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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Advanced Reactor Safeguards & Security 2024 Program Roadmap

The Advanced Reactor Safeguards and Security (ARSS) program was established to provide research support addressing near term challenges that advanced nuclear reactor vendors face in meeting domestic Material Control and Accounting (MC&A), Physical Protection System (PPS), and Cybersecurity requirements for U.S. construction. The technical work in the program is meant to (1) support nuclear reactor vendors with advanced MC&A, PPS, and Cybersecurity designs for next generation reactors, (2) provide technical bases for the regulator, and (3) promote the integration of Safeguards and Security by Design early in the design process. Existing domestic regulations for safeguards and security, as outlined in the Code of Federal Regulations, were written for large light water reactors, and rule-making efforts are underway to develop regulations more suited to different reactor designs. The ARSS program seeks to remove roadblocks in the deployment of new and advanced reactors by solving regulatory challenges, reducing safeguards and security costs, and utilizing the latest technologies and approaches for robust plant monitoring and protection. This roadmap discusses the goals of the ARSS program, current research, and program plan for the next five years.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1973

Saturn satellite encounter opportunities for Mariner Jupiter-Saturn 1977

The opportunities for close satellite encounters which meet the planetary constraints at Saturn that are imposed by science value return and environmental conditions are investigated. Since the satellites travel at various speeds in their orbits, Saturn arrival time is critical and was chosen as the design parameter. Arrival times are recommended which afford close satellite encounters and also meet important mission constraints. A design chart illustrates the satellite opportunities as a function of Saturn arrival date. Through the use of such a design chart, the Saturn encounter design process, which will take place according to recommendations by the selected science investigators over the next several years, will be considerably streamlined. Potential applications are given to illustrate the use of the Saturn satellite opportunity chart in encounter design.

Wallace, R. A.↗
NASA NTRS1983

Development of a Multilevel Optimization Approach to the Design of Modern Engineering Systems

A general algorithm is proposed which carries out the design process iteratively, starting at the top of the hierarchy and proceeding downward. Each subproblem is optimized separately for fixed controls from higher level subproblems. An optimum sensitivity analysis is then performed which determines the sensitivity of the subproblem design to changes in higher level subproblem controls. The resulting sensitivity derivatives are used to construct constraints which force the controlling subproblems into chosing their own designs so as to improve the lower levels subproblem designs while satisfying their own constraints. The applicability of the proposed algorithm is demonstrated by devising a four-level hierarchy to perform the simultaneous aerodynamic and structural design of a high-performance sailplane wing for maximum cross-country speed. Finally, the concepts discussed are applied to the two-level minimum weight structural design of the sailplane wing. The numerical experiments show that discontinuities in the sensitivity derivatives may delay convergence, but that the algorithm is robust enough to overcome these discontinuities and produce low-weight feasible designs, regardless of whether the optimization is started from the feasible space or the infeasible one.

Barthelemy, J. F. M.↗
NASA NTRS1989

Flutter suppression using eigenspace freedoms to meet requirements

A constrained optimization methodology has been developed which allows specific use of eigensystem freedoms to meet design requirements. A subset of the available eigenvector freedoms was employed. The eigenvector freedoms associated with a particular closed-loop eigenvalue are coefficients of basis vectors which span the subspace in which that closed-loop vector must lie. Design requirements are included as a vector of inequality constraints. The procedure was successfully applied to develop an unscheduled controller which stabilizes symmetric flutter of an aeroelastic vehicle to a dynamic pressure 44 percent above the open-loop flutter point. The design process proceeded from full-state feedback to the inclusion of a full-order observer to the selection of an eighth-order controller which preserved the full-state sensitivity characteristics. Only a subset of the design freedoms was utilized (i.e., assuming full-state feedback only four out of 26 eigenvectors were used, and no variations were made in the closed-loop eigenvalues). Utilization of additional eigensystem freedoms could further improve the controller.

