Discrete Element Modelling of VACUUMATICS

Vacuumatics consist of independent particles inside an airtight enclosed membrane, that are prestressed due to a difference in (air) pressure. Analytical and numerical research of vacuum prestressing has illustrated that the effective prestressing forces can be divided into two interrelated prestressing components. Due to the granular characteristics of Vacuumatics, the material behaviour can be modelled by means of the Discrete Element Method (DEM). The individual prestressing components acting on the edge particles of vacuumatic structures can be simulated by means of a specialised Atmospheric Pressure Model in HADES (by Habanera). Analytically defined equations form the basic input in this simulation process. These simulations enable us to analyse (visually as well as numerically) the prestressing forces, but also the contact forces and the displacements of each particle due to this vacuum prestressing. Furthermore, bending phenomena of beam-shaped Vacuumatics can be analysed in detail, providing us with insight to describe and predict the structural properties of any type of vacuumatic structure

Concrete shell structures revisited : introducing a new and 'low-tech' construction method using vacuumatics formwork

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VACUUMATICS; Systematic Flexural Rigidity Analysis

The structural integrity of vacuumatics relies on the principle of prestressing unbound particles inside an enclosed membrane. By introducing a negative pressure (partial vacuum) inside this airtight flexible enclosure, the membrane is tightly wrapped around the outer particles, hence effectively bonding the particle filling to create (adaptable) load-bearing structures. Analytical and numerical studies on the fundamental prestress derivation of vacuumatically prestressed structures have shown that the effective prestressing forces between the particles largely depend, apart from the differential in (air) pressure differential, on the elastic properties of the skin material. The flexural rigidity of vacuumatics is mainly determined by the material properties of the particles and membrane used. Variations in elasticity of the skin and particle filling, and with this the shape, size, compressiveness, roughness, and packing density of the individual particles, highly influence the structural behaviour of vacuumatic structures. In order to explore the influence of different particle and skin characteristics (or parameters) on the flexural rigidity, experimental research has been carried out by means of four point bending tests. Different types of particles were used to discover behavioural trends dependent on the parameters varied. The results of this study provide an enhanced understanding of the true overall structural response of vacuumatics. By systematically elaborating the different parameters, we are able to determine what specific material properties are desired to design the ‘most efficient’ vacuumatic structure for every application

Modelling induced innovation for the low-carbon energy transition: a menu of options

This is the final version. Available from IOP Publishing via the DOI in this record. Data availability statement. All data that support the findings of this study are included within the article (and any supplementary files).Induced innovation is a multi-faceted process characterized by interaction between demand-pull forces, path-dependent self-reinforcing change, and the cost reduction of technology that occurs with cumulative deployment. By endogenously including induced innovation in energy models, policy analysts and modellers could enable a mission-oriented approach to policymaking that envisions the opportunities of accelerating the low-carbon energy transition while avoiding the risks of inaction. While the integrated assessment models used in the intergovernmental panel on climate change (IPCC-IAMs) account for induced innovation, their assumptions of general equilibrium and optimality may reveal weaknesses that produce unsatisfactory results for policymakers. In this paper, we develop a menu of options for modelling induced innovation in the energy transition with non-equilibrium, non-optimal models by a three step methodology: a modelling survey questionnaire, a review of the literature, and an analysis of case studies from modelling applications within the economics of energy innovation and system transition (EEIST) programme. The survey questionnaire allows us to compare 24 models from EEIST partner institutions developed to inform energy and decarbonisation policy decisions. We find that only six models, future technological transformations, green investment barriers mode, stochastic, economy-energy-environment macro-econometric, M3E3 and Dystopian Schumpeter meeting Keynes, represent endogenous innovation—in the form of learning curves, R&D, and spillover effects. The review of the literature and analysis of case studies allow us to form a typology of different models of induced innovation alongside the IPCC-IAMs and develop a decision tree to guide policy analysts and modellers in the choice of the most appropriate models to answer specific policy questions. The paper provides evidence for integrating narrow and systemic approaches to modelling-induced innovation in the context of low-carbon energy transition, and promotes cooperation instead of competition between different but complementary approaches. These findings are consistent with the implementation of risk-opportunity analysis as a policy appraisal method to evaluate low-carbon transition pathways.Department for Energy Security and Net ZeroChildren Investment Fund FoundationEconomics of Energy Innovation Systems TransitionUK Research and InnovationHorizon Europe (UK)Horizon Europe (EU

Beyond forcing scenarios: predicting climate change through response operators in a coupled general circulation model

Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Here we show how to use statistical mechanics to construct operators able to flexibly predict climate change for a variety of climatic variables of interest. We perform our study on a fully coupled model - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO2 increase on a vast range of temporal scales, from inter-annual to centennial, and for very diverse climatic quantities. We investigate within a unified perspective the transient climate response and the equilibrium climate sensitivity and assess the role of fast and slow processes. The prediction of the ocean heat uptake highlights the very slow relaxation to a newly established steady state. The change in the Atlantic Meridional Overturning Circulation (AMOC) and of the Antarctic Circumpolar Current (ACC) is accurately predicted. The AMOC strength is initially reduced and then undergoes a slow and only partial recovery. The ACC strength initially increases as a result of changes in the wind stress, then undergoes a slowdown, followed by a recovery leading to a overshoot with respect to the initial value. Finally, we are able to predict accurately the temperature change in the Northern Atlantic

Introduction to the special issue on the statistical mechanics of climate

We introduce the special issue on the Statistical Mechanics of Climate by presenting an informal discussion of some theoretical aspects of climate dynamics that make it a topic of great interest for mathematicians and theoretical physicists. In particular, we briefly discuss its nonequilibrium and multiscale properties, the relationship between natural climate variability and climate change, the different regimes of climate response to perturbations, and critical transitions