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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 NTRS1992

Semi-coupled flow and thermal analysis of the field joint during rapid pressurization of the redesigned solid rocket motor

A transient, semi-coupled, multi-dimensional thermal and flow analysis methodology was developed to predict the thermal/gas dynamic conditions in the field joint region of the Redesigned Solid Rocket Motor (RSRM). Transient temperature response, pressure history, and combustion gas flow rate (within the field joint region), were of principle interest, in the course of this study. The thermal environment in the field joint was modeled using SINDA, a finite difference based thermal network analyzer. The combustion gas flow boundary condition was generated using the FLAP code; this code performs a transient, lumped-parameter, control volume analysis to solve the mass, momentum, and energy conservation equations. The FLAP computer code was modified to account for erosion of the NBR insulation material, following ignition. An independent grid sensitivity study was conducted to determine an appropriate grid distribution near the wall. The predicted results, obtained using an optimum grid distribution and computer generated flow boundary condition, were compared with subscale test data.

Ghaffarian, Benny↗
NASA NTRS2005

Solar Cycle/Seasonal Variations of H, D, H2 and He Distributions and Escape on Mars as Determined by the Mars Thermosphere Global Circulation Model (MTGCM)

The Mars Thermosphere General Circulation Model (MTGCM) was exercised for Ls = 90 (aphelion) solar minimum, and Ls = 270 perihelion) solar maximum conditions. Simulated MTGCM outputs (i.e. helium density distributions) were compared to those previously observed for Earth and Venus. Winter polar night bulges of helium are predicted on Mars, similar to those observed on the nightside of Venus and in the winter polar regions of Earth. A poster on this research was presented at the European Geophysical Society Meeting (EGS) in 2003. This research paves the way for what might be expected in the polar night regions of Mars during upcoming aerobraking and mapping Campaigns. Lastly, Mars thermosphere (approx. 100-130 km) winter polar warming was observed at high Northern latitudes during the perihelion season, but not at high Southern latitudes during the opposite aphelion season. Presumably, the Mars thermospheric circulation is responsible for the dynamically controlled heating needed to warm polar night temperatures above radiative equilibrium values. Again, MTGCM simulations were conducted for Ls = 90 and Ls = 270 conditions; polar temperatures were examined and found to be much warmer at Northern high latitudes (perihelion) than at Southern high latitudes (aphelion), similar to Mars aerobraking datasets. The Mars thermospheric circulation is found to be stronger during perihelion solstice conditions than during aphelion conditions, owing to both stronger seasonal solar and dust heating during Mars perihelion. An invited talk was given at the Spring AGU 2004 on this research. A forthcoming GRL paper was drafted on this same topic, but not submitted before the termination of this 1-year grant.

Bougher, Stephen↗
DOE OSTI2026

Continual Learning for Particle Accelerators

Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts.

Schram, Malachi [Thomas Jefferson National Acceler↗
DOE OSTI2026

Continual Learning for Particle Accelerators

Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts

Rajput, Kishansingh [Thomas Jefferson National Acc↗
DOE OSTI2024

Systems and methods for randomized energy draw or supply requests

The present disclosure can provide a distributed and anonymous approach to demand response of an electricity system. The approach can conceptualize energy consumption and production of distributed-energy resources (DERs) via discrete energy packets that are coordinated by a cyber computing entity that grants or denies energy packet requests from the DERs. The approach leverages a condition of a DER, which is particularly useful for (1) thermostatically-controlled loads, (2) non-thermostatic conditionally-controlled loads, and (3) bi-directional distributed energy storage systems, among others. In a first aspect of the present approach, each DER independently requests the authority to switch on for a fixed amount of time (i.e., packet duration). The coordinator determines whether to grant or deny each request based electric grid and/or energy or power market conditions. In a second aspect, bi-directional DERs, such as distributed-energy storage systems (DESSs) are further able to request to supply energy to the grid.

