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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

TPSAS-NF1676L-12725-DND

Uncertainty analysis and robust design - increase confidence and consistency in aerospace vehicle safety predictions by developing improved methods for quantifying and managing uncertainty. Quantifying: uncertainty modeling (model uncertainty based on experimental data, simulations and/or expert opinion) and uncertainty propagation (given uncertainty models of a system’s inputs, how to propagate them through system models, to efficiently evaluate the corresponding system’s outputs?). Managing: robust design (generate designs that robustly accommodate uncertainty) and uncertainty decomposition (identify uncertainties that contribute the most to performance degradation and determine the parameters that should (not) be modeled as uncertain).

Sean P Kenny↗
DOE OSTI2024

Toward digital design at the exascale: An overview of project ICECap

High performance computing has entered the Exascale Age. Capable of performing over 1018 floating point operations per second, exascale computers, such as El Capitan, the National Nuclear Security Administration's first, have the potential to revolutionize the detailed in-depth study of highly complex science and engineering systems. However, in addition to these kind of whole machine “hero” simulations, exascale systems could also enable new paradigms in digital design by making petascale hero runs routine. Currently, untenable problems in complex system design, optimization, model exploration, and scientific discovery could all become possible. Motivated by the challenge of uncovering the next generation of robust high-yield inertial confinement fusion (ICF) designs, project ICECap (Inertial Confinement on El Capitan) attempts to integrate multiple advances in machine learning (ML), scientific workflows, high performance computing, GPU-acceleration, and numerical optimization to prototype such a future. Built on a general framework, ICECap is exploring how these technologies could broadly accelerate scientific discovery on El Capitan. In addition to our requirements, system-level design, and challenges, we describe some of the key technologies in ICECap, including ML replacements for multiphysics packages, tools for human-machine teaming, and algorithms for multifidelity design optimization under uncertainty. As a test of our prototype pre-El Capitan system, we advance the state-of-the art for ICF hohlraum design by demonstrating the optimization of a 17-parameter National Ignition Facility experiment and show that our ML-assisted workflow makes design choices that are consistent with physics intuition, but in an automated, efficient, and mathematically rigorous fashion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Targeted Adaptive Design

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.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Scalable foundation models for numerical simulations on HPC platforms

In recent years, foundation models (FMs) have begun to reshape numerical simulations on high-performance computing (HPC) platforms. These large, pre-trained AI models enable rapid predictions across a broad range of physical domains, including Earth system modeling, fluid dynamics, materials science, as well as complex multi-modal simulations in aerospace engineering and fusion research. By training on diverse datasets, FMs learn intricate relationships and underlying physical behavior while also enabling the quantification of uncertainty in their predictions. This capability allows simulations that once required days of numerical calculation to be completed in minutes (FM inference), supporting real-time design optimization, uncertainty-aware decision making, and more comprehensive exploration of complex scenarios.

AI↗
NASA NTRS1989

Infrared-fiber-optic fire sensor developments - Role of measurement uncertainty in evaluation of background limited range

Fire-detector systems based on distributed infrared fiber-sensors have been investigated for potential applications in the aerospace industry. Responsivities to blackbody and flame radiations were measured with various design configurations of an infrared fiber-optic sensor. Signal processing techniques were also investigated, and the results show significant differences in the fire-sensor performance depending on the design configuration. Measurement uncertainties were used to determine the background-limited ranges for the various fire-sensor concepts, and the probability of producing false alarms caused by fluctuations in the background signals were determined using extreme probability theory. The results of the research show that infrared fiber-optic fire sensors are feasible for application on manned spacecraft; however, additional development work will be required to eliminate false alarms caused by high temperature objects such as incandescent lamps.

