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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Mesh Adaptive Search Optimization in SERPENT2 Stereolithography Geometry

SERPENT2 Monte Carlo program has the capability to model reactor cores by stereolithography (STL) geometry. In this geometry, volumes are defined by the union of triangulated surfaces. Using the STL geometry offers unique benefits, including: 1) the model can be printed on 3D printers; 2) the possibility to use directly geometrical models from Computer-Aided Design (CAD); 3) the capability to perform multi-physics simulations coupling neutronics, thermal-hydraulics, and material science computations. In this work the STL geometry has been created by the CUBIT software, which is designed for finite elements mesh generation. The materials in the STL geometry have been assigned by a simple C program using the colors of the volumes in the CUBIT model. The goal of this work is to minimize the SERPENT2 computing time using mesh adaptive search algorithms. The basic idea is to split the geometry of the core into two zones: one zone containing the fuel elements (including the moderator and the coolant) and the other containing the reflector (and the target zone of the core, if it is driven by an external neutron source). By performing this splitting, two separate meshes are used, which results in a considerable computing time saving. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Applying State-of-the-Art Tools for Safety-Optimized D and D - 17410

Decommissioning, Demolition and Disposal of 'hot' facilities (D3) is a relatively new science to the extent it has been part our public consciousness for ∼50-years. Due to the high hazard of uncontrolled exposure and the possibility of environmental release, the technologies applied to D3 have not embraced many of the recently developed engineering tools, especially those that leverage the digital and optical advances of the past 10-years. This summary paper provides an overview of how we are layering readily available technologies with sophisticated techniques to D3, ranging from agile program management to advanced modular construction to augmented reality. Using this approach, we are significantly improving safety and ALARA aspects while saving costs, optimizing schedules, maintaining quality and engaging the customer and the regulator in the D3 environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

An introduction to optimal power flow: Theory, formulation, and examples

The set of optimization problems in electric power systems engineering known collectively as Optimal Power Flow (OPF) is one of the most practically important and well-researched subfields of constrained nonlinear optimization. OPF has enjoyed a rich history of research, innovation, and publication since its debut five decades ago. Nevertheless, entry into OPF research is a daunting task for the uninitiated--both due to the sheer volume of literature and because OPF's ubiquity within the electric power systems community has led authors to assume a great deal of prior knowledge that readers unfamiliar with electric power systems may not possess. This article provides an introduction to OPF from an operations research perspective; it describes a complete and concise basis of knowledge for beginning OPF research. The discussion is tailored for the operations researcher who has experience with nonlinear optimization but little knowledge of electrical engineering. Topics covered include power systems modeling, the power flow equations, typical OPF formulations, and common OPF extensions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery

Conventional practices of siting all biomass preprocessing operations at the biorefinery is widely believed to be the most cost-effective solution for feedstock supply because of economies of scale. Yet, biomass preprocessing operations could be decentralized by moving the preprocessing operations to distributed biomass preprocessing centers, also known as “depots” located near biomass sources. We present a comparative case study with multiple biomass resources to analyze biorefinery feedstock supply logistics designs having distributed depots and a primary depot co-located with the biorefinery. A mixed-integer linear programming model was developed to simultaneously optimize feedstock sourcing decisions, and optimal preprocessing depot locations and size, utilizing biomass resources from agricultural residue, energy and municipal solid waste to meet carbohydrate specifications and feedstock demand for a biochemical conversion process. Findings from a case study in the US showed that a biorefinery could increase its feedstock supply draw area and supply volume by 57.3%, 177.4% respectively without increasing the feedstock delivered cost by adopting distributed depot-in the feedstock supply chain design. A distributed-depot-based supply chain can be more economical by selecting optimal mix of biomass resource, optimal siting and depot scales during feedstock supply chain design. The results from this study indicate that a biorefinery can utilize dynamic blending to meet the feedstock quality specifications as well as larger supply radius in the distributed depot-based supply chain design to access more available biomass to handle potential feedstock supply uncertainty.

