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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 sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Analytic redundancy management for large flexible structures

An analytic redundancy management approach for on-line component failure detection is described and illustrated using a simulation of the NASA Langley Spacecaft Control Laboratory Experiment (SCOLE) research facility. The SCOLE experimental apparatus simulated is a functional model of the Space Shuttle with a large, flexible, offset-feed antenna cantilevered from the payload bay. This approach uses a single, active, Kalman filter selected from a bank of filters, each element of which was previously designed to accommodate a specific failure condition. The residuals of this active filter are processed through a sequential probability ratio test (SPRT) filter to identify the failure state of the system and, hence, closing the failure accommodation loop, to select the active filter. Results are presented that illustrate the ability of the system to detect and recover from failures introduced in the angular rate and linear acceleration sensors on the SCOLE facility.

Shenhar, J.↗
DOE OSTI2022

A physics-informed multi-agents model to predict thermo-oxidative/hydrolytic aging of elastomers

This paper introduces a novel physics-informed multi-agents constitutive model to propose prediction in quasi-static constitutive behavior of cross-linked elastomer and the loss of mechanical performance during environmental aging. The presented model is used to simulate the effect of single-mechanism chemical aging (i.e. thermal-inducedor hydrolytic aging) on the behavior of the material in this hybrid framework. Those environmental single-mechanism damages change the polymer matrix over time due to massive chain scission, chain formations, and changing the arrangement of molecules in the polymer matrix. Here we propose a data-driven super-constrained machine-learned engine to represent damage in the polymer matrix and capture the changes in material behavior, including its inelastic features such as Mullins effect and permanent set in the course of aging. We have simplified the 3D stress–strain tensor mapping problem into a small number of super-constrained 1D mapping problems by means of a sequential order reduction. An assembly of multiple replicated conditional neural-network learning-agents (L-agents) is trained to systematically simplify the high-dimensional mapping problem into multiple 1D problems, each represented by a different type of agent. Our hybrid framework is designed to capture the effect of deformation history, aging time, and aging temperature. The model is validated with respect to a comprehensive set of experiments specifically designed to benchmark model capabilities and also against available data in the literature. Thermodynamic consistency and frame independency have been verified. Besides acceptable predictive abilities, a significant reduction of computational cost to predict behavior at multiple states of deformation is the most significant feature of this model.

42 ENGINEERING↗
DOE OSTI2023

Simplifying the Advanced Test Reactor LOWE Element Test Series

The Advanced Test Reactor (ATR) is one of six remaining high performance research reactors in the United States scheduled to be converted from 93% high-enriched uranium (HEU) fuel to 19.75% low-enriched uranium (LEU) fuel as part of the Department of Energy (DOE), National Nuclear Security Administration (NNSA), Office of Material Management and Minimization (MMM) reactor conversion efforts(1). The specific LEU fuel element design for the ATR is called the Low Enriched (LOWE) element. A series of fuel qualification tests are scheduled to occur over the next decade before the ATR is fully converted. In addition to several experiments of demonstration plates, a series of Element Tests (ETs) are planned for conversion, in which full sized LOWE elements are placed in ATR driver positions. The purpose of these ETs was generally to sequentially increase the amount of LEU and core power to full power, therefore creating a representative safety profile in which LEU could operate for the duration of the ATR lifetime. The planned element tests were (2): ET-1: one LOWE element at low power for once cycle ET-2: ~8 LOWE elements at low/medium power for multiple cycles, and ET-3: >8 LOWE elements for a full lobe of elements at high power for multiple cycles. Given recent improvements in modeling fidelity, scheduling considerations, and an opportunity to combine later ETs, the LEU conversion program successfully defined the operational requirements for the “ET-ATR” test, which combines the needed information collected from ET-2 and ET-3 into a single test.

