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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The High Capacity Type B Waste Transport Cask to Serve Dismantling Project - 18344

The United States have already announced around 20 reactor shutdown and many more in the next 10 year. Financial constraints on plant operators and the low cost of fossil energy contribute to accelerate the shutdown of additional reactors. The industry has been gaining experience with reactor dismantling and is continuously trying to improve the cost efficiency of the upcoming projects. To do so, larger and more capacitive transport casks are needed to transport increasing volume of Low Level Waste (LLW) at a more attractive cost. Waste disposal is also a major cost element in a dismantling project. Consequently, the capacity to segment, package and transport the waste in the most optimized configuration will result in significant cost savings. While for LLW, the constraints for package requirements are limited, activated waste resulting mainly from reactor vessel and vessel internals segmentation require additional shielding to meet disposal and transportation regulations. The key element to succeed is the availability on the market of a licensed type B transport package with a larger payload that allows at the same time an optimization of the waste segmentation. AREVA TN has designed and licensed versatile high capacity type B casks for the transport of spent fuel canisters as part of the NUHOMS{sup R} system that can also be used to transport radioactive waste. While it will take a few more years to transport spent fuel to a consolidated interim storage facility and even more to a repository, the type B casks can be used to transport activated LLW from dismantled reactors to disposal sites. A first of a kind project will be performed with AREVA's partner NorthStar at Vermont Yankee Nuclear Power Plant. AREVA's team will perform the reactor segmentation and package the material into an AREVA's large capacity type B cask. This unmatched cask capacity is expected to significantly decrease the LLW disposal costs, as well as the onsite operations costs, while optimizing the schedule. The package will be transported by rail to waste disposal facilities. This paper will present the main characteristics of the package, provide an update of the overall schedule, and explain the innovations that contribute to simpler and more cost effective transport and operation. Finally, it will emphasize the benefits of using larger type B casks for immediate and future transportation needs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Development of an Alternative Approach to Demonstrating Environmental Performance in the UK - 19354

European basic safety standards require that exposure of humans to the potentially harmful effects of ionising radiation are optimised so that they are as low as reasonably achievable, taking account of economic and societal factors. In the United Kingdom the responsibility for ensuring that exposures to humans are optimised is split between two regulatory functions. The Office of Nuclear Regulation regulates exposures to workers in all scenarios and to members of the public in the event of an accident. Environmental regulators in each of the four nations comprising the United Kingdom regulate exposures to members of the public from normal operations. Since the early 1990's, all permissions granted to nuclear sites in the UK for the discharge/disposal of radioactive waste to the environment have contained conditions requiring holders to demonstrate that they minimise the generation of radioactive waste, apply appropriate abatement and discharge/dispose of it in a way that minimises impacts on members of the public and the environment. For many years, the industry standard for providing this demonstration, which was heavily influenced by regulatory expectations and feedback, was to undertake one or a series of multi-attribute decision assessments (MADA). Wood's team of environmental specialists has been involved in undertaking such MADA studies for many years. Since the mid-2000's, our team has become increasingly aware of some of the limitations of undertaking MADA to demonstrate environmental performance for large scale new nuclear build projects and, in particular, the next generation of new nuclear power stations that are being planned and implemented in the UK. We have collaborated with the vendors of reactor technologies, the prospective/owner operators of new nuclear power stations and the developers of new facilities on existing sites to develop an alternative approach to demonstrating environmental performance. Our alternative approach comprises three main pillars which are summarised as: - Evolution - benefit from progressive improvements, operational experience and recent permitting activities. Our alternative approach uses the claim, argument, evidence approach which is commonly used for nuclear safety cases and which allows us to 'tell the story' of how environmental performance has been achieved. We have successfully deployed this approach for all new nuclear power stations proposed in the UK. - Integration - ensure that optimisation is integrated into the project programme and forms part of the 'big picture'. Our alternative approach allows environmental performance to be managed better throughout the life cycle of the project and ensures that our outputs are 'living' documents and do not 'sit on the shelf'. We have successfully demonstrated how this can be applied during rationalisation of major schemes and significant design changes on nuclear new build projects. - Opportunity - identify the best time to deliver elements of the programme. Our alternative approach aims to minimise the overall time, trouble and costs associated with demonstrating environmental performance by ensuring that decisions are made at the time when they offer greatest benefit and by minimising unnecessary rework. Our advice has helped to reduce the project costs and minimise delays associated with regulatory queries and interventions. This paper describes the journey that we have taken with our clients in developing our alternative approach to demonstrating environmental performance. We explain the UK regulatory context and explore the need for change. We present a number of case studies related to new nuclear power stations and other new facilities on existing nuclear sites that demonstrate the successful application of our alternative approach. We provide examples of how we have successfully implemented the outputs of our alternative approach into project and corporate management arrangements. Finally, we examine feedback from clients, regulators and other interested parties to propose future refinements. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Implementing computer-based procedures: thinking outside the paper margins - 236

