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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Variational Quantum Algorithms for Semidefinite Programming

A semidefinite program (SDP) is a particular kind of convex optimization problem with applications in operations research, combinatorial optimization, quantum information science, and beyond. In this work, we propose variational quantum algorithms for approximately solving SDPs. For one class of SDPs, we provide a rigorous analysis of their convergence to approximate locally optimal solutions, under the assumption that they are weakly constrained (i.e., N$\gg$M, where N is the dimension of the input matrices and M is the number of constraints). We also provide algorithms for a more general class of SDPs that requires fewer assumptions. Finally, we numerically simulate our quantum algorithms for applications such as MaxCut, and the results of these simulations provide evidence that convergence still occurs in noisy settings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

System and method for managing electrical components for energy usage

A system for managing performance of one or more electrical components in real-time includes one or more sensors to provide working conditions of one or more energy consuming devices. The system further includes one or more actuators coupled to and configured to control the one or more energy consuming devices. Additionally, the system includes a computing device in electrical communication with the one or more sensors and the one or more actuators. The system also includes a database capable of retaining an instruction program for the computing device. The computing device includes a processor that is configured to receive data from the one or more sensors, analyze data from the one or more sensors, and execute the instruction program received from the database in order to optimize operation of the one or more energy consuming devices based on one or more criteria.

Chen, Jie↗
DOE OSTI2021

Solvability, Operability, and Security for Cyber-Physical Systems: New Computational Methods with Revised Assumptions

In this paper discusses the use and integration of disparate but complementary tools for dealing with solvability, operability, and security challenges in Cyber-Physical Systems (CPSs): the Koopman Operator (KO) for solvability, Disjunctive Programming (DP) for operability, and Multi-Level Optimisation (MLO) for security. These methods can obviate the need for some of the traditional assumptions used in modelling CPSs. This paper demonstrates the methods' capabilities and considers ways to advance each method individually. It concludes by discussing how to integrate the different methods and identify useful synergies generated by doing so.

koopman operator, disjunctive programming, multi-l↗
DOE OSTI2020

PREEMPT: Scalable Epidemic Interventions Using Submodular Optimization on Multi-GPU Systems

Preventing and slowing the spread of epidemics is achieved through techniques such as vaccination and social distancing. Given practical limitations on the number of vaccines and cost of administration, optimization becomes a necessity. Previous approaches using mathematical programming methods have shown to be effective but are limited by computational costs. In this work, we make several contributions: First, we present a new approach for intervention via maximizing the influence of vaccinated nodes on the network. We call this method \preempt. Next, we prove submodular properties associated with the objective function of our method so that it aids in construction of an efficient greedy approximation strategy. Consequently, we present a new parallel algorithm based on greedy hill climbing for \preempt, and present an efficient parallel implementation for distributed CPU-GPU heterogeneous platforms. Our results demonstrate that \preempt{} is able to achieve a significant reduction (up to 6.75$\times$) in the percentage of people infected on a city-scale network. We also show strong scaling results of \preempt{} on 128 nodes of the Summit supercomputer. Our parallel implementation is able to significantly reduce time to solution, from hours to minutes on large networks. This work represents a first-of-its-kind effort in parallelizing greedy hill climbing and applying it toward devising effective interventions for epidemics.

Minutoli, Marco↗
DOE OSTI2022

Data and Multistage Optimization for the New Grid

Three essential capabilities for using exascale computing resources on next generation power grid applications are: generating large renewable energy datasets, modeling damage and operations during and after extreme events, and employing multi-stage optimization for infrastructure planning. Powerscenarios, developed as part of the ExaSGD project, addresses these capabilities by enabling users to build synthetic wind farms for large test systems using numerical weather prediction-based data sources. We share examples of using Powerscenarios to build out wind farms on the ACTIVSg2000 test system, to enable simulated operations and emergency asset allocation during a hurricane strike, and to compute multi-stage infrastructure buildouts.

economic dispatch↗
DOE OSTI2023

Evolution of Scenario Generation Capabilities in the ExaSGD Project

High-fidelity renewable energy scenarios and rare-event high-impact contingencies are essential for modeling operations and infrastructure expansion of the next generation power grids using exascale computing resources. As the ExaSGD project progressed, our capabilities for generating scenarios for modeling wind power output at multiple wind farms significantly improved, evolving from the use of independent random perturbations to importance sampling-based techniques capturing representative spatial-temporal relations. Contingency generation also improved, evolving from standard N-1 techniques to probabilistic models of infrastructure damage resulting from extreme weather events. We review the developments in the realistic intermittent-energy scenario forecasting and extreme-event contingency creation as the ExaSGD project progressed and discuss the future work in these areas.

