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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Electron tomography of unirradiated and irradiated nuclear graphite

Graphite is the moderator material of several Generation IV nuclear reactor concepts, as well as the British Advanced Gas-cooled Reactors (AGR). Porosity can heavily influence the material properties, mechanical irradiation response, and neutron induced shrinkage or swelling of nuclear-grade graphite. Due to the sub-micron size of several types of pores found in graphite, only a high-resolution imaging technique such as electron tomography are capable of visualizing these features in three dimensions. In this research, we used electron tomography to characterize as-received and neutron irradiated samples of IG-110 nuclear-grade graphite to show for the first time the 3D structure of both native and irradiation-induced nano-cracks. This technique also reveals unique characteristics of graphite such as the structure that surrounds pores and could be used to inform molecular dynamic simulations of irradiated graphite and experimental techniques such as gas-absorption. This work also shows the utility of this technique for the study of other nuclear porous carbon-based materials.

36 MATERIALS SCIENCE↗
DOE OSTI2013

A model to simulate the oxygen distribution in hypoxic tumors for different vascular architectures

Purpose: As hypoxic cells are more resistant to photon radiation, it is desirable to obtain information about the oxygen distribution in tumors prior to the radiation treatment. Noninvasive techniques are currently not able to provide reliable oxygenation maps with sufficient spatial resolution; therefore mathematical models may help to simulate microvascular architectures and the resulting oxygen distributions in the surrounding tissue. Here, the authors present a new computer model, which uses the vascular fraction of tumor voxels, in principle measurable noninvasively in vivo, as input parameter for simulating realistic PO2 histograms in tumors, assuming certain 3D vascular architectures.Methods: Oxygen distributions were calculated by solving a reaction-diffusion equation in a reference volume using the particle strength exchange method. Different types of vessel architectures as well as different degrees of vascular heterogeneities are considered. Two types of acute hypoxia (ischemic and hypoxemic) occurring additionally to diffusion-limited (chronic) hypoxia were implemented as well.Results: No statistically significant differences were observed when comparing 2D- and 3D-vessel architectures (p > 0.79 in all cases) and highly heterogeneously distributed linear vessels show good agreement, when comparing with published experimental intervessel distance distributions and PO2 histograms. It could be shown that, if information about additional acute hypoxia is available, its contribution to the hypoxic fraction (HF) can be simulated as well. Increases of 128% and 168% in the HF were obtained when representative cases of ischemic and hypoxemic acute hypoxia, respectively, were considered in the simulations.Conclusions: The presented model is able to simulate realistic microscopic oxygen distributions in tumors assuming reasonable vessel architectures and using the vascular fraction as macroscopic input parameter. The model may be used to generate PO2 histograms, which are needed as input in models predicting the radiation response of hypoxic tumors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Machine-Learned Linear Structural Dynamics

The tension between accuracy and computational cost is a common thread throughout computational simulation. One such example arises in the modeling of mechanical joints. Joints are typically confined to a physically small domain and yet are computationally expensive to model with a high-resolution finite element representation. A common approach is to substitute reduced-order models that can capture important aspects of the joint response and enable the use of more computationally efficient techniques overall. Unfortunately, such reduced-order models are often difficult to use, error prone, and have a narrow range of application. In contrast, we propose a new type of reduced-order model, leveraging machine learning, that would be both user-friendly and extensible to a wide range of applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Fuel-injector/air-swirl characterization

The objectives of this program are to establish an experimental data base documenting the behavior of gas turbine engine fuel injector sprays as the spray interacts with the swirling gas flow existing in the combustor dome, and to conduct an assessment of the validity of current analytical techniques for predicting fuel spray behavior. Emphasis is placed on the acquisition of data using injector/swirler components which closely resemble components currently in use in advanced aircraft gas turbine engines, conducting tests under conditions that closely simulate or closely approximate those developed in actual combustors, and conducting a well-controlled experimental effort which will comprise using a combination of low-risk experiments and experiments requiring the use of state-of-the-art diagnostic instrumentation. Analysis of the data is to be conducted using an existing, TEACH-type code which employs a stochastic analysis of the motion of the dispersed phase in the turbulent continuum flow field.