In the past year there has been increased interest from the nuclear industry in adopting the use of electronic work packages and computer-based procedures (CBPs) in the field. The goal is to incorporate the use of technology in order to meet the Nuclear Promise requirements of reducing costs, and improving efficiency and decreasing human error rates in plant operations. Researchers, together with the nuclear industry, have been investigating the benefits of an electronic work package system and specifically CBPs would have over current paper-based procedure practices. There are several classifications of CBPs ranging from a straight copy of the paper-based procedure in PDF format to a more intelligent dynamic CBP. A CBP system offers a vast variety of potential improvements, such as context driven job aids, integrated human performance tools (e.g., place-keeping and correct component verification), and dynamic step presentation. However, the implementation of a CBP system does not automatically improve the quality of procedures. Utilities should review, standardize format and update current procedure content before transitioning to a computerized process. Implementation of a CBP system can be a time to break out of traditional procedure writing processes and create new processes and procedures that take advantage of the capabilities a CBP system. This paper summarizes INL research findings related to challenges with implementing a CBP system and provides suggestions to take into consideration. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Data-Driven Unit Commitment Refinement - a Scalable Approach for Complex Modern Power Grids

Integration of renewable generation, which is often intermittent and decentralized, substantially increases the stochasticity and complexity of power grid operations. Future power systems planning will require significant computational capability to evaluate balance between demand and supply under varying conditions, both temporally and spatially. The standard approach for generation unit commitment is to use mixed-integer linear programming to find the optimal generation schedule considering ramping and generator constraints. In the future grid this poses computational scalability challenges because generation and demand are not known with certainty due to stochasticity in weather and complexity of the grid. To address this challenge, we present a data-driven unit commitment approach that can efficiently include stochastic weather impacts and contingency considerations to improve unit commitment. Our approach uses graph-based data analytics techniques on solutions to the security constrained (and possibly stochastic) economic dispatch problem to identify potential improvements to a given unit commitment. Recent breakthroughs in fully-parallel stochastic economic dispatch software allow this approach to be scalably deployed. Simulations on synthetic South Carolina and Texas grids show this method can improve grid reliability with security constraints over a set of contingencies, while also meaningfully lowering total generation cost.

Holt, Timothy↗
DOE OSTI2012

RF optimization and analysis of the 805-MHz cavity for the MuCool program using ACE3P

An 805 MHz pillbox cavity tested at Fermilab's MTA facility showed significant degradation in gradient when operated in a several Tesla solenoidal magnetic field. We have used the advanced ACE3P simulation codes developed at SLAC to study the cavity dark current and multipacting characteristics to gain more insight into the gradient limitations. We also checked whether there is an optimal cavity length that minimizes the dark current impact energy. Finally, we have improved on the cavity design, significantly lowering the fields outside the beam area. These and other results are presented in this paper.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗
DOE OSTI2022

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks: Preprint

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous–enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗
DOE OSTI2018

Chance-Constrained Day-Ahead Hourly Scheduling in Distribution System Operation

This paper aims to propose a two-step approach for day-ahead hourly scheduling in a distribution system operation, which contains two operation costs, the operation cost at substation level and feeder level. In the first step, the objective is to minimize the electric power purchase from the day-ahead market with the stochastic optimization. The historical data of day-ahead hourly electric power consumption is used to provide the forecast results with the forecasting error, which is presented by a chance constraint and formulated into a deterministic form by Gaussian mixture model (GMM). In the second step, the objective is to minimize the system loss. Considering the nonconvexity of the three-phase balanced AC optimal power flow problem in distribution systems, the second-order cone program (SOCP) is used to relax the problem. Then, a distributed optimization approach is built based on the alternating direction method of multiplier (ADMM). The results shows that the validity and effectiveness method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Development Optimization and Uncertainty Analysis Methods for Oil and Gas Reservoirs

