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The Vehicle Routing Problem (VRP) is one of the most optimized tasks studied and it is implemented in a huge variety of industrial applications. The objective is to design a set of minimum cost paths for each vehicle in order to serve a given set of customers. Our attention is focused on a variant of VRP, the capacitated vehicle routing problem when applied to natural gas distribution networks. Managing natural gas distribution networks includes facing a variety of decisions ranging from human resources and material resources to facilities, infrastructures, and carriers. Despite the numerous papers available on vehicle routing problem, there are only a few that study and analyze the problems occurring in capillary distribution operations such as those found in a metropolitan area. Therefore, this work introduces a new algorithm based on the Saving Algorithm heuristic approach which aims to solve a Capacitated Vehicle Routing Problem with time and distance constraints. This joint algorithm minimizes the transportation costs and maximizes the workload according to customer demand within the constraints of a time window. Results from a real case study in a natural gas distribution network demonstrates the effectiveness of the approach.

A big amount of the pressure energy content in the natural gas distribution networks is wasted in throttling valves of pressure reduction stations (PRSs). Just a few energy recovery systems are currently installed in PRSs and are mostly composed of radial turboexpanders coupled with cogeneration internal combustion engines or gas-fired heaters providing the necessary preheating. This paper clarifies the reason for the scarce diffusion of energy recovery systems in PRSs and provides guidelines about the most feasible energy recovery technologies. Nine thousand PRSs are monitored and allocated into 12 classes, featuring different expansion ratios and available power. The focus is on PRSs with 1-to-20 expansion ratio and 1-to-500 kW available power. Three kinds of expanders are proposed in combination with different preheating systems based on boilers, heat pumps, or cogeneration engines. The goal is to identify, for each class, the most feasible combination by looking at the minimum payback period and maximum net present value. Results show that small size volumetric expanders with low expansion ratios and coupled with gas-fired heaters have the highest potential for large-scale deployment of energy recovery from PRSs. Moreover, the total recoverable energy using the feasible recovery systems is approximately 15% of the available energy.

In a carbon-constrained world, natural gas with low emission intensity plays an important role in the energy consumption area. Energy consumers and distribution networks are linked via energy hubs. Meanwhile, reconfiguration that optimizes operational performance while maintaining a radial network topology is a worldwide technique in the electricity distribution system. To improve the overall efficiency of energy infrastructure, the expansion of electricity distribution lines and elements within energy hubs should be co-planned. In this paper, the co-planning process is modeled as a mixed integer quadratic programming problem to handle conflicting objectives simultaneously. We propose a novel model to identify the optimal co-expansion plan in terms of total cost. Operational factors including energy storages and reconfiguration are considered within the systems to serve electricity, cooling and heating loads. Reconfiguration and elements in energy hubs can avoid or defer new elements’ installation to minimize the investment cost, maintenance cost, operation cost, and interruption cost in the planning horizon. The proposed co-planning approach is verified on 3 and 12-node electricity and natural gas distribution systems coupled via energy hubs. Numerical results show the ability of our proposed expansion co-planning approach based on energy hub in meeting energy demand.

This paper focuses on expansion co-planning studies of natural gas and electricity distribution systems. The aim is to develop a mixed-integer linear programming (MILP) model for such problems to guarantee the finite convergence to optimality. To this end, at first the interconnection of electricity and natural gas networks at demand nodes is modelled by the concept of energy hub (EH). Then, mathematical model of expansion studies associated with the natural gas, electricity and EHs are extracted. The optimization models of these three expansion studies incorporate investment and operation costs. Based on these separate planning problems, which are all in the form of mixed-integer nonlinear programming (MINLP), joint expansion model of multi-carrier energy distribution system is attained and linearized to form a MILP optimization formulation. The presented optimization framework is illustratively applied to an energy distribution network and the results are discussed.

