Results for “Advanced Optimization” — Page 52

DOE OSTI2022

M2CT-22IN1202096 Design for Carbon Conversion Product Pathways with Nuclear Power Plant Integration

Coal is a globally abundant resource that historically has been used for power generation via combustion. As the power industry replaces coal with cleaner methods of generation, energy-rich coal could be used in other chemical and fuel applications. This study presents a coal utilization option in which coal combustion is replaced with a carbon-free nuclear power plant and the coal is upgraded to valuable products for a variety of markets. Coal is prepared for conversion first by the pyrolysis process, which will optimize solid, liquid, and gaseous products based on the market size and potential product value, maximizing the monetary value of coal. This process is designed using bituminous coal from the Appalachian region as a basis to provide a pathway to preserve or transition coal-related jobs and create new jobs associated with the clean energy transition. Process modeling in the AspenOne Suite will be used to determine each component’s sensitivities, costs, inputs, and outputs. Dispatch modeling in the FORCE toolset will optimize the entire system and calculate the NPV for the refinery lifetime. Advanced and light-water reactors are considerations to supply the heat, steam, and electricity to the process. This paper focuses on the technical and market analysis used to determine the optimal processes and product pathways for the carbon refinery. Product pathways are on activated carbon, formic acid synthesis, and methanol synthesis for further upgrading to marketable chemical and polymer products.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

M2CT-22IN1202096 Design for Carbon Conversion Product Pathways with Nuclear Power Plant Integration

Coal is a globally abundant resource that historically has been used for power generation via combustion. As the power industry replaces coal with cleaner methods of generation, energy-rich coal could be used in other chemical and fuel applications. This study presents a coal utilization option in which coal combustion is replaced with a carbon-free nuclear power plant and the coal is upgraded to valuable products for a variety of markets. Coal is prepared for conversion first by the pyrolysis process, which will optimize solid, liquid, and gaseous products based on the market size and potential product value, maximizing the monetary value of coal. This process is designed using bituminous coal from the Appalachian region as a basis to provide a pathway to preserve or transition coal-related jobs and create new jobs associated with the clean energy transition. Process modeling in the AspenOne Suite will be used to determine each component’s sensitivities, costs, inputs, and outputs. Dispatch modeling in the FORCE toolset will optimize the entire system and calculate the NPV for the refinery lifetime. Advanced and light-water reactors are considerations to supply the heat, steam, and electricity to the process. This paper focuses on the technical and market analysis used to determine the optimal processes and product pathways for the carbon refinery. Product pathways are on activated carbon, formic acid synthesis, and methanol synthesis for further upgrading to marketable chemical and polymer products.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2014

DROPWISE CONDENSATION ON MICRO- AND NANOSTRUCTURED SURFACES

In this review we cover recent developments in the area of surface-enhanced dropwise condensation against the background of earlier work. The development of fabrication techniques to create surface structures at the micro-and nanoscale using both bottom-up and top-down approaches has led to increased study of complex interfacial phenomena. In the heat transfer community, researchers have been extensively exploring the use of advanced surface structuring techniques to enhance phase-change heat transfer processes. In particular, the field of vapor-to-liquid condensation and especially that of water condensation has experienced a renaissance due to the promise of further optimizing this process at the micro-and nanoscale by exploiting advances in surface engineering developed over the last several decades.

Enright, R↗

DOE OSTI2024

Binary Quantum Control Optimization with Uncertain Hamiltonians

Optimizing the controls of quantum systems plays a crucial role in advancing quantum technologies. The time-varying noises in quantum systems and the widespread use of inhomogeneous quantum ensembles raise the need for high-quality quantum controls under uncertainties. In this paper, we consider a stochastic discrete optimization formulation of a discretized binary optimal quantum control problem involving Hamiltonians with predictable uncertainties. We propose a sample-based reformulation that optimizes both risk-neutral and risk-averse measurements of control policies, and solve these with two gradient-based algorithms using sum-up-rounding approaches. Furthermore, we discuss the differentiability of the objective function and prove upper bounds of the gaps between the optimal solutions to binary control problems and their continuous relaxations. We conduct numerical simulations on various sized problem instances based on two applications of quantum pulse optimization; we evaluate different strategies to mitigate the impact of uncertainties in quantum systems. In conclusion, we demonstrate that the controls of our stochastic optimization model achieve significantly higher quality and robustness compared with the controls of a deterministic model.