Adams, William M., Jr.↗
NASA NTRS2018

Gaps in Thermal Design Guidelines in the Goddard Space Flight Center GOLD Rules

The GSFC (Goddard Space Flight Center) GOLD Rules (Goddard Open Learning Design; GSFC-STD-1000) provide a reasonably comprehensive list of guidelines for the design and testing of spacecraft and instruments based on the long heritage of successful GSFC missions. In general, all GSFC missions are required to comply with the GOLD Rules across a number of subsystems or to seek waivers to particular GOLD rules where compliance is not practical, either due to the risk posture of a mission or the cost and/or schedule associated with compliance. In thermal subsystems, GOLD Rules are applied to design margins throughout the project life cycle and include temperature margins, heater power margins, and two-phase transport margins. However, no explicit guidance is provided for two thermal design aspects: heater control authority (for stability requirements) and cryogenic design margins (which are often not reasonable to express in terms of temperatures). This can lead to ambiguity and inconsistency among projects when demonstrating GOLD Rules compliance. Two current GSFC projects, TIRS-2 (Thermal InfraRed Sensor 2) and WFIRST (Wide Field InfraRed Survey Telescope), are both missions with cryogenic aspects and active thermal control for stability. This paper seeks to outline the characterization of cryogenic margins during the design process for TIRS-2 and WFIRST as well as the project derived guidelines for heater control authority margin. This effort serves as potential first steps for updating the GOLD Rules to address these two areas in guiding thermal designs at GSFC.

Modeling↗
NASA NTRS2014

Badger COMET Compartmentalized Onboard Material Extrusion Technology

In response to the 2014 NASA Academic Innovation Challenge, the University of Wisconsin – Madison team presents the design of a collapsible Fused Deposition Modeling (FDM) system for in situ manufacturing in a space habitat environment, the Badger Compartmentalized Onboard Material Extrusion Technology (COMET). The proposed mechanism incorporates one year of design and testing on an array of current additive manufacturing techniques, with the goal of providing a reliable and maintainable manufacturing solution. Seven Level 1 requirements were employed to guide the design process, based on information in the challenge, communications with NASA, and the evolving systems feedback of project work groups. These requirements provided a baseline for the development of the System Requirements Document (SRD, Appendix I), which framed the design of the system. The design requirements deemed critical to the success of the systems are as follows: - The system shall compose an FDM workstation capable of producing parts within industry standard tolerances. - The system shall reduce to a minimum of 50 percent or less of its deployed volume when not in use, and must collapse without the need for disassembly. - The system shall meet all relevant NASA safety and functional standards. The final design for the Badger COMET was selected from multiple design iterations, which balanced the critical design requirements listed above with system reliability, with the final goal of providing a minimal system weight. The system collapses in the vertical direction, allowing for a maximum reduction in volume. Guide rods and precision, anti-backlash lead screws provide all linear movement in the device. Stepper motors were chosen to actuate each system axis, due to their high precision and repeatable accuracy. The system is controlled through an on-board computer system and embedded electronics package.

Frederick T. Elder↗
DOE OSTI2022

Descriptor Aided Bayesian Optimization for Many-Level Qualitative Variables With Materials Design Applications

Abstract Engineering design often involves qualitative and quantitative design variables, which requires systematic methods for the exploration of these mixed-variable design spaces. Expensive simulation techniques, such as those required to evaluate optimization objectives in materials design applications, constitute the main portion of the cost of the design process and underline the need for efficient search strategies—Bayesian optimization (BO) being one of the most widely adopted. Although recent developments in mixed-variable Bayesian optimization have shown promise, the effects of dimensionality of qualitative variables have not been well studied. High-dimensional qualitative variables, i.e., with many levels, impose a large design cost as they typically require a larger dataset to quantify the effect of each level on the optimization objective. We address this challenge by leveraging domain knowledge about underlying physical descriptors, which embody the physics of the underlying physical phenomena, to infer the effect of unobserved levels that have not been sampled yet. We show that physical descriptors can be intuitively embedded into the latent variable Gaussian process approach—a mixed-variable GP modeling technique—and used to selectively explore levels of qualitative variables in the Bayesian optimization framework. This physics-informed approach is particularly useful when one or more qualitative variables are high dimensional (many-level) and the modeling dataset is small, containing observations for only a subset of levels. Through a combination of mathematical test functions and materials design applications, our method is shown to be robust to certain types of incomplete domain knowledge and significantly reduces the design cost for problems with high-dimensional qualitative variables.

