Wind energy is foundational for achieving 100 % renewable electricity production, and significant innovation is required as the grid expands and accommodates hybrid plant systems, energy-intensive products such as fuels, and a transitioning transportation sector. The sizable investments required for wind power plant development and integration make the financial and operational risks of change very high in all applications but especially offshore. Dependence on a high level of modeling and simulation accuracy to mitigate risk and ensure operational performance is essential. Therefore, the modeling chain from the large-scale inflow down to the material microstructure, and all the steps in between, needs to predict how the wind turbine system will respond and perform to allow innovative solutions to enter commercial application. Critical unknowns in the design, manufacturing, and operability of future turbine and plant systems are articulated, and recommendations for research action are laid out. This article focuses on the many unknowns that affect the ability to push the frontiers in the design of turbine and plant systems. Modern turbine rotors operate through the entire atmospheric boundary layer, outside the bounds of historic design assumptions, which requires reassessing design processes and approaches. Traditional aerodynamics and aeroelastic modeling approaches are pressing against the limits of applicability for the size and flexibility of future architectures and flow physics fundamentals. Offshore wind turbines have additional motion and hydrodynamic load drivers that are formidable modeling challenges. Uncertainty in turbine wakes complicates structural loading and energy production estimates, both around a single plant and for downstream plants, which requires innovation in plant operations and flow control to achieve full energy capture and load alleviation potential. Opportunities in co-design can bring controls upstream into design optimization if captured in design-level models of the physical phenomena. It is a research challenge to integrate improved materials into the manufacture of ever-larger components while maintaining quality and reducing cost. High-performance computing used in high-fidelity, physics-resolving simulations offer opportunities to improve design tools through artificial intelligence and machine learning, but even the high-fidelity tools are yet to be fully validated. Finally, key actions needed to continue the progress of wind energy technology toward even lower cost and greater functionality are recommended.

Establishing consistent criteria for assessing the performance of structural systems and infrastructure networks is a critical component of communities’ efforts to optimize investment decisions for the upkeep and renewal of the built environment. Although member-level performance and reliability assessment procedures are currently well-established, it is widely recognized that a member-oriented approach does not necessarily lead to an efficient utilization of limited resources when making decisions related to the management of existing deteriorating structures or lifeline systems, especially those that may be exposed to extreme events. For this reason, researchers have renewed their interests in developing system-level assessment methods as a basis to modern structural and infrastructure performance evaluation and design processes. Specifically, system-level performance metrics and characteristics such as reliability, redundancy, robustness, resilience, and risk continue to be refined. The objective of this paper is to extend the content of the accompanying paper on reliability-based performance indicators for structural members by reviewing proposals for the development and implementation of performance-based criteria for structural systems and infrastructure networks. The paper reviews established concepts of reliability design along with emerging ideas of performance-based and resilience-based design that are especially relevant for assessing and managing system-level risk. The paper also studies structural redundancy and robustness concepts as well as network-level performance metrics along with ranking approaches. Insights from these analyses reveal the need for transitioning structural and infrastructure design processes from a traditional component-level reliability-based approach, to one that seeks uniform levels of risk across scales (from structural systems to interconnected infrastructure networks across communities). Implementation examples are drawn from experiences with buildings, bridges, offshore oil and gas platforms, and a variety of infrastructure systems. The paper also reflects on promising avenues for pursuing practical and calibrated system-level performance indicators that support life cycle performance, safety, reliability, and risk of structural and infrastructure systems as integral parts of resilient communities.

The implementation of reliability methods for designing new structures and assessing the safety and evaluating the performance of existing structures and infrastructure systems has gained widespread acceptance. Consequently, reliability-based design specifications in the form of load and resistance factor design (LRFD) methods have dominated the development of current codes and standards. This paper reviews the reliability-based performance criteria used to calibrate design and evaluation codes and standards for assessing the strength, serviceability, and fatigue resistance of structural components. The review shows that large differences exist in the target reliability levels adopted for evaluating the strength of various types of structural members and materials. These differences result from many factors, including (1) intended structure design and service life; (2) expected member modes of failure (e.g., ductile or brittle); (3) importance of the individual member to overall system integrity (...

Fatigue analysis for wind turbines is typically carried out in the time domain, using cycle counting techniques such as ASTM's Rainflow Cycle-Counting Algorithm. As an alternative, earlier workers investigated the feasibility of estimating wind turbine fatigue loads using spectral techniques such as Dirlik's method to estimate stress range probability distributions that are based on spectral moments of the load in question. The present paper re-examines this approach with a particular view to assessing its limitations and advantages in the context of modern, large-scale wind turbines and design methods. These relative advantages are considered in terms of accuracy, statistical reliability, and efficiency of calculation. Field data on loads from a utility-scale 1.5 MW turbine near Lamar, Colorado in the Colorado Green Wind Farm are analyzed here as a representative example. The results show that valuable and reliable information about tower loads can be obtained very efficiently. By contrast, the limitations of the Dirlik method are highlighted by poor results for edgewise blade loads.