Improving urban bus emission and fuel consumption modeling by incorporating passenger load factor for real world driving

Vehicle Specific Power (VSP) has been increasingly used as a good indicator for the instantaneous power demand on engines for real world driving in the field of vehicle emission and fuel consumption modeling. A fixed vehicle mass is normally used in VSP calculations. However, the influence of passenger load was always been neglected. The major objective of this paper is to quantify the influence of passenger load on diesel bus emissions and fuel consumption based on the real-world on-road emission data measured by the Portable Emission Measurement System (PEMS) on urban diesel buses in Nanjing, China. Meanwhile, analyses are conducted to investigate whether passenger load affected the accuracy of emission and fuel consumption estimations based on VSP. The results show that the influence of passenger load on emission and fuel consumption rates were related to vehicle's speed and acceleration. As for the distance-based factors, the influence of passenger load was not obvious when the buses were driving at a relative high speed. However the effects of passenger load were significant when the per-passenger factor was used. Per-passenger emission and fuel consumption factors decreased as the passenger load increased. It was also found that the influence of passenger load can be omitted in the emission and fuel consumption rate models at low and medium speed bins but has to be considered in the models for high speed and VSP bins. Otherwise it could lead to an error of up to 49%. The results from this research will improve the accuracy of urban bus emission and fuel consumption modeling and can be used to improve planning and management of city buses and thus achieve energy saving and emission reduction

Catalytic, Kinetic, and Mechanistic Insights into the Fixation of CO2 with Epoxides Catalyzed by Phenol-Functionalized Phosphonium Salts

A series of hydroxy-functionalized phosphonium salts were studied as bifunctional catalysts for the conversion of CO2 with epoxides under mild and solvent-free conditions. The reaction in the presence of a phenol-based phosphonium iodide proceeded via a first order rection kinetic with respect to the substrate. Notably, in contrast to the aliphatic analogue, the phenol-based catalyst showed no product inhibition. The temperature dependence of the reaction rate was investigated, and the activation energy for the model reaction was determined from an Arrhenius-plot (Ea =39.6 kJ mol-1 ). The substrate scope was also evaluated. Under the optimized reaction conditions, 20 terminal epoxides were converted at room temperature to the corresponding cyclic carbonates, which were isolated in yields up to 99 %. The reaction is easily scalable and was performed on a scale up to 50 g substrate. Moreover, this method was applied in the synthesis of the antitussive agent dropropizine starting from epichlorohydrin and phenylpiperazine. Furthermore, DFT calculations were performed to rationalize the mechanism and the high efficiency of the phenol-based phosphonium iodide catalyst. The calculation confirmed the activation of the epoxide via hydrogen bonding for the iodide salt, which facilitates the ring-opening step. Notably, the effective Gibbs energy barrier regarding this step is 97 kJ mol-1 for the bromide and 72 kJ mol-1 for the iodide salt, which explains the difference in activity

The dynamics of financial stability in complex networks

We address the problem of banking system resilience by applying off-equilibrium statistical physics to a system of particles, representing the economic agents, modelled according to the theoretical foundation of the current banking regulation, the so called Merton-Vasicek model. Economic agents are attracted to each other to exchange `economic energy', forming a network of trades. When the capital level of one economic agent drops below a minimum, the economic agent becomes insolvent. The insolvency of one single economic agent affects the economic energy of all its neighbours which thus become susceptible to insolvency, being able to trigger a chain of insolvencies (avalanche). We show that the distribution of avalanche sizes follows a power-law whose exponent depends on the minimum capital level. Furthermore, we present evidence that under an increase in the minimum capital level, large crashes will be avoided only if one assumes that agents will accept a drop in business levels, while keeping their trading attitudes and policies unchanged. The alternative assumption, that agents will try to restore their business levels, may lead to the unexpected consequence that large crises occur with higher probability

Dynamic reconfiguration of cloud application architectures

[EN] Service-based cloud applications are software systems that continuously evolve to satisfy new user requirements and technological changes. This kind of applications also require elasticity, scalability, and high availability, which means that deployment of new functionalities or architectural adaptations to fulfill service level agreements (SLAs) should be performed while the application is in execution. Dynamic architectural reconfiguration is essential to minimize system disruptions while new or modified services are being integrated into existing cloud applications. Thus, cloud applications should be developed following principles that support dynamic reconfiguration of services, and also tools to automate these reconfigurations at runtime are needed. This paper presents an extension of a model-driven method for dynamic and incremental architecture reconfiguration of cloud services that allows developers to specify new services as software increments, and the tool to generate the implementation code for the services integration logic and the deployment and architectural reconfiguration scripts specific to the cloud environment in which the service will be deployed (e.g., Microsoft Azure). We also report the results of a quasi-experiment that empirically validate our method. It was conducted to evaluate their perceived ease of use, perceived usefulness, and perceived intention to use. The results show that the participants perceive the method to be useful, and they also expressed their intention to use the method in the future. Although further experiments must be carried out to corroborate these results, the method has proven to be a promising architectural reconfiguration process for cloud applications in the context of agile and incremental development processes.This research is supported by the Value@Cloud project (MINECO TIN2013-46300-R), DIUC_XIV_2016_038 project, and the Microsoft Azure Research AwardZúñiga-Prieto, MÁ.; Gonzalez-Huerta, J.; Insfran, E.; Abrahao Gonzales, SM. (2018). Dynamic reconfiguration of cloud application architectures. Software Practice and Experience. 48(2):327-344. https://doi.org/10.1002/spe.2457S32734448