Engineering↗
DOE OSTI2026

Phenomena-based graph representations and applications to chemical process simulation

Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture the physical phenomena taking place in the process (e.g., material and energy conservation, phase equilibrium, reactions). In this work, we show that graph-theoretic representations of the physical phenomena within unit operations can help navigate and decompose equations to systematically identify alternative approaches for fast and robust numerical solutions. Specifically, we present a graph-theoretic abstraction that captures the connectivity between the model variables/equations and use this abstraction to group variables/equations into fundamental phenomena. We show that phenomena-based decomposition of the underlying equations can help decouple nonlinearities and enforce material/energy conservation at the process level to accelerate convergence. The proposed decomposition approach differs from the more traditional sequential modular simulation approach, in which equations are grouped and decomposed by unit operations. We implemented the phenomena-based decomposition in BioSTEAM—an open-source process simulation platform in Python—and demonstrated that this approach can converge a variety of separation process models. Compared to sequential modular simulation, the phenomena-based approach can converge idealized systems faster, but it can be slower for (or even fail to converge) highly coupled and nonideal process systems.

Convergence↗
DOE OSTI2025

Surrogate-driven design optimization with uncertainty constraints in Monte Carlo simulations

In multi-objective design tasks, the computational cost increases rapidly when high-fidelity simulations are used to evaluate objective functions. Surrogate models help mitigate this cost by approximating the simulation output, simplifying the design process. However, under high uncertainty, surrogate models trained on noisy data can produce inaccurate predictions, as their performance depends heavily on the quality of training data. This study investigates the impact of data uncertainty on two multi-objective design problems modelled using Monte Carlo transport simulations: a neutron moderator and an ion-to-neutron converter. For each, a grid search was performed using five different tally uncertainty levels to generate training data for neural network surrogate models. These models were then optimized using NSGA-III. The recovered Pareto-fronts were analyzed across uncertainty levels: in the moderator problem, normalized hypervolume dropped from 0.886 at 1.0% uncertainty to 0.748 at 10% uncertainty, while in the converter problem it remained near 0.50 for all cases. Average simulation times were also compared to evaluate the trade-off between accuracy and computational cost. Results show that the influence of simulation uncertainty is strongly problem-dependent. In the neutron moderator case, higher uncertainties led to exaggerated objective sensitivities and distorted Pareto-fronts, reducing normalized hypervolume. In contrast, the ion-to-neutron converter task was less affected—low-fidelity simulations produced results similar to those from high-fidelity data. These findings suggest that a fixed-fidelity approach is not optimal. Surrogate models can recover the Pareto-front under noisy conditions, and multi-fidelity studies help identify suitable uncertainty levels for each problem to balance efficiency and accuracy.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1988

Results of an integrated structure-control law design sensitivity analysis

Next generation air and space vehicle designs are driven by increased performance requirements, demanding a high level of design integration between traditionally separate design disciplines. Interdisciplinary analysis capabilities have been developed, for aeroservoelastic aircraft and large flexible spacecraft control for instance, but the requisite integrated design methods are only beginning to be developed. One integrated design method which has received attention is based on hierarchal problem decompositions, optimization, and design sensitivity analyses. This paper highlights a design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changess in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient that finite difference methods for the computation of the equivalent sensitivity information.

Gilbert, Michael G.↗
NASA NTRS1989

Results of an integrated structure/control law design sensitivity analysis

A design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations is discussed. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changes in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient than finite difference methods for the computation of the equivalent sensitivity information.

Gilbert, Michael G.↗
NASA NTRS1990

Methods for the development of a bioregenerative life support system

Presented here is a rudimentary approach to designing a life support system based on the utilization of plants and animals. The biggest stumbling block in the initial phases of developing a bioregenerative life support system is encountered in collecting and consolidating the data. If a database existed for the systems engineer so that he or she may have accurate data and a better understanding of biological systems in engineering terms, then the design process would be simplified. Also addressed is a means of evaluating the subsystems chosen. These subsystems are unified into a common metric, kilograms of mass, and normalized in relation to the throughput of a few basic elements. The initial integration of these subsystems is based on input/output masses and eventually balanced to a point of operation within the inherent performance ranges of the organisms chosen. At this point, it becomes necessary to go beyond the simplifying assumptions of simple mass relationships and further define for each organism the processes used to manipulate the throughput matter. Mainly considered here is the fact that these organisms perform input/output functions on differing timescales, thus establishing the need for buffer volumes or appropriate subsystem phasing. At each point in a systematic design it is necessary to disturb the system and discern its sensitivity to the disturbance. This can be done either through the introduction of a catastrophic failure or by applying a small perturbation to the system. One example is increasing the crew size. Here the wide range of performance characteristics once again shows that biological systems have an inherent advantage in responding to systemic perturbations. Since the design of any space-based system depends on mass, power, and volume requirements, each subsystem must be evaluated in these terms.