Uncertainty complicates the development optimization of oil and gas exploration and production projects, but methods have been devised to analyze uncertainty and its impact on optimal decision-making. This paper compares two methods for development optimization and uncertainty analysis: Monte Carlo (MC) simulation and stochastic programming. Two example problems for a gas field development and an oilfield development are solved and discussed to elaborate the advantages and disadvantages of each method. Development optimization involves decisions regarding the configuration of initial capital investment and subsequent operational decisions. Uncertainty analysis involves the quantification of the impact of uncertain parameters on the optimum design concept. The gas field development problem is designed to highlight the differences in the implementation of the two methods and to show that both methods yield the exact same optimum design. The results show that both MC optimization and stochastic programming provide unique benefits, and that the choice of method depends on the goal of the analysis. While the MC method generates more useful information, along with the optimum design configuration, the stochastic programming method is more computationally efficient in determining the optimal solution. Reservoirs comprise multiple compartments and layers with multiphase flow of oil, water, and gas. We present a workflow for development optimization under uncertainty for these reservoirs, and solve an example on the design optimization of a multicompartment, multilayer oilfield development.

02 PETROLEUM↗
DOE OSTI2016

Simit: A Language for Physical Simulation

With existing programming tools, writing high-performance simulation code is labor intensive and requires sacrificing readability and portability. Here, the alternative is to prototype simulations in a high-level language like Matlab, thereby sacrificing performance. The Matlab programming model naturally describes the behavior of an entire physical system using the language of linear algebra. However, simulations also manipulate individual geometric elements, which are best represented using linked data structures like meshes. Translating between the linked data structures and linear algebra comes at significant cost, both to the programmer and to the machine. High-performance implementations avoid the cost by rephrasing the computation in terms of linked or index data structures, leaving the code complicated and monolithic, often increasing its size by an order of magnitude. In this article, we present Simit, a new language for physical simulations that lets the programmer view the system both as a linked data structure in the form of a hypergraph and as a set of global vectors, matrices, and tensors depending on what is convenient at any given time. Simit provides a novel assembly construct that makes it conceptually easy and computationally efficient to move between the two abstractions. Using the information provided by the assembly construct, the compiler generates efficient in-place computation on the graph. We demonstrate that Simit is easy to use: a Simit program is typically shorter than a Matlab program; that it is high performance: a Simit program running sequentially on a CPU performs comparably to hand-optimized simulations; and that it is portable: Simit programs can be compiled for GPUs with no change to the program, delivering 4 to 20× speedups over our optimized CPU code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

SU-E-T-234: Modulated Photon Radiotherapy (XMRT):The Impact of Incorporating Energy Modulation Into Intensity Modulated Radiotherapy (IMRT) Optimization

Purpose: To develop a new radiotherapy plan optimization technique that, for a given organ geometry, will find the optimal photon beam energies and fluences to produce a desirable dose distribution. This new modulated (both in energy and fluence) photon radiotherapy (XMRT) was compared with intensity modulated radiotherapy (IMRT) for a simple organ geometry. Methods: The XMRT optimization was formulated using a linear programming approach where the objective function is the mean dose to the healthy organs and dose-point constraints were assigned to each organ of interest. The organ geometry consisted of a target, two organs at risk (OARs), and normal tissue. A seven-equispaced-coplanar beam arrangement was used. For conventional IMRT, only 6 MV beams were available, while XMRT was optimized using 6 and 18 MV beams. A prescribed dose (PD) of 72 GY was assigned to the target, with upper and lower bounds of 110% and 95% of the PD, respectively. Both OARs were assigned a maximum dose of 64 Gy, while the normal tissue was assigned a maximum dose of 66 Gy. A numerical solver, Gurobi, generated solutions for the XMRT and IMRT problems. The dose-volume histograms from IMRT and XMRT solutions were compared. Results: The maximum, minimum, mean, and homogeneity of the dose to the target were comparable between IMRT and XMRT. Though IMRT had improved dose conformity relative to XMRT, XMRT reduced the mean dose to both OARs by more than 1 Gy. For normal tissue, an increase of 5 Gy in mean dose and 27 percent in integral dose was seen for IMRT relative to XMRT. Conclusion: This work demonstrates the benefits of simultaneously modulating photon beam energy and fluence using our XMRT approach in a given phantom geometry. While target coverage was comparable, dose to healthy structures was reduced using XMRT.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

Impulsive Control for Continuous-Time Markov Decision Processes: A Linear Programming Approach