conditional value-at-risk (CVaR)↗

DOE OSTI2020

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids with Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids With Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. Demand-side participation cannot be leveraged effectively without explicitly including the distribution system dynamics in the optimization-based wholesale market operations. This project grew from a vision for co-optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the lower voltage system (distribution or microgrid) can also sell (buy) excess (necessary) energy from the transmission system. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. An ideal microgrid is defined as an electric entity capable of operating in both interconnected (with the high-voltage grid) and islanded mode. As such, the microgrid should incorporate generating units (traditional units and intermittent) and if needed, exchange power with the high-voltage grid. The interplay between the microgrid and high-voltage grid motivated the development of the co-optimization approach to ensure efficient performance of the interconnected network. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Performance of asynchronous optimized Schwarz with one-sided communication

In asynchronous iterative methods on distributed-memory computers, processes update their local solutions using data from other processes without an implicit or explicit global synchronization that corresponds to advancing the global iteration counter. Here in this work, we test the asynchronous optimized Schwarz domain-decomposition iterative method using various one-sided (remote direct memory access) communication schemes with passive target completion. The results show that when one-sided communication is well-supported, the asynchronous version of optimized Schwarz can outperform the synchronous version even for perfectly balanced partitionings of the problem on a supercomputer with uniform nodes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Final Project Report for DOE/EERE High-Capacity and Low-Cost Hydrogen-Storage Sorbents for Automotive Applications

This report provides a review of the objectives, progress, and milestones of the research conducted during this project on the topic of developing innovative metal-organic frameworks (MOFs) and porous organic polymers (POPs) for high-capacity and low-cost hydrogen-storage sorbents in automotive applications.1 The objectives of the proposed research were to develop new materials as next-generation hydrogen storage sorbents that meet or exceed DOE’s 2017 performance targets of gravimetric capacity of 0.055 kg H 2 /kg system and volumetric capacity of 0.040 kg H 2 /L system at a cost of $400/kg H 2 stored . Texas A&M University (TAMU) and Argonne National Laboratory (ANL) collaborated in developing low-cost and high-capacity hydrogen-storage sorbents with appropriate stability, sorption kinetics, and thermal conductivity. The research scope and methods developed to achieve the project’s goals include the following: Advanced ligand design and synthesis to construct MOF sorbents with optimal hydrogen storage capacities, low cost and high stability; Substantially improve the hydrogen uptake capacity and chemical stability of MOF-based sorbents by incorporating high valent metal ions during synthesis or through the post-synthetic metal metathesis oxidation approach; Enhance sorbent storage capacity through material engineering and characterization; Generate a better understanding of the H 2 -sorbent interaction through advanced characterization and simulation. Over the course of the project 5 different MOFs were developed and studied: PCN-250, PCN-12, PCN-12’, PCN-608 and PCN-609.2-3 Two different samples were submitted to the National Renewable Energy Laboratory (NREL) in order to validate their hydrogen adsorption capacity, PCN-250 and PCN-12. Neither of these samples reached the project’s Go/No-Go requirements but the data obtained did further prove the hypothesis that the presence of open metal sites oriented towards MOF pores help to surpass the predicted hydrogen uptakes described by Chahine’s rule.4 These observations are believed to have a major impact on the hydrogen storage community, and may potentially lead to the development of a material that could meet the DOE goals for hydrogen storage systems for automotive applications.