Goldman, Michelle↗
NASA NTRS1992

Survey - Applications of structural optimization methods to fixed wing aircraft and spacecraft

Results of a technical survey of the practical applications of structural optimization methods in the U.S. aerospace industry through 1980s are summarized. One of the most important developments in the 80s is the more widespread acceptance of structural optimization as one of the design tools that support practical structural design. Another significant advance is the development of large software tools for production applications. Attention is also given to the tailoring of the computerized design process to the specific environment of each company. The two most important aspects of this tailoring are seamless and easy-to-use incorporation of structural optimization in the overall aerospace design/production process and multidisciplinary integration aimed at ultimate performance optimization of the final product. Some specific applications discussed include the X-29 forward swept wing demonstrator aircraft, composite wing and vertical tail program, fighter wing redesign evaluations, high speed aircraft design, and space structures.

Miura, Hirokazu↗
NASA NTRS1995

Wing-section optimization for supersonic viscous flows

The recent interest in High Speed Civil Transport (HSCT) has resulted in renewed research studies of optimized supersonic cruise transport configurations. Incorporation of flow viscosity effects in the design process of such a supersonic wing is currently under investigation. This may lead to more accurate problem formulations and, in turn, greater aerodynamic efficiency than can be obtained by the traditional, inviscid, linear theories. In this context, for a design code to be a candidate for a complex optimization problem, such as three-dimensional viscous supersonic wing design, it should be validated using simpler building-block shapes. To optimize the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wing design task, the present investigation concentrated on testing the flexibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with very similar features. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber, which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and the sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for problem formulations which should contribute to an effective wing shape optimization.

Item, Cem C.↗
NASA NTRS1999

DRACO Flowpath Performance and Environments

The Advanced Space Transportation (AST) project office has challenged NASA to design, manufacture, ground-test and flight-test an axisymmetric, hydrocarbon-fueled, flight-weight, ejector-ramjet engine system testbed no later than 2005. To accomplish this, a multi-center NASA team has been assembled. The goal of this team, led by NASA-Marshall Space Flight Center (MSFC), is to develop propulsion technologies that demonstrate rocket and airbreathing combined-cycle operation (DRACO). Current technical activities include flowpath conceptual design, engine systems conceptual design, and feasibility studies investigating the integration and operation of the DRACO engine with a Lockheed D-21B drone. This paper focuses on the activities of the Flowpath Systems Product Development Team (PDT), led by NASA-Glenn Research Center (GRC) and supported by NASA-MSFC and TechLand Research, Inc. The objective of the Flowpath PDT at the start of the DRACO program was to establish a conceptual design of the flowpath aerodynamic lines, determine the preliminary performance, define the internal environments, and support the DRACO testbed concept feasibility studies. To accomplish these tasks, the PDT convened to establish a baseline flowpath concept. With the conceptual lines defined, cycle analysis tasks were planned and the flowpath performance and internal environments were defined. Additionally, sensitivity studies investigating the effects of inlet reference area, combustion performance, and combustor/nozzle materials selection were performed to support the Flowpath PDT design process. Results of these tasks are the emphasis of this paper and are intended to verify the feasibility of the DRACO flowpath and engine system as well as identify the primary technical challenges inherent in the flight-weight design of an advanced propulsion technology demonstration engine. Preliminary cycle performance decks were developed to support the testbed concept feasibility studies but are not discussed further in this paper.

Komar, D. R.↗
NASA NTRS2009

Turboelectric Distributed Propulsion Engine Cycle Analysis for Hybrid-Wing-Body Aircraft

