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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

Black-Box Neural System Identification and Differentiable Programming to Improve Earth System Model Predictions February

Focal Area(s): Focal Area 2: AI for predictive modeling, including AI-derived model components, and AI-enabled applications including parameter optimization, data assimilation, and uncertainty quantification. Focal Area 1: AI-assisted data assimilation using numerical Earth system models. Science Challenge: Earth system models have structural biases that lead to uncertain predictions, and their complexity and expense makes it difficult constraining the models with data or improved physical understanding.

54 ENVIRONMENTAL SCIENCES↗

The SAND detector for the DUNE experiment

The Deep Underground Neutrino Experiment (DUNE) is a next-generation project aiming to study several neutrino properties. It will feature two experimental setups: a near detector that will be installed at Fermilab, in proximity of the neutrino-production point, and a far detector at a distance of 1300 km and 1500 m underground, at the SURF laboratory. The DUNE design and configuration will allow the study of neutrino oscillation, astrophysical neutrinos, and beyond standard model physics. The near detector complex foresees three detectors to be installed. Among these, the System for on-Axis Neutrino Detection (SAND) will serve as on-axis beam monitor, reduce the systematic uncertainties for the oscillation analysis, and search for physics beyond the standard model. SAND will be composed of three sub-detectors, surrounded by a 0.6 T superconducting magnet. The outermost detector will be a lead/scintillating-fiber electromagnetic calorimeter while the inner volume will include a 1-ton liquid argon active target placed upstream followed by a target tracker system. The SAND detector and its goals will be shown in this poster.

Alemanno, Francesca [Salento U.; INFN, Lecce]↗

Multivariable control of the Space Shuttle Remote Manipulator System

Linear controllers are designed to regulate the end effector of the Space Shuttle Remote Manipulator System (SRMS) operating in position hold mode. Design techniques used include H2 and H-infinity optimization. The nonlinear SRMS is linearized by modeling the effects of the significant nonlinearities as uncertain parameters. Each regulator design is evaluated for robust stability using both the small gain theorem with an H-infinity norm and the less conservative mu-analysis test. Regulator designs offer significant improvement over the current system for the nominal plant. Unfortunately, the SRMS model suffers from lightly damped poles with real parametric uncertainty. Under such conditions, the mu-analysis test, which allows for complex perturbations, cannot guarantee robust stability.

Adams, Neil J.↗

Substructure Synthesis: A Controls Approach

Substructure synthesis from a controls perspective is considered. An efficient and computationally robust method for synthesis of substructures is developed. The method considers the interface forces/moments as control inputs and redefines the synthesis problem in terms of obtaining a constant gain compensator which would ensure the connectivity requirements of the combined structure. Orthogonal similarity transformations are used to provide simplified synthesized dynamics of the combined system. The simplicity of form in transformed coordinates are exploited to effectively deal with modeling parametric and non-parametric uncertainties at substructure level. Uncertainty models of reasonable size and complexity are derived for the combined structure from those in the substructure models.

Maghami, Peiman G.↗

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗

Robust Solution Verification Experiments on Nonuniform Meshes

The activities of verification, validation, and uncertainty quantification (VVUQ) provide a comprehensive means to assess the credibility of computational models. Within VVUQ, solution verification assesses numerical errors and evaluates whether the simulation is sufficiently accurate for its intended applications. As computational modeling gains traction in the development of complex, high-consequence systems, the need for robust solution verification intensifies, particularly because experimental data for these systems are often limited. This work examines improvements in the robustness of Richardson extrapolation (RE), a method commonly used in solution verification to study the discretization error of computational models using a power law. Nonuniform mesh refinement is discussed alongside other pollutants that affect the robustness of the power law model. Maximum likelihood estimation (MLE) is proposed as a robust strategy to address the uncertainty generated by nonuniform mesh refinement. An exploratory computational fluid dynamics (CFD) study of a 2D planar Poiseuille flow is conducted to determine if nonuniform mesh noise can be modeled with this MLE approach for more robust RE.

