Parametric analysis and conceptual design of a radioisotope-thermionic space power generation system.
Parametric analysis and conceptual design of radio isotope-thermionic space power generation system
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Parametric analysis and conceptual design of radio isotope-thermionic space power generation system
Micro-Spec (μ-Spec) is a direct-detection spectrometer that integrates all the components of a diffraction-grating spectrometer onto a ∼10-cm2 chip using superconducting microstrip transmission lines on a single-crystal silicon substrate. The second-generation μ-Spec has been designed to operate with a spectral resolution of ∼512 in the far-infrared and submillimeter (420–540 GHz, 714–555 μm) wavelength range, a band of interest for NASA’s EXperiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM). EXCLAIM will be a high-altitude balloon mission that is being designed to map the emission of redshifted carbon monoxide and singly-ionized carbon lines over a redshift range 0 < z < 3.5. EXCLAIM will be the first demonstration of the μ-Spec technology in a space-like environment. This work reviews the status of the μ-Spec design for the EXCLAIM instrument, with emphasis on the spectrometer’s two-dimensional diffractive region, through which light of different wavelengths is focused on microwave kinetic inductance detectors (MKIDs) along the spectrometer focal plane. An optimization process generates a geometrical configuration of the diffractive region that satisfies specific requirements on size, operating spectral range and performance. An initial optical design optimized for EXCLAIM is presented in terms of geometric layout, spectral purity and efficiency.
This study presents a numerical evaluation of the performance of the first stage of a new-generation turbine design. The numerical method solves the two-dimensional Navier-Stokes equations using a system of patched grids. Three-dimensional effects of stream-tube contraction are also modeled. The study focuses on the effects of axial gap variation on the unsteady rotor-stator interactions and on stage performance. Results are presented for three different axial gaps. The results indicate that the unsteady interactions can be very large in this design. These interactions affect not only the stage efficiency but also substantially alter the time-averaged features of the flow. In particular, for the case of the smallest axial gap, it was found that there was an unsteady shock on the stator suction surface which spanned the gap region and impinged upon the moving rotor airfoils.
As Moore’s law approaches its limits, chalcogenides offer a promising route to next-generation computing and sensing, thanks to their topological, magnetoelectric, excitonic, and spintronic properties. Yet the same traits that make them appealing, e.g., exotic properties at monolayer thickness, clean van der Waals interfaces, and strong many-body effects, also heighten sensitivity to fabrication, hindering translation into scalable devices. Progress is further constrained by fragmented knowledge across synthesis, processing, and integration, and by the lack of systematic links between fabrication parameters and performance metrics. This Perspective examines key obstacles in controlling chalcogenide heterostructures and stresses the need for an integrated co-design framework, uniting materials growth, processing, and device architecture to accelerate practical technologies.
The design experience associated with a benchmark aeroelastic design of an out of production transport aircraft is discussed. Current work being performed on a high aspect ratio wing design is reported. The Preliminary Aeroelastic Design of Structures (PADS) system is briefly summarized and some operational aspects of generating the design in an automated aeroelastic design environment are discussed.
This analysis of the deformation of rotary combustion engine housings targeted the following objectives: (1) the development and verification of a finite element model of the trochoid housing, (2) the prediction of the stress and deformation fields present within the trochoid housing during operating conditions, and (3) the development of a specialized preprocessor which would shorten the time necessary for mesh generation of a trochoid housing's FEM model from roughly one month to approximately two man hours. Executable finite element models were developed for both the Mazda and the Outboard Marine Corporation trochoid housings. It was also demonstrated that a preprocessor which would hasten the generation of finite element models of a rotary engine was possible to develop. The above objectives are treated in detail in the attached appendices. The first deals with finite element modeling of a Wankel engine center housing, and the second with the development of a preprocessor that generates finite element models of rotary combustion engine center housings. A computer program, designed to generate finite element models of user defined rotary combustion engine center housing geometries, is also included.
This paper describes the maturation of a control allocation technique designed to assist pilots in the recovery from pilot induced oscillations (PIOs). The Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) is designed to enable next generation high efficiency aircraft designs. Energy efficient next generation aircraft require feedback control strategies that will enable lowering the actuator rate limit requirements for optimal airframe design. One of the common issues flying with actuator rate limits is PIOs caused by the phase lag between the pilot inputs and control surface response. CAPIO utilizes real-time optimization for control allocation to eliminate phase lag in the system caused by control surface rate limiting. System impacts of the control allocator were assessed through a piloted simulation evaluation of a non-linear aircraft simulation in the NASA Ames Vertical Motion Simulator. Results indicate that CAPIO helps reduce oscillatory behavior, including the severity and duration of PIOs, introduced by control surface rate limiting.
Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.
