PranCS: A protocol and discrete controller synthesis tool

© 2017, Springer International Publishing AG. PranCS is a tool for synthesizing protocol adapters and discrete controllers. It exploits general search techniques such as simulated annealing and genetic programming for homing in on correct solutions, and evaluates the fitness of candidates by using model-checking results. Our Proctocol and Controller Synthesis (PranCS) tool uses NuSMV as a back-end for the individual model-checking tasks and a simple candidate mutator to drive the search. PranCS is also designed to explore the parameter space of the search techniques it implements. In this paper, we use PranCS to study the influence of turning various parameters in the synthesis process

LES-based Study of the Roughness Effects on the Wake of a Circular Cylinder from Subcritical to Transcritical Reynolds Numbers

This paper investigates the effects of surface roughness on the flow past a circular cylinder at subcritical to transcritical Reynolds numbers. Large eddy simulations of the flow for sand grain roughness of size k/D = 0.02 are performed (D is the cylinder diameter). Results show that surface roughness triggers the transition to turbulence in the boundary layer at all Reynolds numbers, thus leading to an early separation caused by the increased momentum deficit, especially at transcritical Reynolds numbers. Even at subcritical Reynolds numbers, boundary layer instabilities are triggered in the roughness sublayer and eventually lead to the transition to turbulence. The early separation at transcritical Reynolds numbers leads to a wake topology similar to that of the subcritical regime, resulting in an increased drag coefficient and lower Strouhal number. Turbulent statistics in the wake are also affected by roughness; the Reynolds stresses are larger due to the increased turbulent kinetic energy production in the boundary layer and separated shear layers close to the cylinder shoulders.We acknowledge “Red Española de Surpercomputación” (RES) for awarding us access to the MareNostrum III machine based in Barcelona, Spain (Ref. FI-2015-2-0026 and FI-2015-3-0011). We also acknowledge PRACE for awarding us access to Fermi and Marconi Supercomputers at Cineca, Italy (Ref. 2015133120). Oriol Lehmkuhl acknowledges a PDJ 2014 Grant by AGAUR (Generalitat de Catalunya). Ugo Piomelli acknowledges the support of the Natural Sciences and Engineering Research Council (NSERC) of Canada under the Discovery Grant Programme (Grant No. RGPIN-2016-04391). Ricard Borrell acknowledges a Juan de la Cierva postdoctoral grant (IJCI-2014-21034). Ivette Rodriguez, Oriol Lehmkuhl, Ricard Borrell and Assensi Oliva acknowledge Ministerio de Economía y Competitividad, Secretaría de Estado de Investigación, Desarrollo e Innovación, Spain (ref. ENE2014-60577-R).Peer ReviewedPostprint (author's final draft

Complexity and Expressivity of Branching- and Alternating-Time Temporal Logics with Finitely Many Variables

We show that Branching-time temporal logics CTL and CTL*, as well as Alternating-time temporal logics ATL and ATL*, are as semantically expressive in the language with a single propositional variable as they are in the full language, i.e., with an unlimited supply of propositional variables. It follows that satisfiability for CTL, as well as for ATL, with a single variable is EXPTIME-complete, while satisfiability for CTL*, as well as for ATL*, with a single variable is 2EXPTIME-complete,--i.e., for these logics, the satisfiability for formulas with only one variable is as hard as satisfiability for arbitrary formulas.Comment: Prefinal version of the published pape

Climate impact research: Beyond patchwork

Despite significant progress in climate impact research, the narratives that science can presently piece together of a 2, 3, 4, or 5 degrees C warmer world remain fragmentary. Here we briefly review past undertakings to characterise comprehensively and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to compare impact models across sectors and scales systematically, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of the available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impact knowledge through integrated cross-sectoral assessments, and that the climate impact community is now in a favourable position to do so

HAUSGARTEN: Multidisciplinary investigations at a deep-sea, long-term observatory in the Arctic Ocean