42 ENGINEERING↗
DOE OSTI2023

200-DV-1 Laboratory Treatability Study: Proof-of-Principle Results

This document presents the Phase 1 technical approach and results of laboratory-scale treatability testing of nine in situ remedial technologies for their consideration in a future Feasibility Study (FS) for the 200-DV-1 OU. The primary objective of this initial assessment was a proof-of-principle testing evaluation primarily via batch experiments to determine the potential reduction and sequestration of primary contaminants of interest with and without potential co-contaminants of interest. An effectiveness rate of 35% transformation to immobile or nontoxic end products, along with other experimental indicators, was used by the project team to determine the technologies that advanced to Phase 2 for further evaluations. For most technologies, the performance was evaluated based on a series of sequential extractions designed to evaluate the mobility of contaminants before and after treatment, with each subsequent extraction representing a relative decrease in mobility. The results of this study will be used to inform testing for Phase 2 of the treatability study for further evaluation of selected technologies. The final results from the treatability study, following the completion of remaining experimental phases, will be used to determine whether the technologies tested can be appropriately evaluated in a FS to expand on the limited number of viable DVZ remediation technologies. After completion of the laboratory treatability study and the 200-DV-1 OU Remedial Investigation (RI) and Resource Conservation and Recovery Act Facility Investigation (RFI) of the waste sites, results will be evaluated to determine whether field studies are needed to provide additional information on effectiveness, implementability, or costs for evaluating these technologies in the FS for their site-specific application.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1992

Control-structure-thermal interactions in analysis of lunar telescopes

The lunar telescope project was an excellent model for the CSTI study because a telescope is a very sensitive instrument, and thermal expansion or mechanical vibration of the mirror assemblies will rapidly degrade the resolution of the device. Consequently, the interactions are strongly coupled. The lunar surface experiences very large temperature variations that range from approximately -180 C to over 100 C. Although the optical assemblies of the telescopes will be well insulated, the temperature of the mirrors will inevitably fluctuate in a similar cycle, but of much smaller magnitude. In order to obtain images of high quality and clarity, allowable thermal deformations of any point on a mirror must be less than 1 micron. Initial estimates indicate that this corresponds to a temperature variation of much less than 1 deg through the thickness of the mirror. Therefore, a lunar telescope design will most probably include active thermal control, a means of controlling the shape of the mirrors, or a combination of both systems. Historically, the design of a complex vehicle was primarily a sequential process in which the basic structure was defined without concurrent detailed analyses or other subsystems. The basic configuration was then passed to the different teams responsible for each subsystem, and their task was to produce a workable solution without requiring major alterations to any principal components or subsystems. Consequently, the final design of the vehicle was not always the most efficient, owing to the fact that each subsystem design was partially constrained by the previous work. This procedure was necessary at the time because the analysis process was extremely time-consuming and had to be started over with each significant alteration of the vehicle. With recent advances in the power and capacity of small computers, and the parallel development of powerful software in structural, thermal, and control system analysis, it is now possible to produce very detailed analyses of intermediate designs in a much shorter period of time. The subsystems can thus be designed concurrently, and alterations in the overall design can be quickly adopted into each analysis; the design becomes an iterative process in which it is much easier to experiment with new ideas, configurations, and components. Concurrent engineering has the potential to produce efficient, highly capable designs because the effect of one subystem on another can be assessed in much more detail at a very early point in the program. The research program consisted of several tasks: scale a prototype telescope assembly to a 1 m aperture, develop a model of the telescope assembly by using finite element (FEM) codes that are available on site, determine structural deflections of the mirror surfaces due to the temperature variations, develop a prototype control system to maintain the proper shape of the optical elements, and most important of all, demonstrate the concurrent engineering approach with this example. In addition, the software used for the finite element models and thermal analysis was relatively new within the Program Development Office and had yet to be applied to systems this large or complex; understanding the software and modifying it for use with this project was also required. The I-DEAS software by Structural Dynamics Research Corporation (SDRC) was used to build the finite element models, and TMG developed by Maya Heat Transfer Technologies, Ltd. (which runs as an I-DEAS module) was used for the thermal model calculations. All control system development was accomplished with MATRIX(sub X) by Integrated Systems, Inc.

Thompson, Roger C.↗
DOE OSTI2024

Designing workflows for materials characterization

Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. In this study, we discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research.