09 BIOMASS FUELS↗
DOE OSTI2018

Optimal self-healing strategy for microgrid islanding

Renewable resource based microgrids provide reliable and cost-effective electricity with low carbon emissions. The flexibility of operating in grid-connected or islanded modes enables a microgrid to serve loads reliably. In the case of unexpected events happening to the main grid, the microgrid will isolate itself and operate in islanded mode to prevent any adversary impacts. The availability of renewable generation in the microgrid has significant impacts on the islanding strategy and different scenarios need to be considered. This study proposes a comprehensive microgrid self-healing strategy under different circumstances. The proposed strategy encompasses generation re-dispatch, network reconfiguration, and load shedding. The microgrid self-healing problem is formulated as a mixed-integer quadratic programming problem, which provides a globally optimal solution to facilitate smooth islanding of the microgrid. A modified Consortium for Electric Reliability Technology Solutions microgrid is used to conduct simulation under various scenarios. The simulation results demonstrate the efficiency of the proposed self-healing strategy in minimising costs of load shedding and generation with optimal switching actions.

optimal self-healing strategy↗
DOE OSTI2016

Strengthening the SDP Relaxation of AC Power Flows with Convex Envelopes, Bound Tightening, and Valid Inequalities

Here this work revisits the Semidefine Programming (SDP) relaxation of the AC power flow equations in light of recent results illustrating the benefits of bounds propagation, valid inequalities, and the Convex Quadratic (QC) relaxation. By integrating all of these results into the SDP model a new hybrid relaxation is proposed, which combines the benefits from all of these recent works. This strengthened SDP formulation is evaluated on 71 AC Optimal Power Flow test cases from the NESTA archive and is shown to have an optimality gap of less than 1% on 63 cases. This new hybrid relaxation closes 50% of the open cases considered, leaving only 8 for future investigation.

42 ENGINEERING↗
DOE OSTI2023

Optimal Wind Turbine Design for H2 Production

The Optimal Wind Turbine Design for Hydrogen Production work seeks to address the H2@Scale program's goal to "advance affordable hydrogen production" by optimizing the wind turbine design specifically for hydrogen (H2) production. The project identifies optimal wind turbine designs made specifically for hydrogen production to advance affordable green hydrogen production. The project also couples wind turbine, wind plant, solar plant, and electrolyzer models to predict hydrogen production from variable, renewable power sources.

electrolyzer↗
DOE OSTI2022

Resource distribution under spatiotemporal uncertainty of disease spread: Stochastic versus robust approaches

We consider the problem of optimizing locations of distribution centers (DCs) and plans for distributing resources such as test kits and vaccines, under spatiotemporal uncertainties of disease spread and demand for the resources. We aim to balance the operational cost (including costs of deploying facilities, shipping, and storage) and quality of service (reflected by demand coverage), while ensuring equity and fairness of resource distribution across multiple populations. We compare a sample-based stochastic programming (SP) approach with a distributionally robust optimization (DRO) approach using a moment-based ambiguity set. Numerical studies are conducted on instances of distributing COVID-19 vaccines in the United States and test kits, to compare SP and DRO models with a deterministic formulation using estimated demand and with the current resource distribution plans implemented in the US. We demonstrate the results over distinct phases of the pandemic to estimate the cost and speed of resource distribution depending on scale and coverage, and show the “demand-driven” properties of the SP and DRO solutions. Furthermore, our results further indicate that if the worst-case unmet demand is prioritized, then the DRO approach is preferred despite of its higher overall cost. Nevertheless, the SP approach can provide an intermediate plan under budgetary restrictions without significant compromises in demand coverage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

A Bound- and Equality-Constrained Quadratic Programming Method for Image Reconstruction

