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Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes.

In this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed.

The results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk.

To the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.

The spatial conflicts and congestion of construction resources are challenges that lead to the reduction in efficiency. The purpose of this paper is to enable users to detect and resolve workspace conflicts by implementing four resolution strategies in a five-dimensional (5D) CAD model. In addition to resolving conflicts, the model should be able to optimize time and cost of the projects. In other words, three variables of spatial conflicts, time and cost of project are considered simultaneously in the proposed model to find the optimum solution.

In the first step, a 5D simulation model is developed that includes time, cost and geometrical information of a project. Then, time-cost trade-off analysis was carried out to distinguish optimum schedule. The schedule was imported to the 5D CAD model to detect spatial conflicts. Finally, a novel algorithm was implemented to solve identified conflicts while imposing minimum project’s time and cost. Several iterations are performed to resolve all clashes using conflict resolution algorithm and visual simulation model.

The proposed methodology in this research was applied to a real case. Results showed that in comparison to the normal and initial schedule with 19 conflicts, the finalized schedule has no conflict, while time and cost of the project are both reduced.

Implementing the proposed methodology in construction projects requires proper technical basis in this field. In this regard, the executive user should have a proper understanding of the principles, concepts and tools of building information modeling and have project management knowledge. Also, the implementation conditions of the basic model requires the determination of the construction methods, estimated volumes of working items, scheduling and technical specification. The designed methodology also has two limitations regarding to its implementation. The first is the fact that strategies should be applied manually to the schedule. The other one pertains to the number of strategies used in the research. Four strategies have been used in the conflict resolution algorithm directly and the two others (spatial divisibility and activities breakdown strategies) have been used as default strategies in the visual simulation model. Since the unused strategies including the changing of construction method and the activity resources are subjective and depend upon the planner and project manager’s personal opinion, the authors have avoided using them in this research.

The method proposed in this research contributes the coordination of the working teams at the planning and execution phases of the project. In fact, the best location and work direction for each working team is presented as a schedule, so that the space conflict may not come about and the cost can be minimized. This visual simulation not only deepens the planners’ views about the executive barriers and the spatial conditions of the worksite, it also makes the construction engineers familiar on a daily basis with their executive scope. Therefore, it considerably improves the interactions and communication of the planning and construction teams. Another advantage and application of this methodology is the use of initial and available projects’ documents including the schedule and two-dimensional drawings. The integration of these basic documents in this methodology helps identify the spatial conflicts efficiently. To achieve this, the use of the existing and widely-used construction tools has facilitated the implementation of the methodology. Using this system, planners have applied the strategies in an order of priority and can observe the results of each strategy visually and numerically in terms of time, cost and conflicts. This methodology by providing the effective resolution strategies guides the practitioner to remove conflicts while optimum time and cost are imposed to project.

Contrary to the previous models that ignore cost, the proposed model is a 5D visual simulation model, which considers the variable of cost as a main factor for conflict identification and resolution. Moreover, a forward-pass approach is introduced to implement resolution strategies that are novel compared to other investigations.

This paper sets out to implement bounded high‐order (HO) resolution schemes in a hybrid finite volume/finite element method for the solution of the radiative transfer equation.

The hybrid finite volume/finite element method had formerly been developed using the step scheme, which is only first‐order accurate, for the spatial discretization. Here, several bounded HO resolution schemes, namely the MINMOD, CLAM, MUSCL and SMART schemes, formulated using the normalized variable diagram, were implemented using the deferred correction procedure.

The results obtained reveal an interaction between spatial and angular discretization errors, and show that the HO resolution schemes yield improved accuracy over the step scheme if the angular discretization error is small.

Although the HO resolution schemes reduce the spatial discretization error, they do not influence the angular discretization error. Therefore, the global error is only reduced if the angular discretization error is also small.

The use of HO resolution schemes is only effective if the angular refinement yields low‐angular discretization errors. Moreover, spatial and angular refinement should be carried out simultaneously.

The paper extends a methodology formerly developed in computational fluid dynamics, and aimed at the improvement of the solution accuracy, to the hybrid finite volume/finite element method for the solution of the radiative transfer equation.

