Modern large urban centers face serious environmental, social, and economic challenges. A sustainable solution to these challenges is the utilization of urban underground space in modern city planning development. Countries like Singapore and Japan, and cities such as Montreal and Paris, have consistently developed underground space for metro lines, underground parking lots, and roads to cope with these modern challenges. However, in many cases underground projects are not implemented; often stalled at the decision-making stage. The main reason for this stagnation is the unfavorable comparison between underground structures and their aboveground counterparts, primarily due to the significantly higher capital costs associated with underground development, the poorly understood concept of the value of underground space, and finally the inexperience of most urban planners and engineers to apply methods for the determination of the aforementioned value. The aim of this study was, first, to conduct a thorough critical review of the existing literature so that the current methodologies for the estimation of the value of underground space could be gathered and assessed in a systematic way. In addition, each method’s pros and cons were analyzed and discussed. Second, the authors provided general and practical guidelines that aim to direct and “steer” future engineers and urban planners as to which method is more appropriate to use for specific project scenarios. Finally, the majority of the methodologies were applied to specific case studies to further demonstrate each method’s strong and weak points, respectively; through these case studies the general economic scopes of the used methods were revealed, along with other strong conclusions pertaining to their capabilities and limitations.
Power systems are being reshaped by decarbonization, digitalization, and high shares of renewables. At the same time, increasingly severe extreme conditions expose the limits of traditional reliability frameworks, calling for risk-aware, resilience-oriented approaches to address high-impact, low-probability (HILP) events. In this context, this paper presents a comprehensive overview of the foundations of power system resilience. It revisits the transition from reliability to resilience, formalizes key concepts and metrics, and introduces advanced approaches for resilience assessment, including fragility-based modeling, cascading failure analysis, and tail-risk indicators. The paper further examines resilience-oriented investment planning, operational strategies across all event phases, and the role of distributed energy resources, microgrids, and cybersecurity. The analysis highlights that resilience extends reliability by focusing on extreme conditions, fundamentally reshaping decision-making and requiring coordinated strategies across infrastructure, operation, and governance.
This paper introduces a new paradigm for frequency control in power systems based on optimization through Model Predictive Control (MPC). The approach unifies primary and secondary frequency regulation in a multi-horizon structure that coordinates distinct time scales, bridging conventional synchronous generation and converter-interfaced generation (CIG), while also enabling inertial response. This approach enhances system stability while providing a cost-effective solution that respects market inputs and operational constraints. To demonstrate the performance of the proposed paradigm, a two-area system is studied, comprising synchronous generators with prime movers as well as CIG, including battery energy storage systems operating at zero net energy over the long term.
AI agents may soon become capable of autonomously completing valuable, long-horizon tasks in diverse domains. Current benchmarks either do not measure real-world tasks, or are not sufficiently difficult to meaningfully measure frontier models. To this end, we present Terminal-Bench 2.0: a carefully curated hard benchmark composed of 89 tasks in computer terminal environments inspired by problems from real workflows. Each task features a unique environment, human-written solution, and comprehensive tests for verification. We show that frontier models and agents score less than 65% on the benchmark and conduct an error analysis to identify areas for model and agent improvement. We publish the dataset and evaluation harness to assist developers and researchers in future work at tbench.ai.
The utilization of food processing by-products for the manufacturing of added-value products promotes circularity in food systems. The upcycling of agro-industrial side streams, generated in urban areas, fosters the sustainability of local food production and consumption, alleviating the waste management systems. Brewers’ Spent Grain (BSG) is the main by-product of the brewing industry. In this study, BSG was incorporated into a bread product to examine its potential as an effective ingredient for enhancing bread nutritional quality. Breads, consisting of flour, yeast, sugar, salt and BSG (flour substitution by 15 and 30
