Freeform Fabrication of Stochastic and Ordered Cellular Structures

Cellular materials provide a unique challenge to SFF technology. Such materials have unique properties of low mass, high strength, and good insulation properties. To produce such cellular structures, SFF systems require a designed microstructure with a feature size significantly lower than the resolution of the process. In this paper, we examine means of producing stochastic foams using the instability of a viscous thread and various methods for production of closed celled foams. These techniques allow for the production of foams without the need for pre-described cell structures. Such foams, when made from elastic materials can act as novel actuating materials.Mechanical Engineerin

Tropical forcing of increased Southern Ocean climate variability revealed by a 140-year subantarctic temperate reconstruction

Occupying 14% of the world’s surface, the Southern Ocean plays a fundamental role in global climate, ocean circulation, carbon cycling and Antarctic ice-sheet stability. Unfortunately, high interannual variability and a dearth of instrumental observations before the 1950s limits our understanding of how marine-atmosphere-ice domains interact on multi-decadal timescales and the impact of anthropogenic forcing. Here we integrate climate-sensitive tree growth with ocean and atmospheric observations on southwest Pacific subantarctic islands that lie at the boundary of polar and subtropical climates (52–54˚S). Our annually-resolved temperature reconstruction captures regional change since the 1870s and demonstrates a significant increase in variability from the mid-twentieth century, a phenomenon predating the observational record. Climate reanalysis and modelling shows a parallel change in tropical Pacific sea surface temperatures that generate an atmospheric Rossby wave train which propagates across a large part of the Southern Hemisphere during the austral spring and summer

Multi-decadal variations in Southern Hemisphere atmospheric ¹⁴C: Evidence against a Southern Ocean sink at the end of the Little Ice Age CO₂ anomaly.

Northern Hemisphere-wide cooling during the Little Ice Age (LIA; CE 1650-1775) is associated with a ~5 ppmv decrease in atmospheric carbon dioxide. Changes in terrestrial and ocean carbon reservoirs have been postulated as possible drivers of this relatively large shift in atmospheric CO₂, potentially providing insights into the mechanisms and sensitivity of the global carbon cycle. Here we report decadally-resolved radiocarbon (¹⁴C) levels in a network of tree rings series spanning CE 1700-1950 located along the northern boundary of, and within, the Southern Ocean. We observe regional dilutions in atmospheric radiocarbon (relative to the Northern Hemisphere) associated with upwelling of ¹⁴CO₂–depleted abyssal waters. We find the inter-hemispheric ¹⁴C offset approaches zero during increasing global atmospheric CO₂ at the end of the LIA, with reduced ventilation in the Southern Ocean and a Northern Hemisphere source of old carbon (most probably originating from deep Arctic peat layers). The coincidence of the atmospheric CO₂ increase and reduction in the inter-hemispheric ¹⁴C offset imply a common climate control. Possible mechanisms of synchronous change in the high latitudes of both hemispheres are discussed

Harmonized gap-filled datasets from 20 urban flux tower sites

A total of 20 urban neighbourhood-scale eddy covariance flux tower datasets are made openly available after being harmonized to create a 50 site-year collection with broad diversity in climate and urban surface characteristics. Variables needed as inputs for land surface models (incoming radiation, temperature, humidity, air pressure, wind and precipitation) are quality controlled, gap-filled and prepended with 10 years of reanalysis-derived local data, enabling an extended spin up to equilibrate models with local climate conditions. For both gap filling and spin up, ERA5 reanalysis meteorological data are bias corrected using tower-based observations, accounting for diurnal, seasonal and local urban effects not modelled in ERA5. The bias correction methods developed perform well compared to methods used in other datasets (e.g. WFDE5 or FLUXNET2015). Other variables (turbulent and upwelling radiation fluxes) are harmonized and quality controlled without gap filling Site description metadata include local land cover fractions (buildings, roads, trees, grass etc.), building height and morphology, aerodynamic roughness estimates, population density and satellite imagery. This open collection can help extend our understanding of urban environmental processes through observational synthesis studies or in the evaluation of land surface environmental models in a wide range of urban settings. These data can be accessed from https://doi.org/10.5281/zenodo.7104984 (Lipson et al., 2022).Peer reviewe

