Optimization-based Approaches for Design of Chemical Process Families Using ReLU Surrogates
Presentation delivered at 2023 Foundations of Computer-Aided Process Operations (FOCAPO) and Chemical Process Control (CPC) conference.
Stinchfield, Georgia↗
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Cabin Thermal Management Analysis for SuperTruck II Next-Generation Hybrid Electric Truck Design
In this article, we present a multistage, coupled thermal management simulation approach, informed by physical testing where available, to aid design decisions for PACCAR's SuperTruck II hybrid truck cabin concept. Focus areas include cabin insulation, battery sizing, and sleeper curtain position, as well as heating, ventilating, and air-conditioning (HVAC) component and accessory configurations, to maintain or improve thermal comfort while saving energy. The authors analyzed weather data and determined the national vehicle miles traveled weighted temperature and solar conditions for long-haul trucks. Example weather day profiles were selected to approximate the 5th and 95th percentile weighted conditions. A daylong drive cycle was developed to impose appropriate external wind conditions during rest and driving periods. Using the National Renewable Energy Laboratory's vehicle HVAC modeling and simulation tool VTCab, HVAC load design trade-off studies for the new truck geometry concept were completed. Parameters analyzed included effects of paint color, insulation, glass transmissivity, and curtain location. Simulation results helped with early design material selections for efficient cabin climate control. A detailed three-dimensional computer-aided engineering (CAE), computational fluid dynamics (CFD), radiation, and human physiology co-simulation, referred to in this article as CAE Thermal-CFD, was used to evaluate thermal comfort and energy impacts of diffuser configurations and air supply settings in driving and hoteling modes. Analysis revealed that it is more difficult to heat the cabin in hoteling mode during the winter than to cool the space in the summer. This seasonal load profile drives the requirement of additional energy storage for heating comfort. To determine the battery capacity requirement, multiday HVAC operation drive cycle simulations were then completed, showing that a 15-kWh battery would be required for HVAC operation during hoteling. Results helped reduce cabin thermal loads, determine component sizing requirements, and improve occupant comfort to save fuel and contribute to the economic viability of the hybrid system.
33 ADVANCED PROPULSION SYSTEMS↗
Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions
This perspective sheds light on the transformative impact of recent computational advancements in the field of protein therapeutics, with a particular focus on the design and development of antibodies. Cutting-edge computational methods have revolutionized our understanding of protein–protein interactions (PPIs), enhancing the efficacy of protein therapeutics in preclinical and clinical settings. Central to these advancements is the application of machine learning and deep learning, which offers unprecedented insights into the intricate mechanisms of PPIs and facilitates precise control over protein functions. Despite these advancements, the complex structural nuances of antibodies pose ongoing challenges in their design and optimization. Our review provides a comprehensive exploration of the latest deep learning approaches, including language models and diffusion techniques, and their role in surmounting these challenges. We also present a critical analysis of these methods, offering insights to drive further progress in this rapidly evolving field. The paper includes practical recommendations for the application of these computational techniques, supplemented with independent benchmark studies. These studies focus on key performance metrics such as accuracy and the ease of program execution, providing a valuable resource for researchers engaged in antibody design and development. Through this detailed perspective, we aim to contribute to the advancement of antibody design, equipping researchers with the tools and knowledge to navigate the complexities of this field.
59 BASIC BIOLOGICAL SCIENCES↗
Hybrid Manufacturing of Conformal Cooling Channels for Tooling
Computer-aided manufacturing (CAM) techniques for hybrid manufacturing have led to new application areas in the manufacturing industry. In the tooling industry, cooling channels are used to enable specific heating and cooling cycles to improve the performance of the process. These internal cooling channels have been designed with limited manufacturing processes in mind, so, until recently, they were often straight in shape for cross-drilling operations and manufactured from a cast billet. To show a novel application of this common technology, a tool with integrated conformal cooling channels was manufactured using hybrid manufacturing (blown-powder DED and CNC machining) techniques. The computer-aided manufacturing strategy used, and the lessons learned are presented and discussed to enable future work in this industrial application space.
