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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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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Electrochemical Salt Wasteform Development: A Review of Salt Treatment and Immobilization Options

Electrochemical reprocessing, also referred to as pyroprocessing, is a technique for recycling actinides from used nuclear fuel (UNF) to produce fuel for future reactors. Here, UNF is dissolved in a molten salt (e.g., LiCl-KCl eutectic) within an electrorefiner. After UNF dissolution, fission products are released into the electrolyte salt and converted to chlorides. This paper discusses wasteform options for processing the base electrolyte salt with the fission product salts as well as just the rare-earth fission products (as RECl 3 , REOCl, or REO x ) with the intent of finding optimal methods for reducing total waste salt volumes or partitioning the salt for alternate wasteform options. Furthermore, two of the more detailed partitioning options discussed herein include halide removal from the salt (dehalogenation), which accounts for more than half of the salt on a molar basis, and RE fission product removal for wasteforms with high-RE loadings. Wasteform properties are compared with emphasis on wasteform volume starting from a given amount of (1) total salt cations or (2) RE cations. Comparisons are also made of wasteform chemical durabilities, with the data available from like testing methods. A main conclusion from this work is the justification of subsequent salt processing after electrorefiner operations for achieving significant wasteform volume reduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Porting Classical Approaches for Quantum Simulations to Quantum Computers

Simulating quantum many-body systems is one of the most promising problems in which we might anticipate that quantum computers should show quantum advantage. Unfortunately, there is still a gap between this promise and actual practice. New quantum algorithms need to be developed and the current quantum algorithms have various difficulties - e.g efficient state preparation - which must be overcome and improved upon. In many cases, classical approaches need to be ported over to quantum devices. In this project we have developed a suite of new quantum algorithms which makes progress in this regard. We developed a new optimization scheme for variational quantum eigensolvers, UBOS, which mitigates problems with local minimas and barren plateaus while improving convergence to the ground state by an order of magnitude. We developed a new way to utilize qubitization to find ground states of nearly frustration-free Hamiltonians faster than all previous methods. We developed a series of state preparation techniques which helps initialize parameterized quantum circuits into reasonable starting points on which quantum algorithms are then applied. In addition to the development of novel algorithms, it is critical to have classical simulation techniques for approximately simulating quantum circuits which can be used to benchmark and understand quantum algorithms. Toward that end, we developed a novel POVM formalism to simulate quantum circuits as well as exemplify the massive parallelization of tensor network methodologies. Finally, we developed physical understanding of entanglement phase transitions such as many-body localization and random tensor networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2005

Distributed Adaptive Control: Beyond Single-Instant, Discrete Variables

In extensive form noncooperative game theory, at each instant t, each agent i sets its state x, independently of the other agents, by sampling an associated distribution, q(sub i)(x(sub i)). The coupling between the agents arises in the joint evolution of those distributions. Distributed control problems can be cast the same way. In those problems the system designer sets aspects of the joint evolution of the distributions to try to optimize the goal for the overall system. Now information theory tells us what the separate q(sub i) of the agents are most likely to be if the system were to have a particular expected value of the objective function G(x(sub 1),x(sub 2), ...). So one can view the job of the system designer as speeding an iterative process. Each step of that process starts with a specified value of E(G), and the convergence of the q(sub i) to the most likely set of distributions consistent with that value. After this the target value for E(sub q)(G) is lowered, and then the process repeats. Previous work has elaborated many schemes for implementing this process when the underlying variables x(sub i) all have a finite number of possible values and G does not extend to multiple instants in time. That work also is based on a fixed mapping from agents to control devices, so that the the statistical independence of the agents' moves means independence of the device states. This paper also extends that work to relax all of these restrictions. This extends the applicability of that work to include continuous spaces and Reinforcement Learning. This paper also elaborates how some of that earlier work can be viewed as a first-principles justification of evolution-based search algorithms.