08 HYDROGEN↗

DOE OSTI2025

Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies

As the chemical industry shifts toward sustainable practices, there is a growing initiative to replace conventional fossil-derived solvents with environmentally friendly alternatives such as ionic liquids (ILs) and deep eutectic solvents (DESs). Artificial intelligence (AI) plays a key role in the discovery and design of novel solvents and the development of green processes. This review explores the latest advancements in AI-assisted solvent screening with a specific focus on machine learning (ML) models for physicochemical property prediction and separation process design. Additionally, this paper highlights recent progress in the development of automated high-throughput (HT) platforms for solvent screening. Finally, this paper discusses the challenges and prospects of ML-driven HT strategies for green solvent design and optimization. To this end, this review provides key insights to advance solvent screening strategies for future chemical and separation processes.

Artificial intelligence↗

DOE OSTI2018

Utilization of Renewable Energy to Meet New National Challenges in Energy and Climate Change

The project aims to design a microgrid system to promote utilization of renewable energy resources such as wind and solar to address the national challenges in energy and climate change. Different optimization techniques and simulation software are used to study the performance of the renewable energy system under study. A series of research works performed under the grant Department of Energy (DOE) is presented. This grant opportunity affords Howard faculty, students, graduates, undergraduates, K-12, postdocs and visiting scholars to benefit state of the art research work. The research work has led to improve or advance understanding of new hardware technologies, software development and engineering optimization methods necessary and sufficient for handling probabilistic models and real-time computation and functions necessary for development of microgrid system. Consistent with State of Project Objective Howard University has partitioned the task into the following integrated activities: 1. Stochastic Model for RER and Load • Development of modeling Renewable Energy Resources (RER) and load which is used to perform distribution power flow study which leads to publication in refereed journals and conferences. The work was also published at the IEEE conference. 2. Stochastic optimization for voltage/Var • The development of voltage VAr optimization based on a review of existing knowledge in optimization led to the use of stochastic program and evolution of programming optimization method for V/VAr optimization. Papers were presented at the North America Power Systems Conference and the IEEE PES general meeting. 3. Modeling RER and Storage • Extending the concept of optimization method an RER with storage, such as the development of microgrid V/VAr and storage is performed. Several papers were published at the North America Power Systems Conference and the IEEE PES general meeting. 4. Power Game • Development of power game experiment using Labvolt to allow for hands on understanding of design and development of microgrid functions is performed. Publication were done by students at the end of their summer program. 5. Designing Microgrid Testbed • Example microgrid test bed is developed. In addition, function of the test bed are developed. The papers were presented at the North America Power Systems Conference and the IEEE general meeting. 6. Outreach Program • From the outreach program, topics from the project have been included in the revision of courses at Howard University, new book called Energy Processing and Smartgrid has being developed. • Hosted masters students from University of Denver to complete their projects with us. • Hosted high school students for early exposure for careers in STEM • Representations made in IEEE conferences to share the lessons learned in the use of micro grid to expose students to STEM education and research.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Droplet microfluidics for synthetic biology

Here, synthetic biology is an interdisciplinary field that aims to engineer biological systems for useful purposes. Organism engineering often requires the optimization of individual genes and/or entire biological pathways (consisting of multiple genes). Advances in DNA sequencing and synthesis have recently begun to enable the possibility of evaluating thousands of gene variants and hundreds of thousands of gene combinations. However, such large-scale optimization experiments remain cost-prohibitive to researchers following traditional molecular biology practices, which are frequently labor-intensive and suffer from poor reproducibility. Liquid handling robotics may reduce labor and improve reproducibility, but are themselves expensive and thus inaccessible to most researchers. Microfluidic platforms offer a lower entry price point alternative to robotics, and maintain high throughput and reproducibility while further reducing operating costs through diminished reagent volume requirements. Droplet microfluidics have shown exceptional promise for synthetic biology experiments, including DNA assembly, transformation/transfection, culturing, cell sorting, phenotypic assays, artificial cells and genetic circuits.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer-Based Hydrogen Production Facility: Preprint

