• Energy Research
• 2016-2025close
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Abstract. Flooding in the Amazon basin is frequently attributed to modes of large-scale climate variability, but little attention is paid to how these modes influence the timing and duration of floods despite their importance to early warning systems and the significant impacts that these flood characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (GloFAS 2.1) and observed data at 58 gauging stations are used to examine whether positive or negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (1979–2015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative El Niño–Southern Oscillation (ENSO) phases when the sea surface temperature (SST) anomaly is positioned in the central tropical Pacific. This response is not identified for the eastern Pacific index, highlighting how the response can differ between ENSO types. Although flood magnitude and duration were found to be highly correlated, the impacts of large-scale climate variability on these characteristics are non-linear; some increases in annual flood maxima coincide with decreases in flood duration. The impact of flood timing, however, does not follow any notable pattern for all indices analysed. Finally, observed and simulated changes are found to be much more highly correlated for negative ENSO phases compared to the positive phase, meaning that GloFAS struggles to accurately simulate the differences in flood characteristics between El Niño and neutral years. These results have important implications for both the social and physical sectors working towards the improvement of early warning action systems for floods.

Abstract The use of electric bus fleets has become a topical issue in recent years. Several companies and municipalities, either voluntarily or to comply with legal requirements, will transition to greener bus fleets in the next decades. Such transitions are often established by fleet electrification targets, which dictate the number of electric buses that should be in the fleet by a given time period. In this paper we introduce a comprehensive optimization-based decision making tool to support such transitions. More precisely, we present a fleet replacement problem which allows organizations to determine bus replacement plans that will meet their fleet electrification targets in a cost-effective way, namely considering purchase costs, salvage revenues, operating costs, charging infrastructure investments, and demand charges. We account for several charging infrastructure options, such as slow and fast plug-in stations, overhead pantograph chargers, and inductive (wireless) chargers. We refer to this problem as the electric bus fleet transition problem, and we model it as an integer linear program. We apply our model to conduct computational experiments based on several scenarios. We use real data provided by a public transit agency in order to draw insights into optimal transition plans.

New energy generation and storage systems are continuously being developed due to climate change, resource scarcity, and environmental laws. Some systems are incremental innovations of existing systems while others are radical innovations. Radical innovation systems are risky investments due to their relevant technical and economic uncertainties. Prototyping can hedge these risks by spending a fraction of the cost of a full-scale system and in return receiving economic and technical information regarding the system. In economic terms, prototyping is an option to hedge risk coming at a cost that needs to be properly assessed. Real options analysis is the project appraisal approach for these assessments. This paper aims to introduce and test an algorithm based on real options analysis to quantitatively assess the “option to prototype” in the energy sector. First, the interrelated research areas of prototyping, energy systems, and real options analysis are reviewed. Then, a novel algorithm is presented and applied to an innovative Generation Integrated Energy Storage system: Wind-driven Thermal Pumping to demonstrate the effectiveness of option to prototype and the main parameters influencing this decision. Results show that the cost of the prototype and the market size (number of identical systems to build) are key parameters.

Within the Best Estimate Plus Uncertainty framework for the safety analysis of Nuclear Power Plants, the quantification of the uncertainties affecting the Thermal-Hydraulics (T-H) codes used is crucial. For this, Inverse Uncertainty Quantification (IUQ) methodologies are being developed for determining the probability density functions of relevant T-H codes input parameters, based on experimental data from Separate Effect Tests (SETs) experimental facilities. In practice, IUQ is challenged by the large range of variability of the experimental data in terms of Initial and Boundary Conditions (ICs & BCs), because the experimental campaigns are designed to cover the widest possible domain of conditions with the smallest number of experiments, so that same or similar ICs and BCs are seldomly repeated. To address this issue, we propose to use global sensitivity analysis, to tailor the IUQ on specific sub-regions described by segmented ICs & BCs domains. The methodology proposed is exemplified on two SETs, namely Sozzi-Sutherland and Super Moby Dick, whose experimental databases have been made available in the ATRIUM (Application Tests for Realization of Inverse Uncertainty quantification and validation Methodologies in thermal hydraulics) project promoted by the OECD/NEA/CSNI. The results obtained are superior to those of traditional IUQ methodologies for models highly sensitive to ICs & BCs.

AbstractThe FAMU experiment aims to measure for the first time the hyperfine splitting of the muonic hydrogen ground state. From this measurement the proton Zemach radius can be derived and this will shed light on the determination of the proton charge radius. In this paper, we describe the scientific goal, the method and the detailed preparatory work. This includes the outcome of preliminary measurements, subsequent refined simulations and the evaluation of the expected results. The experimental setup being built for the measurement of the hyperfine splitting to be performed at the RAL laboratory muon facility is also described.

Abstract The sustainability of the built environment largely depends on its energy and environmental performances. The overall objective, across the different phases of the building life cycle, is to improve building and system performances in terms of economics, comfort, environmental impact and durability. Several modelling methodologies have been developed in order to evaluate the energy performance of buildings. Generally, every modelling methodology responds effectively to some specific tasks, but there exists a lack of integration in particular with respect to the cross-disciplinary role of data. Given the multi-scale and multi-objective nature of the problem of optimization of the energy and environmental performances of the built environment, an appropriate synthesis and integration process in modelling methodologies has to be identified, addressing realistically the uncertainties inherently present in modelling strategies. Visualization and data analysis techniques are successfully used in a wide variety of applications, both in theoretical and applied domains, but questions remains about their robustness, efficiency and applicability to the problems introduced before. The paper aims to analyze critically these topics by means of case studies, showing a possible path to create a multi-scale methodology able to synthesize all the relevant aspects.

A novel reactor system is presented and investigated for the production of a hydrogen rich gas stream for power or ammonia production, based on pre-combustion chemical looping (PCCL) technology using dynamically operated packed bed reactors. In this process, the oxygen carrier (OC) is alternately oxidized with a gas mixture of air and steam to produce a H2/N2 product gas stream combining oxidation by air and water-splitting, and subsequently reduced with syngas producing a concentrated CO2 stream. The process is carried out at elevated pressure, but at intermediate temperature (in the range of 600-900 °C), which allows circumventing the extremely high temperatures required in chemical-looping combustion. In addition, the N2/H2 gas stream can be produced at the required composition for ammonia production, rendering this process also competitive with the conventional ammonia production. A preliminary experimental study has been carried out in a 2 kWth packed bed reactor using an iron-based oxygen carrier. The influence of the operating temperature and the initial solid composition during the oxidation cycle on the H2-rich gas yield has been investigated. The complete reduction to pure iron reduces the reactivity of the material due to sintering, whereas a controlled reduction to wüstite (FeO) allows to maintain a higher stability of the material, although the oxygen capacity is decreased.A preliminary thermodynamic assessment of the integrated PCCL plant for power production with natural gas has been carried out reaching an electrical efficiency of 49-51.5% (depending on the plant arrangement) with a carbon capture rate above 95%. The main parameter affecting the plant performance was found to be the steam requirement during the oxidation cycle. The comparison with benchmark technologies has confirmed the potential of the PCCL system.