Prediction & optimization of alkali-activated concrete based on the random forest machine learning algorithm

Alkali-activated concrete (AAC) is regarded as a promising alternative construction material to reduce the CO₂ emission induced by Portland cement (PC) concrete. Due to the diversity in raw materials and complexity of reaction mechanisms, a commonly applied design code is still absent to date. This study attempts to directly...

Dynamic optimization for minimal HVAC demand with latent heat storage, heat recovery, natural ventilation, and solar shadings

Satisfying thermal comfort in indoor spaces is still a challenge in terms of energy saving, and several HVAC (Heating, Ventilation, and Air-Conditioning) systems have been proposed for this purpose. This paper conducts an analysis to evaluate and optimize the long-term operation of a novel HVAC system installed at The Green Village, a living...

Hierarchical Model Predictive Control for on-Line High-Speed Railway Delay Management and Train Control in a Dynamic Operations Environment

In practice, the operation of high-speed trains is often affected by adverse weather conditions or equipment failures, which result in delays and even cancellations of train services. In this article, a novel two-layer hierarchical model predictive control (MPC) model is proposed for on-line high-speed railway delay management and train...

Distributed Adaptive Optimization with Weight-Balancing

This article addresses the continuous-time distributed optimization of a strictly convex summation-separable cost function with possibly nonconvex local functions over strongly connected digraphs. Distributed optimization methods in the literature require convexity of local functions, or balanced weights, or vanishing step sizes, or algebraic...

An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks

Railways are a well-recognized sustainable transportation mode that helps to satisfy the continuously growing mobility demand. However, the management of railway traffic in large-scale networks is a challenging task, especially when both a major disruption and various disturbances occur simultaneously. We propose an automatic rescheduling...

Efficient freeway MPC by parameterization of ALINEA and a speed-limited area

Freeway congestion can reduce the freeway throughput due to the capacity drop or due to blocking caused by spillback to upstream ramps. Research has shown that congestion can be reduced by the application of ramp metering and variable speed limits. Model predictive control is a promising strategy for the optimization of the ramp metering...

Timely condition-based maintenance planning for multi-component systems

Last-minute maintenance planning is often undesirable, as it may cause downtime during operational hours, may require rescheduling of other activities, and does not allow to optimize the management of spare parts, material, and personnel. In spite of the aforementioned drawbacks of last-minute planning, most existing methods plan maintenance...

Model Predictive Control for continuous piecewise affine systems using optimistic optimization

This paper considers model predictive control for continuous piecewise affine (PWA) systems. In general, this leads to a nonlinear, nonconvex optimization problem. We introduce an approach based on optimistic optimization to solve the resulting optimization problem. Optimistic optimization is based on recursive partitioning of the feasible set...