Glycyrrhiza has a long history of applications and a wide range of pharmacological effects. It is known as the “king of all herbs”. Glycyrrhiza is effective in clearing heat, detoxifying, relieving cough, and tonifying qi and has good bioactivity in multiple inflammatory, immune, and tumor diseases. This review aims to summarize the origin, distribution, and anti-digestive system tumor mechanism of glycyrrhiza and its homologous applications in medicine and food. The active compounds include triterpenoids, flavonoids, and coumarins, which are widely used in clinical treatments, disease prevention, and daily foods because of their “enhancement of efficacy” and “reduction of toxicity” against digestive system tumors. This paper reviews the use of glycyrrhiza in digestive system tumors and provides an outlook on future research and clinical applications.

Since the value of the hydraulic resistance depends on flow rate, problem of flow distribution per pipes in a gas or water distributive looped pipelines has to be solved using iterative procedure. A number of iterative methods for determining of hydraulic solution of pipeline networks, such as, Hardy Cross, Modified Hardy Cross, Node-Loop method, Modified Node method and M.M. Andrijašev method are shown in this paper. Convergence properties are compared and discussed using a simple network with three loops. In a municipal gas pipeline, natural gas can be treated as incompressible fluid. Even under this circumstance, calculation of water pipelines cannot be literary copied and applied for calculation of gas pipelines. Some diferences in calculations of networks for distribution of these two fluids, i.e. water apropos natural gas are also noted.

Nitrile hydratase (NHase, EC 4.2.1.84) is one type of metalloenzyme participating in the biotransformation of nitriles into amides. Given its catalytic specificity in amide production and eco-friendliness, NHase has overwhelmed its chemical counterpart during the past few decades. However, unclear catalytic mechanism, low thermostablity, and narrow substrate specificity limit the further application of NHase. During the past few years, numerous studies on the theoretical and industrial aspects of NHase have advanced the development of this green catalyst. This review critically focuses on NHase research from recent years, including the natural distribution, gene types, posttranslational modifications, expression, proposed catalytic mechanism, biochemical properties, and potential applications of NHase. The developments of NHase described here are not only useful for further application of NHase, but also beneficial for the development of the fields of biocatalysis and biotransformation.

Complex networks are ubiquitous: a cell, the human brain, a group of people and the Internet are all examples of interconnected many-body systems characterized by macroscopic properties that cannot be trivially deduced from those of their microscopic constituents. Such systems are exposed to both internal, localized, failures and external disturbances or perturbations. Owing to their interconnected structure, complex systems might be severely degraded, to the point of disintegration or systemic dysfunction. Examples include cascading failures, triggered by an initially localized overload in power systems, and the critical slowing downs of ecosystems which can be driven towards extinction. In recent years, this general phenomenon has been investigated by framing localized and systemic failures in terms of perturbations that can alter the function of a system. We capitalize on this mathematical framework to review theoretical and computational approaches to characterize robustness and resilience of complex networks. We discuss recent approaches to mitigate the impact of perturbations in terms of designing robustness, identifying early-warning signals and adapting responses. In terms of applications, we compare the performance of the state-of-the-art dismantling techniques, highlighting their optimal range of applicability for practical problems, and provide a repository with ready-to-use scripts, a much-needed tool set.Complex biological, social and engineering systems operate through intricate connectivity patterns. Understanding their robustness and resilience against disturbances is crucial for applications. This Review addresses systemic breakdown, cascading failures and potential interventions, highlighting the importance of research at the crossroad of statistical physics and machine learning.