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at the National Renewable Energy Laboratory (NREL)'s Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗

DOE OSTI2015

WE-EF-BRA-07: High Performance Preclinical Irradiation Through Optimized Dual Focal Spot Dose Painting and Online Virtual Isocenter Radiation Field Targeting

Purpose: Advances in radiotherapy practice facilitated by collimation systems to shape radiation fields and image guidance to target these conformal beams have motivated proposals for more complex dose patterns to improve the therapeutic ratio. Recent progress in small animal radiotherapy platforms has provided the foundation to validate the efficacy of such interventions, but robustly delivering heterogeneous dose distributions at the scale and accuracy demanded by preclinical studies remains challenging. This work proposes a dual focal spot optimization method to paint spatially heterogeneous dose regions and an online virtual isocenter targeting method to accurately target the dose distributions. Methods: Two-dimensional dose kernels were empirically measured for the 1 mm diameter circular collimator with radiochromic film in a solid water phantom for the small and large x-ray focal spots on the X-RAD 225Cx microirradiator. These kernels were used in an optimization framework which determined a set of animal stage positions, beam-on times, and focal spot settings to optimally deliver a given desired dose distribution. An online method was developed which defined a virtual treatment isocenter based on a single image projection of the collimated radiation field. The method was demonstrated by optimization of a 6 mm circular 2 Gy target adjoining a 4 mm semicircular avoidance region. Results: The dual focal spot technique improved the optimized dose distribution with the proportion of avoidance region receiving more than 0.5 Gy reduced by 40% compared to the large focal spot technique. Targeting tests performed by irradiating ball bearing targets on radiochromic film pieced revealed the online targeting method improved the three-dimensional accuracy from 0.48 mm to 0.15 mm. Conclusion: The dual focal spot optimization and online virtual isocenter targeting framework is a robust option for delivering dose at the preclinical level and provides a new experimental option for unique radiobiological investigations This work is supported, in part, by the Natural Sciences and Engineering Research Council of Canada and a Mitacs-Accelerate fellowship. P.E. Lindsay, and D.A. Jaffray are listed as inventors of the system described herein. This system has been licensed to Precision X-Ray Inc. for commercial development.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-FG-207-00: Technological Advances in PET/MR Imaging

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-FG-207-01: Technological Advances and Challenges: Experience with the First Integrated Whole-Body PET/MRI

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-FG-207-02: Technological Advances and Challenges: Experience with Time-Of-Flight PET Combined with 3-Tesla MRI

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

MO-FG-207-03: Maximizing the Utility of Integrated PET/MRI in Clinical Applications

The use of integrated PET/MRI systems in clinical applications can best benefit from understanding their technological advances and limitations. The currently available clinical PET/MRI systems have their own characteristics. Thorough analyses of existing technical data and evaluation of necessary performance metrics for quality assurances could be conducted to optimize application-specific PET/MRI protocols. This Symposium will focus on technical advances and limitations of clinical PET/MRI systems, and how this exciting imaging modality can be utilized in applications that can benefit from both PET and MRI. Learning Objectives: To understand the technological advances of clinical PET/MRI systems To correctly identify clinical applications that can benefit from PET/MRI To understand ongoing work to further improve the current PET/MRI technology Floris Jansen is a GE Healthcare employee.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

AI-Driven Detector Design for the EIC (Final Technical Report)

We developed an optimization workflow based on DNN-based fast-simulation and reconstruction algorithms. We used these methods to advance the design of calorimeter systems for the Electron-Ion Collider (EIC). This DNN-driven optimization provides a blueprint for integrating gradient-based methods into detector-design workflows. All software pipelines and methods have been released publicly and incorporated into the EIC collaboration’s physics studies, broadening their impact. Three journal articles detailing the methods developed here serve as a reference for the design and optimal use of next generation high-granularity calorimeter systems in nuclear and particle physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