Mcvey, J. B.↗
NASA NTRS1995

CDMA with interference cancellation for multiprobe missions

Code division multiple-access spread spectrum has been proposed for use in future multiprobe/multispacecraft missions. This article considers a general parallel interference-cancellation scheme that significantly reduces the degradation effect of probe (user) interference but with a lesser implementation complexity than the maximum-likelihood technique. The scheme operates on the fact that parallel processing simultaneously removes from each probe (user) the total interference produced by the remaining most reliably received probes (users) accessing the channel. The parallel processing can be done in multiple stages. The proposed scheme uses tentative decision devices with different optimum thresholds at the multiple stages to produce the most reliably received data for generation and cancellation of probe/spacecraft interference. The one-stage interference cancellation was analyzed for two types of tentative decision devices, namely, hard and null zone decisions. Simulation results are given for one- and two-stage interference cancellation for equal as well as unequal received power probes.

Divsalar, D.↗
DOE OSTI2024

Leveraging graph clustering techniques for cyber‐physical system analysis to enhance disturbance characterisation

Abstract Cyber‐physical systems have behaviour that crosses domain boundaries during events such as planned operational changes and malicious disturbances. Traditionally, the cyber and physical systems are monitored separately and use very different toolsets and analysis paradigms. The security and privacy of these cyber‐physical systems requires improved understanding of the combined cyber‐physical system behaviour and methods for holistic analysis. Therefore, the authors propose leveraging clustering techniques on cyber‐physical data from smart grid systems to analyse differences and similarities in behaviour during cyber‐, physical‐, and cyber‐physical disturbances. Since clustering methods are commonly used in data science to examine statistical similarities in order to sort large datasets, these algorithms can assist in identifying useful relationships in cyber‐physical systems. Through this analysis, deeper insights can be shared with decision‐makers on what cyber and physical components are strongly or weakly linked, what cyber‐physical pathways are most traversed, and the criticality of certain cyber‐physical nodes or edges. This paper presents several types of clustering methods for cyber‐physical graphs of smart grid systems and their application in assessing different types of disturbances for informing cyber‐physical situational awareness. The collection of these clustering techniques provide a foundational basis for cyber‐physical graph interdependency analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

THE DISTANCE DUALITY RELATION FROM STRONG GRAVITATIONAL LENSING

Under very general assumptions of the metric theory of spacetime, photons traveling along null geodesics and photon number conservation, two observable concepts of cosmic distance, i.e., the angular diameter and the luminosity distances are related to each other by the so-called distance duality relation (DDR) D{sup L}=D{sup A}(1+z){sup 2}. Observational validation of this relation is quite important because any evidence of its violation could be a signal of new physics. In this paper we introduce a new method to test the DDR based on strong gravitational lensing systems and type Ia supernovae (SNe Ia) under a flat universe. The method itself is worth attention because unlike previously proposed techniques, it does not depend on all other prior assumptions concerning the details of cosmological model. We tested it using a new compilation of strong lensing (SL) systems and JLA compilation of SNe Ia and found no evidence of DDR violation. For completeness, we also combined it with previous cluster data and showed its power on constraining the DDR. It could become a promising new probe in the future in light of forthcoming massive SL surveys and because of expected advances in galaxy cluster modeling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Control of machining-induced residual stress via tool geometry and process parameter modification