Wolpert, David H.↗

DOE OSTI2025

Methods and Tools To Assess Robustness of Nuclear Plant Outages

Refueling outages are one of the most challenging phases in a nuclear power plant (NPP) operating cycle. Refueling outages are extremely costly for an NPP due to the large amount of required resources and because of lost revenue due to plant being off the grid. Outage durations have steadily decreased across the industry over that last few decades primarily due to improved planning and coordination, but there are still many plants that struggle to meet the performance metrics accomplished by other utilities. Schedule resilience is one of the issues. NPP outages require scheduling thousands of activities within 30 days on average. Despite detailed planning, once the outage starts, numerous emergent issues typically appear along with schedule delays requiring continuous replanning and adjustment. When schedule disruption occurs during an outage, plant staff make urgent efforts to recover but are often not able to maintain the planned outage duration. These outage delays can cost a utility several million dollars per day. Tools that could help outage schedulers create a more resilient schedule and allow them to optimally reschedule emergent work could significantly reduce outage delays. One key aspect of creating a resilient schedule is to have accurate estimates for activity duration. Another important outage scheduling capability is the ability to schedule emergent work with minimal disruption. This paper focuses on developing tools and methods to support NPPs with outage schedule optimization and it describes the initial development of tools to support outage management that leverage computational and machine learning methods.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Piecewise linear approximation with minimum number of linear segments and minimum error: A fast approach to tighten and warm start the hierarchical mixed integer formulation

In several areas of economics and engineering, it is often necessary to fit discrete data points or approximate nonlinear functions with continuous functions. Piecewise linear (PWL) functions are a convenient way to achieve this. PWL functions can be modeled in mathematical problems using only linear and integer variables. Moreover, there is a computational benefit in using PWL functions that have the least possible number of segments. This work proposes a novel hierarchical mixed integer linear programming (MILP) formulation that identifies a continuous PWL approximation with minimum number of linear segments for a given target maximum error. The proposed MILP formulation also identifies the solution with the least maximum error among the solutions with minimum number of segments. Then, this work proposes a fast iterative algorithm that identifies non necessarily continuous PWL approximations by solving O(S log N) linear programming (LP) problems, where N is the number of data points and S is the minimum number of segments in the non necessarily continuous case. This work demonstrates that tight bounds for the MILP problem can be derived from these approximations. Next, a fast algorithm is introduced to transform a non necessarily continuous PWL approximation into a continuous one. Finally, the tight bounds and the continuous PWL approximations are used to tighten and warm start the MILP problem. The tightened formulation is shown in experimental results to be more efficient, especially for large data sets, with a solution time that is up to two orders of magnitude less than the existing literature.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

GPU Acceleration of Large-Scale Full-Frequency GW Calculations

Many-body perturbation theory is a powerful method to simulate electronic excitations in molecules and materials starting from the output of density functional theory calculations. By implementing the theory efficiently so as to run at scale on the latest leadership high-performance computing systems it is possible to extend the scope of GW calculations. Here, we present a GPU acceleration study of the full-frequency GW method as implemented in the WEST code. Excellent performance is achieved through the use of (i) optimized GPU libraries, e.g., cuFFT and cuBLAS, (ii) a hierarchical parallelization strategy that minimizes CPU-CPU, CPU-GPU, and GPU-GPU data transfer operations, (iii) nonblocking MPI communications that overlap with GPU computations, and (iv) mixed precision in selected portions of the code. A series of performance benchmarks has been carried out on leadership high-performance computing systems, showing a substantial speedup of the GPU-accelerated version of WEST with respect to its CPU version. Good strong and weak scaling is demonstrated using up to 25 920 GPUs. Finally, we showcase the capability of the GPU version of WEST for large-scale, full-frequency GW calculations of realistic systems, e.g., a nanostructure, an interface, and a defect, comprising up to 10 368 valence electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Switch Opening and Exchange Method for Stochastic Distribution Network Reconfiguration