Reduced carbon use efficiency and increased microbial turnover with soil warming

Global soil carbon (C) stocks are expected to decline with warming, and changes in microbial processes are key to this projection. However, warming responses of critical microbial parameters such as carbon use efficiency (CUE) and biomass turnover (rB) are not well understood. Here, we determine these parameters using a probabilistic inversion approach that integrates a microbial-enzyme model with 22 years of carbon cycling measurements at Harvard Forest. We find that increasing temperature reduces CUE but increases rB, and that two decades of soil warming increases the temperature sensitivities of CUE and rB. These temperature sensitivities, which are derived from decades-long field observations, contrast with values obtained from short-term laboratory experiments. We also show that long-term soil C flux and pool changes in response to warming are more dependent on the temperature sensitivity of CUE than that of rB. Using the inversion-derived parameters, we project that chronic soil warming at Harvard Forest over six decades will result in soil C gain of \u3c1.0% on average (1st and 3rd quartiles: 3.0% loss and 10.5% gain) in the surface mineral horizon. Our results demonstrate that estimates of temperature sensitivity of microbial CUE and rB can be obtained and evaluated rigorously by integrating multidecadal datasets. This approach can potentially be applied in broader spatiotemporal scales to improve long-term projections of soil C feedbacks to climate warming

Probabilistic Graphs for Sensor Data-driven Modelling of Power Systems at Scale

The growing complexity of the power grid, driven by increasing share of distributed energy resources and by massive deployment of intelligent internet-connected devices, requires new modelling tools for planning and operation. Physics-based state estimation models currently used for data filtering, prediction and anomaly detection are hard to maintain and adapt to the ever-changing complex dynamics of the power system. A data-driven approach based on probabilistic graphs is proposed, where custom non-linear, localised models of the joint density of subset of system variables can be combined to model arbitrarily large and complex systems. The graphical model allows to naturally embed domain knowledge in the form of variables dependency structure or local quantitative relationships. A specific instance where neural-network models are used to represent the local joint densities is proposed, although the methodology generalises to other model classes. Accuracy and scalability are evaluated on a large-scale data set representative of the European transmission grid

Estudio aplicación del modelo de madurez capacidad de ingeniería. En seguridad de los sistemas (SSE-CMM) por áreas de proyecto y organización

<p>Secondary organic aerosol (SOA) particles have been found to be efficient ice-nucleating particles under the cold conditions of (tropical) upper-tropospheric cirrus clouds. Whether they also are efficient at initiating freezing under slightly warmer conditions as found in mixed-phase clouds remains undetermined. Here, we study the ice-nucleating ability of photochemically produced SOA particles with the combination of the Manchester Aerosol Chamber and Manchester Ice Cloud Chamber. Three SOA systems were tested resembling biogenic and anthropogenic particles as well as particles of different phase state. These are namely <i>α</i>-pinene, heptadecane, and 1,3,5-trimethylbenzene. After the aerosol particles were formed, they were transferred into the cloud chamber, where subsequent quasi-adiabatic cloud activation experiments were performed. Additionally, the ice-forming abilities of ammonium sulfate and kaolinite were investigated as a reference to test the experimental setup. <br/><br/> Clouds were formed in the temperature range of &minus;20 to &minus;28.6 °C. Only the reference experiment using dust particles showed evidence of ice nucleation. No ice particles were observed in any other experiment. Thus, we conclude that SOA particles produced under the conditions of the reported experiments are not efficient ice-nucleating particles starting at liquid saturation under mixed-phase cloud conditions.</p

Evidence for a flux transfer event generated by multiple X-line reconnection at the magnetopause

Magnetic flux transfer events (FTEs) are signatures of unsteady magnetic reconnection, often observed at planetary magnetopauses. Their generation mechanism, a key ingredient determining how they regulate the transfer of solar wind energy into magnetospheres, is still largely unknown. We report THEMIS spacecraft observations on 2007-06-14 of an FTE generated by multiple X-line reconnection at the dayside magnetopause. The evidence consists of (1) two oppositely-directed ion jets converging toward the FTE that was slowly moving southward, (2) the cross-section of the FTE core being elongated along the magnetopause normal, probably squeezed by the oppositely-directed jets, and (3) bidirectional field-aligned fluxes of energetic electrons in the magnetosheath, indicating reconnection on both sides of the FTE. The observations agree well with a global magnetohydrodynamic model of the FTE generation under large geomagnetic dipole tilt, which implies the efficiency of magnetic flux transport into the magnetotail being lower for larger dipole tilt