Image deblurring is modeled as an ill-posed, linear inverse problem and can be written in terms of an optimization problem. By adding bound and equality constraints and/or penalty terms to the objective function, the problem is regularized and a viable solution exists; however, there are few methods available for solving such constrained problems. Here we formulate two regularized solutions into constrained optimization problems and adapt an iterative augmented Lagrangian solver. Results are shown on synthetic data in one- and two-dimensions, as well as on a radiograph used to calibrate the transmission curve of a pulsed power X-ray source at a U.S. Department of Energy radiography facility.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Feasibility Study of Spectrophotometry to Support a Promethium Production Program at ORNL

Optical spectroscopy can be used to optimize analytical measurements for lanthanide elements and provide real-time feedback to help guide production operations. This study evaluates spectrophotometry for the determination of samarium (Sm 3+ ) and neodymium (Nd 3+ ) in aqueous and organic solutions at concentrations relevant to a promethium (Pm) program separation scheme. Detection limits approached 0.5 mM for Nd 3+ and 2 mM for Sm 3+ using Ocean Insight spectrophotometers. Additionally, Sm 3+ detection limits using laser fluorescence spectra for Sm 3+ approached single ppm (mg∙L -1 ) levels. An absorption spectrum containing Nd and Pm is also reported and discussed. This work demonstrates proofof-principle concepts for applying spectrophotometry to online monitoring applications in support of a future Pm production program.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Optimal Location of Radiation Therapy Centers With Respect to Geographic Access

Purpose: To develop a framework with which to evaluate locations of radiation therapy (RT) centers in a region based on geographic access. Methods and Materials: Patient records were obtained for all external beam radiation therapy started in 2011 for the province of British Columbia, Canada. Two metrics of geographic access were defined. The primary analysis was percentage of patients (coverage) within a 90-minute drive from an RT center (C90), and the secondary analysis was the average drive time (ADT) to an RT center. An integer programming model was developed to determine optimal center locations, catchment areas, and capacity required under different scenarios. Results: Records consisted of 11,096 courses of radiation corresponding to 161,616 fractions. Baseline geographic access was estimated at 102.5 minutes ADT (each way, per fraction) and 75.9% C90. Adding 2 and 3 new centers increased C90 to 88% and 92%, respectively, and decreased ADT by between 43% and 61%, respectively. A scenario in which RT was provided in every potential location that could support at least 1 fully utilized linear accelerator resulted in 35.3 minutes' ADT and 93.6% C90. Conclusions: The proposed framework and model provide a data-driven means to quantitatively evaluate alternative configurations of a regional RT system. Results suggest that the choice of location for future centers can significantly improve geographic access to RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Experimental Evaluation of the Fast-Neutron Passive Collar (FNPC) Performance (Interim Report)

This report represents a deliverable in the Safeguards Technology WBS # Project Title, 24.1.3.1, Task 3 (Report on laboratory-based performance testing of the FNPC). A new, simplified method for the verification of the 235 U mass in fresh LEU fuel assemblies that is relatively independent of burnable poison content is being developed. LWR fresh fuel is currently verified using the uranium neutron coincidence collar (UNCL), which relies on an AmLi source to induce fission in the 235 U. AmLi neutrons are slowed down in polyethylene, so the induced fission is primarily due to thermal neutrons. Burnable poisons, which are added to nuclear fuel assemblies to extend the lifetime of the fuel, absorb neutrons that would otherwise have induced fission in the fuel, thereby reducing the neutron count rate and thus the measured 235 U mass. To remove this bias factor a correction is applied based on the operator’s declared burnable poison content. The new technique uses 238 U spontaneous fission in LWR fresh fuel rods to self-interrogate the 235 U mass. The 238 U spontaneous fission neutrons have a hard neutron energy spectrum, which means that the technique is less sensitive to burnable poisons than the AmLi based systems. This project has continued the work done over the past two years to study this new technique using the optimized 3 He based fastneutron passive collar (FNPC). Fabrication of the FNPC has been completed and measurements are in progress using the LANL mockup PWR fuel assembly. Also, preliminary evaluations of advanced analysis techniques and unattended mode operation have been performed. In FY18, the 3 He tube based detector was compared with a 10 B sealed cell based detector for the same set of PWR fuel assemblies in the Rodeo-II program. The results were that the optimized 3 He detector had higher efficiency and less weight than the 10 B based system where both systems had about the same cost. Thus, the FY19 work continued exclusively with the 3 He based detector; although, either system had the potential for future applications. However, the high efficiency of the FPNC (~24%) is critical for precise measurements of the triples rate necessary in the multiplicity advanced analysis technique which can solve for the burnable poison content.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Lightweight Integrated Optical Sensor for Atmospheric Measurements on Mobile Platforms

