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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Testing in Support of the Development of EPP Plus SMT Design Method at ORNL (FY2021)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY21. This report focuses on the methodology for developing the EPP+SMT creep-fatigue (CF) design curves at low strain ranges. The creep damage-based method and dissipated work-based method were used to evaluate the available CF data at the low strain range region. A set of failure criteria were determined, and a simple extrapolation method was developed to predict the CF life cycles at low strain ranges that are not accessible by experiments due to the extraordinarily long failure times at the low strain region (thousands to hundreds of thousands of years) and the inability of the test machine to control these small strain ranges due to the signal to noise issues. An experimental method with the concept of block-strain range CF testing was proposed to generate the information needed to extrapolate the CF design curves to low strain ranges. Based on this new testing approach, a preliminary EPP+SMT CF design curve was developed for Alloy 617 at 950°C with tension hold time of 100 s. The analysis in this report shows the potential of generating a set of EPP+SMT CF design curves with different hold times within a reasonable amount of time and testing effort. Based on such a progress, a hold time extrapolation procedure for low strain ranges will be developed in FY22 and critical testing will be carried out to complete the development of the EPP+SMT CF design curves for Alloy 617.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Toward an electrical power utility for space exploration

Plans for space exploration depend on today's technology programs addressing the novel requirements of space-based enterprise. The requirements for electrical power will be formidable: megawatts in magnitude, reliability for multi-year missions and the flexibility to adapt to needs unanticipated at design time. The reasons for considering the power management and distribution in the various systems from a total mission perspective, rather than simply extrapolating current spacecraft design practice, are discussed. A utility approach to electric power being developed at the Lewis Research Center is described. It integrates requirements from a broad selection of current development programs with studies in which both space and terrestrial technologies are conceptually applied to exploration mission scenarios.

Bercaw, Robert W.↗
DOE OSTI2025

Multi-faceted framework for extrapolating early age flexural strength to facilitate rapid lifting/handling of high-volume fly ash precast members

Maintaining adequate early-age structural performance for precast concrete components has grown in importance as more sustainable mix designs become more widespread. Achieving high-early flexural strength is particularly crucial to facilitate rapid removal of hardened concrete components from formwork, often within 24 h after fresh concrete placement. Limited research has assessed the effectiveness of traditional design methods in correlating flexural strength with compressive strength for next-generation mix designs, or demonstrated extrapolation of such material performance to larger-scale structural tests. This paper presents a multi-faceted framework to reassess early-age flexural strength for concretes made with relatively high proportions of fly ash from both fresh and harvested sources. Here, the framework provides several pathways, from which the user can select based upon available resources and the specific application, to improve accuracy of early-age cracking moment calculations. Furthermore, the scope includes evaluation of strength performance under curing conditions emulative of those in a precast facility, recommending modulus of rupture equations which are more performance-driven than current design provisions, and experimental tests on prefabricated concrete beams to validate the proposed methodologies. Correlations of early-age strength with both concrete age and maturity measurements compare the effectiveness of utilizing in-situ data to further enhance the prediction methods. Ultimately, the proposed framework helped reduce errors when calculating cracking moment capacity at early ages by tailoring calculations to reflect mix-dependent behavior. Furthermore, most estimates of cracking moment were within 25 % of their corresponding experimental test results, thus promoting confidence for using these strategies with high-volume fly ash precast structures.

42 ENGINEERING↗
NASA NTRS1999

Mid-Field Sonic Boom Extrapolation Methodology

In the design cycle of low-boom airplanes, sonic boom prediction must be accurate and efficient. The classical linear method, Whitham's F-function theory, has been widely applied to predict sonic boom signatures. However, linear theory fails to capture the nonlinear effects created by large civil transport. Computational fluid dynamics (CFD) has been used successfully to predict sonic boom signals at the near and mid fields. Nevertheless, it is computationally expansive in airplane design runs. In the present study, the method of characteristics is used to predict sonic boom signals in an efficient fashion. The governing equations are the axisymmetric Euler's equations with constant enthalpy. Since the method solves Euler's equations, it captures more nonlinear effects than the classical Whitham's F-function technique. Furthermore, the method of characteristics is an efficient marching scheme for initial value problems. In this study, we will first review the current CFD extrapolation technique and the work previously done in sonic boom extrapolation. Then, we will introduce the governing equations and the method of characteristics. Finally, we will show that the present method yields the same accurate results as previous CFD techniques, but with higher efficiency.