Benchmarks for the Urban-PLUMBER model evaluation project Phase 1 (AU-Preston)

AU-Preston benchmarks for the Urban-PLUMBER project These timeseries data are associated with the study: “Evaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results” These are empirical models of various complexity used as benchmarks to evaluate land surface models in the project. The benchmarking process follows the methods in the PLUMBER project (Best et al., 2015). Benchmarks Physically based Manabe_1T: A simple ‘slab and bucket’ model (Fig. 1a) based on physical principles (i.e. conservation of energy, mass and momentum). The impervious (built) fraction is simulated using a one-tile slab scheme (Best, 2005). For the pervious fraction a simple representation allows precipitation to fill a store which overflows when full, and otherwise freely evaporate (Manabe, 1969). At each timestep, the impervious and pervious tile outputs are calculated and aggregated with a weighted mean. Empirical (out-of-sample) REG1-SWdown: Linear regression with one variable (SWdown, e.g. Fig. 1b) is used separately to predict SWup, LWup, Qh, Qle, and Qtau. At night predicted values are constant where SWdown = 0. REG2-SWdown-Tair: Two-variable (SWdown and Tair) linear regression (e.g. Fig. 5c) provides some information at night and more generally for variables closely dependent on temperature (e.g. Lwup and Qh). KM3-SWdown-Tair-RH: Following PLUMBER’s conceptual arguments, three predictor variables (SWdown, Tair and RH data) are split into three (low, medium and high) to create 3^3=27 groups, for which independent regressions are trained. K-means clustering is used to determine the training data groups (e.g. Fig. 1d). To use this piecewise regression benchmark, at each time step the input data’s proximity to one of the 27 cluster centroids is determined to select the regression to apply. This benchmark equates to PLUMBER’s EMP3KM27 (Best et al., 2015), which based on common metrics outperformed all their participating land surface models when predicting sensible and latent heat fluxes across 20 sites. Empirical (in-sample) KM3-IS-SWdown-Tair-RH: This follows the KM3-SWdown-Tair-RH method, but trained with in-sample data only (i.e. AU-Preston). This should outperform an out-of-sample model because of the reuse of the forcing data, but performance is expected to degrade if applied to dissimilar conditions (i.e. another site). KM4-IS-SWdown-Tair-RH-Wind: The k-means approach is applied again, but with an additional variable (wind speed), which increases the clusters to 81 (3^4) given the above rationale. Wind speed provides information that helps to predict turbulent heat and momentum fluxes. Authors Emperical benchmarks were developed by Mathew Lipson: https://orcid.org/0000-0001-5322-1796 The physical benchmark was developed by Martin Best: https://orcid.org/0000-0003-4468-876X Co-authors for the associated manuscript are: Mathew Lipson, Sue Grimmond, Martin Best, Gab Abramowitz, Andrew Coutts, Nigel Tapper, Jong-Jin Baik, Meiring Beyers, Lewis Blunn, Souhail Boussetta, Elie Bou-Zeid, Martin G. De Kauwe, Cécile de Munck, Matthias Demuzere, Simone Fatichi, Krzysztof Fortuniak, Beom-Soon Han, Maggie Hendry, Yukihiro Kikegawa, Hiroaki Kondo, Doo-Il Lee, Sang-Hyun Lee, Aude Lemonsu, Tiago Machado, Gabriele Manoli, Alberto Martilli, Valéry Masson, Joe McNorton, Naika Meili, David Meyer, Kerry A. Nice, Keith W. Oleson, Seung-Bu Park, Michael Roth, Robert Schoetter, Andres Simon, Gert-Jan Steeneveld, Ting Sun, Yuya Takane, Marcus Thatcher, Aristofanis Tsiringakis, Mikhail Varentsov, Chenghao Wang, Zhi-Hua Wang References Observational data Lipson, M., Grimmond, S., Best, M., Chow, W., Christen, A., Chrysoulakis, N., Coutts, A., Crawford, B., Earl, S., Evans, J., Fortuniak, K., Heusinkveld, B. G., Hong, J.-W., Hong, J., Järvi, L., Jo, S., Kim, Y.-H., Kotthaus, S., Lee, K., Masson, V., McFadden, J. P., Michels, O., Pawlak, W., Roth, M., Sugawara, H., Tapper, N., Velasco, E., and Ward, H. C.: Data for “Harmonized gap-filled dataset from 20 urban flux tower sites” for the Urban-PLUMBER project, https://doi.org/10.5281/zenodo.7104984, 2022. Benchmark references Best, M. J., Abramowitz, G., Johnson, H. R., Pitman, A. J., Balsamo, G., Boone, A., Cuntz, M., Decharme, B., Dirmeyer, P. A., Dong, J., Ek, M., Guo, Z., Haverd, V., Hurk, B. J. J. van den, Nearing, G. S., Pak, B., Peters-Lidard, C., Santanello, J. A., Stevens, L., and Vuichard, N.: The Plumbing of Land Surface Models: Benchmarking Model Performance, Journal of Hydrometeorology, 16, 1425–1442, https://doi.org/10.1175/JHM-D-14-0158.1, 2015. Best, M. J.: Representing urban areas within operational numerical weather prediction models, Boundary-Layer Meteorol, 114, 91–109, https://doi.org/10.1007/s10546-004-4834-5, 2005. Manabe, S.: CLIMATE AND THE OCEAN CIRCULATION: I. THE ATMOSPHERIC CIRCULATION AND THE HYDROLOGY OF THE EARTH’S SURFACE, Monthly Weather Review, 97, 739–774, https://doi.org/10.1175/1520-0493(1969)0972.3.CO;2, 1969

