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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

A Near-Term Concept for Trajectory Based Operations with Air/Ground Data Link Communication

An operating concept and required system components for trajectory-based operations with air/ground data link for today's en route and transition airspace is proposed. Controllers are fully responsible for separation as they are today, and no new aircraft equipage is required. Trajectory automation computes integrated solutions to problems like metering, weather avoidance, traffic conflicts and the desire to find and fly more time/fuel efficient flight trajectories. A common ground-based system supports all levels of aircraft equipage and performance including those equipped and not equipped for data link. User interface functions for the radar controller's display make trajectory-based clearance advisories easy to visualize, modify if necessary, and implement. Laboratory simulations (without human operators) were conducted to test integrated operation of selected system components with uncertainty modeling. Results are based on 102 hours of Fort Worth Center traffic recordings involving over 37,000 individual flights. The presence of uncertainty had a marginal effect (5%) on minimum-delay conflict resolution performance, and windfavorable routes had no effect on detection and resolution metrics. Flight plan amendments and clearances were substantially reduced compared to today s operations. Top-of-descent prediction errors are the largest cause of failure indicating that better descent predictions are needed to reliably achieve fuel-efficient descent profiles in medium to heavy traffic. Improved conflict detections for climbing flights could enable substantially more continuous climbs to cruise altitude. Unlike today s Conflict Alert, tactical automation must alert when an altitude amendment is entered, but before the aircraft starts the maneuver. In every other failure case tactical automation prevented losses of separation. A real-time prototype trajectory trajectory-automation system is running now and could be made ready for operational testing at an en route Center in 1-2 years.

McNally, David↗
NASA NTRS2011

Direct Numerical Simulations of Transitional/Turbulent Wakes

The interest in transitional/turbulent wakes spans the spectrum from an intellectual pursuit to understand the complex underlying physics to a critical need in aeronautical engineering and other disciplines to predict component/system performance and reliability. Cylinder wakes have been studied extensively over several decades to gain a better understanding of the basic flow phenomena that are encountered in such flows. Experimental, computational and theoretical means have been employed in this effort. While much has been accomplished there are many important issues that need to be resolved. The physics of the very near wake of the cylinder (less than three diameters downstream) is perhaps the most challenging of them all. This region comprises the two detached shear layers, the recirculation region and wake flow. The interaction amongst these three components is to some extent still a matter of conjecture. Experimental techniques have generated a large percentage of the data that have provided us with the current state of understanding of the subject. More recently computational techniques have been used to simulate cylinder wakes, and the data from such simulations are being used to both refine our understanding of such flows as well as provide new insights. A few large eddy and direct numerical simulations (LES and DNS) of cylinder wakes have appeared in the literature in the recent past. These investigations focus on the low Reynolds number range where the cylinder boundary layer is laminar (sub-critical range). However, from an engineering point of view, there is considerable interest in the situation where the upper and/or lower boundary layer of an airfoil is turbulent, and these turbulent boundary layers separate from the airfoil to contribute to the formation of the wake downstream. In the case of cylinders, this only occurs at relatively large unit Reynolds numbers. However, in the case of airfoils, the boundary layer has the opportunity to transition to turbulence on the airfoil surface at a relatively lower unit Reynolds number because the characteristic length of the airfoil is typically one to two orders of magnitude larger than the trailing edge diameter. This transition to turbulence would occur unless there is a strong favorable pressure gradient that results in the boundary layer remaining laminar or transitional over the surface of the airfoil. This presentation will focus on two direct numerical simulations that have been performed at NASA ARC. The first is of a cylinder wake with laminar separating boundary layers. The second is the wake of a flat plate with a circular trailing edge. The upper and lower plate surface boundary layers are both turbulent and statistically identical. Thus the computed wake is symmetric in a statistical sense. This flow is more representative of airfoil wakes than cylinder wakes. Results from the two simulations including flow visualization and turbulence statistics in the near wake will be presented at the seminar.

wakes↗
NASA NTRS2016

Status of Computational Aerodynamic Modeling Tools for Aircraft Loss-of-Control

A concerted effort has been underway over the past several years to evolve computational capabilities for modeling aircraft loss-of-control under the NASA Aviation Safety Program. A principal goal has been to develop reliable computational tools for predicting and analyzing the non-linear stability & control characteristics of aircraft near stall boundaries affecting safe flight, and for utilizing those predictions for creating augmented flight simulation models that improve pilot training. Pursuing such an ambitious task with limited resources required the forging of close collaborative relationships with a diverse body of computational aerodynamicists and flight simulation experts to leverage their respective research efforts into the creation of NASA tools to meet this goal. Considerable progress has been made and work remains to be done. This paper summarizes the status of the NASA effort to establish computational capabilities for modeling aircraft loss-of-control and offers recommendations for future work.