Tapphorn, Ralph M.↗
DOE OSTI2022

Design and execution of a verification, validation, and uncertainty quantification plan for a numerical model of left ventricular flow after LVAD implantation

Left ventricular assist devices (LVADs) are implantable pumps that act as a life support therapy for patients with severe heart failure. Despite improving the survival rate, LVAD therapy can carry major complications. Particularly, the flow distortion introduced by the LVAD in the left ventricle (LV) may induce thrombus formation. While previous works have used numerical models to study the impact of multiple variables in the intra-LV stagnation regions, a comprehensive validation analysis has never been executed. The main goal of this work is to present a model of the LV-LVAD system and to design and follow a verification, validation and uncertainty quantification (VVUQ) plan based on the ASME V&V40 and V&V20 standards to ensure credible predictions. The experiment used to validate the simulation is the SDSU cardiac simulator, a bench mock-up of the cardiovascular system that allows mimicking multiple operation conditions for the heart-LVAD system. The numerical model is based on Alya, the BSC’s in-house platform for numerical modelling. Alya solves the Navier-Stokes equation with an Arbitrary Lagrangian-Eulerian (ALE) formulation in a deformable ventricle and includes pressure-driven valves, a 0D Windkessel model for the arterial output and a LVAD boundary condition modeled through a dynamic pressure-flow performance curve. The designed VVUQ plan involves: (a) a risk analysis and the associated credibility goals; (b) a verification stage to ensure correctness in the numerical solution procedure; (c) a sensitivity analysis to quantify the impact of the inputs on the four quantities of interest (QoIs) (average aortic root flow $Q^{avg}_{Ao}$, maximum aortic root flow $Q^{max}_{Ao}$, average LVAD flow $Q^{avg}_{VAD}$, and maximum LVAD flow $Q^{max}_{VAD}$; (d) an uncertainty quantification using six validation experiments that include extreme operating conditions. Numerical code verification tests ensured correctness of the solution procedure and numerical calculation verification showed a grid convergence index (GCI)95% <3.3%. The total Sobol indices obtained during the sensitivity analysis demonstrated that the ejection fraction, the heart rate, and the pump performance curve coefficients are the most impactful inputs for the analysed QoIs. The Minkowski norm is used as validation metric for the uncertainty quantification. It shows that the midpoint cases have more accurate results when compared to the extreme cases. The total computational cost of the simulations was above 100 [core-years] executed in around three weeks time span in Marenostrum IV supercomputer. This work details a novel numerical model for the LV-LVAD system, that is supported by the design and execution of a VVUQ plan created following recognised international standards. We present a methodology demonstrating that stringent VVUQ according to ASME standards is feasible but computationally expensive.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Coal-Based Fuel-Cell Powerplants

Report assesses advanced technologyy design alternatives for integrated coal-gasifier/fuel-cell powerplants. Various gasifier, cleanup, and fuelcell options evaluated. Evaluation includes adjustments to assumed performances and costs of proposed technologies where required. Analysis identifies uncertainties remaining in designs and most promising alternatives and research and development required to develop these technologies. Bulk of report summary and detailed analysis of six major conceptual designs and variations of each. All designs for plant that uses Illinois No. 6 coal and produces 675 MW of net power.

Ferral, J. F.↗
DOE OSTI2021

Quantifying the Multi-Objective Cost of Uncertainty

Various real-world applications involve modeling complex systems with immense uncertainty and optimizing multiple objectives based on the uncertain model. Quantifying the impact of the model uncertainty on the given operational objectives is critical for designing optimal experiments that can most effectively reduce the uncertainty that affect the objectives pertinent to the application at hand. In this paper, we propose the concept of mean multi-objective cost of uncertainty (multi-objective MOCU) that can be used for objective-based quantification of uncertainty for complex uncertain systems considering multiple operational objectives. We provide several illustrative examples that demonstrate the concept and strengths of the proposed multi-objective MOCU. Furthermore, we present a real-world example based on the mammalian cell cycle network to demonstrate how the multi-objective MOCU can be used for quantifying the operational impact of model uncertainty when there are multiple, possibly competing, objectives.

42 ENGINEERING↗
NASA NTRS2011

JPL Thermal Design Modeling Philosophy and NASA-STD-7009 Standard for Models and Simulations - A Case Study

The Standard JPL thermal engineering practice prescribes worst-case methodologies for design. In this process, environmental and key uncertain thermal parameters (e.g., thermal blanket performance, interface conductance, optical properties) are stacked in a worst case fashion to yield the most hot- or cold-biased temperature. Thus, these simulations would represent the upper and lower bounds. This, effectively, represents JPL thermal design margin philosophy. Uncertainty in the margins and the absolute temperatures is usually estimated by sensitivity analyses and/or by comparing the worst-case results with "expected" results. Applicability of the analytical model for specific design purposes along with any temperature requirement violations are documented in peer and project design review material. In 2008, NASA released NASA-STD-7009, Standard for Models and Simulations. The scope of this standard covers the development and maintenance of models, the operation of simulations, the analysis of the results, training, recommended practices, the assessment of the Modeling and Simulation (M&S) credibility, and the reporting of the M&S results. The Mars Exploration Rover (MER) project thermal control system M&S activity was chosen as a case study determining whether JPL practice is in line with the standard and to identify areas of non-compliance. This paper summarizes the results and makes recommendations regarding the application of this standard to JPL thermal M&S practices.