Distortion generated in machined, monolithic, thin-walled aerospace components due to residual stresses leads to significant material and economic waste in the manufacturing industry. Inherent residual stress (IRS) present in stock materials combines with machining-induced residual stress (MIRS) to influence the final machined part distortion. It is hypothesized that MIRS can be controlled, based on the part geometry, through deliberate cutting tool geometry and process parameter modifications to negate the effect of IRS on distortion, consequently resulting in distortion-free parts. A finite element (FE) orthogonal cutting model is developed to study how tool geometry and process parameters influence machining-induced residual stress (MIRS). Orthogonal cutting experiments are performed on Al 7075-T651 samples to measure cutting forces and MIRS. A cutting force dynamometer is used to measure forces during cutting and a novel digital image correlation (DIC) based hole drilling technique is employed to measure the near-surface residual stress (RS) in the cut samples. These data are subsequently utilized to validate the FE prediction model. Various cases of cutting simulations involving different depths of cut, tool tip radii, and rake angles are performed to study their effects on RS. Similar to prior literature, increasing the depth of cut, tool tip radius, or rake angle is found to promote the formation of near-surface tensile stresses. The competing effects of material plowing and temperature are shown to determine the type of RS at the end of the cut. Moreover, a window of variation of RS (up to ± 400 MPa) is estimated within the given range of conditions, allowing for the control of MIRS through tool and process modification.

Mathews, Ritin [ORNL] (ORCID:0000000301440828)↗
DOE OSTI2020

Assessments of data centers for provision of frequency regulation

There are numerous opportunities for data centers to participate in demand response programs considering their large energy capacities, flexible working environments and workloads, redundant design and operation, etc. As a type of demand response, frequency regulation requires fast response, and its potential is not fully explored by data centers yet. This paper proposes a synergistic control strategy for data center frequency regulation which uses both IT and cooling systems. It combines power management techniques at the server level with control of the chilled water supply temperature to track the regulation signal from the electrical market. A frequency regulation flexibility factor is also proposed to increase the IT capacity for frequency regulation. The performance of the control strategy is studied through numerical simulations using an equation based object-oriented Modelica platform designed for data centers. Simulation results show that with well-tuned control parameters, data centers can provide frequency regulation service in both regulation up and down. The performance of data centers in providing frequency regulation service is largely influenced by the regulation capacity bid, frequency regulation flexibility factor, workload condition, and cooling mode of the cooling system, and not significantly influenced by the time constant of chillers. In addition, compared with a server-only control strategy, the proposed synergistic control strategy can provide an extra regulation capacity of 3% of the design power when chillers are activated. Here, when chillers are deactivated, both strategies have a similar regulation capacity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1986

Development of buried wire gages for measurement of wall shear stress in Blastane experiments

Buried Wire Gages operated from a Constant Temperature Anemometer System are among the special types of instrumentation to be used in the Boundary Layer Apparatus for Subsonic and Transonic flow Affected by Noise Environment (BLASTANE). These Gages are of a new type and need to be adapted for specific applications. Methods were developed to fabricate Gage inserts and mount those in the BLASTANE Instrumentation Plugs. A large number of Gages were prepared and operated from a Constant Temperature Anemometer System to derive some of the calibration constants for application to fluid-flow wall shear-stress measurements. The final stage of the calibration was defined, but could not be accomplished because of non-availability of a suitable flow simulating apparatus. This report provides a description of the Buried Wire Gage technique, an explanation of the method evolved for making proper Gages and the calibration constants, namely Temperature Coefficient of Resistance and Conduction Loss Factor.

Murthy, S. V.↗
NASA NTRS1996

Monitoring of Time-Dependent System Profiles by Multiplex Gas Chromatography with Maximum Entropy Demodulation

The maximum entropy technique was successfully applied to the deconvolution of overlapped chromatographic peaks. An algorithm was written in which the chromatogram was represented as a vector of sample concentrations multiplied by a peak shape matrix. Simulation results demonstrated that there is a trade off between the detector noise and peak resolution in the sense that an increase of the noise level reduced the peak separation that could be recovered by the maximum entropy method. Real data originated from a sample storage column was also deconvoluted using maximum entropy. Deconvolution is useful in this type of system because the conservation of time dependent profiles depends on the band spreading processes in the chromatographic column, which might smooth out the finer details in the concentration profile. The method was also applied to the deconvolution of previously interpretted Pioneer Venus chromatograms. It was found in this case that the correct choice of peak shape function was critical to the sensitivity of maximum entropy in the reconstruction of these chromatograms.