Frolik, Jeff↗
DOE OSTI2018

Internal influences of hydrolysis conditions on rutile TiO2 pigment production via short sulfate process

Highlights: • A novel short sulfate process was proposed to produce rutile TiO{sub 2} pigment. • Effects and internal influences of hydrolysis conditions were investigated in detail. • Intrinsic relationship between hydrolysis conditions and pigment properties were revealed. - Abstract: Rutile TiO{sub 2} white pigment was prepared via short sulfate process by using the unenriched industrial TiOSO{sub 4} solution as titanium source through authigenic seed hydrolysis process. The effects and internal influences of hydrolysis conditions on the structure, particle size distribution and pigment properties for the as-synthesized samples were investigated, involving the inducing hydrolysis water volume ratio, ripening time and hydrolysis time after the second boiling point. These hydrolysis factors influenced the number and quality of the initial formed hydrolysis nuclei, the crystal growth and the particle aggregation velocity, eventually determined the pigment properties. And the conditions had internal mathematical regression correlation with crystal structure, particle polydispersity index and pigment properties. The optimal inducing hydrolysis water volume ratio is of 0.123, ripening time is of 29.05 min, and hydrolysis time is of 2.6 h.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Microwave-assisted conversion of methane over H-(Fe)-ZSM-5: Evidence for formation of hot metal sites

We report microwave-assisted catalysis offers great promise as an “intensified” technology for chemical processing. The present study investigates microwave-assisted direct conversion of methane with focus on the design and evaluation of microwave-sensitive H-(Fe)ZSM-5 catalysts for the existence of hotspot formation. Isomorphous substituted H-(Fe)ZSM-5 catalysts are tuned to identify key design parameters that control their microwave sensitivity. Increasing the amount of Al and Fe substitution in the zeolite lattice is found to result in higher microwave sensitivity due to improved dielectric properties and hence facilitated microwave heating of the catalyst bed. Comparison between the performance of these catalysts in a conventional thermally-heated (CH) fixed-bed and a microwave (MW) reactor allows identification of the effect of microwave irradiation on the catalyst activity. Methane conversion is drastically enhanced at MW conditions (from 3% at CH conditions to 40% at MW conditions), indicating accelerated methane activation over the metal site and hence suggesting a hot metal site despite much lower catalyst bulk temperature measured in the microwave reactor. The existence of metal hotspot formation is further supported by the reaction product distribution and spent catalyst analysis. At MW conditions, C 2 (ethane and ethylene) and coke (mainly carbon nanotubes and nanofibers) selectivity are much higher at the cost of aromatics make compared to CH conditions. This can be explained by reduced aromatization activity at the Brønsted acid sites of the zeolite due to its lower relative temperature of the zeolite. The much-enhanced metal aggregation observed in the spent catalyst from the MW reactor along with the distribution of coke species further confirms the existence of selective heating (i.e. hotspot formation) occurring at the active metal site in the catalyst at MW conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Heat load measurements for the PIP-II pHB650 cryomodule