thermal blanket performance↗
NASA NTRS1981

Multiobjective insensitive design of airplane control systems with uncertain parameters

A multiobjective computer-aided design algorithm has been developed which minimizes the sensitivity of the design objectives to uncertainties in system parameters. The more important uncertain parameters are described by a gaussian random vector with known covariance matrix, and a vector sensitivity objective function is defined as the probabilities that the design objectives will violate specified requirements constraints. Control system parameters are found which minimize the sensitivity vector in a Pareto-optimal sense, using constrained minimization algorithms. Example results are shown for lateral stability augmentation system (SAS) design for three Shuttle flight conditions.

Schy, A. A.↗
NASA NTRS1972

Design of minimax output feedback controller for system with parameter uncertainty

The problem of controlling a time-invariant system with parameter uncertainty is considered with incomplete state feedback. The controller is designed by minimaximizing a quadratic performance criterion and a sensitivity (or loss) criterion, involving the state of the system, the control, and the uncertainty vector. The resulting optimal controller is linear and optimal feedback gain matrix must satisfy a set of nonlinear algebraic equations. some algorithms for algebraic minimax problems are presented.

Basuthakur, S.↗
NASA NTRS1998

Towards a Probabilistic Criterion for Preliminary Shell Design

Thin-walled stiffened or unstiffened, metallic or composite shells are widely used structural elements in aeronautical and space applications. Buckling strength, which is a major concern in all these areas, is affected by the uncertainties in the definition of loads, material properties, geometric variables, engineering models and the accuracy of the analysis tools used in the design phase. The NASA design criteria monographs from the late sixties account for these design uncertainties by the use of a lump sum safety factor or the so-called "knockdown" factor gamma, which usually results in an overly conservative design. In the present paper a new, reliability based, probabilistic design procedure for buckling critical imperfect isotropic shells is proposed. It essentially consists of a stochastic approach based on a new, improved "knockdown" factor lambda(sub a) that is not as conservative as the traditional one. It is felt that by quantifying and understanding the "problem uncertainties" such as initial imperfections and their influence on the design variables, one can develop a better engineered, better designed and safer system.

Arbocz, Johann↗
NASA NTRS2011

Fission Power System Technology for NASA Exploration Missions

Under the NASA Exploration Technology Development Program, and in partnership with the Department of Energy (DOE), NASA is conducting a project to mature Fission Power System (FPS) technology. A primary project goal is to develop viable system options to support future NASA mission needs for nuclear power. The main FPS project objectives are as follows: 1) Develop FPS concepts that meet expected NASA mission power requirements at reasonable cost with added benefits over other options. 2) Establish a hardware-based technical foundation for FPS design concepts and reduce overall development risk. 3) Reduce the cost uncertainties for FPS and establish greater credibility for flight system cost estimates. 4) Generate the key products to allow NASA decisionmakers to consider FPS as a preferred option for flight development. In order to achieve these goals, the FPS project has two main thrusts: concept definition and risk reduction. Under concept definition, NASA and DOE are performing trade studies, defining requirements, developing analytical tools, and formulating system concepts. A typical FPS consists of the reactor, shield, power conversion, heat rejection, and power management and distribution (PMAD). Studies are performed to identify the desired design parameters for each subsystem that allow the system to meet the requirements with reasonable cost and development risk. Risk reduction provides the means to evaluate technologies in a laboratory test environment. Non-nuclear hardware prototypes are built and tested to verify performance expectations, gain operating experience, and resolve design uncertainties.