Frink, Neal T.↗
NASA NTRS2017

PHM Enabled Autonomous Propellant Loading Operations

The utility of Prognostics and Health Management (PHM) software capability applied to Autonomous Operations (AO) remains an active research area within aerospace applications. The ability to gain insight into which assets and subsystems are functioning properly, along with the derivation of confident predictions concerning future ability, reliability, and availability, are important enablers for making sound mission planning decisions. When coupled with software that fully supports mission planning and execution, an integrated solution can be developed that leverages state assessment and estimation for the purposes of delivering autonomous operations. The authors have been applying this integrated, model-based approach to the autonomous loading of cryogenic spacecraft propellants at Kennedy Space Center.

Walker, Mark↗
NASA NTRS2018

Prognostics As-A-Service (PaaS)

Deep awareness of aircraft system health-state is critical for maintaining safe, efficient growth in global operations and enabling autonomy. Maintainers, operators, controllers, dispatchers, pilots, and autonomous systems must have reliable real-time predictions of vehicle health to preserve safety and efficiency. We will explore the feasibility and challenges of cloud enhanced prognostics. Aircraft request PaaS in flight to supplement onboard systems or provide complete health awareness. We will explore and demonstrate the ability to address six major challenges of PaaS: Generality, Environmental Complexity, Utility, Trust, Communications, and Security. We will also explore the factors in the decision to host prognostics onboard vs As-A-Service.

Prognostics As A Service↗
NASA NTRSDate not supplied

A Technology Maturation Plan for the Development of Nuclear Electric Propulsion

Over the last two years NASA’s Space Nuclear Propulsion (SNP) Project formulated a Technology Maturation Plan (TMP) for development of the sub-systems needed for a MW-class Nuclear Electric Propulsion (NEP) system which, combined with a high thrust chemical propulsion stage, would be suitable for human missions to Mars. Two recent assessments, independently conducted by the National Academies for Science, Engineering, and Medicine and the NASA Engineering & Safety Center, concluded that the technologies required for a high-power NEP system are immature and the attendant risks insufficiently quantified to justify initiating a flight project. For NEP to be available as a viable option to meet flight opportunities in the late 2030s / 2040s time frame, development of the key sub-systems must begin now. SNP has subdivided the NEP system into five Critical Technology Elements (CTE): the nuclear reactor, power conversion, power management and distribution, electric propulsion sub-system, and the primary heat rejection system. Development plans for each of these CTEs have been drafted which will serve as the template for a focused milestone-driven research and development campaign intended to advance each CTE to Technology Readiness Level (TRL) 5. This will be accomplished by building and testing hardware at relevant power levels (~ 1 MW) and for relevant durations (2,500 hours, ~10% of the required operational lifetime) and conducting numerical modeling of the CTEs anchored by the accumulated test data to predict system performance and reliability. Concurrent with this work, high-level coupled system/mission modeling will be carried out to refine the key performance parameters that the various CTEs must achieve. Non-advocate reviews will be held at milestone points to assess progress and inform down-select decisions. The strategy for formulating the TMP was described previously; this paper describes ongoing progress on the drafting and baselining of the plan, including key specific details.

Space Nuclear Propulsion↗
NASA NTRSDate not supplied

A Technology Maturation Plan for the Development of Nuclear Electric Propulsion

Over the last two years NASA’s Space Nuclear Propulsion (SNP) Project formulated a Technology Maturation Plan (TMP) for development of the sub-systems needed for a MW-class Nuclear Electric Propulsion (NEP) system which, combined with a high thrust chemical propulsion stage, would be suitable for human missions to Mars. Two recent assessments, independently conducted by the National Academies for Science, Engineering, and Medicine and the NASA Engineering & Safety Center, concluded that the technologies required for a high-power NEP system are immature and the attendant risks insufficiently quantified to justify initiating a flight project. For NEP to be available as a viable option to meet flight opportunities in the late 2030s / 2040s time frame, development of the key sub-systems must begin now. SNP has subdivided the NEP system into five Critical Technology Elements (CTE): the nuclear reactor, power conversion, power management and distribution, electric propulsion sub-system, and the primary heat rejection system. Development plans for each of these CTEs have been drafted which will serve as the template for a focused milestone-driven research and development campaign intended to advance each CTE to Technology Readiness Level (TRL) 5. This will be accomplished by building and testing hardware at relevant power levels (~ 1 MW) and for relevant durations (2,500 hours, ~10% of the required operational lifetime) and conducting numerical modeling of the CTEs anchored by the accumulated test data to predict system performance and reliability. Concurrent with this work, high-level coupled system/mission modeling will be carried out to refine the key performance parameters that the various CTEs must achieve. Non-advocate reviews will be held at milestone points to assess progress and inform down-select decisions. The strategy for formulating the TMP was described previously*; this paper describes ongoing progress on the drafting and baselining of the plan, including key specific details. * “Strategy for Developing Technologies for Megawatt-class Nuclear Electric Propulsion Systems”, K.A. Polzin, et. al., International Electric Propulsion Conference IEPC 2022, IEPC-2022-155