The marine Arctic has played an essential role in the history of our planet over the past 130 million years and contributes considerably to the present functioning of Earth and its life. The global cycles of a variety of materials fundamental to atmospheric conditions and thus to life depend to a signifi cant extent on Arctic marine processes (Aargaard et al., 1999). The past decades have seen remarkable changes in key Arctic variables. The decrease of sea-ice extent and sea-ice thickness in the past decade is statistically signifi - cant (Cavalieri et al., 1997; Parkinson et al., 1999; Walsh and Chapman, 2001; Partington et al., 2003; Johannessen et al., 2004). There have also been large changes in the upper and intermediate layers of the ocean, which have environmental implications. For instance, the deep Greenland Sea has continued its decadal trend towards warmer and saltier conditions, with a corresponding decrease in oxygen content, refl ecting the lack of effective local convection and ventilation (Dickson et al., 1996; Boenisch et al., 1997). Changes in temperature and salinity and associated shifts in nutrient distributions will directly affect the marine biota on multiple scales from communities and populations to individuals, consequently altering food-web structures and ecosystem functioning (Benson and Trites, 2002; Moore, 2003; Schumacher et al., 2003; Wiltshire and Manly, 2004; Perry et al., 2005). Today, we do not know whether the severe alterations in abiotic parameters represent perturbations due to human impacts, natural long-term trends, or new equilibriums (Bengtson et al., 2004). Because Arctic organisms are highly adapted to extreme environmental conditions with strong seasonal forcing, the accelerating rate of recent climate change challenges the resilience of Arctic life (Hassol, 2004). The entire system is likely to be severely affected by changing ice and water conditions, varying primary production and food availability to faunal communities, an increase in contaminants, and possibly increased UV irradiance. The stability of a number of Arctic populations and ecosystems is probably not strong enough to withstand the sum of these factors, which might lead to a collapse of subsystems. To detect and track the impact of large-scale environmental changes in the transition zone between the northern North Atlantic and the central Arctic Ocean, and to determine experimentally the factors controlling deep-sea biodiversity, the German Alfred Wegener Institute for Polar and Marine Research (AWI) established the deepsea, long-term observatory HAUSGARTEN, representing the fi rst, and by now only, open-ocean, long-term station in a polar region

Climate and southern Africa's water-energy-food nexus

In southern Africa, the connections between climate and the water-energy-food nexus are strong. Physical and socioeconomic exposure to climate is high in many areas and in crucial economic sectors. Spatial interdependence is also high, driven for example, by the regional extent of many climate anomalies and river basins and aquifers that span national boundaries. There is now strong evidence of the effects of individual climate anomalies, but associations between national rainfall and Gross Domestic Product and crop production remain relatively weak. The majority of climate models project decreases in annual precipitation for southern Africa, typically by as much as 20% by the 2080s. Impact models suggest these changes would propagate into reduced water availability and crop yields. Recognition of spatial and sectoral interdependencies should inform policies, institutions and investments for enhancing water, energy and food security. Three key political and economic instruments could be strengthened for this purpose; the Southern African Development Community, the Southern African Power Pool, and trade of agricultural products amounting to significant transfers of embedded water

Perpetually Dominating Large Grids

In the Eternal Domination game, a team of guard tokens initially occupies a dominating set on a graph G. A rioter then picks a node without a guard on it and attacks it. The guards defend against the attack: one of them has to move to the attacked node, while each remaining one can choose to move to one of his neighboring nodes. The new guards' placement must again be dominating. This attack-defend procedure continues perpetually. The guards win if they can eternally maintain a dominating set against any sequence of attacks, otherwise the rioter wins. We study rectangular grids and provide the first known general upper bound for these graphs. Our novel strategy implements a square rotation principle and eternally dominates m x n grids by using approximately (mn)/5 guards, which is asymptotically optimal even for ordinary domination

A framework for the cross-sectoral integration of multi-model impact projections: land use decisions under climate impacts uncertainties

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making

Water scarcity hotspots travel downstream due to human interventions in the 20th and 21st century

Water scarcity is rapidly increasing in many regions. In a novel, multi-model assessment, we examine how human interventions (HI: land use and land cover change, man-made reservoirs and human water use) affected monthly river water availability and water scarcity over the period 1971–2010. Here we show that HI drastically change the critical dimensions of water scarcity, aggravating water scarcity for 8.8% (7.4–16.5%) of the global population but alleviating it for another 8.3% (6.4–15.8%). Positive impacts of HI mostly occur upstream, whereas HI aggravate water scarcity downstream; HI cause water scarcity to travel downstream. Attribution of water scarcity changes to HI components is complex and varies among the hydrological models. Seasonal variation in impacts and dominant HI components is also substantial. A thorough consideration of the spatially and temporally varying interactions among HI components and of uncertainties is therefore crucial for the success of water scarcity adaptation by HI

Climatic risks and impacts in South Asia: extremes of water scarcity and excess

This paper reviews the current knowledge of climatic risks and impacts in South Asia associated with anthropogenic warming levels of 1.5°C to 4°C above pre-industrial values in the 21st century. It is based on the World Bank Report “Turn Down the Heat, Climate Extremes, Regional Impacts and the Case for Resilience” (2013). Many of the climate change impacts in the region, which appear quite severe even with relatively modest warming of 1.5–2°C, pose significant hazards to development. For example, increased monsoon variability and loss or glacial meltwater will likely confront populations with ongoing and multiple challenges. The result is a significant risk to stable and reliable water resources for the region, with increases in peak flows potentially causing floods and dry season flow reductions threatening agriculture. Irrespective of the anticipated economic development and growth, climate projections indicate that large parts of South Asia’s growing population and especially the poor are likely to remain highly vulnerable to climate change