INL employee PhD Dissertation - The Molten Salt Reactor (MSR) concept is a rapidly evolving Generation IV design that has recently attracted favorable attention due to the potential for reducing waste generation, realizing passive safety features, and seizing on the opportunity for cost effective economics. This thesis investigates the performance benefit of a new device invented by the doctoral candidate. The device is referred to as a Wrapped Helix around an Inclined Plane or WHIP. The WHIP is protected under a provisional patent filed with the USA Patent Office on 28 September 2021 under application number 63/261,776, BEA docket number BA-1254. The WHIP device can be located in-core or near-core to promoted enhanced thermal-hydraulics and neutronics performance. While the WHIP can be employed in a variety of solid or liquid fuel designs, this thesis investigates the device’s benefit in the application of a natural-circulation, micro-molten salt nuclear battery concept (MsNB). This thesis will specifically investigate the temperature coefficient of the MsNB fuel (FLiNaK) using novel temperature sensitivity techniques unique to Serpent particle transport code, evaluate the WHIP’s thermal-hydraulic and neutronic performance effects using both established (STAR-CCM+) and novel (Python code developed to estimate the circulation effective delayed neutron fraction, ßef f ) analytical and numerical methods, evaluate the neutron noise behavior of the MsNB and how the WHIP may alter the character of the MsNB’s transfer function, and how the WHIP affects the autonomous, load-following performance under transient power conditions using Python code developed by the candidate. The sum body of this work, in part, has been published in three journal articles as the timing of the provisional patent process has allowed. Results show that creative utilization of WHIP engineering design and function reduces reactor system volume, fuel loading, control/stability in the buoyant regime
Lockheed Martin has been an active participant in NASA's Space Launch Initiative (SLI) programs over the past several years. SLI, part of NASA's Integrated Space Transportation Plan (ISTP), was restructured in November 2002 to focus the overall theme of safer, more affordable space transportation along two paths the Orbital Space Plane (OSP) and the Next Generation Launch Technology programs. The Orbital Space Plane program has the goal of providing rescue capability from the International Space Station by 2008 or earlier and transfer capability for crew (and contingency cargo) by 2012. The Next Generation Launch Technology program is combining research and development efforts from the 2d Generation Reusable Launch Vehicle (2GRLV) program with cutting-edge, advanced space transportation programs (previously designated 31d Generation) into one program aimed at enabling safe, reliable, cost-effective reusable launch systems by the middle of the next decade. Lockheed Martin is one of three prime contractors working to bring Orbital Space Plane system concepts to a system design level of maturity by December 2003. This paper and presentation will update the aerospace community on the progress of the OSP program, from an industry perspective, and provide insights into Lockheed Martin's role in enabling the vision of a safer, more affordable means of taking people to and from space.
The generation of custom hardware accelerators for applications implemented within high-level productive programming frameworks requires considerable manual effort. To automate this process, we introduce \sodaopt, a compiler tool that extends the MLIR infrastructure. \sodaopt automatically searches, outlines, tiles, and pre-optimizes relevant code regions to generate high-quality accelerators through high-level synthesis. \sodaopt can support any high-level programming framework and domain-specific language that interface with the MLIR infrastructure. By leveraging MLIR, \sodaopt solves compiler optimization problems with specialized abstractions. Backend synthesis tools connect to \sodaopt through progressive intermediate representation lowerings. \sodaopt interfaces to a design space exploration engine to identify the combination of compiler optimization passes and options that provides high-performance generated designs for different backends and targets. We demonstrate the practical applicability of the compilation flow by exploring the automatic generation of accelerators for deep neural networks operators outlined at arbitrary granularity and by combining outlining with tiling on large convolution layers. Experimental results with kernels from the PolyBench benchmark show that \sodaopt high-level optimizations improve execution delays of synthesized accelerators up to 60x. We also show that for the selected kernels, our solution outperforms the current of state-of-the art in more than 70% of the benchmarks and provides better average speedup in 55% of them.
The Molten Salt Reactor (MSR) concept is a rapidly evolving Generation IV design that has recently attracted favorable attention due to the potential for reducing waste generation, realizing passive safety features, and seizing on the opportunity for cost effective economics. An investigation into the power transient behavior of an autonomous load-following, closed-loop, natural circulation MSR system is important to quantifying operational and safety performance under dynamic conditions. This paper presents the results of a STAR-CCM+ and a comparatively simple asymmetric, one-dimensional, numerical model to solve the compound dynamic MSR power behavior subject to flow and temperature reactivity feedback only. Results show that reactor power is affected by fuel salt flow velocity (global) and temperatures (local bulk volume averages) in a coupled, time-delayed manner that results in a unique compound dynamic, closed-loop power feedback mechanism. The 1-D simulation approach opens the possibility of performing inexpensive computations to evaluate time-dependent reactor performance relative to thermo-physical fuel salt limitations. Results also potentially motivate a convincing conclusion that natural circulation MSRs provide a leap in safety and reliability.
The design, development, fabrication and test evaluation of two prototype fluidic emergency thrusters (FET) for aircraft stabilization are discussed. The fluidic control units were designed to provide, between two diametrically opposed nozzles, a thrust differential proportional to an input voltage signal. The emergency roll control requirements of the X-14 VTOL research aircraft were defined as typical design goals. Two control units, one on each wing tip, are intended to provide a maximum thrust of 224 pounds per unit. The units are designed to operate with 2500 psig, 2000 F gas from a solid propellant gas generator. The emergency system including the gas generator was designed to add less than 11 pounds per wing tip. The operating time under emergency conditions was specified as five seconds. The fluidic emergency thruster is similar in concept to a JATO system but has the added feature of controllable thrust.