This study presents a brief overview of the 1st and 2nd phases and an in-depth analysis of the 3rd phase heat load testing performed on the pHB650 (prototype High Beta 650 MHz) cryomodule at PIP2IT (PIP-II Injector Test Facility), with a focus on both the results and the methodological advancements that have improved testing efficiency and accuracy. A key challenge identified in the testing campaign is the higher-than-expected heat loads observed in the first PIP-II (Proton Improvement Plan II) prototype cryomodules (pSSR1 and pHB650) tested at PIP2IT. Elevated heat loads are concerning given the fixed capacity of the PIP-II cryoplant that is currently being installed at Fermilab. However, understanding the sources of these elevated heat loads offers a critical opportunity to implement effective heat load mitigations on upcoming PIP-II cryomodules to stay within the available capacity of the PIP-II cryoplant. The study includes a summary of test results, descriptions of measurement procedures, and key observations on parameters directly and indirectly related to heat load measurements. Direct observations include measured heat loads and the effectiveness of JT heat exchanger under varying conditions, while indirect observation analyze factors such as the temperature distribution on the two-phase pipe and relief piping under varying conditions. Thermal acoustic oscillations (TAO) were identified during testing, which was mitigated by replacing the original G10 stem with a stainless steel stem equipped with wipers for the cryomodule cooldown valve. A major innovation during pHB650 Phase 3 testing was the development of an automated Python script to streamline data acquisition, analysis, and reporting of heat load results. This script automatically retrieved data from ACNET (Accelerator Control Network), performed heat load calculations, and generated detailed reports featuring plots and tables. This advancement significantly reduced manual labor and enhanced the thoroughness of data analysis compared to earlier campaigns. The heat load test reports were promptly uploaded to the electronic logbook shortly after each test, enabling rapid feedback and collaboration between the SRF and cryogenic teams. The heat load measurements included various components: HTTS (high-temperature thermal shield), LTTS (low-temperature thermal shield), 2K isothermal and non-isothermal heat loads. Results were recorded both within the cryomodule and between the bayonet can supply and return. Measurements were conducted under different operating conditions such as "standard", "linac", and "simulated dynamic". Additionally, HTTS and LTTS heat loads were calculated in real time, allowing for the tracking of thermal stability and identification of changes during testing, both in steady-state and transient conditions. The results of this testing campaign not only provide valuable insights into the performance of the pHB650 cryomodule but also highlight best practices and lessons learned that will inform future cryomodule testing at PIP2IT. These include adopting automated tools for data analysis, refining real-time measurement capabilities, and emphasizing detailed pre-test planning. The framework established in this campaign aims to set an improved standard for cryomodule testing and heat load reporting in future cryomodule test campaigns.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.]↗
NASA NTRS1946

Investigation of Operating Characteristics of an Engine Equipped with Modifications to Eliminate Fuel-Evaporation Icing

Two modified fuel-injection systems, a drilled-inducer type and a spinner type, that prevent serious fuel-evaporation icing were installed on a V-type, liquid-cooled aircraft engine and a preliminary investigation was conducted to determine the effect on engine operating characteristics. The spinner system was also ground - and flight tested on a twin-engine fighter airplane. Flight measurements of cylinder-head temperature over a range of fuel-air ratios and engine power conditions were made at an altitude of approximately 10,000 feet. Starting and accelerating of the engine on the ground were unaffected by the fuel-injection modifications. During the flight investigation, no appreciable variation occurred between the maximum and minimum cylinder-head temperature with the standard and modified system for the same power condition and no irregularity of mixture distribution could be detected throughout the power range of the engine. Normal mixture distribution was also indicated by a similar response of cylinder-head temperature for variations of fuel-air ratio at manifold pressures of 25 and 35 inches of mercury absolute. Both modified fuel-injection systems required less fuel-nozzle pressure than the standard system to obtain the desired fuel-air ratio for given air-flow condition.

Mulholland, Donald R.↗
DOE OSTI2017

Isomerization of Second-Generation Isoprene Peroxy Radicals: Epoxide Formation and Implications for Secondary Organic Aerosol Yields

We report chamber measurements of secondary organic aerosol (SOA) formation from isoprene photochemical oxidation, where radical concentrations were systematically varied and the molecular composition of semi to low volatility gases and SOA were measured online. Using a detailed chemical mechanism, we find that to explain the behavior of low volatility products and SOA mass yields relative to input H2O2 concentrations, the second generation dihydroxy hydroperoxy peroxy radical (C5H11O6•) must undergo an intra-molecular H-shift with a net forward rate constant of order 0.1 s-1 or higher, consistent with quantum chemical calculations which suggest a net forward rate constant of 0.3-0.9 s-1. Furthermore, these calculations suggest the dominant product of this isomerization is a dihydroxy hydroperoxy epoxide (C5H10O5) which is expected to have a saturation vapor pressure ~2 orders of magnitude higher than the dihydroxy dihydroperoxide, ISOP(OOH)2 (C5H12O6), a major product of the peroxy radical reacting with HO2. These results provide strong constraints on the likely volatility distribution of isoprene oxidation products under atmospheric conditions and thus on the importance of non-reactive gas-particle partitioning of isoprene oxidation products as an SOA source.