Meeting NASA's N+3 goals requires a fundamental shift in approach to aircraft and engine design. Material and design improvements allow higher pressure and higher temperature core engines which improve the thermal efficiency. Propulsive efficiency, the other half of the overall efficiency equation, however, is largely determined by the fan pressure ratio (FPR). Lower FPR increases propulsive efficiency, but also dramatically reduces fan shaft speed through the combination of larger diameter fans and reduced fan tip speed limits. The result is that below an FPR of 1.5 the maximum fan shaft speed makes direct drive turbines problematic. However, it is the low pressure ratio fans that allow the improvement in propulsive efficiency which, along with improvements in thermal efficiency in the core, contributes strongly to meeting the N+3 goals for fuel burn reduction. The lower fan exhaust velocities resulting from lower FPRs are also key to meeting the aircraft noise goals. Adding a gear box to the standard turbofan engine allows acceptable turbine speeds to be maintained. However, development of a 50,000+ hp gearbox required by fans in a large twin engine transport aircraft presents an extreme technical challenge, therefore another approach is needed. This paper presents a propulsion system which transmits power from the turbine to the fan electrically rather than mechanically. Recent and anticipated advances in high temperature superconducting generators, motors, and power lines offer the possibility that such devices can be used to transmit turbine power in aircraft without an excessive weight penalty. Moving to such a power transmission system does more than provide better matching between fan and turbine shaft speeds. The relative ease with which electrical power can be distributed throughout the aircraft opens up numerous other possibilities for new aircraft and propulsion configurations and modes of operation. This paper discusses a number of these new possibilities. The Boeing N2 hybrid-wing-body (HWB) is used as a baseline aircraft for this study. The two pylon mounted conventional turbofans are replaced by two wing-tip mounted turboshaft engines, each driving a superconducting generator. Both generators feed a common electrical bus which distributes power to an array of superconducting motor-driven fans in a continuous nacelle centered along the trailing edge of the upper surface of the wing-body. A key finding was that traditional inlet performance methodology has to be modified when most of the air entering the inlet is boundary layer air. A very thorough and detailed propulsion/airframe integration (PAI) analysis is required at the very beginning of the design process since embedded engine inlet performance must be based on conditions at the inlet lip rather than freestream conditions. Examination of a range of fan pressure ratios yielded a minimum Thrust-specific-fuel-consumption (TSFC) at the aerodynamic design point of the vehicle (31,000 ft /Mach 0.8) between 1.3 and 1.35 FPR. We deduced that this was due to the higher pressure losses prior to the fan inlet as well as higher losses in the 2-D inlets and nozzles. This FPR is likely to be higher than the FPR that yields a minimum TSFC in a pylon mounted engine. 1

Felder, James L.↗
NASA NTRS2022

Design of a Low-Cost, Submersible, Digital Holographic Microscope for in Situ Microbial Imaging

The methodologies for studying marine microbiology typically consist of utilizing instrumentation within a laboratory. This typically requires extracting a sample from its place of origin prior to examination, which may be days after collection. Oftentimes, the solution is to bring the lab to the ocean, which may be costly and provide further limitations for a sterile and stable laboratory environment. Here we present a low-cost, submersible, digital holographic microscope (DHM) designed to image marine microorganisms (such as bacteria and plankton) in their natural underwater environment. Our instrument eliminates the need to transport samples and allows for instantaneous data collection of microbes in-situ. The DHM achieves sub-micron spatial resolution and is paired with artificial intelligence for the detection and tracking of specimens to reduce the overall collected data. This instrument also aims to reduce the cost of manufacturing and field expenses relative to marine microbiological research. “Off the shelf” components were selected in the design process of this instrument which allows us to achieve precise results without sacrificing data quality. The DHM itself costs under one thousand dollars and features a low-cost high-resolution camera, the Arducam MT9J001. Included in the design were five main subsystems: optical, mechanical, electrical, power, and machine learning. Our on board computer and artificial intelligence consist of a Raspberry Pi 4 (8 Gb) and Google Coral USB Tensorflow accelerator. Instrument testing has successfully proven our abilities of data acquisition for at least two hours in depths of at least forty meters below sea level. Additionally, our artificial intelligence system is currently capable of tracking up to ten areas of interest in a fraction of a second with over ninety percent confidence via the neural net driven by the tensor cores on the Google Coral. Furthermore, we have demonstrated the versatility of our instrument by mounting it on an ocean-going ROV, the BlueRov2 by BlueRobotics. Our tests on the BlueRov2 exemplified the cost-effective nature of a submersible and reusable instrument that can be implemented in moderate environments and on most vessels.

Wallace, James Kent↗
DOE OSTI2020

BioSTEAMDevelopmentGroup/biosteam

BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM’s framework is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM’s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM. Through the open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts. Additionally, an agile life cycle assessment (LCA) platform has been designed to interface with BioSTEAM, BioSTEAM-LCA. This open-source, installable package allows users to perform streamlined LCAs of biorefineries. The focus of BioSTEAM-LCA is to streamline and automate early-stage environmental impact analyses of processes and technologies, and to enable rigorous sensitivity and uncertainty analyses linking process design, performance, economics, and environmental impacts.

Cortes-Peña, Yoel↗