Cheung, Samson↗
NASA NTRS1989

Toward an electrical power utility for space exploration

Future electrical power requirements for space exploration are discussed. Megawatts of power with enough reliability for multi-year missions and with enough flexibility to adapt to needs unanticipated at design time are some of the criteria which space power systems must be able to meet. The reasons for considering the power management and distribution in the various systems, from a total mission perspective rather than simply extrapolating current spacecraft design practice, are discussed. A utility approach to electric power integrating requirements from a broad selection of current development programs, with studies in which both space and terrestrial technologies are conceptually applied to exploration mission scenarios, is described.

Bercaw, Robert W.↗
DOE OSTI2026

Machine learning based prediction of airflow maldistribution in air-to-refrigerant heat exchangers

Flow maldistribution is a common challenge in heat exchanger (HX) design and particularly important for air-to-refrigerant geometries where capacity losses can approach 65%. This has a major impact on central air conditioning systems, as compact duct design motivates the use of A-type HXs which are known to be affected by airflow maldistribution. Because velocity profiles are difficult to predict, components are often oversized leading to increased material cost, system footprint, and refrigerant charge. Several studies detail airflow maldistribution for individual HXs and packages, but findings cannot always be extrapolated to new designs. In this work, a machine learning (ML) based flow profile prediction framework is developed and applied to two common package configurations: (i) A-type and (ii) U-type HXs, across a broad range of HX geometries and flow rates. Porous media CFD simulations are validated against independent data for both package types as well as comprehensive in house measurements for a finless geometry with shape optimized non-round tubes, which validates the framework for new heat transfer surfaces. The ML models are trained on the porous media CFD simulations, predicting volumetric flow rate (VFR) within 1.1% and 1.9% with maximum relative L 2 norm errors of 0.48 and 0.65, respectively, while also delivering 10 5 speed up factor compared to full porous media CFD. HX level simulations show an up to 9% reduction in heat transfer from flow maldistribution, with greater losses occurring at smaller half apex angles. This framework enables rapid and highly accurate prediction of airflow maldistribution induced capacity degradation.

42 ENGINEERING↗
DOE OSTI2024

Voltage Calculations in Secondary Distribution Networks via Physics-Inspired Neural Network Using Smart Meter Data

The increasing penetration of distributed energy resources (DERs) leads to voltage issues across distribution networks, necessitating voltage calculations by utilities. Electric model-free voltage calculation offers an enticing solution. However, most researches mainly focus on primary distribution networks ignoring secondary distribution networks and commonly overlook extreme voltage case calculations, which require the model’s extrapolation abilities. Here, in addressing the gaps, this paper presents a customized physics-inspired neural network (PINN) model, the structure of which is inspired by the derived coupled power flow model of primary-secondary distribution networks. To ensure precision and rapid convergence, a crafted training framework for the PINN model is proposed. The PINN’s “structure-mimetic” design enables superior extrapolation for unseen scenarios and enhances physical information awareness. We demonstrate this through two applications: hosting capacity analysis and customer-transformer connectivity. The effectiveness and advantages of the proposed PINN model are validated on two public testing systems and one utility distribution feeder model.

Distribution network↗
NASA NTRS1995

1025:1 Area Ratio Nozzle Evaluated at High Combustion Chamber Pressure

A recently completed experimental test program obtained performance data on an optimally contoured nozzle with an exit-to-throat area ratio of 1025:1 and on a truncated version of this nozzle with an area ratio of 440:1. The nozzles were tested with gaseous hydrogen and liquid oxygen propellants at combustion chamber pressures of 12.4 to 16.5 mPa (1800 to 2400 psia). Testing was conducted in the altitude test capsule at the NASA Lewis Research Center's Rocket Engine Test Facility (RETF), and results were compared with analytical performance predictions. This testing builds on previous work with this nozzle at Lewis, where testing was completed at nominal chamber pressure of 350 psia. High-area-ratio nozzles have long been sought as a means to increase the performance of spacebased rocket engines. However, as the area ratio increases, the physical size and weight of the nozzle also increase. As a result, engine and vehicle designers must make tradeoffs between nozzle size and performance enhancement. Until this test program, very little experimental data existed on the performance of the high-area-ratio nozzles used in rocket engine designs. The computer codes being used by rocket engine designers rely on data extrapolated from tests of low-area-ratio nozzles, and these extrapolations do not always provide the accuracy needed for a reliable design assessment. Therefore, we conducted this high-area-ratio nozzle testing program to provide performance data for use in rocket engine design and analysis computer codes. The nozzle had a nominal 2.54-cm- (1-in.-) diameter throat, an exit diameter of 81.3-cm (32.0-in.) at an exit-to-throat area ratio of 1025, and a length of 128.6 cm (50.6 in.). Testing was conducted in an altitude test capsule to simulate the static pressure at altitude by vacuum pumping. Data such as propellant mass flow, oxidizer-to-fuel mixture, and thrust were measured. These measurements were then used to calculate performance factors such as the thrust coefficient, the characteristic exhaust velocity efficiency, and the vacuum specific impulse. In addition, the nozzle temperature was measured to calculate the amount of heat transferred from the combustion gases to the nozzle.

