flow rate of unused heat for thermal energy storage. Finally, this relationship was incorporated into the numerical design of a heat-charging device, to evaluate the effect of bagasse drying on the thermal energy storage system. The coefficient of performance (COP) of the heat-charging system with bagasse drying was 1.6 times higher than that without bagasse drying.

The potential of the natural gas grid to accommodate hydrogen as an energy vector in transition towards a fully renewable energy system

The temporal and geographical availability of renewable energy sources is highly variable, which imposes the importance of correct choices for energy storage and energy transport systems. This paper presents a smart strategy to utilize the natural gas distribution grid to transport and store the hydrogen. The goal is twofold: evaluating the capacity limits of the grid to accommodate “green hydrogen” for preset increasing shares of renewable energy sources (RESs) and determining at the same time the optimal mix of wind, photovoltaic (PV), biomethane and power-to-gas systems that minimizes the investment and operation costs. To this end, the energy supply system of an entire country is modelled and optimized considering the real characteristics and pressure levels of the gas grid, which is assumed to be the only storage mechanism of green hydrogen. The operational concept is to fill up the gas grid with hydrogen during the day and with natural gas during the night while always consuming the natural gas-hydrogen blend. Green hydrogen is generated by electrolysers powered by PVs, wind turbines and biomethane power systems. Results of the optimizations showed that: i) as long as the share of RES does not exceed 20%, there is no need to use the gas grid as RES storage system, ii) from 20 to 50% of RES share the gas grid receives the surplus of electricity in the peaks that would be necessary to “complete” the dispatchability of RES electricity, iii) above 50%, the excess of electricity in the peaks has to be used to generate the thermal energy required by the consumers. The gas grid can be used as unique renewable energy carrier and storage system up to 65% of RES share.

Numerical analysis and artificial neural network-based prediction of two-phase flow pressure drop of refrigerants in T-junction

The two-phase flow behaviors in T-junction are quite complex in energy transport systems. In this paper, the two-phase flow pressure drop of refrigerants in a horizontal branching T-junction was analyzed numerically and predicted using artificial neural network. Firstly, the distribution of static and total pressure was obtained based on Eulerian method, and the parametric studies on the local pressure drop were conducted. It is observed that the vortexes in the entrance of branch pipe lead to the pressure fluctuation and irreversible pressure losses, and the “descend-ascend” of static and total pressure happens under high mass flow split ratio in run pipe. Then, the ANN predicting model of local pressure drop coefficients was established. It shows that GA-BPNN and PSO-BPNN has the best predicting ability for K12J and K13J respectively, and the relative errors are within 10% for most cases. Finally, the sensitivity analysis was conducted, indicating that the effect of mass flow split ratio (F) and inlet quality (x1) is the most significant for K12J and K13J respectively.

The Problem of Effort Distribution in Heavy Glycolytic Trials with Special Reference to the 400 m Dash in Track and Field.

Simple SummaryShort, intensive, but above lactate threshold physical trials or competitions which last <1 min but are close to this time limit, are on the border between glycolytic and aerobic efforts. The distribution of effort is critical in these tasks to achieve the best possible results. However, it is still unclear which of the general rules, descending from the theory, should be adopted by athletes (or any other subject facing a similar task). The 400 m dash competition of track and field has been taken in this systematic review as a paradigm for surveying the determinant factors which influence the pacing strategy and the end of effort. From the literature it emerges that there are several approaches, grounded in the philosophical basis of effort, which determine effort distribution. The problem is still open and a clear direction has not yet emerged from the available studies on the topic.Background. Biological factors are ultimately responsible for the cessation of effort in short, maximal glycolytic efforts. However, how these factors are sensed by the brain and act in a loop or feedforward way to regulate the distribution of effort is still unclear. Methods: A systematic review of existing literature on short term glycolytic exercise has been performed on publicly available databases (Google Scholar and Pudmed). Results: The problem of effort termination in fast maximal glycolytic activities after 100 years of research is still open. It is not clear if a central governor of effort exists, if the limitations are in the energy transport and utilization system, or in the psycho-social factors. Conclusions. The solution probably resides in a mixture of factors, but how the different components interact is still a mystery for science due to the philosophical grounding of the experimental approaches.

