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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
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↗
DOE OSTI2021

Modeling the Strategic Behavior of an Active Distribution Network in the ISO Markets

With increasing integration of distributed energy resources (DERs), active distribution networks (ADNs) can actively participate in the electricity markets by dispatching their DERs, which can change the existing electricity market paradigm. It is essential to investigate the strategic behaviors of ADNs and their DER dispatch when they participate in the wholesale market as price-makers. This paper proposes a bi-level optimization model to study the strategic behavior of an ADN in both energy and reserve markets. The optimal scheduling of DERs in the ADN is modeled as the upper level problem and the joint energy and reserve market-clearing of the ISO is modeled as the lower-level problem. The two-level optimization models exchange bidding information and energy/reserve prices with each other. The proposed bi-Ievel optimization problem is converted to a mathematical programming with equilibrium constraints (MPEC) by using Karush-Kuhn Tucker (KKT) conditions and strong duality theory. Further, the MPEC problem is reformulated as a computationally-solvable mixed integer second order cone programming (MISOCP) model. The simulation results on an illustrative case demonstrate the impact of the strategic bidding of the ADN on the day-ahead energy and reserve market prices.

active distribution network↗
DOE OSTI2017

Stochastic optimization of GeantV code by use of genetic algorithms

GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) and handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. Here, the goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Exploring Enhanced Dominant Resource Fairness Using Linear Programming Calculated Weights

Maintaining resource fairness while achieving optimization for various performance metrics such as resource utilization, turnaround time and job latency is a well-known resource scheduling challenge in cloud computing. Despite the significant progress made with the introduction of dominant resource fairness by Ghodsi et al., which ensures major allocation properties such as sharing incentive, strategy-proofness, envy-freeness and Pareto efficiency to be achieved

Yan, Bo [Binghamton University]↗
DOE OSTI2015

Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost

This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2010

Optimization of Rhodium-Based Catalysts for Mixed Alcohol Synthesis -- 2009 Progress Report

Pacific Northwest National Laboratory (PNNL) has been conducting research for the United States Department of Energy, Energy Efficiency Renewable Energy, Biomass Program to investigate the feasibility of producing mixed alcohols from biomass-derived synthesis gas (syngas). This research has involved the screening of potential catalysts, and optimization of the more promising ones, using laboratory scale reactors. During 2009, the main goal of the testing program focused on optimizing selected supported catalysts containing rhodium (Rh) and manganese (Mn). Optimization involved examining different total concentrations and atomic ratios of Rh and Mn as well as that of the more promising promoters (Ir and Li) identified in the earlier screening studies. Evaluation of catalyst performance focused on attaining improvements with respect to the space-time-yield and converted carbon selectivity to C2+ oxygenates, with additional consideration given to the fraction of the oxygenates that were C2+ alcohols.

09 BIOMASS FUELS↗
DOE OSTI2015

Optimized Data Transfers Based on the OpenCL Event Management Mechanism

In standard OpenCL programming, hosts are supposed to control their compute devices. Since compute devices are dedicated to kernel computation, only hosts can execute several kinds of data transfers such as internode communication and file access. These data transfers require one host to simultaneously play two or more roles due to the need for collaboration between the host and devices. The codes for such data transfers are likely to be system-specific, resulting in low portability. Here, this article proposes an OpenCL extension that incorporates such data transfers into the OpenCL event management mechanism. Unlike the current OpenCL standard, the main thread running on the host is not blocked to serialize dependent operations. Hence, an application can easily use the opportunities to overlap parallel activities of hosts and compute devices. In addition, the implementation details of data transfers are hidden behind the extension, and application programmers can use the optimized data transfers without any tricky programming techniques. The evaluation results show that the proposed extension can use the optimized data transfer implementation and thereby increase the sustained data transfer performance by about 18% for a real application accessing a big data file.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Design, characterization and shape recovery behavior of 3D/4D printed shape memory polymers (SMPs)

Shape memory polymers (SMPs) represent a paradigm shift in material science, uniquely capable of undergoing reversible shape transformations triggered by external stimuli, positioning them as pivotal in developing next-generation biomedical devices, aerospace components, and adaptive structures. Extensive research has been done on SMPs with a major focus on high-temperature programming methods, which can limit energy efficiency and applicability with temperature-sensitive materials. Additionally, while various SMP blends have demonstrated great potential, limited work has been done on the suitability for 3D printing these materials, particularly under high-strain and ambient temperature programming conditions. In this study, a three-component optimized SMP composition was evaluated by 3D printing via the Material Extrusion (MEX) technique and investigating its ambient temperature-programming behavior at high strains. The SMP formulation studied was a tailored blend of thermoplastic polyurethane (TPU), polycaprolactone (PCL), and an octadecane diol-based copolymer (OBC) that exhibits robust shape memory behavior, high strain tolerance, and efficient force generation. Rigorous thermal, mechanical, and shape recovery analyses, along with optimized printing parameters and consistent shape recovery rates of up to 90%, were achieved under dynamic mechanical analysis (DMA), even under ambient programming conditions. This work demonstrates the SMP composition’s potential for adaptive, self-deployable systems with 4D printing characteristics ideal for bio-inspired structures and artificial muscle fibers.