In this paper, we investigate an optimization problem for continuous-time Markov decision processes with both impulsive and continuous controls. We consider the so-called constrained problem where the objective of the controller is to minimize a total expected discounted optimality criterion associated with a cost rate function while keeping other performance criteria of the same form, but associated with different cost rate functions, below some given bounds. Our model allows multiple impulses at the same time moment. The main objective of this work is to study the associated linear program defined on a space of measures including the occupation measures of the controlled process and to provide sufficient conditions to ensure the existence of an optimal control.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A novel method for co-optimizing battery sizing and charging strategy of battery electric bus fleets: An application to the city of Paris

Battery-electric buses (BEBs) are a promising technology for replacing diesel buses and reducing their environmental burden. However, their charging process can take several hours, depending on the charging technique and strategy, making them susceptible to schedule disruptions. Furthermore, the selection of the charging strategy and battery size can increase the total capital investment and operational expenses of a BEB fleet, which is a major obstacle to its adoption. Therefore, to minimize the total cost of ownership (TCO) and prevent schedule disruptions, it is essential to establish a well-defined approach to determine an appropriate battery size and charging strategy for BEB fleets. This paper presents a method for reducing the TCO of BEB by determining the optimal battery size and charging strategy for each bus while satisfying operating constraints. The method involves a two-step optimization algorithm that uses Dynamic Programming and Genetic Algorithm. Further, the study applies this approach to the bus fleet serving line 21 in Paris and generates the optimal battery sizing, charging strategy, and required charging infrastructure. The results indicate that 100 kWh batteries offer the best trade-off between capital and operational expenditure for the fleet deployment if used with 65–85 kW chargers at bus terminals.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Improving Mathematical Exposition of an Industrial-Scale Linear Program

Industrial-scale models require considerable setup time; hence, once built, they are used in myriad ways to consider closely related cases. In practice, the code for these models frequently evolves without appropriate notational choices, largely as a result of the lengthy development time of, and the number of individuals contributing to, their formulation. This leads to inefficiencies and obfuscates model structures that might be leveraged to expedite solutions. In this paper, we advocate for an emerging literature on model formulation “best practices” and present the reformulation of a widely used industrial-scale linear program. The efficient mathematical expression of this linear program, used to plan capacity expansion in the energy sector, allows for greater transparency of model structures and enhanced ability to identify computational performance improvements, as well as a lucid interpretation of its solutions. This type of formulation is employed in several mathematical programming courses at our university as an example of the advantages of best practices; the model more broadly is used widely to inform policy in the U.S. energy sector.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Next-Generation Solvers for Mixed-Integer Nonlinear Programs: Structure, Search, and Implementation (Final Report)

The mathematical modeling of systems often requires the use of both nonlinear and discrete components. Problems involving both discrete and nonlinear components are known as mixed-integer nonlinear programs (MINLPs) and are among the most challenging computational optimization problems. This research project added to the understanding of this area by making a number of fundamental advances. First, the work demonstrated many novel, strong, tractable relaxations designed to deal with non-convexities arising in mathematical formulation. Second, the research implemented the ideas in software that is available to the public. Finally, the work demonstrated the importance of these ideas on practical applications and disseminated the work through scholarly journals, survey publications, and conference presentations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Convex quadratic relaxations for mixed-integer nonlinear programs in power systems

Here, this paper presents a set of new convex quadratic relaxations for nonlinear and mixed-integer nonlinear programs arising in power systems. The considered models are motivated by hybrid discrete/continuous applications where existing approximations do not provide optimality guarantees. The new relaxations offer computational efficiency along with minimal optimality gaps, providing an interesting alternative to state-of-the-art semidefinite programming relaxations. Finally, three case studies in optimal power flow, optimal transmission switching and capacitor placement demonstrate the benefits of the new relaxations.

42 ENGINEERING↗
DOE OSTI2020

The Heuristic Dynamic Programming Approach in Boost Converters

In this study, a heuristic dynamic programming controller is proposed to control a boost converter. Conventional controllers such as proportional-integral-derivative (PID) or proportional-integral (PI) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller during the start-up, the load change, or the input voltage variation is not optimal since the system model changes by varying the operating point. The heuristic dynamic programming controller optimally controls the boost converter by following the approximate dynamic programming. The advantage of the HDP is that the neural network-based characteristic of the proposed controller enables boost converters to easily cope with large disturbances. An HDP with a well-trained critic and action networks can perform as an optimal controller for the boost converter. To compare the effectiveness of the traditional PI-based and the HDP boost converter, the simulation results are provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

On the robust optimization to the uncertain vaccination strategy problem

In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.

62 RADIOLOGY AND NUCLEAR MEDICINE↗