Weinmeister, Justin [ORNL] (ORCID:0000000160090237↗

Sensitivity-Driven Experimental Design to Facilitate Control of Dynamical Systems

Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high-fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. Here this article proposes an optimization-centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA’s X-43 hypersonic flight tests.

42 ENGINEERING↗

Heat-Pipe Array for Large-Area Cooling

High rates of heat transfer anticipated. Prototype evaporative cold plate gathers waste heat from equipment mounted on it. Plate made by welding together flanges of several sections of heat pipe. Since plate separates liquid and vapor phases at inlet and outlet ports, eliminates complexities and uncertainties of two-phase flow in zero gravity. On earth, inlet valve enables plate to operate at relatively-large height differences with other plates in same system.

Edelstein, F.↗

A Review of Coupled Geochemical–Geomechanical Impacts in Subsurface CO 2 , H 2 , and Air Storage Systems

Increased demand for decarbonization and renewable energy has led to increasing interest in engineered subsurface storage systems for large-scale carbon reduction and energy storage. In these applications, a working fluid (CO 2 , H 2 , air, etc.) is injected into a deep formation for permanent sequestration or seasonal energy storage. The heterogeneous nature of the porous formation and the fluid–rock interactions introduce complexity and uncertainty in the fate of the injected component and host formations in these applications. Interactions between the working gas, native brine, and formation mineralogy must be adequately assessed to evaluate the efficiency, risk, and viability of a particular storage site and operational regime. This study reviews the current state of knowledge about coupled geochemical–geomechanical impacts in geologic carbon sequestration (GCS), underground hydrogen storage (UHS), and compressed air energy storage (CAES) systems involving the injection of CO 2 , H 2 , and air. Specific review topics include (1) existing injection induced geochemical reactions in these systems; (2) the impact of these reactions on the porosity and permeability of host formation; (3) the impact of these reactions on the mechanical properties of host formation; and (4) the investigation of geochemical-geomechanical process in pilot scale GCS. This study helps to facilitate an understanding of the potential geochemical–geomechanical risks involved in different subsurface energy storage systems and highlights future research needs.

08 HYDROGEN↗

Embracing fine-root system complexity in terrestrial ecosystem modeling

Projecting the dynamics and functioning of the biosphere requires a holistic consideration of whole-ecosystem processes. However, biases toward leaf, canopy, and soil modeling since the 1970s have constantly left fine-root systems being rudimentarily treated. As accelerated empirical advances in the last two decades establish clearly functional differentiation conferred by the hierarchical structure of fine-root orders and associations with mycorrhizal fungi, a need emerges to embrace this complexity to bridge the data-model gap in still extremely uncertain models. In this work, we propose a three-pool structure comprising transport and absorptive fine roots with mycorrhizal fungi (TAM) to model vertically resolved fine-root systems across organizational and spatial–temporal scales. Emerging from a conceptual shift away from arbitrary homogenization, TAM builds upon theoretical and empirical foundations as an effective and efficient approximation that balances realism and simplicity. A proof-of-concept demonstration of TAM in a big-leaf model both conservatively and radically shows robust impacts of differentiation within fine-root systems on simulating carbon cycling in temperate forests. Theoretical and quantitative support warrants exploiting its rich potentials across ecosystems and models to confront uncertainties and challenges for a predictive understanding of the biosphere. Echoing a broad trend of embracing ecological complexity in integrative ecosystem modeling, TAM may offer a consistent framework where modelers and empiricists can work together toward this grand goal.

