Load-specific variant generation of bead cross sections in sheet metal components by unidirectional carbon fibre reinforcement

Beads are widely used to stiffen sheet metal components subjected to bending loads. Often, these bead-stiffened parts are used in product variants that differ significantly in the amount of acting loads. Lamination of unidirectional carbon fibre reinforced plastic (UD-CFRP) on the top flange area of individual beads represents a method for further increasing weight- specific stiffness: By varying the number of plies, a specifically configured component is obtained for each of the load cases. As a result, no changes to the forming tools are necessary and a minimum amount of the UD-CFRP material is required. In this work, a complete manufacturing process for a fibre reinforced bead was developed: First, a bead cross section geometry with an adapted top flange area to accommodate the UD-CFRP plies was designed and stamped into pre-stretched sheet samples of DX56 steel. Subsequently, the suitability of several surface pre-treatment processes to achieve sufficient bond strength of the composite bead was experimentally investigated and the UD-CFRP plies were applied by lamination. Final bending tests quantified the achievable stiffening effect of the investigated bead variants, showing a significant increase of the maximum supportable load compared to the standard non- reinforced cross-section

Large-scale identification of genetic design strategies using local search

In the past decade, computational methods have been shown to be well suited to unraveling the complex web of metabolic reactions in biological systems. Methods based on flux–balance analysis (FBA) and bi-level optimization have been used to great effect in aiding metabolic engineering. These methods predict the result of genetic manipulations and allow for the best set of manipulations to be found computationally. Bi-level FBA is, however, limited in applicability because the required computational time and resources scale poorly as the size of the metabolic system and the number of genetic manipulations increase. To overcome these limitations, we have developed Genetic Design through Local Search (GDLS), a scalable, heuristic, algorithmic method that employs an approach based on local search with multiple search paths, which results in effective, low-complexity search of the space of genetic manipulations. Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing.Hertz Foundatio

Recurrent droughts increase risk of cascading tipping events by outpacing adaptive capacities in the Amazon rainforest

Tipping elements are nonlinear subsystems of the Earth system that have the potential to abruptly shift to another state if environmental change occurs close to a critical threshold with large consequences for human societies and ecosystems. Among these tipping elements may be the Amazon rainforest, which has been undergoing intensive anthropogenic activities and increasingly frequent droughts. Here, we assess how extreme deviations fromclimatological rainfall regimes may cause local forest collapse that cascades through the coupled forest-climate system. We develop a conceptual dynamic network model to isolate and uncover the role of atmospheric moisture recycling in such tipping cascades. We account for heterogeneity in critical thresholds of the forest caused by adaptation to local climatic conditions. Our results reveal that, despite this adaptation, a future climate characterized by permanent drought conditions could trigger a transition to an open canopy state particularly in the southern Amazon.Theloss of atmospheric moisture recycling contributes to one-third of the tipping events.Thus, by exceeding local thresholds in forest adaptive capacity, local climate change impacts may propagate to other regions of the Amazon basin, causing a risk of forest shifts even in regions where critical thresholds have not been crossed locally

Ten new insights in climate science 2023

Non-technical summary. We identify a set of essential recent advances in climate change research with high policy relevance, across natural and social sciences: (1) looming inevitability and implications of overshooting the 1.5°C warming limit, (2) urgent need for a rapid and managed fossil fuel phase-out, (3) challenges for scaling carbon dioxide removal, (4) uncertainties regarding the future contribution of natural carbon sinks, (5) intertwinedness of the crises of biodiversity loss and climate change, (6) compound events, (7) mountain glacier loss, (8) human immobility in the face of climate risks, (9) adaptation justice, and (10) just transitions in food systems. Technical summary. The Intergovernmental Panel on Climate Change Assessment Reports provides the scientific foundation for international climate negotiations and constitutes an unmatched resource for researchers. However, the assessment cycles take multiple years. As a contribution to cross- and interdisciplinary understanding of climate change across diverse research communities, we have streamlined an annual process to identify and synthesize significant research advances. We collected input from experts on various fields using an online questionnaire and prioritized a set of 10 key research insights with high policy relevance. This year, we focus on: (1) the looming overshoot of the 1.5°C warming limit, (2) the urgency of fossil fuel phase-out, (3) challenges to scale-up carbon dioxide removal, (4) uncertainties regarding future natural carbon sinks, (5) the need for joint governance of biodiversity loss and climate change, (6) advances in understanding compound events, (7) accelerated mountain glacier loss, (8) human immobility amidst climate risks, (9) adaptation justice, and (10) just transitions in food systems. We present a succinct account of these insights, reflect on their policy implications, and offer an integrated set of policy-relevant messages. This science synthesis and science communication effort is also the basis for a policy report contributing to elevate climate science every year in time for the United Nations Climate Change Conference. Social media summary. We highlight recent and policy-relevant advances in climate change research – with input from more than 200 experts