The purpose of distribution network reconfiguration (DNR) is to determine the optimal topology of an electricity distribution network, which is an efficient measure to reduce network power losses. Electricity load demand and photovoltaic (PV) output are uncertain and vary with time of day, and will affect the optimal network topology. Single-hour deterministic DNR is incapable of handling this uncertainty and variability. Therefore, this paper proposes to solve a multi-hour stochastic DNR (SDNR). Existing solution methods for DNR are either inaccurate or excessively time-consuming, and are therefore incapable of solving multi-hour SDNRs for large distribution networks. In this regard, a switch opening and exchange (SOE) method is proposed. Starting from a looped network with all switches closed, the SOE consists of three steps. The first step is to sequentially open the switches until all of the loops are opened. The second and third steps modify the status of branches obtained in the first step to obtain better radial topologies. Five test systems are used to validate the accuracy and fast solution speed of the SOE and the superiority of multi-hour SDNR over single-hour deterministic DNR.

distribution network reconfiguration↗

NASA NTRS1982

An on-board near-optimal climb-dash energy management

On-board real time flight control is studied in order to develop algorithms which are simple enough to be used in practice, for a variety of missions involving three dimensional flight. The intercept mission in symmetric flight is emphasized. Extensive computation is required on the ground prior to the mission but the ensuing on-board exploitation is extremely simple. The scheme takes advantage of the boundary layer structure common in singular perturbations, arising with the multiple time scales appropriate to aircraft dynamics. Energy modelling of aircraft is used as the starting point for the analysis. In the symmetric case, a nominal path is generated which fairs into the dash or cruise state. Feedback coefficients are found as functions of the remaining energy to go (dash energy less current energy) along the nominal path.

Weston, A. R.↗

NASA NTRS1983

On-board near-optimal climb-dash energy management

Weston, A. R.↗

NASA NTRS2014

Flexural Fillet Geometry Optimization for Design of Force Transducers Used in Aeronautics Testing

Force transducer designs used in the ground testing aeronautics community have seen minimal change over the last few decades. With increased focus on data quality and long- term performance capabilities over the life of these instruments, it is critical to investigate new methods that improve these designs. One area of focus in the past few years at NASA has been on the design of the exural elements of traditional force balance transducers. Many of the heritage balances that have been heavily used over the last few decades have started to develop fatigue cracks. The recent focus on the exural design of traditional single-piece force balances revolves around the design of these elements such that stress concentrations are minimized, with the overall goal of increasing the fatigue life of the balance. Recent research in the area of using conic shaped llets in the highly stressed regions of traditional force balances will be discussed, with preliminary numerical and experimental data results. A case study will be presented which discusses integration of this knowledge into a new high-capacity semi-span force balance

Lynn, Keith C.↗

DOE OSTI2024

Mitigating Green's function Monte Carlo signal-to-noise problems using contour deformations

The Green's function Monte Carlo (GFMC) method provides accurate solutions to the nuclear many-body problem and predicts properties of light nuclei starting from realistic two- and three-body interactions. Controlling the GFMC fermion sign problem is crucial, as the signal-to-noise ratio decreases exponentially with imaginary time, requiring significant computing resources. Inspired by similar scenarios in lattice quantum field theory and spin systems, in this work, we employ integration contour deformations to improve the GFMC signal-to-noise ratio. Machine learning techniques are used to select optimal contours with minimal variance from parametrized families of deformations. As a proof of principle, we consider the deuteron binding energies and Euclidean density response functions. Here, we only observe mild signal-to-noise improvement for the binding energy case. On the other hand, we achieve an order of magnitude reduction of the variance for Euclidean density response functions, paving the way for computing electron- and neutrino-nucleus cross sections of larger nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1985

Thin-film module circuit design: Practical and reliability aspects

This paper will address several aspects of the design and construction of submodules based on thin film amorphous silicon (a-Si) p i n solar cells. Starting from presently attainable single cell characteristics, and a realistic set of specifications, practical module designs are discussed from the viewpoints of efficient designs, the fabrication requirements, and reliability concerns. The examples center mostly on series interconnected modules of the superstrate type with detailed discussions of each portion of the structure in relation to its influence on module efficiency. Emphasis is placed on engineering topics such as: area coverage, optimal geometries, and cost and reliability. Practical constraints on achieving optimal designs, along with some examples of potential pitfalls in the manufacture and subsequent performance of a-Si modules are discussed.

