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The Flameless Combustion (FC) regime has been pointed out as a promising combustion technique to lower the emissions of nitrogen oxides (NOx) while maintaining low CO and soot emissions, as well as high efficiencies. However, its accurate modeling remains a challenge. The prediction of pollutant species, especially NOx, is affected by the usually low total values that require higher precision from computational tools, as well as the incorporation of relevant formation pathways within the overall reaction mechanism that are usually neglected. The present work explores a multiple step modeling approach to tackle these issues. Initially, a CFD solution with simplified chemistry is generated [both the Eddy Dissipation Model (EDM) as well as the Flamelet Generated Manifolds (FGM) approach are employed]. Subsequently, its computational cells are clustered to form ideal reactors by user-defined criteria, and the resulting Chemical Reactor Network (CRN) is subsequently solved with a detailed chemical reaction mechanism. The capabilities of the clustering and CRN solving computational tool (AGNES—Automatic Generation of Networks for Emission Simulation) are explored with a test case related to FC. The test case is non-premixed burner based on jet mixing and fueled with CH4 tested for various equivalence ratios. Results show that the prediction of CO emissions was improved significantly with respect to the CFD solution and are in good agreement with the experimental data. As for the NOx emissions, the CRN results were capable of reproducing the non-monotonic behavior with equivalence ratio, which the CFD simulations could not capture. However, the agreement between experimental values and those predicted by CRN for NOx is not fully satisfactory. The clustering criteria employed to generate the CRNs from the CFD solutions were shown to affect the results to a great extent, pointing to future opportunities in improving the multi-step procedure and its application.

The assessment of greenhouse gases (GHGs) and air pollutants emitted to and removed from the atmosphere ranks high on international political and scientific agendas. Growing international concern and cooperation regarding the climate change problem have increased the need to consider the uncertainty in inventories of GHG emissions. The approaches to address uncertainty discussed in this special issue reflect attempts to improve national inventories, not only for their own sake but also from a wider, system analytic perspective. They seek to strengthen the usefulness of national emission inventories under a compliance and/or global monitoring and reporting framework. The papers in this special issue demonstrate the benefits of including inventory uncertainty in policy analyses. The issues raised by the authors and featured in their papers, along with the role that uncertainty analysis plays in many of their arguments, highlight the challenges and the importance of dealing with uncertainty. While the Intergovernmental Panel on Climate Change (IPCC) clearly stresses the value of conducting uncertainty analyses and offers guidance on executing them, the arguments made here in favor of performing these studies go well beyond any suggestions made by the IPCC to date. Improving and conducting uncertainty analyses are needed to develop a clear understanding and informed policy. Uncertainty matters and is key to many issues related to inventorying and reducing emissions. Considering uncertainty helps to avoid situations that can create a false sense of certainty or lead to invalid views of subsystems. Dealing proactively with uncertainty allows for the generation of useful knowledge that the international community should have to hand while strengthening the 2015 Paris Agreement, which had been agreed at the 21st Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC). However, considering uncertainty does not come free. Proper treatment of uncertainty is demanding because it forces us to take the step from “simple to complex” and to grasp a holistic system view. Only, thereafter, can we consider potential simplifications. That is, comprehensive treatment of uncertainty does not necessarily offer quick or easy solutions for policymakers. This special issue brings together 13 papers that resulted from the 2015 (4th) International Workshop on Uncertainty in Atmospheric Emissions, in Cracow, Poland. While they deal with many different aspects of the uncertainty in emission estimates, they are guided by the same principal question: “What GHGs shall be verified at what spatio-temporal scale to support conducive legislation at local and national scales, while ensuring effective governance at the global scale?” This question is at the heart of mitigation and adaptation. It requires an understanding of the entire system of GHG sources and sinks, their spatial characteristics and the temporal scales at which they react and interact, the uncertainty (accuracy and/or precision) with which fluxes can be measured, and last but not least, the consequences that follow from all of the aforementioned aspects, for policy actors to frame compliance and/or global monitoring and reporting agreements. This bigger system context serves as a reference for the papers in the special issue, irrespective of their spatio-temporal focus, and is used as a guide for the reader.

The article presents analysis results in the reconstruction of the tectonic conditions dynamics for the formation of local plicative deformations and rupturing under conditions of the research both the macrostructure and its local separation using the example of the southwestern area of Kalmius-Toretska kettle-hole in the Donetsk basin. Authors applied the scientific cognition method, representing a sequence of actions to establish structural links between variables and constant elements of the Investigational tectonic system, based on statistical and mathematical methods of analysis. The characteristics of the anticlinal structure formation in the studied area - fields of the “Butivska” mine were obtained. It was revealed that the initial horizontal attitude of rocks of the studied area was changed by a monoclinal attitude with a north-western dip and a north-east strike. Afterwards, under the conditions of tectonic near latitudinal compression and near meridional tension, anticlinal folding was formed. Then, under the influence of shear fields when the deformation mode was enhanced, a compression duplex was formed within which local echelon folding and fracture was formed - Oktiabrskyi fault #1.