Planning for low-carbon energy-transportation system at metropolitan scale: A case study of Beijing, China

The urbanization and expansion of megalopolises have led to concerns on traffic, energy crisis and deteriorated green-house gas emissions, and thus the electric vehicles (EVs) are expected to be an essential role in alleviating these problems. In this study, a flexible-possibilist chanced constraints programming (FCCP) model is developed to plan low-carbon energy-transportation systems at the metropolitan scale (METS), which can incorporate multiple uncertainties in both the soft constraints and objective function. By integrating the possibilist programming with fuzzy sets and chanced constraint, the FCCP could tackle multiple complexities such as the combination of vague possibilities, flexibilities and probabilities, hence is superior to conventional approaches. The FCCP model is then applied for the planning METS in Beijing, and solutions are obtained under different satisfactory degrees and confidence levels. The results reveal that: 1) the power demand will be increasingly dependent on the imported power and renewable energy in Beijing; 2) the mass roll-out of EVs will reduce 6.7 million tonnes of CH, 44.7 million tonnes of CO and 1.08 × 105 million tonnes of CO2 respectively, while the need of battery supply facilities will cost approximately 4 × 109 dollars; 3) the carbon emissions will decrease with the growing number of EVs, the upgraded power supply pattern and the stringent policies. These findings could support decision-makers to plan the METS system when faced with multiple uncertainties.

Design and partial load operation optimization of integrated ship energy system based on supercritical CO2 waste heat recovery cycle

In the present work, a supercritical CO2 cycle, designed for recovering waste heat originating specifically from heavy-duty turbocharged diesel engines, constitutes the basis of an integrated energy system. The purpose of this system is to cover the time-varying power loads required during the operation of ships, appearing in diverse forms of energy (propulsive/mechanical, electrical, thermal). Optimization procedures are applied for the determination of the optimal design and of the optimal operational characteristics of the CO2 cycle during partial loading conditions. Appropriate techno-economic criteria are used for evaluating the optimality of the proposed engineering solutions. The effects of the added capital costs of the CO2 cycle on its useful power output are investigated, while the temporal variations of the energy loads are appropriately taken into account in the determination of the optimum CO2 cycle design characteristics. The inclusion of the CO2 cycle is economically justified, while a reduction of operational fuel costs from 5.8% to 6.3 % is achieved for a typical yearly energy profile, according to the optimal allocation of the useful power produced by the CO2 waste heat recovery cycle towards the propulsive or electric loads.

Negative Pressure Wave-Based Method for Abnormal Signal Location in Energy Transportation System

Abnormal signal location is an indispensable part to handle unexpected events such as pipeline leak in energy transportation system. However, unclear signal characteristics would make traditional location methods such as wavelet analysis failure in location process. To address it, a data-driven method based on negative pressure wave (NPW) is proposed in this article. First, a signal enhancement model based on Gaussian process regression (GPR) is proposed to highlight the changed signal characteristics. Then, a multi-objective evolutionary computation method is proposed to obtain the location result, which overcomes the shortcoming of unclear signal characteristics. Moreover, the signal transmission attenuation rules are added into the location process, which ensures the rationality and the reliability of the location result. Without introducing extra signal numbers and types, the proposed method could achieve higher accuracy and more robustness than traditional location methods such as wavelet analysis, which has the less 1.2% location deviation of the pipeline. Finally, different experiment results show that the proposed method is a realistic way to provide the position of abnormal signal source.

Analysis of the issue of the selection, operation and improvement of thermal insulation materials for pipelines of heating networks

Improving the energy efficiency of thermal energy generation, transportation and consumption systems is one of the priority tasks of the modern development of the fuel and energy complex of Russia. The climatic conditions of Russia determine the heat supply systems as an energy-intensive industry that consumes up to 40% of the primary energy resources of country. Russia is characterized by a high level of centralized heat supply, mainly from sources of combined generation of heat and electric energy, which led to the creation of an extensive pipeline system with a length of more than 250 thousand km with a diameter of 57 to 1400 mm. In practice, the following methods of laying pipelines are used: canal, canal-free, aboveground. The heat losses of pipelines of thermal networks amount to 324 million gcal/year, which is approximately 16% of the heat released to consumers, this indicates significant reserves of saving thermal energy. The successful solution of the problem of reducing heat losses during the transportation of the heat transfer agent can be achieved by using modern materials and developing highly efficient porous thermal insulation structures, as well as improving the methods of calculating heat networks and the optimal choice of thermal insulation materials for the required operating conditions.

Development of a new type of PCM thermal capsule transport system

Microencapsulated phase change slurry (MPCS) is a multiphase fluid with considerable potential to be a next-generation thermal energy transport material because of its high latent heat capacity and heat transfer rate. However, this encapsulated phase change slurry is difficult to transport because of its high viscosity, and its usage with conventional heat exchangers is complex. Therefore, in this study, a new type of thermal energy transport system using a rotary screw fin heat exchanger is developed for the safe and effective transportation of capsules. The long-distance direct PCM transport and MPCMS transport were firstly validated with the new system. The developed system played a role of pumping and heat exchanger has a pipe that rotates and transports MPCS using screw fins and enables the easy flow of water, resulting in enhancement of convective heat transfer. The results indicate that MPCS (<35% mass concentration) can be transported effectively, and the thermal energy transport per unit flow rate can be increased by a maximum of 180% under a supply–demand temperature difference of 25 °C. Finally, thermal cycle testing is conducted to verify the thermal durability of the capsules and fins, and the results confirm the reliability of the designed device.