Methods for structural design at elevated temperatures

A procedure which can be used to design elevated temperature structures is discussed. The desired goal is to have the same confidence in the structural integrity at elevated temperature as the factor of safety gives on mechanical loads at room temperature. Methods of design and analysis for creep, creep rupture, and creep buckling are presented. Example problems are included to illustrate the analytical methods. Creep data for some common structural materials are presented. Appendix B is description, user's manual, and listing for the creep analysis program. The program predicts time to a given creep or to creep rupture for a material subjected to a specified stress-temperature-time spectrum. Fatigue at elevated temperature is discussed. Methods of analysis for high stress-low cycle fatigue, fatigue below the creep range, and fatigue in the creep range are included. The interaction of thermal fatigue and mechanical loads is considered, and a detailed approach to fatigue analysis is given for structures operating below the creep range

Low-stabilisation scenarios and technologies for carbon capture and sequestration

Endogenous technology scenarios for meeting low stabilization CO2 targets are derived in this study and assessed regarding emission reductions and mitigation costs. The aim is to indentify the most important technology options for achieving low stabilization targets. The significance of an option is indicated by its achieved emission reduction and the mitigation cost increase, if this option were not available. Quantitative results are computed using a global multi-regional hard-linked hybrid model that integrates the economy, the energy sector and the climate system. The model endogenously determines the optimal deployment of technologies subject to a constraint on climate change. The alternative options in the energy sector comprise the most important mitigation technologies: renewables, biomass, nuclear, carbon capture and sequestration (CCS), and biomass with CCS as well as energy efficiency improvements. The results indicate that the availability of CCS technologies and espec. biomass with CCS is highly desirable for achieving low stabilization goals at low costs. The option of nuclear energy is different: although it could play an important role in the primary energy mix, mitigation costs would only mildly increase, if it could not be expanded. Therefore, in order to promote prudent climate change mitigation goals, support of CCS technologies reduces the costs and-thus-is desirable from a social point of view. © 2009 Elsevier Ltd. All rights reserved

Low-stabilisation scenarios and technologies for carbon capture and sequestration

Endogenous technology scenarios for meeting low stabilization CO2 targets are derived in this study and assessed regarding emission reductions and mitigation costs. The aim is to indentify the most important technology options for achieving low stabilization targets. The significance of an option is indicated by its achieved emission reduction and the mitigation cost increase, if this option were not available. Quantitative results are computed using a global multi-regional hard-linked hybrid model that integrates the economy, the energy sector and the climate system. The model endogenously determines the optimal deployment of technologies subject to a constraint on climate change. The alternative options in the energy sector comprise the most important mitigation technologies: renewables, biomass, nuclear, carbon capture and sequestration (CCS), and biomass with CCS as well as energy efficiency improvements. The results indicate that the availability of CCS technologies and espec. biomass with CCS is highly desirable for achieving low stabilization goals at low costs. The option of nuclear energy is different: although it could play an important role in the primary energy mix, mitigation costs would only mildly increase, if it could not be expanded. Therefore, in order to promote prudent climate change mitigation goals, support of CCS technologies reduces the costs and-thus-is desirable from a social point of view. © 2009 Elsevier Ltd. All rights reserved

Macroeconomic drivers of baseline scenarios in dynamic CGE models: review and guidelines proposal

For dynamic computable general equilibrium (CGE) modeling, long-term baseline construction is key and depends on the applied methods and the sources of projections considered. For dynamic CGE models, baseline assumptions and base data are both important determinants of results. This paper reviews the assumptions made by 24 modeling teams on baseline macroeconomic drivers, understood as factor accumulation and gross domestic product (GDP) growth. We critically review the various methods, identifying state-of-the-art practices and propose simple guidelines, particularly focusing on consistency between data sources and models, which is intended to help dynamic CGE modelers build their own baselines

New damage curves and multimodel analysis suggest lower optimal temperature

Economic analyses of global climate change have been criticized for their poor representation of climate change damages. Here we develop and apply aggregate damage functions in three economic Integrated Assessment Models (IAMs) with different degrees of complexity. The damage functions encompass a wide but still incomplete set of climate change impacts based on physical impact models. We show that with medium estimates for damage functions, global damages are in the range of 10% to 12% of GDP by 2100 in a baseline scenario with 3 °C temperature change, and about 2% in a well-below 2 °C scenario. These damages are much higher than previous estimates in benefit-cost studies, resulting in optimal temperatures below 2 °C with central estimates of damages and discount rates. Moreover, we find a benefit-cost ratio of 1.5 to 3.9, even without considering damages that could not be accounted for, such as biodiversity losses, health and tipping points

Exploring the possibility space: taking stock of the diverse capabilities and gaps in integrated assessment models

Integrated assessment models (IAMs) have emerged as key tools for building and assessing long term climate mitigation scenarios. Due to their central role in the recent IPCC assessments, and international climate policy analyses more generally, and the high uncertainties related to future projections, IAMs have been critically assessed by scholars from different fields receiving various critiques ranging from adequacy of their methods to how their results are used and communicated. Although IAMs are conceptually diverse and evolved in very different directions, they tend to be criticised under the umbrella of 'IAMs'. Here we first briefly summarise the IAM landscape and how models differ from each other. We then proceed to discuss six prominent critiques emerging from the recent literature, reflect and respond to them in the light of IAM diversity and ongoing work and suggest ways forward. The six critiques relate to (a) representation of heterogeneous actors in the models, (b) modelling of technology diffusion and dynamics, (c) representation of capital markets, (d) energy-economy feedbacks, (e) policy scenarios, and (f) interpretation and use of model results

Coupling climate and economic models in a cost-benefit framework: a convex optimization approach

In this paper we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99 we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model