59 BASIC BIOLOGICAL SCIENCES↗

Determination of robust stability margin for second-order systems

Robust stabilization of uncertain systems has been extensively investigated and the stability test for the whole set of uncertain parameters has been reduced to a finite number of test points, four points for the characteristic polynomial with independent coefficients. As a result the robust stability margin can be determined using a reasonable amount of computation. It is impossible to apply the results of the test to a practical system as the coefficients of the characteristic polynomial for a physical system are usually functions of uncertain parameters. However, many physical systems may be represented by a second-order mass-spring-damper system with a special multilinear form in its characteristic polynomial. This paper investigates second-order mass-spring-damper systems and the reduction of the number of test points. It is shown that such a system with arbritrary compensators always has a multilinear characteristic polynomial. It is also shown that a line in the two-dimensional parameter space forms the boundary after the mapping of a multilinear characteristic polynomial and this interior extreme line forms a conic curve in the complex plane. The boundary of uncertain domain for a multilinear polynomial with two uncertainty parameters can be determined analytically using this curve, and the four sides image of a square of the uncertain parameter. Therefore, the stability margin may be determined by checking the intersections of the boundary with the zero point. A similar procedure can be used for second-order systems with more than two uncertainty parameters when parameter optimization is used in determining the boundary.

Chuang, C.-H.↗

Uncertainty Management in Remote Sensing of Climate Data. Summary of A Workshop

Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis (NRC, 2007). Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data, including statistical methods used to calibrate and validate satellite instruments, lack an overall mathematically based framework.

Remote sensing↗

235-F GoldSim Fate and Transport Model: Uncertainty Quantification

Building 235-F was configured with two missions in mind: Actinide Billet Line (ABL) and the fabrication of Pu-238 oxide for space program applications. ABL produced Np-237 billets for use in SRS reactors, whereas the design process, fabrication, and examination of Pu-238 oxide powder occurred within the following areas, respectively: Plutonium Experimental Facility (PEF), Plutonium Fuel Form (PuFF), and Old Metallography Lab (OML). By 1990 production ceased and by 2006 de-inventory occurred; however, assays have shown significant holdup remains within ABL and PuFF. As a result, 235-F is a Category 2 nuclear facility, with plans to undergo deactivation and decommission (D and D) via In-Situ Disposal (ISD). The purpose of this project is to ensure United States Environmental Protection Agency (USEPA) groundwater radiation maximum contaminant level (MCL) and dosage standards are met during the D and D of 235-F by quantifying uncertainty through probabilistic modeling and evaluation of various ISD alternatives. GoldSim is a dynamic modeling software package with a graphical, object-oriented interface capable of capturing the influence of complex system input variability on probabilistic system outcomes. A GoldSim stochastic fate and transport model for 235-F was developed and matched with a PORFLOW deterministic model to simulate probabilistic release and flow of radionuclides from ABL and PuFF into the vadose zone, the Upper Three Runs (UTR) Aquifer, and UTR Creek. The GoldSim model was used to probabilistically evaluate four ISD scenarios against USEPA groundwater radiation MCLs and dosage standards. The deterministic 235-F GoldSim fate and transport model continues to be refined to match the results of the PORFLOW deterministic model to ensure the model accurately represents radionuclide movement through the groundwater system. The stochastic variables that are utilized within the GoldSim model are founded on the most current data; a conservative perspective is taken where needed. Alignment with the PORFLOW deterministic model, coupled with input stochastic variability, allows the probabilistic 235-F GoldSim model to capture the conservative breadth of possible outcomes for radionuclide fate within this particular system. This ensures that the USEPA MCLs and dosage limits hold even in the worst case scenarios.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analysis of Transonic Unsteady Aerodynamic Environments using Unsteady Pressure Sensitive Paint for the Space Launch System Block 1 Cargo Launch Vehicle

Predicting launch vehicle unsteady aerodynamic loads due to buffet remains a significant challenge. Current practices for modeling buffet environments involve the development of buffet forcing functions using unsteady pressure measurements acquired during wind-tunnel tests. These practices often result in significant uncertainty in buffet environments for coupled loads analyses due to the complex spatio-temporal nature of the unsteady pressure field and challenge of its estimation using discrete sensors. Unsteady pressure sensitive paint, on the other hand, can provide unsteady pressure data at a comparatively high-spatial-density and may overcome the challenge of unsteady pressure field estimation with discrete sensors and lead to improvements in the development of buffet forcing functions. In this paper, comparisons of the fluctuating pressure field are made for the Space Launch System Block 1 cargo launch vehicle measured using unsteady pressure sensitive paint and pressure transducers.