Nuclear Electric Propulsion↗
NASA NTRS2023

Evaluation of Elements used for Manufacturing of NanoLam Metallized Polymer Film Capacitors

Metallized polymer film capacitors (MPFC) manufactured by NanoLam technology have a better volumetric efficiency and performance that may exceed the reliability of conventional MPFCs typically used in power and high voltage systems that require high insulation resistance and low power losses. These capacitors can be also an effective replacement for electrolytic and stacked ceramic capacitors currently used in space applications looking to save significant volume and mass. This report evaluates the effects of environmental conditions including radiation and storage at room and high temperatures on the characteristics of NanoLam elements used in the production of MPFCs. Assessments of the reliability acceleration factors and predictions for the useful life are made based on highly accelerated life tests (HALT) using distributions of times to parametric failures at different stress conditions. It has been shown that even a relatively small amount of moisture absorbed at room environments in the dielectric layers may substantially change the probability of failure. In the presence of moisture, degradation processes that started after voltage application continue with time during storage.

Metallized polymer film capacitors (MPFC)↗
DOE OSTI2024

Integrating Multi-Source Data for Bi-Level Traffic Simulator Calibration: A Literature Review and Highway Case Study

Traffic simulation serves as a powerful tool for pre-evaluating policies and technologies. In this context, simulation-based Dynamic traffic assignment (DTA) models are capable of capturing traffic dynamics. They are well-known as critical tools in controlling and predicting traffic situations. The reliability of simulation results heavily depends on the calibration process. Most studies in the literature formulate and calibrate simulators based on a single source of collected data or multiple data sets with the same spatiotemporal characteristics. However, in practice, traffic data is collected by various tools with usually different spatial and temporal resolutions. This study introduces a novel approach to taking into account diverse input data from a variety of sources. An iterative bi-level solution is proposed. to equally treat traffic flow and speed data. The upper level solves flow calibration with the exact solution method, and the lower level calibrates the speed with the simultaneous perturbation stochastic approximation (SPSA) algorithm. Subsequently, the effectiveness of the proposed model is investigated using data from a six-mile section of Nashville's I-24 highway in Tennessee. The results demonstrate that our proposed model creates an effective feedback loop between the optimizer and the simulator for calibrating flow and speed to reduce the error between simulated and real data.

42 ENGINEERING↗
DOE OSTI2025

Demand response of loads having thermal reserves

Systems and methods are described herein that improve grid performance by smoothing demand using thermal reserves. The smoothed demand can reduce peak loads as well as the ramp rate of demand that will otherwise require the use of inefficient, expensive generation sources. These improvements are tied to the selective switching on or off electrical loads that are coupled to thermal reserves, effectively using the thermal reserves as an energy storage mechanism. Historical data of past usage can be used to create load model and ensure that effects on customer comfort are minimized while still accomplishing the beneficial effects for the overall grid, which enables grid owners to both reduce their operational cost by avoiding expensive generation and improve system reliability by achieving more predictable power demand.

Ren, Wei↗
DOE OSTI2021

Machine Learning Models to Predict Inhibition of the Bile Salt Export Pump

Cholestatic liver injury is frequently associated with drug inhibition of bile salt transporters, such as the bile salt export pump (BSEP). Reliable in silico models to predict BSEP inhibition directly from chemical structures would significantly reduce costs during drug discovery and could help avoid injury to patients. We report our development of classification and regression models for BSEP inhibition with substantially improved performance over previously published models. We assessed the performance effects of different methods of chemical featurization, data set partitioning, and class labeling and identified the methods producing models that generalized best to novel chemical entities.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Modeling 3-D objects with planar surfaces for prediction of electromagnetic scattering

Electromagnetic scattering analysis of objects at resonance is difficult because low frequency techniques are slow and computer intensive, and high frequency techniques may not be reliable. A new technique for predicting the electromagnetic backscatter from electrically conducting objects at resonance is studied. This technique is based on modeling three dimensional objects as a combination of flat plates where some of the plates are blocking the scattering from others. A cube is analyzed as a simple example. The preliminary results compare well with the Geometrical Theory of Diffraction and with measured data.