We present an algorithm for contact resolution that is valid for a wide variety of polygonal two dimensional shapes and is of linear computational complexity. The algorithm is designed for use in discrete element analysis of granular and multibody systems exhibiting discontinuous behaviour. Contact detection usually consists of a spatial sorting phase and a contact resolution phase. The spatial sorting phase seeks to avoid an all‐to‐all body comparison by culling the number of objects which are potential contactors of a given object. The contact resolution phase resolves the details of the contact between two given objects. The algorithm presented here (called DFR) addresses the contact resolution phase and is applicable to convex geometries and to a restricted set of concave geometries. Examination of the algorithm establishes an upper bound linear computational complexity, of order O(N), with respect to the number of points (N) used to define the object boundary. The DFR algorithm is combined with a modified heapsort algorithm for spatial sorting of M bodies which has complexity O(M log M) and is applied to a baseline granular simulation problem to test its efficiency.

The purpose of this paper is to study planar sensor geometries for the measurement of film thickness in a viscous oil–water flow. The study is relevant due to there are only a few measurement techniques for oil-water flow and these techniques involve oil with low viscosity (close to the water viscosity). Specifically, some techniques have been used in the studies of annular flow (gas–liquid and liquid–liquid flows), but applications in other flow patterns were not encountered.

Different sensor geometries were numerically simulated to compare their characteristics and choose the best to measure the water film thickness in the oil–water flow through an impedance-based technique. Finite element method was used for resolving the tridimensional electric field over each sensor. The compared characteristics were the penetration depth, the sensitivity, the minimum spatial resolution (high spatial resolution) and the quasi-linear curve.

The best geometry tested has a spatial resolution of 2 × 2 mm, a penetration depth of 700 µm and a quasi-linear response in the measuring range. This geometry was tested by means of conductance and capacitance static experiments. From these experiments, it could be determined that conductance and the capacitance systems are promising for measuring water film thickness in an oil–water flow.

Several measurement techniques such as micro-PIV, planar laser-induced fluorescence and planar conductive or capacitive sensors that are supposed to be adaptable to the liquid–liquid flow have been proposed recently. Micro-PIV and planar-induced fluorescence need transparent pipes and fluids. On the other hand, conductive or capacitive methods have been only applied to low viscosity fluids. In that context, this paper proposes to study a new technique for non-intrusive measurement of the liquid-liquid flow. The main goal is the validation of the new planar sensor as a reference tool for the development of instrumentation for oilfield application.

The intended nationally determined contributions (INDCs) is a major outcome of the Paris Agreement on international cooperation to reduce emissions, and is likely to be the future scenario for carbon emissions. This paper aims to obtain the fine spatial pattern of carbon emissions in 2030, identify hot spots and analyze changes of carbon emissions with a spatial grid method.

Based on the integrated quantified INDCs of each economy in 2030, the authors predict the population density pattern in 2030 by using the statistics of current population density, natural growth rates and differences in population growth resulting from urbanization within countries. Then the authors regard population density as a comprehensive socioeconomic indicator for the top-bottom allocation of the INDC data to a 0.1° × 0.1° grid. Then, the grid spatial pattern of carbon emissions in 2030 is compared with that in 2016.

Under the unconditional and conditional scenarios, the global carbon emission grid values in 2030 will be within [0, 59,200.911] ktCO₂ and [0, 51,800.942] ktCO_2, respectively; eastern China, northern India, Western Europe and North America will continue to be the major emitters; grid carbon emissions will increase in most parts of the world compared to 2016, especially in densely populated areas.

While many studies have explored the overall global carbon emissions or warming under the INDC scenario, attention to spatial details is also required to help us make better emissions attributions and policy decisions from the perspective of the grid unit rather than the administrative unit.

The hands of intelligent robots perceive external stimuli and respond effectively according to tactile or pressure sensors. However, the traditional tactile and pressure sensors cannot perform human-skin-like intelligent properties of high sensitivity, large measurement range, multi-function and flexibility simultaneously. The purpose of this paper is to present a flexible tactile-pressure sensor based on hyper-elastics polydimethylsiloxane and plate capacitance.