Global Tipping Points Report 2023: Ch1.5: Climate tipping point interactions and cascades.

This chapter reviews interactions between climate tipping systems and assesses the potential risk of cascading effects. After a definition of tipping system interactions, we map out the current state of the literature on specific interactions between climate tipping systems that may be important for the overall stability of the climate system. For this, we gather evidence from model simulations, observations and conceptual understanding, as well as archetypal examples of palaeoclimate reconstructions where propagating transitions were potentially at play. This chapter concludes by identifying crucial knowledge gaps in tipping system interactions that should be resolved in order to improve risk assessments of cascading transitions under future climate change scenarios

Climate tipping point interactions and cascades: A review

Climate tipping elements are large-scale subsystems of the Earth that may transgress critical thresholds (tipping points) under ongoing global warming, with substantial impacts on the biosphere and human societies. Frequently studied examples of such tipping elements include the Greenland Ice Sheet, the Atlantic Meridional Overturning Circulation (AMOC), permafrost, monsoon systems, and the Amazon rainforest. While recent scientific efforts have improved our knowledge about individual tipping elements, the interactions between them are less well understood. Also, the potential of individual tipping events to induce additional tipping elsewhere or stabilize other tipping elements is largely unknown. Here, we map out the current state of the literature on the interactions between climate tipping elements and review the influences between them. To do so, we gathered evidence from model simulations, observations, and conceptual understanding, as well as examples of paleoclimate reconstructions where multi-component or spatially propagating transitions were potentially at play. While uncertainties are large, we find indications that many of the interactions between tipping elements are destabilizing. Therefore, we conclude that tipping elements should not only be studied in isolation, but also more emphasis has to be put on potential interactions. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 ◦C or on shorter timescales if global warming surpassed 2.0 ◦C. At these higher levels of global warming, tipping cascades may then include fast tipping elements such as the AMOC or the Amazon rainforest. To address crucial knowledge gaps in tipping element interactions, we propose four strategies combining observation-based approaches, Earth system modeling expertise, computational advances, and expert knowledge

On the Impact of Communication Latencies on Distributed Sparse LU Factorization

Sparse LU factorization offers some potential for parallelism, but at a level of very fine granularity. However, most current distributed memory MIMD architectures have too high communication latencies for exploiting all parallelism available. To cope with this, latencies must be avoided by coarsening the granularity and by message fusion. However, both techniques limit the concurrency, thereby reducing the scalability. In this paper, an implementation of a parallel LU decomposition algorithm for linear programming bases is presented for distributed memory parallel computers with noticable communication latencies. Several design decisions due to latencies, including data distribution and load balancing techniques, are discussed. An approximate performance model is set up for the algorithm, which allows to quantify the impact of latencies on its performance. Finally, experimental results for an Intel iPSC/860 parallel computer are reported and discussed. 1 Introduction We consider th..

On the Impact of Communication Latencies on Distributed Sparse LU Factorization

Sparse LU factorization offers some potential for parallelism, but at a level of very fine granularity. However, most current distributed memory MIMD architectures have too high communication latencies for exploiting all parallelism available. To cope with this, latencies must be avoided by coarsening the granularity and by message fusion. However, both techniques limit the concurrency, thereby reducing the scalability. In this paper, an implementation of a parallel LU decomposition algorithm for linear programming bases is presented for distributed memory parallel computers with noticable communication latencies. Several design decisions due to latencies, including data distribution and load balancing techniques, are discussed. An approximate performance model is set up for the algorithm, which allows to quantify the impact of latencies on its performance. Finally, experimental results for an Intel iPSC/860 parallel computer are reported and discussed