36 MATERIALS SCIENCE↗
NASA NTRS2014

NASA Space Launch System Operations Outlook

The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center (MSFC), is working with the Ground Systems Development and Operations (GSDO) Program, based at the Kennedy Space Center (KSC), to deliver a new safe, affordable, and sustainable capability for human and scientific exploration beyond Earth's orbit (BEO). Larger than the Saturn V Moon rocket, SLS will provide 10 percent more thrust at liftoff in its initial 70 metric ton (t) configuration and 20 percent more in its evolved 130-t configuration. The primary mission of the SLS rocket will be to launch astronauts to deep space destinations in the Orion Multi-Purpose Crew Vehicle (MPCV), also in development and managed by the Johnson Space Center. Several high-priority science missions also may benefit from the increased payload volume and reduced trip times offered by this powerful, versatile rocket. Reducing the life-cycle costs for NASA's space transportation flagship will maximize the exploration and scientific discovery returned from the taxpayer's investment. To that end, decisions made during development of SLS and associated systems will impact the nation's space exploration capabilities for decades. This paper will provide an update to the operations strategy presented at SpaceOps 2012. It will focus on: 1) Preparations to streamline the processing flow and infrastructure needed to produce and launch the world's largest rocket (i.e., through incorporation and modification of proven, heritage systems into the vehicle and ground systems); 2) Implementation of a lean approach to reachback support of hardware manufacturing, green-run testing, and launch site processing and activities; and 3) Partnering between the vehicle design and operations communities on state-ofthe- art predictive operations analysis techniques. An example of innovation is testing the integrated vehicle at the processing facility in parallel, rather than sequentially, saving both time and money. These themes are accomplished under the context of a new cross-program integration model that emphasizes peer-to-peer accountability and collaboration towards a common, shared goal. Utilizing the lessons learned through 50 years of human space flight experience, SLS is assigning the right number of people from appropriate backgrounds, providing them the right tools, and exercising the right processes for the job. The result will be a powerful, versatile, and capable heavy-lift, human-rated asset for the future human and scientific exploration of space.

Hefner, William Keith↗
NASA NTRS1987

Guidance simulation and test support for differential GPS flight experiment

Three separate tasks which supported the test preparation, test operations, and post test analysis of the NASA Ames flight test evaluation of the differential Global Positioning System (GPS) are presented. Task 1 consisted of a navigation filter design, coding, and testing to optimally make use of GPS in a differential mode. The filter can be configured to accept inputs from external censors such as an accelerometer and a barometric or radar altimeter. The filter runs in real time onboard a NASA helicopter. It processes raw pseudo and delta range measurements from a single channel sequential GPS receiver. The Kalman filter software interfaces are described in detail, followed by a description of the filter algorithm, including the basic propagation and measurement update equations. The performance during flight tests is reviewed and discussed. Task 2 describes a refinement performed on the lateral and vertical steering algorithms developed on a previous contract. The refinements include modification of the internal logic to allow more diverse inflight initialization procedures, further data smoothing and compensation for system induced time delays. Task 3 describes the TAU Corp participation in the analysis of the real time Kalman navigation filter. The performance was compared to that of the Z-set filter in flight and to the laser tracker position data during post test analysis. This analysis allowed a more optimum selection of the parameters of the filter.

Geier, G. J.↗
DOE OSTI2022

An adaptive stochastic sequential quadratic programming with differentiable exact augmented lagrangians

In this study, we consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints. We assume for the objective that its evaluation, gradient, and Hessian are inaccessible, while one can compute their stochastic estimates by, for example, subsampling. We propose a stochastic algorithm based on sequential quadratic programming (SQP) that uses a differentiable exact augmented Lagrangian as the merit function. To motivate our algorithm design, we first revisit and simplify an old SQP method Lucidi developed for solving deterministic problems, which serves as the skeleton of our stochastic algorithm. Based on the simplified deterministic algorithm, we then propose a non-adaptive SQP for dealing with stochastic objective, where the gradient and Hessian are replaced by stochastic estimates but the stepsizes are deterministic and prespecified. Finally, we incorporate a recent stochastic line search procedure Paquette and Scheinberg into the non-adaptive stochastic SQP to adaptively select the random stepsizes, which leads to an adaptive stochastic SQP. The global "almost sure" convergence for both non-adaptive and adaptive SQP methods is established. Numerical experiments on nonlinear problems in CUTEst test set demonstrate the superiority of the adaptive algorithm.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1979

