Publications

Showing 36 results for Author: Bryan P. Maldonado Puente

View All publications

  • Mar, 2026

    Conference Paper

    Integration of a real-time orientation measurement system for a real-time evaluator (RTE) to measure the position and orientation of crane-lifted components

    Prefabrication of building components holds the potential to revolutionize the construction industry. Prefabrication consists of manufacturing building components, modules, and other elements in a factory to be shipped and installed on a construction site. Prefabricated components have been produced for various applications including precast concrete panels for new constru…

  • Mar, 2026

    Conference Paper

    Deep Point Cloud Building Envelope Segmentation (DeeP-CuBES) using Deep Learning

    Building Information Modeling (BIM) plays an important role in building design and construction, particularly for achieving energy-efficient retrofits. Building envelope retrofits using panelized prefabricated system, such as those popularized by the Energiesprong program, need accurate as-built dimensions of facade features (windows, doors, etc.) to achieve the desired th…

  • Mar, 2026

    Conference Paper

    P2P: Point Cloud to Panel Layout Optimization

    Building envelope retrofits, despite their benefits on enhancing energy efficiency, progress slowly due to high operating costs. Overclad panelized systems present an attractive solution to make retrofits affordable and easy to install. However, several stages of the retrofit process remain disconnected, suboptimal, and require significant human intervention. This study ai…

  • Mar, 2026

    Conference Paper

    Automating Anomaly Detection for Target systems at Spallation Neutron Source

    The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory, produces the world’s most intense pulse neutrons beams. An accelerated proton beam is directed into a mercury target to generate neutrons via spallation. The target system accounted for over 40% of the overall downtime of the facility in 2022. Thus, early detection in anomalies in the target systems can…

  • May, 2025

    Journal

    Dynamic Modeling, Trajectory Optimization, and Linear Control of Cable-Driven Parallel Robots for Automated Panelized Building Retrofits

    The construction industry faces a growing need for automation to reduce costs, improve accuracy and productivity, and address labor shortages. One area that stands to benefit significantly from automation is panelized prefabricated building envelope retrofits, which can improve a building’s energy efficiency in heating and cooling interior spaces. In this paper, we propose…

  • Oct, 2024

    Journal

    Dynamic systems modeling of the spallation neutron source cryogenic moderator system to optimize transient control and prepare for power upgrades

    Through support of the US Department of Energy's Office of Basic Energy Sciences, Oak Ridge National Laboratory has begun applying machine learning methods to improve accelerator and target performance of the Spallation Neutron Source (SNS). These methods are being applied to the control optimization and power upgrade of the SNS Cryogenic Moderator System (CMS). A numerica…

  • Feb, 2024

    Conference Paper

    Automatic Segmentation of Building Envelope Point Cloud Data Using Machine Learning

    About 50% of buildings in the US were constructed before energy codes were introduced. Modular overclad panel retrofits, in which a new envelope is constructed over the existing building, are a promising solution given that it minimizes occupant disruption and shortens construction time at the jobsite. Current state-of-the-art retrofit panel layout and dimensioning consist…

  • Feb, 2024

    Journal

    Reinforcement learning applied to dilute combustion control for increased fuel efficiency

    To reduce the modeling burden for control of spark-ignition engines, reinforcement learning (RL) has been applied to solve the dilute combustion limit problem. Q-learning was used to identify an optimal control policy to adjust the fuel injection quantity in each combustion cycle. A physics-based model was used to determine the relevant states of the system used for traini…

  • Dec, 2023

    Conference Paper

    Automated tracking of prefabricated components for a real-time evaluator to optimize and automate installation

    Trade associations for prefabricated construction estimate that about 50% of prefabricated wall projects have alignment problems that lead to defects and rework. Additionally, component installation times average between 30 and 60 minutes per component. To address these issues, a real-time evaluator (RTE) system was introduced to decrease cost and automate prefabricated co…

  • Nov, 2023

    Conference Paper

    Data-Driven Modeling of a High Capacity Cryogenic System for Control Optimization

    The Cryogenic Moderator System (CMS) is responsible for maintaining a steady flow of cold neutrons for numerous physics experiments at the Spallation Neutron Source (SNS) in Oak Ridge National Laboratory (ORNL). Sudden losses in beam power, known as beam trips, cause a major disturbance to the CMS due to large step changes in cooling demands. Ongoing efforts on upgrading t…

  • Nov, 2023

    Journal

    Analysis of Real-World Preignition Data Using Neural Networks

    Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubrica…

  • Nov, 2023

    Journal

    Artificial Neural Networks for In-Cycle Prediction of Knock Events

    Downsized turbocharged engines have been increasingly popular in modern light-duty vehicles due to their fuel efficiency benefits. However, high power density in such engines is achieved thanks to high in-cylinder pressure and temperature conditions that increase knock propensity. Next-cycle control has been studied as a method to reduce the damaging effects of knock by op…

1
2
3