Mason, Lee↗
DOE OSTI2022

PyApprox: Enabling efficient model analysis

PyApprox is a Python-based one-stop-shop for probabilistic analysis of scientific numerical models. Easy to use and extendable tools are provided for constructing surrogates, sensitivity analysis, Bayesian inference, experimental design, and forward uncertainty quantification. The algorithms implemented represent the most popular methods for model analysis developed over the past two decades, including recent advances in multi-fidelity approaches that use multiple model discretizations and/or simplified physics to significantly reduce the computational cost of various types of analyses. Simple interfaces are provided for the most commonly-used algorithms to limit a user’s need to tune the various hyper-parameters of each algorithm. However, more advanced work flows that require customization of hyper-parameters is also supported. An extensive set of Benchmarks from the literature is also provided to facilitate the easy comparison of different algorithms for a wide range of model analyses. This paper introduces PyApprox and its various features, and presents results demonstrating the utility of PyApprox on a benchmark problem modeling the advection of a tracer in ground water.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

The GPM Combined Algorithm

In this paper, the operational Global Precipitation Measurement (GPM) mission combined radar-radiometer algorithm is thoroughly described. The operational combined algorithm is designed to reduce uncertainties in GPM Core Observatory precipitation estimates by effectively integrating complementary information from the GPM Dual-Frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI) into an optimal, physically consistent precipitation product. Although similar in many respects to previously developed combined algorithms, the GPM combined algorithm has several unique features that are specifically designed to meet the GPM objectives of deriving, based on GPM Core Observatory information, accurate and physically consistent precipitation estimates from multiple spaceborne instruments, and ancillary environmental data from reanalyses. The algorithm features an optimal estimation framework based on a statistical formulation of the Gauss-Newton method, a parameterization for the nonuniform distribution of precipitation within the radar fields of view, a methodology to detect and account for multiple scattering in Ka-band DPR observations, and a statistical deconvolution technique that allows for an efficient sequential incorporation of radiometer information into DPR precipitation retrievals.

Grecu, Mircea↗
NASA NTRS1984

Reliability considerations for the total strain range version of strainrange partitioning

A proposed total strainrange version of strainrange partitioning (SRP) to enhance the manner in which SRP is applied to life prediction is considered with emphasis on how advanced reliability technology can be applied to perform risk analysis and to derive safety check expressions. Uncertainties existing in the design factors associated with life prediction of a component which experiences the combined effects of creep and fatigue can be identified. Examples illustrate how reliability analyses of such a component can be performed when all design factors in the SRP model are random variables reflecting these uncertainties. The Rackwitz-Fiessler and Wu algorithms are used and estimates of the safety index and the probablity of failure are demonstrated for a SRP problem. Methods of analysis of creep-fatigue data with emphasis on procedures for producing synoptic statistics are presented. An attempt to demonstrate the importance of the contribution of the uncertainties associated with small sample sizes (fatique data) to risk estimates is discussed. The procedure for deriving a safety check expression for possible use in a design criteria document is presented.

Wirsching, P. H.↗
DOE OSTI2025

AI Benchmark Democratization and Carpentry

Benchmarks are a cornerstone of modern machine learning, enabling reproducibility, comparison, and scientific progress. However, AI benchmarks are increasingly complex, requiring dynamic, AI-focused workflows. Rapid evolution in model architectures, scale, datasets, and deployment contexts makes evaluation a moving target. Large language models often memorize static benchmarks, causing a gap between benchmark results and real-world performance. Beyond traditional static benchmarks, continuous adaptive benchmarking frameworks are needed to align scientific assessment with deployment risks. This calls for skills and education in AI Benchmark Carpentry. From our experience with MLCommons, educational initiatives, and programs like the DOE's Trillion Parameter Consortium, key barriers include high resource demands, limited access to specialized hardware, lack of benchmark design expertise, and uncertainty in relating results to application domains. Current benchmarks often emphasize peak performance on top-tier hardware, offering limited guidance for diverse, real-world scenarios. Benchmarking must become dynamic, incorporating evolving models, updated data, and heterogeneous platforms while maintaining transparency, reproducibility, and interpretability. Democratization requires both technical innovation and systematic education across levels, building sustained expertise in benchmark design and use. Benchmarks should support application-relevant comparisons, enabling informed, context-sensitive decisions. Dynamic, inclusive benchmarking will ensure evaluation keeps pace with AI evolution and supports responsible, reproducible, and accessible AI deployment. Community efforts can provide a foundation for AI Benchmark Carpentry.

von Laszewski, Gregor [Virginia U.]↗