A simplified method of evaluating the stress wave environment of internal equipment

A simplified method called the transfer function technique (TFT) was devised for evaluating the stress wave environment in a structure containing internal equipment. The TFT consists of following the initial in-plane stress wave that propagates through a structure subjected to a dynamic load and characterizing how the wave is altered as it is transmitted through intersections of structural members. As a basis for evaluating the TFT, impact experiments and detailed stress wave analyses were performed for structures with two or three, or more members. Transfer functions that relate the wave transmitted through an intersection to the incident wave were deduced from the predicted wave response. By sequentially applying these transfer functions to a structure with several intersections, it was found that the environment produced by the initial stress wave propagating through the structure can be approximated well. The TFT can be used as a design tool or as an analytical tool to determine whether a more detailed wave analysis is warranted.

Colton, J. D.↗
NASA NTRS2014

NASA Space Launch System Operations Outlook

The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center (MSFC), is working with the Ground Systems Development and Operations (GSDO) Program, based at the Kennedy Space Center (KSC), to deliver a new safe, affordable, and sustainable capability for human and scientific exploration beyond Earth's orbit (BEO). Larger than the Saturn V Moon rocket, SLS will provide 10 percent more thrust at liftoff in its initial 70 metric ton (t) configuration and 20 percent more in its evolved 130-t configuration. The primary mission of the SLS rocket will be to launch astronauts to deep space destinations in the Orion Multi- Purpose Crew Vehicle (MPCV), also in development and managed by the Johnson Space Center. Several high-priority science missions also may benefit from the increased payload volume and reduced trip times offered by this powerful, versatile rocket. Reducing the lifecycle costs for NASA's space transportation flagship will maximize the exploration and scientific discovery returned from the taxpayer's investment. To that end, decisions made during development of SLS and associated systems will impact the nation's space exploration capabilities for decades. This paper will provide an update to the operations strategy presented at SpaceOps 2012. It will focus on: 1) Preparations to streamline the processing flow and infrastructure needed to produce and launch the world's largest rocket (i.e., through incorporation and modification of proven, heritage systems into the vehicle and ground systems); 2) Implementation of a lean approach to reach-back support of hardware manufacturing, green-run testing, and launch site processing and activities; and 3) Partnering between the vehicle design and operations communities on state-of-the-art predictive operations analysis techniques. An example of innovation is testing the integrated vehicle at the processing facility in parallel, rather than sequentially, saving both time and money. These themes are accomplished under the context of a new cross-program integration model that emphasizes peer-to-peer accountability and collaboration towards a common, shared goal. Utilizing the lessons learned through 50 years of human space flight experience, SLS is assigning the right number of people from appropriate backgrounds, providing them the right tools, and exercising the right processes for the job. The result will be a powerful, versatile, and capable heavy-lift, human-rated asset for the future human and scientific exploration of space.

Hefner, William Keith↗
DOE OSTI2023

Scalable Bayesian optimization with randomized prior networks

Several fundamental problems in science and engineering consist of global optimization tasks involving unknown high-dimensional (black-box) functions that map a set of controllable variables to the outcomes of an expensive experiment. Bayesian Optimization (BO) techniques are known to be effective in tackling global optimization problems using a relatively small number objective function evaluations, but their performance suffers when dealing with high-dimensional outputs. To overcome the major challenge of dimensionality, here we propose a deep learning framework for BO and sequential decision making based on bootstrapped ensembles of neural architectures with randomized priors. Using appropriate architecture choices, we show that the proposed framework can approximate functional relationships between design variables and quantities of interest, even in cases where the latter take values in high-dimensional vector spaces or even infinite-dimensional function spaces. In the context of BO, we augmented the proposed probabilistic surrogates with re-parameterized Monte Carlo approximations of multiple-point (parallel) acquisition functions, as well as methodological extensions for accommodating black-box constraints and multi-fidelity information sources. We test the proposed framework against state-of-the-art methods for BO and demonstrate superior performance across several challenging tasks with high-dimensional outputs, including a constrained multi-fidelity optimization task involving shape optimization of rotor blades in turbo-machinery.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2000