Daiello, R. V.↗

NASA NTRS2016

Development of a Magneto-Resistive Angular Position Sensor for Space Mechanisms

Magnetic microsystems in the form of magneto-resistive (MR) sensors are firmly established in automobiles and industrial applications. They are used to measure travel, angle, electrical current, or magnetic fields. MR technology opens up new sensor possibilities in space applications and can be an enabling technology for optimal performance, high robustness and long lifetime at reasonable costs. In some science missions, the technology is already applied, however, the designs are proprietary and case specific, for instance in case of the angular sensors used for JPL/NASA's Mars rover Curiosity [1]. Since 2013 HTS GmbH and Sensitec GmbH have teamed up to develop and qualify a standardized yet flexible to use MR angular sensor for space mechanisms. Starting with a first assessment study and market survey performed under ESA contract, a very strong industry interest in novel, contactless position measurement means was found. Currently a detailed and comprehensive development program is being performed by HTS and Sensitec. The objective of this program is to advance the sensor design up to Engineering Qualification Model level and to perform qualification testing for a representative space application. The paper briefly reviews the basics of magneto-resistive effects and possible sensor applications and describes the key benefits of MR angular sensors with reference to currently operational industrial and space applications. The key applications and specification are presented and the preliminary baseline mechanical and electrical design will be discussed. An outlook on the upcoming development and test stages as well as the qualification program will be provided.

Hahn, Robert↗

NASA NTRSDate not supplied

Electric Sail Design Sensitivities

Electric Sails (E-Sails) are a promising propulsion technology that seek to enable high characteristic propellentless acceleration for spacecraft to reach distant and/or difficult to reach orbits such as rapid transit to heliopause. The E-Sail system exchanges momentum by using positively charged electrostatic tethers to repel solar wind photons to push it through space. This concept was first theorized by Pekka Janhunen in 2004 with further developments occurring including a NASA Innovative Advanced Concepts Phase 1 and Phase 2 hosted out of NASA’s Marshall Space Flight Center (MSFC). These developments led to further maturation of the overall system, and this paper is designed to help identify different design sensitivities of an integrated Electric Sail system. To approach this, a small team at MSFC took an in-house developed three degrees of freedom (3DoF) simulation tool and a trajectory modelling tool to look at different design parameters and to determine a potential ideal E-Sail configuration. An E-Sail system has different design architectures including a barbell design, hub and spoke design, and a potential hybrid solution. The barbell design features two equally massed satellites that spin around a central point in the tether system. The hub and spoke design features a large central spacecraft with small end spacecraft to aid in formation control of the overall E-Sail system. Leveraging elements from both the hub and spoke, and barbell design, a hybrid option exists where one could have a larger central mass and one or two tethers extended to a smaller end mass [2]. In summary, the hub and spoke design is the ideal configuration for E-Sail with tethers spanning kilometers to achieve the designed design characteristic acceleration of at least one mm/s2 with this architecture being the focus of this study. Different key design parameters were varied as part of this study. These parameters include the total number of tethers, the length of the tethers, spin rate, relative spacecraft mass, tether voltage, inertia per tether, and impact of slew rate changes. These results started from an internal MSFC technology demonstration mission design and then the parameters were varied with engineering judgement to ensure that the results were consistent with expected results. These were varied in the MSFC 3DoF tool and compared to baseline results to generate a candidate ideal E-Sail design system. These results were then used to help inform the mission analysis design for the system. The 3DoF trajectory optimization was performed in the Astrodynamics and Space Science Enabling Toolbox (ASSET) and utilized collocation optimization of control vector pointing with the objective function being transfer duration. A representative model of the E-Sail force was derived as a function of the Sun-pointing vector direction. This model was initialized with a zero Sun Incidence Angle (SIA) trajectory for the initial guess generation, then with a portion of the mission optimized SIA time history for fast outbound transfers. After the trajectory is hyperbolic relative to a heliocentric frame, the SIA is maintained at 0 degrees except for any needed trajectory correction maneuvers. This trajectory optimization looked at different characteristic acceleration values to analyze the impact it had on mission performance. As a result of this study, the team can best inform mission designers and technology development efforts to mature the E-Sail system. This study will allow mission designers to have defined rules-of-thumb to design an E-Sail system to meet desired mission needs as well as providing several sample mission profiles. These design drivers will inform maturation efforts on which design requirements to consider for an integrated E-Sail design.