Aviary, developed by NASA, is an open-source software tool for modeling and optimizing traditional and next-generation aircraft designs. It modernizes legacy design tools and integrates disciplines together more tightly to evaluate new vehicles, like X-66, open-rotor electric aircraft, and blended wing body. Aviary has the potential to revolutionize aircraft analysis by leveraging the complex interactions between disciplines to make aircraft conceptual designs more efficient.
The present invention provides a process for making a flow conditioning device that transforms an input flow into a desired output flow. The process includes the steps of inputting into a computer program a set of design constraints representative of the input flow and the output flow. The computer program generates a design representative of a flow-conditioning device that transforms the input flow into the output flow. The process then provides the output design to an additive manufacturing or other suitable production system adapted to form a solid representation of the flow-conditioning device.
Three-dimensional characterization of materials using X-ray computed tomography (XCT) is challenging due to the complexity of internal structures, noise, and variations in resolution. Traditional computer vision models often struggle to accurately segment these images, particularly in domain-specific applications like materials science. While supervised deep learning approaches have been developed to address the limitations of conventional algorithms, they typically require large amounts of labeled training data and often fail to generalize across different datasets. Self-supervised, few-and zero-shot learning methods have gained prominence in natural image processing and segmentation tasks, but their application to scientific imaging remains limited due to the unique structural complexity, noise, and textural artifacts present in materials science data. In this work, we investigate how domain adaptation, leveraging physics-based and GAN-generated synthetic data, impacts segmentation performance. We introduce a modified Contrastive Unpaired Translation (CUT) model designed to generate realistic labeled data, which can be used for training, pre-training, and fine-tuning segmentation models for real XCT microstructure data. We evaluate the performance of two segmentation approaches: a self-supervised network (SSL-ALPNet) and a foundation model (Segment Anything Model), assessing their improvements when pre-trained and/or fine-tuned on the synthesized data. Our results demonstrate that leveraging synthetic data significantly enhances segmentation performance, particularly in challenging materials science applications.
Modern advanced manufacturing and advanced materials design often require searches of relatively high-dimensional process control parameter spaces for settings that result in optimal structure, property, and performance parameters. The mapping from the former to the latter must be determined from noisy experiments or from expensive simulations. Here, we abstract this problem to a mathematical framework in which an unknown function from a control space to a design space must be ascertained by means of expensive noisy measurements, which locate control settings generating desired design features within specified tolerances, with quantified uncertainty. We describe targeted adaptive design (TAD), a new algorithm that performs this sampling task efficiently. TAD creates a Gaussian process surrogate model of the unknown mapping at each iterative stage, proposing a new batch of control settings to sample experimentally and optimizing the updated expected log-predictive probability density of the target design. TAD either stops upon locating a solution with uncertainties that fit inside the tolerance box or uses a measure of expected future information to determine that the search space has been exhausted with no solution. TAD thus embodies the exploration-exploitation tension in a manner that recalls, but is essentially different from, Bayesian optimization and optimal experimental design.
Moltex is designing a Generation 4 or Advanced nuclear reactor, the molten salt fast spectrum SSR-W. The design intent is to reduce the cost and complexity of the nuclear systems by relying on inherent safety characteristics, instead of engineered systems. One such characteristic as a natural tendency for power to decrease as temperature increases. Another characteristic that improves natural safety is the fact that the working fluids (molten salts) are at atmospheric pressure at operating temperatures. This significantly reduces the need for pressure boundary components and systems. Moltex is highly motivated to develop simple and economic reactors to reduce the carbon intensity and improve energy security of global electricity production. The COST project investigated the opportunities for reducing construction cost of advanced reactors with the adoption of Rigid Elastic Composite Civil works (RECC). The construction design and methods used in currently operational light water power plants would generally be suboptimal for the SSR-W since there is no requirement for civil structures to withstand high pressure accidents such as hydrogen combustion or steam explosion. In parallel to downselecting the most promising RECC-type technology, accident scenarios representing the largest credible challenge to the SSR-W civil and construction design were modelled. The capability of an SSR-W reactor constructed with and without the selected construction technology was evaluated and the consequential licensing challenges identified. A construction schedule and cost estimate of the SSR-W with and without the selected RECC construction technology was developed. Once the above data was collected, then Moltex was able to review the safety performance, license-ability and cost/schedule benefit of applying the preferred construction technology. The CAPEX/NPV benefit was quantified, and the licensing risks and opportunities were documented. Finally, the CAPEX/NPV benefit of the advanced construction technology was modest due to the suitability of traditional stick-built construction for the SSR-W design. However, previously unidentified benefits of the advanced construction technology were revealed during the studies that could credibly de-risk certain aspects of the design to be licensed. Since licensing (duration and delays) are very significant in new build project costs, the cost benefits may be significant. Further studies on the risk reduction of the construction technology are foreseen.