Resin Film Infusion (RFI) Process Modeling for Large Transport Aircraft Wing Structures

This investigation completed the verification of a three-dimensional resin transfer molding/resin film infusion (RTM/RFI) process simulation model. The model incorporates resin flow through an anisotropic carbon fiber preform, cure kinetics of the resin, and heat transfer within the preform/tool assembly. The computer model can predict the flow front location, resin pressure distribution, and thermal profiles in the modeled part. The formulation for the flow model is given using the finite element/control volume (FE/CV) technique based on Darcy's Law of creeping flow through a porous media. The FE/CV technique is a numerically efficient method for finding the flow front location and the fluid pressure. The heat transfer model is based on the three-dimensional, transient heat conduction equation, including heat generation. Boundary conditions include specified temperature and convection. The code was designed with a modular approach so the flow and/or the thermal module may be turned on or off as desired. Both models are solved sequentially in a quasi-steady state fashion. A mesh refinement study was completed on a one-element thick model to determine the recommended size of elements that would result in a converged model for a typical RFI analysis. Guidelines are established for checking the convergence of a model, and the recommended element sizes are listed. Several experiments were conducted and computer simulations of the experiments were run to verify the simulation model. Isothermal, non-reacting flow in a T-stiffened section was simulated to verify the flow module. Predicted infiltration times were within 12-20% of measured times. The predicted pressures were approximately 50% of the measured pressures. A study was performed to attempt to explain the difference in pressures. Non-isothermal experiments with a reactive resin were modeled to verify the thermal module and the resin model. Two panels were manufactured using the RFI process. One was a stepped panel and the other was a panel with two 'T' stiffeners. The difference between the predicted infiltration times and the experimental times was 4% to 23%.

Loos, Alfred C.↗
DOE OSTI2024

Augmenting a Simulation Campaign for Hybrid Computer Model and Field Data Experiments

The Kennedy and O’Hagan (KOH) calibration framework uses coupled Gaussian processes (GPs) to meta-model an expensive simulator (first GP), tune its “knobs” (calibration inputs) to best match observations from a real physical/field experiment and correct for any modeling bias (second GP) when predicting under new field conditions (design inputs). There are well-established methods for placement of design inputs for data-efficient planning of a simulation campaign in isolation, that is, without field data: space-filling, or via criterion like minimum integrated mean-squared prediction error (IMSPE). Analogues within the coupled GP KOH framework are mostly absent from the literature. Here, in this study, we derive a closed form IMSPE criterion for sequentially acquiring new simulator data for KOH. We illustrate how acquisitions space-fill in design space, but concentrate in calibration space. Closed form IMSPE precipitates a closed-form gradient for efficient numerical optimization. We demonstrate that our KOH-IMSPE strategy leads to a more efficient simulation campaign on benchmark problems, and conclude with a showcase on an application to equilibrium concentrations of rare earth elements for a liquid–liquid extraction reaction.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Parallelization of Finite Element Analysis Codes Using Heterogeneous Distributed Computing

Performance gains in computer design are quickly consumed as users seek to analyze larger problems to a higher degree of accuracy. Innovative computational methods, such as parallel and distributed computing, seek to multiply the power of existing hardware technology to satisfy the computational demands of large applications. In the early stages of this project, experiments were performed using two large, coarse-grained applications, CSTEM and METCAN. These applications were parallelized on an Intel iPSC/860 hypercube. It was found that the overall speedup was very low, due to large, inherently sequential code segments present in the applications. The overall execution time T(sub par), of the application is dependent on these sequential segments. If these segments make up a significant fraction of the overall code, the application will have a poor speedup measure.