Source record↗
NASA NTRS1977

Injection of coal by screw feed

The use of the screw feeder for injecting solids through a 20 to 30 psi barrier is common practice in the cement making industry. An analytical extrapolation of that design, accounting for pressure holding characteristics of a column of solids, shows that coal can be fed to zones at several hundred psi with minimal or no loss of gas. A series of curves showing the calculated pressure gradient through a moving column of solids is presented. Mean particle size, solids velocity, and column length are parameters. Further study of this system to evaluate practicality is recommended.

Fisher, R.↗
DOE OSTI2024

Machine Learning Based Prediction of Airflow Maldistribution in A-Type Heat Exchangers

Airflow maldistribution is one of the primary causes of performance degradation in air-to refrigerant heat exchangers (HX) and has been shown to decrease heat transfer by as much as 35%. As a result, many units are oversized to meet the target capacity, resulting in increased system cost and refrigerant charge. Several studies have explored how characteristics like package type and HX geometry impact the flow profile, but results are restricted to a limited range of parameters and cannot be extrapolated to new designs. In this work, a machine learning (ML) model is trained to predict the inlet flow profile of dry air entering A-type HXs across a broad range of geometries and conditions. Flow profiles are generated using a porous media CFD model and used to train an Artificial Neural Network (ANN) which exhibits maximum and average relative L2 norm errors of 0.48 and 0.05. Additionally, these predictions take less than a second to generate resulting in a speed up factor of 2.42E5 compared to CFD. Component-level simulations are conducted to determine the performance degradation resulting from the predicted airflow maldistribution profiles. The new ML model will enable rapid and accurate prediction of performance degradation resulting from airflow maldistribution in A-type HXs, allowing for more accurate and cost-effective HX design.

42 ENGINEERING↗
NASA NTRS1999

Main Chamber and Preburner Injector Technology

This document reports the experimental and analytical research carried out at the Penn State Propulsion Engineering Research Center in support of NASA's plan to develop advanced technologies for future single stage to orbit (SSTO) propulsion systems. The focus of the work is on understanding specific technical issues related to bi-propellant and tri-propellant thrusters. The experiments concentrate on both cold flow demonstrations and hot-fire uni-element tests to demonstrate concepts that can be incorporated into hardware design and development. The analysis is CFD-based and is intended to support the design and interpretation of the experiments and to extrapolate findings to full-scale designs. The research is divided into five main categories that impact various SSTO development scenarios. The first category focuses on RP-1/gaseous hydrogen (GH2)/gaseous oxygen (GO2) tri-propellant combustion with specific emphasis on understanding the benefits of hydrogen addition to RP-1/oxygen combustion and in developing innovative injector technology. The second category investigates liquid oxygen (LOX)/GH2 combustion at main chamber near stoichiometric conditions to improve understanding of existing LOX/GH2 rocket systems. The third and fourth categories investigate the technical issues related with oxidizer-rich and fuel-rich propulsive concepts, issues that are necessary for developing the full-flow engine cycle. Here, injector technology issues for both LOX/GH2 and LOX/RP-1 propellants are examined. The last category, also related to the full-flow engine cycle, examines injector technology needs for GO2/GH2 propellant combustion at near-stoichiometric conditions for main chamber application.

Santoro, Robert J.↗
NASA NTRS1992

Mathematical Model For Engineering Analysis And Optimization

Computational support for engineering design process reveals behavior of designed system in response to external stimuli; and finds out how behavior modified by changing physical attributes of system. System-sensitivity analysis combined with extrapolation forms model of design complementary to model of behavior, capable of direct simulation of effects of changes in design variables. Algorithms developed for this method applicable to design of large engineering systems, especially those consisting of several subsystems involving many disciplines.

Sobieski, Jaroslaw↗
DOE OSTI2021

Layered-rocksalt intergrown cathode for high-capacity zero-strain battery operation

Abstract The dependence on lithium-ion batteries leads to a pressing demand for advanced cathode materials. We demonstrate a new concept of layered-rocksalt intergrown structure that harnesses the combined figures of merit from each phase, including high capacity of layered and rocksalt phases, good kinetics of layered oxide and structural advantage of rocksalt. Based on this concept, lithium nickel ruthenium oxide of a main layered structure ( R $$\bar{3}$$ 3 ¯ m ) with intergrown rocksalt ( Fm $$\bar{3}$$ 3 ¯ m ) is developed, which delivers a high capacity with good rate performance. The interwoven rocksalt structure successfully prevents the anisotropic structural change that is typical for layered oxide, enabling a nearly zero-strain operation upon high-capacity cycling. Furthermore, a design principle is successfully extrapolated and experimentally verified in a series of compositions. Here, we show the success of such layered-rocksalt intergrown structure exemplifies a new battery electrode design concept and opens up a vast space of compositions to develop high-performance intergrown cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2021