Becker, Joseph F.↗
NASA NTRS2011

A Hybrid Parachute Simulation Environment for the Orion Parachute Development Project

A parachute simulation environment (PSE) has been developed that aims to take advantage of legacy parachute simulation codes and modern object-oriented programming techniques. This hybrid simulation environment provides the parachute analyst with a natural and intuitive way to construct simulation tasks while preserving the pedigree and authority of established parachute simulations. NASA currently employs four simulation tools for developing and analyzing air-drop tests performed by the CEV Parachute Assembly System (CPAS) Project. These tools were developed at different times, in different languages, and with different capabilities in mind. As a result, each tool has a distinct interface and set of inputs and outputs. However, regardless of the simulation code that is most appropriate for the type of test, engineers typically perform similar tasks for each drop test such as prediction of loads, assessment of altitude, and sequencing of disreefs or cut-aways. An object-oriented approach to simulation configuration allows the analyst to choose models of real physical test articles (parachutes, vehicles, etc.) and sequence them to achieve the desired test conditions. Once configured, these objects are translated into traditional input lists and processed by the legacy simulation codes. This approach minimizes the number of sim inputs that the engineer must track while configuring an input file. An object oriented approach to simulation output allows a common set of post-processing functions to perform routine tasks such as plotting and timeline generation with minimal sensitivity to the simulation that generated the data. Flight test data may also be translated into the common output class to simplify test reconstruction and analysis.

Moore, James W.↗
NASA NTRS2019

TPSAS-NF1676L-32540-DND

The supersonic/hypersonic ground testing serves a multitude of purposes and objectives. From structural and material integrity, to force and moment models; from pressure mapping, thermal imaging, shock structure to scramjet/ramjet engine operability and ignition studies. Hypersonics has become more of a high profile area of late. Compared to flight testing, ground testing typically it is less expensive and usually is not a one single-test test program. It is more forgiving in the fact that a test program can utilize a single test article and get data from a number of tests. Ground test data is the input to the formation of research databases, as well as, validation of CFD models/tools. To understand the output, one must first understand the inputs. To achieve supersonic/hypersonic speeds the use of compressors or compressed air storage along with converging-diverging nozzles are needed. Flight temperatures also need to be achieved for the ground test to truly simulate flight conditions. At NASA Langley's 8' High Temperature Tunnel (HTT), compressed natural gas (methane) is burned to heat the air. To validate that the desired test condition is met, test instrumentation is used and data is collected from the combustor all the way through the nozzle exit plane. In this talk, NASA Langley's 8' HTT will be the basis for what kind of test capabilities hypersonic ground testing offers. It certainly does not offer every capability within ground testing, nor will the discussion cover all types. Specific test techniques used and data collection methods will be discussed and how these confirm certain flight conditions have been achieved. There will be subsequent thoughts on experimental methods that aid test articles such as thrust stands, model actuation, etc.

Aaron W Fuchs↗
DOE OSTI2017

Application of gas-liquid fluid dynamics techniques to the modeling of sprays

The purpose of this paper is to provide an overview of modern computational techniques for gas-liquid systems as they are found in liquid fuel atomization applications. Fuel atomization – the generation of ligaments and droplets from the bulk of liquid injection – offers several modeling challenges: a localized surface tension force, depending on the accurate evaluation of interface curvature; drastic topology changes, which complicate interface advection and introduce local length scales; and separation of phases that have substantially different physical properties. The techniques presented in this review specifically target the gas-liquid interface and couple its evolution in time with the equations of multiphase fluid dynamics. Recent algorithmic advances in this area are discussed first, including new methods that improve conservation properties and deal with very large density ratios and compressibility effects. This part is followed by a discussion on the issue of convergence in simulations with topology changes (i.e., surface pinch-off) and on the viewpoint offered by atomistic and statistical modeling. State-of the-art simulations for various types of fuel injectors are presented next, with particular attention to numerical convergence and to the inclusion of realistic inlet boundary conditions. The review is concluded by the discussion of some of the challenges that still remains in this field.