With regard to this problem, this paper presents a flexible tactile-pressure sensor based on hyper-elastics PDMS and plate capacitance. The sensor has a size of 10 mm × 10 mm × 1.3 mm and is composed of four upper electrodes, one middle driving electrode and one lower electrode. The authors first analyzed the structure and the tactile-pressure sensing principle of human skin to obtain the design parameters of the sensor. Then they presented the working principle, material selection and mechanical structure design and fabrication process of the sensor. The authors also fabricated several sample devices of the sensor and carried out experiments to establish the relationship between the sensor output and the pressure.

The results show that the tactile part of the sensor can measure a range of 0.05-1N/mm² micro pressure with a sensitivity of 2.93 per cent/N and a linearity of 0.03 per cent. The pressure part of the sensor can measure a range of 1-30N/mm² pressure with a sensitivity of 0.08 per cent/N and a linearity of 0.07 per cent.

This paper analyzes the tactile and pressure sensing principles of human skin and develop an intelligent sensitive human-skin-like tactile-pressure sensor for intelligent robot perception systems. The sensor can achieve to imitate the tactile and pressure function simultaneously with a measurement resolution of 0.01 N and a spatial resolution of 2 mm.

With the growing deployment of variable renewable energy sources, such as wind and PV and the increasing interconnection of the power grid, multi-regional energy system models (ESMs) are increasingly challenged by the growth of model complexity. Therefore, the need for developing ESMs, which are realistic but also solvable with acceptable computational resources without losing output accuracy, arises. The purpose of this study is to propose a statistical approach to investigate asynchronous extreme events for different regions and then assess their ability to keep the output accuracy at the level of the full-resolution case.

To extract the extreme events from the residual demands, the paper focuses on analyzing the tail of the residual demand distributions by using statistical approaches. The extreme events then are implemented in an ESM to assess the effect of them in protecting the accuracy of the output compared with the full-resolution output.

The results show that extreme-high and fluctuation events are the most important events to be included in data input to maintain the flexibility output of the model when reducing the resolution. By including these events into the reduced data input, the output's accuracy reaches the level of 99.1% compared to full resolution case, while reducing the execution time by 20 times.

Moreover, including extreme-fluctuation along with extreme-high in the reduced data input helps the ESM to avoid misleading investment in conventional and low-efficient generators.

Risk assessment is imperative for disaster risk reduction. The risk is rooted to various physical, social, economic, demographic and environmental factors that determine the probable magnitude of loss during an extreme event. By way of bringing a conceptual model into practice, this paper aims to examine the flood risk of the Srinagar city.

The “risk triangle” model has been adopted in the present investigation evaluating parameters, reflective of hazard (intensity), exposure (spatial) and vulnerability (sensitivity) using Landsat-8 operational land imager scene (10 September 2014), global positioning system, Cartosat-1 digital elevation model and socioeconomic and demographic data (Census of India, 2011). The authors characterise flood hazard intensity on the basis of variability in water depth during a recent event (September 2014 Kashmir flood); spatial exposure as a function of terrain elevation; and socioeconomic structure and demographic composition of each municipal ward of the city as a determinant factor of the vulnerability. Statistical evaluation and geographic information system-based systematic integration of all the multi-resolution data layers helped to develop composite flood risk score of each ward of the city.

Principal deliverable of this study is flood risk map of the Srinagar city. The results reveal that approximately 46 per cent of the city comprising 33 municipal wards is at high risk, while rest of the area, i.e. 17 and 37 per cent, exhibit moderate and low levels of risk, constituting 23 and 12 municipal wards, respectively. It is very likely that the municipal wards expressing high risk may witness comparatively more damage (impact) during any future flood event. Thus, there is a need of planned interventions (structural and non-structural) to minimise the emergent risk.

Very rare attempts have been made to bring theoretical models of disaster research in practice; this is mainly because of the complexities associated with the data (selection, availability and subjectivity), methodology (integration, quantification) and resolution (spatial scales). In this direction, this work is expected to have considerable impact, as it provides a clear foundation to overcome such issues for the studies aiming at disaster risk assessment. Furthermore, using varied primary and secondary data, this paper demonstrates the relative (municipal wards) flood risk status of the Srinagar city, which is one of the key aspects for flood hazard mitigation.