Stellarators as a fast path to fusion

Herein this paper is focused on three points: (1) overcoming obstacles to tokamak power plants may require a configuration modification as large as that of a stellarator. (2) The demonstrated reliability of the computational design of stellarators should change fusion strategy. (3) Deployment of carbon-free energy sources is mandated by the thirty-year doubling of carbon dioxide emissions. Carbon-free energy options must be developed and fully deployed within a few doubling times. Unit size and cost of electricity are only relevant in comparison to alternative worldwide energy solutions. Intermittency, site specificity, waste management, and nuclear proliferation make fusion attractive as the basis for a carbon-free energy system compared to the alternatives. Nonetheless, fusion is not an option for deployment until a power plant has successfully operated. A critical element in a minimal time and risk program is the use of computational design as opposed to just extrapolation. Only the stellarator has an empirical demonstration of the reliable computational design through large changes in configuration properties and scale. The computational design of stellarators should proceed while the inventions necessary for a more tokamak-like power plant are sought. The cost of computational design is extremely small, but adequate time is required for the development of ideas that maximize attractiveness and minimize risk. Rapid power-plant construction without many intermediate steps may seem risky, but the price is small compared to the cost of trillions of dollars for each year's delay in addressing carbon-dioxide emissions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Mechanistic modeling of lifetime distribution of SiC/SiC composite claddings

Silicon carbide (SiC) fiber-reinforced SiC matrix (SiC/SiC) composites have emerged as a new material candidate for fuel claddings in light water reactors. Recent studies showed that the load capacity of SiC/SiC materials exhibits a considerable statistical variation. Therefore, reliability analysis plays a critical role in design of SiC/SiC composite claddings. Here, this paper presents a probabilistic model for the lifetime distribution of SiC/SiC composites. The model is anchored by a multiaxial stress-based failure criterion and subcritical damage accumulation mechanism. Based on the kinetics of subcritical damage growth, the lifetime distribution of a laboratory test specimen for any given loading history can be calculated. A finite weakest-link model is used to extrapolate the lifetime distribution of test specimens to full-length claddings. It is shown that the damage accumulation mechanism has a strong influence on the lifetime distribution of the cladding. This finding highlights the importance of understanding the static fatigue behavior of SiC/SiC composites. The present analysis also demonstrates an intricate length effect on the failure probability of the cladding, which is expected to play a crucial role in design extrapolation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗
DOE OSTI2022

An extrapolation method for strain ranges and hold times in developing the EPP+SMT creep-fatigue design curves for Alloy 617

Experimental and numerical studies in developing the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY2022. This report focuses on the methods for extrapolating the EPP+SMT creep-fatigue (CF) design curves at long hold times and low strain ranges. In this study, the available CF failure data on Alloy 617 at 950°C were analyzed to determine a set of CF failure criteria. At very low strain ranges and long hold times, CF failure data are not accessible by experiments because of the extraordinarily long test durations and the inability of the test machines to accurately control these small strain ranges. A CF experimental approach with the concept of block-strain range CF testing protocol was developed. Tests using this protocol were conducted to generate the needed information for calibrating material parameters of the numerical material models. The Time Fraction based method and Dissipated Energy method were used to extrapolate the CF life curves to low strain ranges and long hold times. Based on the new experimental approach and CF life prediction methods, the CF life curves with various hold times were developed for Alloy 617 at 950°C. In addition, an experiment was designed and is being performed to verify the predicted CF curves at 950°C. The extrapolation procedure will be applied at lower temperatures to complete the development of the EPP+SMT CF design curves for Alloy 617 in F2023.

36 MATERIALS SCIENCE↗
NASA NTRS1987

An algorithm for a generalization of the Richardson extrapolation process

The paper presents a recursive method, designated the W exp (m)-algorithm, for implementing a generalization of the Richardson extrapolation process. Compared to the direct solution of the linear sytems of equations defining the extrapolation procedure, this method requires a small number of arithmetic operations and very little storage. The technique is also applied to solve recursively the coefficient problem associated with the rational approximations obtained by applying a d-transformation to power series. In the course of development a new recursive algorithm for implementing a very general extrapolation procedure is introduced, for solving the same problem. A FORTRAN program for the W exp (m)-algorithm is also appended.

Ford, William F.↗