Transfer learning for process design with reinforcement learning

Process design is a creative task that is currently performed manually by engineers. Artificial intelligence provides new potential to facilitate process design. Specifically, reinforcement learning (RL) has shown some success in automating process design by integrating data-driven models that learn to build process flowsheets with process...

Structural Design and Testing of Digitally Manufactured Concrete Structures

The form freedom enabled by digital fabrication with concrete technologies provides advantages for a wide range of concrete based objects, from architectural to structural elements. The current chapter focuses on the specifics of structural design and engineering of DFC with emphasis on those technologies based on Additive Manufacturing with...

Reinforcement Learning for the Knapsack Problem

Combinatorial optimization (CO) problems are at the heart of both practical and theoretical research. Due to their complexity, many problems cannot be solved via exact methods in reasonable time; hence, we resort to heuristic solution methods. In recent years, machine learning (ML) has brought immense benefits in many research areas,...

Chloride Ion Penetration into Cracked UHPFRC During Wetting-drying Cycles

The subject of this paper is the extent to which, during wetting–drying cycles, chloride ions can penetrate Ultra-high-Performance Fibre Reinforced Cementitious Composites (UHPFRC) specimens subjected to combined mechanical and environmental load. Pre-cracking was obtained by subjecting prismatic specimens (40 × 40 × 60mm³) to four...