Abstract Various assumptions are often made to model turbomachinery bladed assemblies. In particular, the cyclic symmetry of single rotor stages, and dynamically independence of isolated rotor stages are frequently used. The first assumption enables a drastic reduction of the required computational resources by considering only one sector instead of the entire assembly to model and analyze the dynamic behavior of the complete structure. However, small random blade-to-blade structural variations, known as mistuning, exist due to manufacturing tolerances, etc. and significantly affect the dynamic behavior of bladed disks. The second assumption also reduces the needed computational resources and time. However, ignore inter-stage coupling does not always describe accurately the disk or drum flexibility especially at the inter-stage boundaries. In this work, the component mode mistuning method is used for multi-stage assemblies to create a mistuning identification approach. An experimental modal analysis is performed on a two-stage monobloc academic bladed drum. The frequency response function is measured using a base excitation with an electrodynamic shaker and one measurement point per blade of each stage is used. The approach is used to identify mistuning in a multi-stage rotor. Numerical and experimental results are presented. Results show that the proposed approach is effective even for modes which are multi-stage.

Abstract This paper presents some research activities conducted at the Centre Spatial de Liege (CSL) in the field of space solar arrays and concentration. With the new generation of high efficiency solar cells, solar concentration brings new insights for future high power spacecrafts. A trade-off study is presented in this paper. Two different trough concentrators, and a linear Fresnel lens concentrator are compared to rigid arrays. Thermal and optical behaviors are included in the analysis. Several technical aspects are discussed: • Off-pointing with concentrators induces collection loss and illumination non uniformity, reducing the PV efficiency. • Concentrator deployment increases the mission risk. • Reflective trough concentrators are attractive and already proven. Coating is made of VDA (Aluminum). A comprehensive analysis of PV conversion increase with protected silver is presented. • Solar concentration increases the heat load on solar cells, while the conversion efficiency is significantly decreasing at warm temperatures. To conclude, this paper will point out the new trends and the key factors to be addressed for the next generation of solar generators.

Abstract The present work focuses on the numerical simulation of Moderate or Intense Low oxygen Dilution combustion condition, using the Partially-Stirred Reactor model for turbulence-chemistry interactions. The Partially-Stirred Reactor model assumes that reactions are confined in a specific region of the computational cell, whose mass fraction depends both on the mixing and the chemical time scales. Therefore, the appropriate choice of mixing and chemical time scales becomes crucial to ensure the accuracy of the numerical simulation prediction. Results show that the most appropriate choice for mixing time scale in Moderate or Intense Low oxygen Dilution combustion regime is to use a dynamic evaluation, in which the ratio between the variance of mixture fraction and its dissipation rate is adopted, rather than global estimations based on Kolmogorov or integral mixing scales. This is supported by the validation of the numerical results against experimental profiles of temperature and species mass fractions, available from measurements on the Adelaide Jet in Hot Co-flow burner. Different approaches for chemical time scale evaluation are also compared, using the species formation rates, the reaction rates and the eigenvalues of the formation rate Jacobian matrix. Different co-flow oxygen dilution levels and Reynolds numbers are considered in the validation work, to evaluate the applicability of Partially-Stirred Reactor approach over a wide range of operating conditions. Moreover, the influence of specifying uniform and non-uniform boundary conditions for the chemical scalars is assessed. The present work sheds light on the key mechanisms of turbulence-chemistry interactions in advanced combustion regimes. At the same time, it provides essential information to advance the predictive nature of computational tools used by scientists and engineers, to support the development of new technologies.

Abstract This paper investigates the impact of urbanization on energy consumption by applying the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) in case of Malaysia. The study covers the time period of 1970Q1–2011Q4. The unit root test and the ARDL bounds testing approach have been applied to examine integrating properties and long run relationship in the presence of structural breaks. Our results validated the existence of cointegration and exposed that urbanization is a major contributor in energy consumption. Affluence raises energy demand. Capital stock boosts energy consumption. Trade openness leads to affluence and hence increases energy consumption. The causality analysis finds that urbanization Granger causes energy consumption. The feedback effect is found between energy consumption and affluence and, energy consumption and capital. The bidirectional causality exists between trade openness and energy consumption.