D’Ambro, Emma L. (ORCID:0000000230419027)↗
DOE OSTI2023

Uncertainty Quantification of Capacitor Switching Transient Location using Machine Learning

Identification of capacitor switching transient location provides valuable insight into the state of the associated equipment. Machine learning (ML) models, and convolutional neural networks (CNNs) in particular, have demonstrated remarkable performance in signal location. However, ML models are data driven whose predictions are affected by noise in data and may also suffer from large extrapolation errors when applied to new conditions. Uncertainty quantification (UQ) is necessary to ensure model trustworthiness and avoid overconfident predictions in extrapolation. Here, in this work, we propose a novel UQ method, called PI3NN, to quantify prediction uncertainty of ML models and integrate the method with CNNs for transient source location. PI3NN calculates Prediction Intervals by training 3 Neural Networks and uses root-finding methods to determine the interval precisely. Additionally, PI3NN can identify out-of-distribution (OOD) data in a nonstationary condition to avoid overconfident prediction. Results indicate that with PI3NN, transient signals are not only correctly identified, but when said signals are subject to corruptions characteristic of an actual power monitoring system (e.g. non-ideal sensors), the model recognizes when it is uncertain about its predictions, effectively letting the user know when to accept or discard the results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Evolution of a Modified Binomial Random Graph by Agglomeration

In the classical Erdős–Rényi random graph G(n, p) there are n vertices and each of the possible edges is independently present with probability p. The random graph G(n, p) is homogeneous in the sense that all vertices have the same characteristics. On the other hand, numerous real-world networks are inhomogeneous in this respect. Such an inhomogeneity of vertices may influence the connection probability between pairs of vertices. The purpose of this paper is to propose a new inhomogeneous random graph model which is obtained in a constructive way from the Erdős-Rényi random graph G(n, p). Given a configuration of n vertices arranged in N subsets of vertices (we call each subset a super-vertex), we define a random graph with N super-vertices by letting two super-vertices be connected if and only if there is at least one edge between them in G(n, p). Our main result concerns the threshold for connectedness. We also analyze the phase transition for the emergence of the giant component and the degree distribution. Even though our model begins with G(n, p), it assumes the existence of some community structure encoded in the configuration. Furthermore, under certain conditions it exhibits a power law degree distribution. Both properties are important for real-world applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1971

Frequency domain stability criteria for distributed nonlinear sampled-data systems.

Popov-type sufficient conditions are presented for the absolute stability of a class of closed loop sampled-data systems. The closed loop system consists of a linear distributed element, a feedback controller (linear or nonlinear), a sampler, and possibly a zero-order hold circuit. The distributed element is assumed to be finite Hankel transformable, and such that its dynamics can be represented by a transfer function which is the ratio of the multiple (Laplace and finite Hankel) transforms of output and input. The input is assumed to be distributed. The stability criterion presented here parallels the criterion for distributed systems that are finite Fourier transformable. An example is given to illustrate the applications of the stability criterion.

Nagarajan, N.↗
NASA NTRS1986

A study of the stochastic energization of charged particles with and without synchrotron energy loss

A momentum-diffusion formulation that takes the initial values of the particle distribution functions and momentum-space boundary conditions is presently employed for the computational and analytical study of the stochastic energization of charged particles by plasma waves. The nature of the particle distribution functions resulting from stochastic energization and the validity of the momentum-diffusion formulation for the energization are determined. The validity of the momentum-diffusion formulation with power law diffusion coefficients is assessed.