36 MATERIALS SCIENCE↗
Strategies for Computer-Aided Discovery of Novel Open-Shell Polymers
Organic π-conjugated polymers with a triplet ground state have been the focus of recent research for their interesting and unique electronic properties, arising from the presence of the two unpaired electrons. These compounds are usually built from alternating electron-donating and electron-accepting monomer pairs which lower the HOMO–LUMO gap and yield a triplet state instead of the typical singlet ground state. In this paper, we use density functional theory calculations to explore the design rules that govern the creation of a ground-state triplet conjugated polymer and find that a small HOMO–LUMO gap in the singlet state is the best predictor for the existence of a triplet ground state, compared to previous use of a pro-quinoidal bonding character. Furthermore, this work can accelerate the discovery of new stable triplet materials by reducing the computational resources needed for electronic-state calculations and the number of potential candidates for synthesis.
36 MATERIALS SCIENCE↗
Pyomo.GDP: an ecosystem for logic based modeling and optimization development
We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.
42 ENGINEERING↗
Autonomous aerial flight path inspection using advanced manufacturing techniques
Robotic systems have shown capabilities to perform inspection tasks in dangerous and difficult-to-access environments, such as those found in different components of power plants. However, most of the current robotic inspection technology is designed for specific components. Aerial robots, commonly termed as Drones, have raised an option to inspect a wider range of structural components. Nevertheless, current aerial inspecting technology still relies on a human pilot with limited line of sight, field of view and a reduced perception as the drone flies away, which prevents performing close-quarter inspection in intricate, structurally complex and GPS-denied environments. This work introduces offline inspection path generation methods based on robotics-integrated to manufacturing techniques. One method uses computer-aided manufacturing (CAM) techniques and the other an additive manufacturing (AM) approach to generate the flight path. That is to say, the drone would fly along the path described by a 3D (Three Dimensional) printer’s extruder or a CNC (Computer Numerical Control) machining tool, enabling to fly very close the structure even in physical structures with a complex geometry. Once the trajectories are generated, they are introduced for its validation in the Gazebo robotics simulator. Simulation results demonstrate the proper performance of the method and confirm that this approach can be used for close inspection of structural components.
42 ENGINEERING↗
Computer-Aided Engineering of a Non-Phosphorylating Glyceraldehyde-3-Phosphate Dehydrogenase to Enable Cell-Free Biocatalysis
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Discovery of hybrid chemical synthesis pathways with DORAnet
Developing efficient tools for discovering novel synthesis pathways is essential to advance chemical production methods that maximize the use of resources and energy. We introduce DORAnet (Designing Optimal Reaction Avenues Network Enumeration Tool), an open-source computational framework that addresses key limitations in current computer-aided synthesis planning (CASP) tools. DORAnet integrates both chemical/chemocatalytic (i.e., non-enzymatic) and enzymatic transformations, enabling the discovery of hybrid synthesis pathways. With 390 expert-curated chemical/chemocatalytic reaction rules and 3606 enzymatic rules derived from MetaCyc, it provides extensive flexibility for synthetic chemists and biotechnologists. The framework features customizable network expansion strategies, advanced filtering, and pathway search, ranking, and visualization tools. Validated against known reaction data, DORAnet successfully identified both established and novel synthesis routes for key industrial chemicals. In a case study involving 51 high-volume targets, DORAnet frequently ranked known commercial pathways among the top three results, demonstrating its practical relevance and ranking accuracy, while also uncovering numerous alternative (hybrid) synthesis pathways that were highly ranked.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Laser 3D printing of highly compacted protonic ceramic electrolyzer stack
Solid oxide electrolysis cells (SOECs) for H 2 production is a core technology for H2@scale. However, its conventional manufacturing methods adapted from the manufacture of solid oxide fuel cells (SOFC) need high cost, especially for small-volume production. The emerging laser 3D printing (L3DP) technology with computer-aided 3D printing and computer-controlled laser processing can fulfill layer-by-layer digital shaping and rapid in-situ consolidating feedstock into complicated geometries. L3DP, a promising additive manufacturing (AM) technology, has achieved significant success in manufacturing plastic and metal parts, which is currently attracting considerable attention for the cost-effective, rapid, and flexible manufacturing of heterogeneous multilayered ceramic devices (e.g., SOECs, SOFCs, and solid-state batteries). It is believed that the L3DP can integrate the advantages of selective consolidation of heterogeneous layers, accurate control of layer microstructures, high processing heat efficiency, high processing speed, high stack compactness, high stack design flexibility, and low stack sealing area for cost-effective, rapid, and flexible manufacturing of SOECs to meet DOE’s electrolyzer target.
08 HYDROGEN↗