buffet↗

Strategic Technology Investment Analysis: An Integrated System Approach

Complex technology investment decisions within NASA are increasingly difficult to make such that the end results are satisfying the technical objectives and all the organizational constraints. Due to a restricted science budget environment and numerous required technology developments, the investment decisions need to take into account not only the functional impact on the program goals, but also development uncertainties and cost variations along with maintaining a healthy workforce. This paper describes an approach for optimizing and qualifying technology investment portfolios from the perspective of an integrated system model. The methodology encompasses multi-attribute decision theory elements and sensitivity analysis. The evaluation of the degree of robustness of the recommended portfolio provides the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy nontechnical constraints. The methodology is presented in the context of assessing capability development portfolios for NASA technology programs.

decision support↗

Analysis of Transonic Unsteady Aerodynamic Environments using Unsteady Pressure Sensitive Paint for the Space Launch System Block 1 Cargo Launch Vehicle

Predicting launch vehicle unsteady aerodynamic loads due to buffet remains a significant challenge. Current practices for modeling buffet environments involve the development of buffet forcing functions using discrete unsteady pressure measurements acquired during wind-tunnel tests. These practices often result in significant uncertainty in buffet environments for coupled loads analyses due to the complex spatio-temporal nature of the unsteady pressure field and the challenge of its estimation using discrete sensors. Unsteady pressure sensitive paint, on the other hand, can provide unsteady pressure data at a comparatively high spatial density and may overcome the challenge of unsteady pressure field estimation with discrete sensors and lead to improvements in the development of buffet forcing functions. In this paper, comparisons of the fluctuating pressure field are made for the Space Launch System Block 1 cargo launch vehicle measured using unsteady pressure sensitive paint and pressure transducers.

buffet↗

Analysis of Transonic Unsteady Aerodynamic Environments using Unsteady Pressure Sensitive Paint for the Space Launch System Block 1 Cargo Launch Vehicle

Predicting launch vehicle unsteady aerodynamic loads due to buffet remains a significant challenge. Current practices for modeling buffet environments involve the development of buffet forcing functions using discrete unsteady pressure measurements acquired during wind-tunnel tests. These practices often result in significant uncertainty in buffet environments for coupled loads analyses due to the complex spatio-temporal nature of the unsteady pressure field and the challenge of its estimation using discrete sensors. Unsteady pressure sensitive paint, on the other hand, can provide unsteady pressure data at a comparatively high spatial density and may overcome the challenge of unsteady pressure field estimation with discrete sensors and lead to improvements in the development of buffet forcing functions. In this paper, comparisons of the fluctuating pressure field are made for the Space Launch System Block 1 cargo launch vehicle measured using unsteady pressure sensitive paint and pressure transducers.

buffet↗

Testing Facility Uncertainty Analyses for RBCC Systems Testing

The Rocket Based Combined Cycle (RBCC) engine is expected to evolve based upon past combined-cycle propulsion test experience/data and new extensive test data. Currently, it is envisioned that a portion of the component and system testing will be pursued at NASA Stennis Space Center (SSC). To realize the greatest benefit of the test data, uncertainty analyses are being performed on the relevant RBCC components and systems to be tested at NASA SSC to ascertain the needed measurement requirements. These studies pertain to the existing E-Complex test stands as well as a new facility, E-4. This paper describes the approach used in the studies and gives examples to demonstrate the approach and the usefulness of the results. Future work will greatly increase the reliability of the test data while minimizing costs by focusing expenditures in the proper areas that are critical to program success and not allowing resources to be wasted in areas that are not significant relative to overall program goals.

Hudson, Susan T.↗