The goal of the Phase I program was to develop a novel open path sensor platform technology based on integration of semiconductor waveguides with efficient optoelectronic components on a monolithic platform. The successful Phase I effort resulted in demonstration of a novel optical resonator structure based on semiconductor high contrast gratings (HCGs) that will enable implementation of an ultra-compact, low-power gas sensor suitable for use on mobile platforms. Extensive numerical modeling was performed to design a device optimized for measuring CO2 at a wavelength for which a laser was available for proof of concept. Devices were fabricated and tested to match the target wavelength, angle, and operating temperature. This demonstration is the first implementation of HCGs at the wavelengths of interest and shows the flexibility of the proposed architecture for gas sensing applications. The measured cavity Q was lower than anticipated due to fabrication process challenges. The PSI and UC Berkeley team has identified solutions to these challenges and will produce optimized devices in a Phase II program where a prototype sensor will be fabricated and tested.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Cost-optimal evaluation of centralized and distributed microgrid topologies considering voltage constraints

Optimal design of hybrid renewable mini-grids requires both economic and power quality considerations. Existing modeling approaches address these considerations via separate or loosely coupled models. Here, we extend REopt—a techno-economic optimization model developed at the National Renewable Energy Laboratory—to consider both within a single model. REopt formulates the design problem as a mixed-integer linear program that solves for a site's optimal technology mix, sizing, and operation to minimize life cycle cost. REopt has traditionally assumed a single node system. In the work presented here, we expand the REopt platform to consider multiple connected nodes with associated voltage constraints. In order to do this, we model power flow using a fixed-point linear approximation method. Additionally, we then use the model to explore design considerations of mini-grids in Sub-Saharan Africa. Specifically, we evaluate under what combinations of transmission line distance and capacity it is technically viable and economically preferable to build multiple isolated mini-grids versus an interconnected, centralized system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Ready for the Frontier: Preparing Applications for the World’s First Exascale System

Frontier, a supercomputer at the Oak Ridge Leadership Computing Facility (OLCF), debuted atop the Top500 list of the world’s most powerful supercomputers in June 2022 as the very first computer to produce exascale performance. Making sure scientific applications are optimized on this architecture is the critical link necessary to translate the newly available computational power into scientific insight and solutions. To that goal, the OLCF developed the Center for Accelerated Application Readiness (CAAR) program to ensure that a suite of highly optimized applications is ready for scientific runs at the onset of production operations for Frontier. This paper describes our experience in porting and optimizing such suite of applications in the OLCF’s CAAR program.

Budiardja, Reuben↗
DOE OSTI2022

Strategies for Optimizing WIP Investment in State Energy Offices

This report outlines strategies for Weatherization and Intergovernmental Programs Office (WIP) investment aimed at improving state energy office programs. The project was funded by WIP within the U.S. Department of Energy (DOE) office of Energy Efficiency and Renewable Energy (EERE). WIP aims "to enable strategic investments in energy efficiency and renewable energy technologies through the use of innovative practices across the United States in partnership with a wide range of stakeholders, including state and local organizations and community-based nonprofits." Across its programs, WIP has created thousands of jobs, maintains an investment ratio of 4.1 to 1, and increases U.S. economic output by 1.2 billion a year. This project was funded in the FY21 budget cycle and originally focused on improving WIP energy efficiency funding and programs. The project gathered information from various state energy offices to understand how WIP funding and processes can be optimized to improve state-level energy efficiency programs. We propose that the conclusions are also broadly applicable to weatherization and renewable energy deployment programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