E-Sail↗

DOE OSTI2025

Optimally sited microgrids for energy resilience in Mount Desert Island, ME

Mount Desert Island (MDI) (≈110 sq mi; ≈10,000 year‑round residents) is located on the eastern coast of Maine. Acadia National Park is located on the island, protecting 47,000+ acres of land which draws millions of visitors annually. The island is divided into four towns (Tremont, Southwest Harbor, Mount Desert, Bar Harbor). The island’s distribution system is supplied by a single 35‑kV mainland feeder and a mix of aging distribution components; outage exposure is not uniform across the island. Residents fear that outage events are starting to exceed resilience expectations. MDI community leaders asked Sandia National Laboratories to characterize energy system vulnerability and to develop conceptual microgrid solutions that improve community resilience while also producing co‑benefits for reliability, access, and sustainable development.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1983

On-board near-optimal climb-dash energy management

On-board real time flight control is studied in order to develop algorithms which are simple enough to be used in practice, for a variety of missions involving three-dimensional flight. The intercept mission in symmetric flight is emphasized. Extensive computation is required on the ground prior to the mission but the ensuing on-board exploitation is extremely simple. The scheme takes advantage of the boundary layer structure common in singular perturbations, arising with the multiple time scales appropriate to aircraft dynamics. Energy modelling of aircraft is used as the starting point for the analysis. In the symmetric case, a nominal path is generated which fairs into the dash or cruise state. Previously announced in STAR as N84-16116

Weston, A. R.↗

NASA NTRS2015

Flexural Fillet Geometry Optimization for Design of Force Transducers Used in Aeronautics Testing

Force transducer designs used in the ground testing aeronautics community have seen minimal change over the last few decades. With increased focus on data quality and long-term performance capabilities over the life of these instruments, it is critical to investigate new methods that improve these designs. One area of focus in the past few years at NASA has been on the design of the flexural elements of traditional force balance transducers. Many of the heritage balances that have been heavily used over the last few decades have started to develop fatigue cracks. The recent focus on the flexural design of traditional single-piece force balances revolves around the design of these elements such that stress concentrations are minimized, with the overall goal of increasing the fatigue life of the balance. Recent research in the area of using conic shaped fillets in the highly stressed regions of traditional force balances will be discussed, with preliminary numerical and experimental data results. A case study will be presented which discusses integration of this knowledge into a new high-capacity semi-span force balance.

Lynn, Keith C.↗

DOE OSTI2020

Power Split Supercharging: A Mild Hybrid Approach to Boost Fuel Economy

This work investigates an innovative low-voltage (<60 V) hybrid device that enables engine boosting and downsizing in addition to mild hybrid functionalities such as regenerative braking, start-stop, and torque assist. A planetary gear set and a brake permit the power split supercharger (PSS) to share a 9 kW motor between supercharging the engine and direct torque supply to the crankshaft. In contrast, most e-boosting schemes use two separate motors for these two functionalities. This single motor structure restricts the PSS operation to only one of the supercharging or parallel hybrid modes; therefore, an optimized decision making strategy is necessary to select both the device mode and its power split ratio. An adaptive equivalent consumption minimization strategy (A-ECMS), which uses the battery state of charge (SoC) history to adjust the equivalence factor, is developed for energy management of the PSS. The A-ECMS effectiveness is compared against a dynamic programming (DP) solution with full drive cycle preview through hardware-in-the-loop experiments on an engine dynamometer testbed. The experiments show that the PSS with A-ECMS reduces vehicle fuel consumption by 18.4% over standard FTP75 cycle, compared to a baseline turbocharged engine, while global optimal DP solution decreases the fuel consumption by 22.8% compared to the baseline.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