Parallel Computing in HP-OCP

The most computationally demanding part of structural design optimization is the solution of the FE equations and design of the structural model. Therefore, there is a need for the implementation of strategies that can reduce the computational cost of each iteration and thus manage to achieve the same optimized result with considerable reduction in the optimization time. High Performance Optimization Computing Platform (HP-OCP) is an optimization software developed in C# programming language by ISAAR-NTUA and OptiStructre Ltd. [1] which provides a holistic optimization approach for civil engineering structures. It combines powerful derivative-based and derivative-free optimization algorithms like the Projected Quasi-Newton (PQN), Constrained Optimization by Linear Approximation (COBYLA), Latin Hypercube (LH), Differential Evolution etc. [2] integrated with different structural analysis software's like SAP2000, ETABS & SCIA Engineer utilizing their abilities in finite element analysis and most importantly different design codes into the optimization procedure. To deal with the computational demand deriving from this coupling of optimization algorithms and commercial structural analysis software's parallel computational procedures have been implemented to HP-OCP. These procedures were tested in real world civil engineering problems and produced very good results. Parallel strategies are implemented both at the level of the optimization algorithm, by exploiting the natural parallelization features of the evolutionary algorithms, as well as at the level of the repeated structural analysis problems that are required by the optimization algorithm. The numerical tests presented demonstrate the computational advantages of the proposed parallel strategies, which become more pronounced in large-scale optimization problems.

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

<scp>ReSurveyEurope</scp>: A database of resurveyed vegetation plots in Europe

AbstractAimsWe introduce ReSurveyEurope — a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions.ResultsReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover–abundance classes such as variants of the Braun‐Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020.ConclusionsReSurveyEurope is a new resource to address a wide range of research questions on fine‐scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well‐established European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome.</jats:sec

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Characteristics of the soil seed bank in Mediterranean temporary ponds and its role in ecosystem dynamics

11 pages, 3 figures, 2 tables, 51 references.Species in temporary ponds overcome periods of unfavorable weather conditions by building up a large seed bank. With this strategy, the species diversity of ponds is preserved and information on their dynamics and structure is retained. Little is known about the characteristics, spatial patterns and role in the vegetation dynamics of the soil seed banks of Mediterranean temporary ponds, which are regarded as priority habitats under protection. We studied two sites of western Crete: Omalos, a mountain plateau at 1,060 m a.s.l. and Elafonisos, located near the coast at 60 m a.s.l. The seed bank was surveyed along transects using the germination method. Aboveground vegetation was measured on quadrats along the same transects. Canonical Correspondence Analysis (CCA) was run to define the zonation patterns. High density and species richness were recorded in both sites, with an average of 75,662 seeds/m2 found in Omalos and 22,941 seeds/m2 in Elafonisos. The community composition of both sites was remarkably different but in both locations perennial species were inconspicuous while annuals, prevailed in the seed banks. An important array of protected or rare species as well as several others which were absent from the vegetation were hosted in the soil seed banks, thereby rendering a low similarity between their composition. Soil seed banks in these ecosystems indicated a spatial heterogeneity that mirrored the aboveground vegetation distribution, sorted along the moisture gradient by their tolerance to flooding. Soil seed banks play a key role in the vegetation recovery after summer drought. The acts of preserving the soil seed bank and ensuring a transient flooding regime are essential to protect the unique vegetation communities of Mediterranean temporary ponds.The work presented in this paper was carried out in the framework of the LIFE-Nature project entitled ‘‘Actions for the Conservation of the Mediterranean Temporary Ponds in Crete’’ (LIFE04 NAT/GR/000105) and a scholarship granted to the first author by the Mediterranean Agronomic Institute of Chania, Greece (MAICh-CIHEAM).Peer reviewe

A Simple Matlab Code for Material Design Optimization Using Reduced Order Models

The main part of the computational cost required for solving the problem of optimal material design with extreme properties using a topology optimization formulation is devoted to solving the equilibrium system of equations derived through the implementation of the finite element method (FEM). To reduce this computational cost, among other methodologies, various model order reduction (MOR) approaches can be utilized. In this work, a simple Matlab code for solving the topology optimization for the design of materials combined with three different model order reduction approaches is presented. The three MOR approaches presented in the code implementation are the proper orthogonal decomposition (POD), the on-the-fly reduced order model construction and the approximate reanalysis (AR) following the combined approximations approach. The complete code, containing all participating functions (including the changes made to the original ones), is provided

Topology Optimization Based Material Design for 3D Domains Using MATLAB

In this work, a simple, easy to use MATLAB code is presented for the optimal design of materials for 3D domains. For the optimal design of materials, the theoretical framework of topology optimization and that of homogenization were utilized to develop a formulation where the design of the micro-structure of the material is affected among others by the loading and boundary conditions of the 3D macro domain. The final result of the micro-scale can then be converted into an stl file, which can be utilized for 3D printing; however, the continuity of the unit cells when assembled to form the macro structure should be taken into account. The transition of the design of the material problem formulation from 2D to 3D domains generates drastically increased computational needs in order to perform the design procedures, which might narrow its formulation scales and the corresponding sizes of the adopted finite element discretization. Thus, in addition to the optimal design of materials implementation, the utilization of three different model order reduction (MOR) approaches is presented, aiming to assist towards the reduction of the computational cost of the two scales formulation. On-the-fly reduced order model, proper orthogonal decomposition (POD), and approximate reanalysis (AR) following the combined approximations are the three approaches adopted for the purposes of this study, while the code implementation enables the addition of new ones easily