economic dispatch↗
DOE OSTI2022

User-Oriented Improvements in the MOOSE framework in support of Multiphysics Simulation

The MOOSE Framework is a foundational capability used by NEAMS to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms including optimization, improved user experience, streamlined APIs, parallelism, and new capability. The work transcribed in the report was in direct support of the simulation tools and is already deployed or will be deployed in the coming months. The capabilities implemented were, in the same order as this report, chainable execution objects or executors, support for transfers between applications at the same level in a coupling scheme, support for boundary/subdomain restricted transfers, support for transfers between applications with different coordinate or unit systems, support for MOOSE applications in the NEAMS workbench, deployment of MOOSE application of the INL HPC OnDemand platform, addition of a triangular meshing library in libMesh and increased support of face variables.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗
DOE OSTI2016

TH-EF-BRB-02: Feasibility of Optimization for Dynamic Trajectory Radiotherapy

Purpose: Over the last years, volumetric modulated arc therapy (VMAT) has been widely introduced into clinical routine using a coplanar delivery technique. However, VMAT might be improved by including dynamic couch and collimator rotations, leading to dynamic trajectory radiotherapy (DTRT). In this work the feasibility and the potential benefit of DTRT was investigated. Methods: A general framework for the optimization was developed using the Eclipse Scripting Research Application Programming Interface (ESRAPI). Based on contoured target and organs at risk (OARs), the structures are extracted using the ESRAPI. Sampling potential beam directions, regularly distributed on a sphere using a Fibanocci-lattice, the fractional volume-overlap of each OAR and the target is determined and used to establish dynamic gantry-couch movements. Then, for each gantry-couch track the most suitable collimator angle is determined for each control point by optimizing the area between the MLC leaves and the target contour. The resulting dynamic trajectories are used as input to perform the optimization using a research version of the VMAT optimization algorithm and the ESRAPI. The feasibility of this procedure was tested for a clinically motivated head and neck case. Resulting dose distributions for the VMAT plan and for the dynamic trajectory treatment plan were compared based on DVH-parameters. Results: While the DVH for the target is virtually preserved, improvements in maximum dose for the DTRT plan were achieved for all OARs except for the inner-ear, where maximum dose remains the same. The major improvements in maximum dose were 6.5% of the prescribed dose (66 Gy) for the parotid and 5.5% for the myelon and the eye. Conclusion: The result of this work suggests that DTRT has a great potential to reduce dose to OARs with similar target coverage when compared to conventional VMAT treatment plans. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Microgrid design and multi-year dispatch optimization under climate-informed load and renewable resource uncertainty

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Biomass District Heat System for Interior Rural Alaska Villages

Alaska Village Initiatives (AVI) from the outset of the project had a goal of developing an integrated village approach to biomass in Rural Alaskan villages. A successful biomass project had to be ecologically, socially/culturally and economically viable and sustainable. Although many agencies were supportive of biomass programs in villages none had the capacity to deal effectively with developing all of the tools necessary to build a complete integrated program. AVI had a sharp learning curve as well. By the end of the project with all the completed tasks, AVI developed the tools and understanding to connect all of the dots of an integrated village based program. These included initially developing a feasibility model that created the capacity to optimize a biomass system in a village. AVI intent was to develop all aspects or components of a fully integrated biomass program for a village. This meant understand the forest resource and developing a sustainable harvest system that included the “right sized” harvest equipment for the scale of the project. Developing a training program for harvesting and managing the forest for regeneration. Making sure the type, quality, and delivery system matched the needs of the type of boiler or boilers to be installed. AVI intended for each biomass program to be of the scale that would create jobs and a sustainable business.

09 BIOMASS FUELS↗
DOE OSTI2015

Sustainable Hydropower in Lower Mekong Countries: Technical Assessment and Training Travel Report Thailand