Ozguner, Fusun↗
DOE OSTI2023

AutoTG: Reinforcement Learning-Based Symbolic Optimization for AI-Assisted Power Converter Design

Power converters are pervasive in modern electronic component design. They can be found in all electronic devices from household appliances and cellphone chargers to vehicles. Currently, designing new circuit topologies is hard because it requires human expertise based on experience and is difficult to automate. However, artificial-intelligence-assisted design can significantly facilitate the development of new power converters and/or improve the final result. Intelligently designed highly efficient power converters can have a significant effect on many important attributes, such as power efficiency, layout size, cost, heat dissemination, energy requirements, etc. We propose Autonomous Topology Generator (AutoTG), a reinforcement-learning-based framework that generates power converter topology candidates based on user specifications, optimized for user preferences. By modeling power converter design as a symbolic optimization problem, we sequentially sample components in an autoregressive manner until new topologies are formed, providing both the topology specification and the sizing (magnitude of each component parameter) of the proposed power converter. Here, we provide an empirical evaluation and show that AutoTG is able to generate varied high-efficiency topologies within component restrictions based on user input and show that previously unknown topologies can be found for further evaluation.

(AI)-based design↗
NASA NTRS1980

Development of an earth resource pushbroom scanner utilizing a 90-element 8-14 micrometer /Hg,Cd/Te array

A detailed description is presented of thermal infrared 'pushbroom' scanners being developed for NASA's earth resources survey experiments in the middle to late 1980's. The devices offer high spectral, temporal and spatial resolution, and great reliability as well, due to simplicity of design. Their mode of operation does not require moving optics, since chopping and calibration are integral. The specific device described, a 90-element IR/CCD instrument, was developed to demonstrate scan imagery in the 8-14 micron spectral region in simulated aircraft tests. The scanning operation covers a straight-line path with a linear array of solid-state IR detectors, whose elements are activated sequentially in the cross-track direction while being swept forward along a flight path that, at an aircraft altitude of 10 km, is 7 km wide.

Brown, T. J.↗
DOE OSTI2025

Open Architecture for Cost Savings in Advanced Nuclear Reactors

Recently, nuclear power plant build projects in the West have run over budget due to high capital costs and schedule overruns. Compared to other sources of energy, nuclear power plants have higher capital costs. Reactors are often different at every site, resulting in a lack of standardization. Nuclear is expected to compete with other low carbon sources of energy which have lower capital costs making it essential for nuclear to develop ways of reducing costs. Strategies such as standardization, learning rates, modularization, and schedule reduction in advanced reactors can reduce nuclear costs by about 40%. Standardization as a way of cutting capital costs has been explored even in large nuclear power plants. Standardization of certain plant components can result in lower component and installation costs and higher learning from experience. Standardization can be achieved by adopting a criterion of key performance indicators and general design principles for a specific system or component such as the balance of plant. Modularization allows the construction of certain components of SMRs in a factory, which saves time, increases productivity, and encourages higher learning rates. Production learning decreases the time and the cost related to an activity. The potential for modularized components of advanced reactors to be manufactured in factories makes it conducive to achieving higher learning rates. Developing large-capacity nuclear programs through sequential builds cultivates a higher learning rate, which in effect may reduce schedule overruns. Open architecture has been identified as a way to drive standardization among advanced reactor designs and result in cost savings. Open architecture (OA) is defined as a design enabling a diverse supply chain by defining and publishing requirements of systems or equipment in functional and/or interface terms, utilizing technical standards in widespread use. Currently, the nuclear industry’s approach is to use closed architecture, making most designs proprietary. However, collaboration between various advanced reactor vendors and suppliers utilizing the concept of open architecture can result in modular and standardized architecture of subsystems or subcomponents of a nuclear power plant. Completely standardizing nuclear power plants may be impossible, however, certain common subsystems amongst the various reactor designs could be standardized and/or access a wider supply chain and leverage existing learning from other sectors. Open architecture will save time and allocate resources to the parts of the plants that have the most unique features. A key advantage of open architecture is its ability to improve production learning across advanced reactors (AR) types in the industry, by providing and utilizing the same kind of component. Sodium fast reactor (SFR), High Temperature Gas Reactor (HTGR) and Molten Salt Reactor (MSR) are the advanced reactors considered for this project. This paper aims to determine the cost savings in advanced reactor programs due to open architecture learning rate. This work is an extension of work done on light water reactor small modular reactors; the cost methodology was utilized to investigate the impact of open architecture on advanced reactors with a particular focus on sodium fast reactors. The cost data on sodium fast reactors used in the model presented the most adequate information required for the analysis.

Advanced Nuclear Reactors↗