Characterizing and attributing methane (CH4) emissions across varying scales are important from environmental, safety, and economic perspectives and are essential for designing and evaluating effective mitigation strategies. Mobile real-time measurements of CH4 in ambient air offer a fast and effective method to identify and quantify local CH4 emissions in urban areas. We carried out extensive campaigns to measure CH4 mole fractions at the street level in Utrecht, the Netherlands (2018 and 2019), and Hamburg, Germany (2018). We detected 145 leak indications (LIs; i.e., CH4 enhancements of more than 10 % above background levels) in Hamburg and 81 LIs in Utrecht. Measurements of the ethane-to-methane ratio (C2:C1), methane-to-carbon dioxide ratio (CH4:CO2), and CH4 isotope composition (δ13C and δD) show that in Hamburg about 1∕3 of the LIs, and in Utrecht 2∕3 of the LIs (based on a limited set of C2:C1 measurements), were of fossil fuel origin. We find that in both cities the largest emission rates in the identified LI distribution are from fossil fuel sources. In Hamburg, the lower emission rates in the identified LI distribution are often associated with biogenic characteristics or (partly) combustion. Extrapolation of detected LI rates along the roads driven to the gas distribution pipes in the entire road network yields total emissions from sources that can be quantified in the street-level surveys of 440±70 t yr−1 from all sources in Hamburg and 150±50 t yr−1 for Utrecht. In Hamburg, C2:C1, CH4:CO2, and isotope-based source attributions show that 50 %–80 % of all emissions originate from the natural gas distribution network; in Utrecht more limited attribution indicates that 70 %–90 % of the emissions are of fossil origin. Our results confirm previous observations that a few large LIs, creating a heavy tail, are responsible for a significant proportion of fossil CH4 emissions. In Utrecht, 1∕3 of total emissions originated from one LI and in Hamburg >1/4 from two LIs. The largest leaks were located and fixed quickly by GasNetz Hamburg once the LIs were shared, but 80 % of the (smaller) LIs attributed to the fossil category could not be detected and/or confirmed as pipeline leaks. This issue requires further investigation.

Atmospheric inverse modelling has the potential to provide observation-based estimates of greenhouse gas emissions at the country scale, thereby allowing for an independent validation of national emission inventories. Here, we present a regional-scale inverse modelling study to quantify the emissions of methane (CH4) from Switzerland, making use of the newly established CarboCount-CH measurement network and a high-resolution Lagrangian transport model. In our reference inversion, prior emissions were taken from the \"bottom-up\" Swiss Greenhouse Gas Inventory (SGHGI) as published by the Swiss Federal Office for the Environment in 2014 for the year 2012. Overall we estimate national CH4 emissions to be 196 ± 18 Gg yr−1 for the year 2013 (1σ uncertainty). This result is in close agreement with the recently revised SGHGI estimate of 206 ± 33 Gg yr−1 as reported in 2015 for the year 2012. Results from sensitivity inversions using alternative prior emissions, uncertainty covariance settings, large-scale background mole fractions, two different inverse algorithms (Bayesian and extended Kalman filter), and two different transport models confirm the robustness and independent character of our estimate. According to the latest SGHGI estimate the main CH4 source categories in Switzerland are agriculture (78 %), waste handling (15 %) and natural gas distribution and combustion (6 %). The spatial distribution and seasonal variability of our posterior emissions suggest an overestimation of agricultural CH4 emissions by 10 to 20 % in the most recent SGHGI, which is likely due to an overestimation of emissions from manure handling. Urban areas do not appear as emission hotspots in our posterior results, suggesting that leakages from natural gas distribution are only a minor source of CH4 in Switzerland. This is consistent with rather low emissions of 8.4 Gg yr−1 reported by the SGHGI but inconsistent with the much higher value of 32 Gg yr−1 implied by the EDGARv4.2 inventory for this sector. Increased CH4 emissions (up to 30 % compared to the prior) were deduced for the north-eastern parts of Switzerland. This feature was common to most sensitivity inversions, which is a strong indicator that it is a real feature and not an artefact of the transport model and the inversion system. However, it was not possible to assign an unambiguous source process to the region. The observations of the CarboCount-CH network provided invaluable and independent information for the validation of the national bottom-up inventory. Similar systems need to be sustained to provide independent monitoring of future climate agreements.