The U.S. Agency for International Development (USAID), through their partnership with the U.S. Department of the Interior (DOI), requested the support of Oak Ridge National Laboratory (ORNL) to provide specialized technical assistance as part of the Smart Infrastructure for the Mekong (SIM) Program in Thailand. Introduced in July 2013 by U.S. Secretary of State John Kerry, SIM is a U.S. Government Inter-Agency program that provides Lower Mekong partner countries with targeted, demand-driven technical and scientific assistance to support environmentally sound, climate conscious and socially equitable infrastructure, clean energy development, and water resources optimization. The U.S. Government is committed to supporting sustainable economic development within the region by providing tools, best practices, technical assistance, and lessons learned for the benefit of partner countries. In response to a request from the Electricity Generating Authority of Thailand (EGAT), a SIM project was developed with two main activities: 1) to promote hydropower sustainability and efficiency through technical assessment training at two existing hydropower assets in Thailand, and 2) the design and implementation of one national and two or three regional science and policy workshops, to be co-hosted with EGAT, to build common understanding of and commitment to environmental and social safeguards for Mekong Basin hydropower projects. The U.S. Department of Energy (DOE) is leading the technical assessment (Activity 1), and has contracted ORNL to provide expert technical assistance focused on increasing efficiency at existing projects, with the goal of increasing renewable energy generation at little to no capital cost. ORNL is the leading national laboratory in hydropower analysis, with a nationally recognized and highly qualified team of scientists addressing small to large-scale systems (basin-, regional-, and national-scale) energy generation optimization analysis for DOE. The mission of the ORNL Water Power Program is to develop technologies, decision-support tools, and methods of analysis that enable holistic management of water-dependent energy infrastructure and natural resources in support of the DOE Energy Efficiency and Renewable Energy Office (DOE-EERE), Federal hydropower agencies, Federal Energy Regulatory Commission (FERC), Nuclear Regulatory Commission (NRC), energy producers, and other entities. In support of SIM, ORNL completed technical assessments of two hydropower plants owned and operated by the Electricity Generating Authority of Thailand (EGAT): Vajiralongkorn (VRK), with an installed capacity of 300 MW, and Rajjaprabha (RPB), with an installed capacity of 240MW. Technical assessment is defined as the assessment of hydropower operation and performance, and the identification of potential opportunities for performance improvement through plant optimization. At each plant, the assessment included an initial analysis of hydropower operating and performance metrics, provided by dam owners. After this analysis, ORNL engaged with the plant management team in a skills exchange, where best practices, operational methods, and technical challenges were discussed. The technical assessment process was outlined to plant management followed by a presentation of preliminary results and analysis based on 50 days of operational data. EGAT has agreed to provide a full year of operational data so a complete and detailed assessment that captures seasonal variability can be completed. The results of these assessments and discussions will be used to develop a set of best practices, training, and procedure recommendations to improve the efficiency of the two assessed plants.

13 HYDRO ENERGY↗
DOE OSTI2019

A Bi-Level Formulation And Solution Method For The Integration Of Process Design And Scheduling

Design and operation decisions of manufacturing plants can often be expressed within a hierarchical structure, where optimal decisions at lower operating level provide constraints for the decision raking at a higher decision level. In this work, we are addressing the case of a hierarchical design and scheduling optimization problem. The integration of design and scheduling decisions can play a big role in designing economically profitable plants and improving their operational performance. This problem can be expressed as a bi-level problem, where design related decisions occur at the upper level and operational scheduling decisions at the lower level. Since discrete decisions are involved in both optimization levels, the resulting formulation typically corresponds to bi-level mixed-integer programming problems (B-MIP). The solution of B-MIP problems is very challenging, and typically requires the use of global optimization techniques, with many algorithms not able to guarantee feasibility. To overcome the challenges in solving this class of problems we propose the use of a multi-parametric based algorithm for the solution of bi-level mixed-integer linear and quadratic programming problems, capable of providing the exact and global solution. The main idea of this approach is to treat the lower scheduling problem as a multi-parametric programming problem in which the design decisions are considered as parameters. Here, the resulting parametric solutions can then be substituted into the upper level design problem, which can be solved as a set of single-level deterministic programming problems. Through the developed formulation and algorithm we are able to supply the decision makers with the exact solution of the integrated design and scheduling problem.