Model development for urban climates

Cities face pressing challenges from rapidly growing populations, a warming global climate, air pollution, resource depletion and energy scarcity. Computational models can assist in understanding interactions and planning solutions. This thesis documents a series of developments intended to improve the accuracy and capability of environmental models that represent urban land surfaces in weather and climate simulations. Developments focus on efficiently representing physical and behavioural processes at the neighbourhood to city scale.Major contributions and key findings include:1) Development of a new heat conduction scheme which is more accurate than a method commonly used. Through a change in the discrete formulae representing conduction, the new scheme is better able to match exact solutions to heat transfer through typical urban materials, and reduces land-atmosphere flux errors when integrated within an existing urban land surface model. Improvements are achieved without increasing computational expense.2) Development of a new building energy model that predicts neighbourhood-scale energy consumption based on weather conditions and building structure. The scheme includes important internal-external heat transfer processes, as well as a novel representation of human behaviours derived from a statistical model of the national electricity network. The scheme is integrated within an existing urban canopy model to capture dynamic feedbacks between energy use and the greater urban environment, and is able to reproduce observed diurnal and seasonal variability in building energy use. More complex physics-based processes are found to be beneficial only when human behaviours are appropriately represented. 3) Development of a new land-atmosphere coupled framework which simulates interactions between energy use, waste heat, urban and global climate. The new framework is evaluated and used to run 100-year simulations under the climate change projection scenario RCP8.5 to investigate how energy demand will change in a warming climate. With rising global temperature and increasing air conditioner use, peak electricity demand will likely surpass gas demand in Melbourne this century.These developments are integrated within a free, open source model: the Urban CLimate and Energy Model (UCLEM). Integrated modelling tools such as these will be instrumental in planning for better environmental, health and economic outcomes in cities