Koch, M. B.↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗
DOE OSTI2023

Development of a Systematic and Extensible Force Field for Peptoids (STEPs)

Peptoids (N-substituted glycines) are a class of biomimetic polymers that have attracted significant attention due to their accessible synthesis and enzymatic and thermal stability relative to their naturally occurring counterparts (polypeptides). While these polymers provide the promise of more robust functional materials via hierarchical approaches, they present a new challenge for computational structure prediction for material design. The reliability of calculations hinges on the accuracy of interactions represented in the force field used to model peptoids. For proteins, structure prediction based on sequence and de novo design has made dramatic progress in recent years; however, these models are not readily transferable for peptoids. Current efforts to develop and implement peptoid-specific force fields are spread out, leading to replicated efforts and a fragmented collection of parameterized sidechains. Here, we developed a peptoid-specific force field containing 70 different side chains, using GAFF2 as starting point. The new model is validated based on the generation of Ramachandran-like plots from DFT optimization compared against force field reproduced potential energy and free energy surfaces as well as the reproduction of equilibrium cis/trans values for some residues experimentally known to form helical structures. In conclusion, equilibrium cis/trans distributions (Kct) are estimated for all parameterized residues to identify which residues have an intrinsic propensity for cis or trans states in the monomeric state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

A review of propeller noise prediction methodology: 1919-1994

This report summarizes a review of the literature regarding propeller noise prediction methods. The review is divided into six sections: (1) early methods; (2) more recent methods based on earlier theory; (3) more recent methods based on the Acoustic Analogy; (4) more recent methods based on Computational Acoustics; (5) empirical methods; and (6) broadband methods. The report concludes that there are a large number of noise prediction procedures available which vary markedly in complexity. Deficiencies in accuracy of methods in many cases may be related, not to the methods themselves, but the accuracy and detail of the aerodynamic inputs used to calculate noise. The steps recommended in the report to provide accurate and easy to use prediction methods are: (1) identify reliable test data; (2) define and conduct test programs to fill gaps in the existing data base; (3) identify the most promising prediction methods; (4) evaluate promising prediction methods relative to the data base; (5) identify and correct the weaknesses in the prediction methods, including lack of user friendliness, and include features now available only in research codes; (6) confirm the accuracy of improved prediction methods to the data base; and (7) make the methods widely available and provide training in their use.

Metzger, F. Bruce↗
DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Assessment of software methods for estimating protein-protein relative binding affinities

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83–98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Universality between vector-like and chiral quiver gauge theories: anomalies and domain walls

We study low-energy dynamics of [SU($\textit{N}$)]$^K$ chiral quiver gauge theories in connection with $\mathcal{N}$ = 1 super Yang-Mills (SYM) theory, and quantum chromodynamics with bi-fundamental fermions (QCD(BF)). These theories can be obtained by $\mathbb Z_K$ orbifold projections of $\mathcal{N}$ = 1 SU($\textit{N K}$) SYM theory, but the perturbative planar equivalence does not extend nonperturbatively for $\textit{K}$ ≥ 3. In order to study low-energy behaviors, we analyze these systems using ’t Hooft anomaly matching and reliable semiclassics on $\mathbb R^3 × S^1$. Thanks to ’t Hooft anomaly that involves 1-form center symmetry and discrete chiral symmetry, we predict that chiral symmetry must be spontaneously broken in the confinement phase, and there exist $\textit{N}$ vacua. Theories with even $\textit{K}$ possess a physical θ angle despite the presence of massless fermions, and we further predict the $\textit{N}$-branch structure associated with it; the number of vacua is enhanced to 2$\textit{N}$ at θ = π due to spontaneous $\textit{C P}$ breaking. Both of these predictions are explicitly confirmed by reliable semiclassics on $\mathbb R^3 × S^1$ with the double-trace deformation. Symmetry and anomaly of odd-$\textit{K}$ theories are the same as those of the $\mathcal{N}$ = 1 SYM, and the ones of even-$\textit{K}$ theories are same as those of QCD(BF). We unveil why there exists universality between vector-like and chiral quiver theories, and conjecture that their ground states can be continuously deformed without quantum phase transitions. We briefly discuss anomaly inflow on the domain walls connecting the vacua of the theory and possible anomaly matching scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