42 ENGINEERING↗
DOE OSTI2019

Progress of indirect drive inertial confinement fusion in the United States

Abstract Indirect drive converts high power laser light into x-rays using small high- Z cavities called hohlraums. X-rays generated at the hohlraum walls drive a capsule filled with deuterium–tritium (DT) fuel to fusion conditions. Recent experiments have produced fusion yields exceeding 50 kJ where alpha heating provides ~3× increase in yield over PdV work. Closing the gaps toward ignition is challenging, requiring optimization of the target/implosions and the laser to extract maximum energy. The US program has a three-pronged approach to maximize target performance, each closing some portion of the gap. The first item is optimizing the hohlraum to couple more energy to the capsule while maintaining symmetry control. Novel hohlraum designs are being pursued that enable a larger capsule to be driven symmetrically to both reduce 3D effects and increase energy coupled to the capsule. The second issue being addressed is capsule stability. Seeding of instabilities by the hardware used to mount the capsule and fill it with DT fuel remains a concern. Work reducing the impact of the DT fill tubes and novel capsule mounts is being pursed to reduce the effect of mix on the capsule implosions. There is also growing evidence native capsule seeds such as a micro-structure may be playing a role on limiting capsule performance and dedicated experiments are being developed to better understand the phenomenon. The last area of emphasis is the laser. As technology progresses and understanding of laser damage/mitigation advances, increasing the laser energy seems possible. This would increase the amount of energy available to couple to the capsule, and allow larger capsules, potentially increasing the hot spot pressure and confinement time. The combination of each of these focus areas has the potential to produce conditions to initiate thermo-nuclear ignition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Pellet Cladding Interaction In-Reactor Ramp Testing in a World without the Halden Boiling Water Reactor

One of the most crucial performance areas for fuel rods in water cooled nuclear power plants is interaction between cladding tubes and fuel pellets. Experimental programs in test reactors have provided key data to help fuel developers and plant operators understand Pellet Cladding Interaction (PCI) phenomena and optimize their strategies for reliable fuel performance. Approximately 50 years of “ramp” testing programs, where the fission heating rate is deliberately manipulated in test rods, have been performed in a handful of test reactors to reveal and understand PCI behaviors such as iodine-assisted stress corrosion cracking. Unfortunately, the test reactors most engaged in this type of work have all been retired over the years up to the recent and unexpected closure of the Halden Boiling Water Reactor which effectively caused a hiatus in PCI ramp testing programs. The need for ramp testing is crucial at this time to enable refined PCI understanding as more plants consider implementing flexible operations, increased fuel rod burnup limits, and new fuel technologies with enhanced accident tolerance. This paper reviews some of the key PCI phenomena that must be addressed with in-pile testing and surveys past test reactor’s methods for achieving the needed conditions. A strategic approach is then presented using test reactors and complimentary facilities which are still available today. Near term data opportunities are put forth along with capability development strategies that will ensure future longevity in this field of research.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Risk-Sensitive Control of Pure Jump Process on Countable Space with Near Monotone Cost

In this article, we study risk-sensitive control problem with controlled continuous time pure jump process on a countable space as state dynamics. We prove multiplicative dynamic programming principle, elliptic and parabolic Harnack’s inequalities. Using the multiplicative dynamic programing principle and the Harnack’s inequalities, we prove the existence and a characterization of optimal risk-sensitive control under the near monotone condition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Networked Microgrid Optimal Design and Operations Tool: Regulatory and Business Environment Study

Microgrids aim to increase the resilience of the electric supply to the loads within the microgrid through the ability to disconnect from the distribution utility in the event of a power outage and by supplying power to the microgrid loads from a combination of multiple power generation assets and storage systems. Microgrids can also improve reliability at the distribution level by reducing the load on the system under stress conditions. Networking two or more microgrids has the potential to increase reliability and resilience at a reduced cost by taking advantage of economies of scale and increasing the diversity of the generation assets and loads. This report is part of a collaborative effort among several U.S. Department of Energy national laboratories to develop a networked microgrid (NMG) Optimal Design and Operations (OD&O) tool. This tool addresses the goal defined in the Grid Modernization Multi-Year Program Plan to develop a suite of tools that addresses functional requirements for system optimal design and the operations of NMGs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Systems-Level Modeling for CRISPR-Based Metabolic Engineering

The CRISPR-Cas system has enabled the development of sophisticated, multigene metabolic engineering programs through the use of guide RNA-directed activation or repression of target genes. To optimize biosynthetic pathways in microbial systems, we need improved models to inform design and implementation of transcriptional programs. Recent progress has resulted in new modeling approaches for identifying gene targets and predicting the efficacy of guide RNA targeting. Genome-scale and flux balance models have successfully been applied to identify targets for improving biosynthetic production yields using combinatorial CRISPR-interference (CRISPRi) programs. Here, the advent of new approaches for tunable and dynamic CRISPR activation (CRISPRa) promises to further advance these engineering capabilities. Once appropriate targets are identified, guide RNA prediction models can lead to increased efficacy in gene targeting. Developing improved models and incorporating approaches from machine learning may be able to overcome current limitations and greatly expand the capabilities of CRISPR-Cas9 tools for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