Sudan, Kavish [University of Louisville, KY]↗
DOE OSTI2018

Optimal Control for Battery Storage Using Nonlinear Models

Battery storage system (BSS) becomes increasingly popular for grid applications due to the advance in battery and power electronics technologies as well as the growing need of flexibility and reserve from power systems with rapidly developed renewable generation. Successful assessment and deployment of BSS requires optimizing its operation and therefore maximizing the potential benefits. Although there exist studies that develop optimal control for evaluation or operational scheduling of BSS, modeling of charging/discharging operation and the corresponding impacts on state-of-charge (SOC) is over simplified in these methods. This paper develops an optimal control for BSS evaluation and operational scheduling using a general nonlinear model that expresses the change of SOC as a function of charging/discharging power and SOC level. The proposed method is compared with a typical existing method through a real-world energy storage evaluation project to show the significance of the proposed method.

battery, energy storage system, dynamic programmin↗
DOE OSTI2018

Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: A bi-level programming approach via real-time pricing

In order to coordinate the scheduling problem between an isolated microgrid (IMG) and electric vehicle battery swapping stations (BSSs) in multi-stakeholder scenarios, a new bi-level optimal scheduling model is proposed for promoting the participation of BSSs in regulating the IMG economic operation. In this model, the upper-level sub-problem is formulated to minimize the IMG net costs, while the lower-level aims to maximize the profits of the BSS under real-time pricing environments determined by demand responses in the upper-level decision. To solve the model, a hybrid algorithm, called JAYA-BBA, is put forward by combining a real/integer-coded JAYA algorithm and the branch and bound algorithm (BBA), in which the JAYA and BBA are respectively employed to address the upper- and lower- level sub-problems, and the bi-level model is eventually solved through alternate iterations between the two levels. The simulation results on a microgrid test system verify the effectiveness and superiority of the presented approach.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Design Considerations of a Coordinative Demand Charge Mitigation Strategy

This paper presents a coordinative demand charge mitigation (DCM) strategy for reducing electricity consumption during system peak periods. Available DCM resources include batteries, diesel generators, controllable loads, and conservation voltage reduction. All resources are directly controlled by load serving entities. A mixed integer linear programming based energy management algorithm is developed to optimally coordinate of DCM resources considering the load payback effect. To better capture system peak periods, two different kinds of load forecast are used: the day-ahead load forecast and the peak-hour probability forecast. Five DCM strategies are compared for reconciling the discrepancy between the two forecasting results. The DCM strategies are tested using actual utility data. Simulation results show that the proposed algorithm can effectively mitigate the demand charge while preventing the system peak from being shifted to the payback hours. We also identify the diminishing return effect, which can help load serving entities optimize the size of their DCM resources.

Hu, Rongxing↗
DOE OSTI2017

Level set topology optimization of structural problems with interface cohesion

Summary This paper presents a finite element topology optimization framework for the design of two‐phase structural systems considering contact and cohesion phenomena along the interface. The geometry of the material interface is described by an explicit level set method, and the structural response is predicted by the extended finite element method. In this work, the interface condition is described by a bilinear cohesive zone model on the basis of the traction‐separation constitutive relation. The non‐penetration condition in the presence of compressive interface forces is enforced by a stabilized Lagrange multiplier method. The mechanical model assumes a linear elastic isotropic material, infinitesimal strain theory, and a quasi‐static response. The optimization problem is solved by a nonlinear programming method, and the design sensitivities are computed by the adjoint method. The performance of the presented method is evaluated by 2D and 3D numerical examples. The results obtained from topology optimization reveal distinct design characteristics for the various interface phenomena considered. In addition, 3D examples demonstrate optimal geometries that cannot be fully captured by reduced dimensionality. The optimization framework presented is limited to two‐phase structural systems where the material interface is coincident in the undeformed configuration, and to structural responses that remain valid considering small strain kinematics. Copyright © 2017 John Wiley & Sons, Ltd.

Behrou, Reza↗