Borovsky, J. E.↗
DOE OSTI2017

Understanding controls on redox processes in floodplain sediments of the Upper Colorado River Basin

Floodplains, heavily used for water supplies, housing, agriculture, mining, and industry, are important repositories of organic carbon, nutrients, and metal contaminants. The accumulation and release of these species is often mediated by redox processes. By understanding the physicochemical, hydrological, and biogeochemical controls on the distribution and variability of sediment redox conditions we can develop conceptual and numerical models of contaminant transport within floodplains. The Upper Colorado River Basin (UCRB) is impacted by former uranium and vanadium ore processing, resulting in contamination by V, Cr, Mn, As, Se, Mo and U. Previous authors have suggested that sediment redox activity occurring within organic carbon-enriched bodies located below the groundwater level may be regionally important to the maintenance and release of contaminant inventories, particularly uranium. To help assess this hypothesis, vertical distributions of Fe and S redox states and sulfide mineralogy were assessed in sediment cores from three floodplain sites spanning a 250 km transect of the central UCRB. Our results support the hypothesis that organic-enriched reduced sediments are important zones of biogeochemical activity within UCRB floodplains. Furthermore, we found that the presence of organic carbon, together with pore saturation, are the key requirements for maintaining reducing conditions, which were dominated by sulfate-reduction products. Sediment texture was found to be of secondary importance and to moderate the response of the system to external forcing, such as oxidant diffusion. Consequently, fine-grain sediments are relatively resistant to oxidation in comparison to coarser-grained sediments. Exposure to oxidants consumes precipitated sulfides, with a disproportionate loss of mackinawite (FeS) as compared to the more stable pyrite. The accompanying loss of redox buffering capacity creates the potential for release of sequestered radionuclides and metals. Because of their redox reactivity and stores of metals, C, and N, organic-enriched sediments are likely to be important to nutrient and contaminant mobility within UCRB floodplain aquifers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Heterogeneous creep deformation in Dissimilar Metal Welds (DMWs)

Dissimilar Metal Welds (DMWs) made between ferritic low alloy steels and austenitic alloys are widely used in high temperature components of nuclear and fossil energy power plants. Literature shows that these bimetallic welds fail prematurely by creep mechanism close to the interface of the ferritic (BCC) and austenitic regions (FCC), with lifetimes much less than the creep lives of both materials. These creep failures are associated with cavity formation close to BCC/FCC interfaces. However, the spatial and temporal variations of creep strain rates in these DMWs have not been measured. In this research, DMW coupons were fabricated between 2.25Cr-1Mo steel and Alloy 800 H base material using a Ni base Inconel weld consumable. These samples were aged at 600 °C for 2000 h and 4000 h to induce two different sizes and distributions of Type I interfacial carbides and further subjected to a short term (~1 month) creep testing. Here, surface strains were measured with Digital Image Correlation (DIC) technique to extract local creep strain rates. In both samples, creep strain concentration occurred in the BCC matrix. The location of creep strain concentration from the BCC/FCC interface, changed from 5 µm (2000 h aged condition) to 400 µm (4000 h aged condition) depending on the initial carbide distributions in these regions.

36 MATERIALS SCIENCE↗
NASA NTRS2001

A Latency-Tolerant Partitioner for Distributed Computing on the Information Power Grid

NASA's Information Power Grid (IPG) is an infrastructure designed to harness the power of graphically distributed computers, databases, and human expertise, in order to solve large-scale realistic computational problems. This type of a meta-computing environment is necessary to present a unified virtual machine to application developers that hides the intricacies of a highly heterogeneous environment and yet maintains adequate security. In this paper, we present a novel partitioning scheme. called MinEX, that dynamically balances processor workloads while minimizing data movement and runtime communication, for applications that are executed in a parallel distributed fashion on the IPG. We also analyze the conditions that are required for the IPG to be an effective tool for such distributed computations. Our results show that MinEX is a viable load balancer provided the nodes of the IPG are connected by a high-speed asynchronous interconnection network.

Das, Sajal K.↗