42 ENGINEERING↗
DOE OSTI2025

Development of a thermal creep model for aluminum alloy 6061 cladding in U-10Mo monolithic fuel plates

Plate-type fuel elements consisting of a high-density, low-enriched uranium (LEU) U–10Mo-based fuel foil encapsulated in an aluminum alloy (AA) cladding are fabricated using the hot isostatic pressing (HIP) technique. During the HIP process, the fuel plate system is heated to 560 °C, then cooled to room temperature. This heat cycle significantly affects the mechanical properties of the aluminum cladding, and experimental investigations have shown that, post-HIP bonding, the mechanical properties of the aluminum cladding transition from those of AA 6061-T6 to something closer to the O temper. More specifically, the ultimate strength of the cladding decreases while its ductility increases, making it challenging to capture the changes in mechanical behavior and material properties. Understanding the residual stresses generated during the HIP process is critical for assessing the fuel plate’s integrity under various temperature, pressure, and irradiation. To simulate the HIP bonding process, the elastic, plastic, and thermal properties of the cladding are assumed to be similar to those of AA 6061-O temper. However, the primary challenge lies in the lack of available data for the creep model of the AA 6061 cladding during this transient process of HIP. The present study focuses on developing a computational model that predicts the creep behavior of the aluminum cladding in the fuel plates during the HIP process, as cladding creep significantly influences the residual stresses generated in U-10Mo fuel plates during HIP fabrication. Furthermore, as HIP bonding occurs at high temperatures that are nearing the melting point of aluminum, the present work considered a temperature-dependent Arrhenius-type creep model. In particular, a hyperbolic sine creep model is employed to estimate the creep properties of the as-fabricated aluminum cladding. In conclusion, the residual stresses predicted in the U-10Mo fuel when using the newly calibrated creep model closely align with the experimental measurements, validating the model’s accuracy.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A systematic feature extraction and selection framework for data-driven whole-building automated fault detection and diagnostics in commercial buildings

In data-driven automated fault detection and diagnostics (AFDD) modeling for building energy systems, feature engineering is a critical process of extracting information from high-dimensional and noisy sensor measurement and turning it into informative and representative inputs or features for data-driven modeling. However, few studies specifically discuss the feature engineering, especially the interactions between feature extraction and feature selection in whole-building AFDD. We developed a systematic feature extraction and selection framework for whole-building AFDD. In this framework, features are aggressively extracted from raw sensor data using statistical feature extraction techniques with various window sizes and statistics. With many features extracted, a hybrid feature selection algorithm that combines the filter and wrapper method then selects the best feature set. The framework considers diversity in the duration of fault behavior among fault types in whole-building AFDD, thus achieving high model generalization. We implemented our developed framework in a virtual testbed calibrated with measured data from Oak Ridge National Laboratory's Flexible Research Platform designed to mimic the operation of a typical small commercial building. The AFDD model is trained by the simulation data generated from the virtual testbed. The results show that (1) the developed framework improves the generalization of the AFDD model by 10.7% compared with literature-reported feature extraction and selection methods and (2) features with diverse window sizes and statistics are selected, providing insight into physical systems beyond the current understanding of buildings and faults and improving the detection and diagnostics of multiple fault types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

On the performance of exponential integrators for problems in magnetohydrodynamics

Exponential integrators have been introduced as an efficient alternative to explicit and implicit methods for integrating large stiff systems of differential equations. Over the past decades these methods have been studied theoretically and their performance was evaluated using a range of test problems. While the results of these investigations showed that exponential integrators can provide significant computational savings, the research on validating this hypothesis for large scale systems and understanding what classes of problems can particularly benefit from the use of the new techniques is in its initial stages. Resistive magnetohydrodynamic (MHD) modeling is widely used in studying large scale behavior of laboratory and astrophysical plasmas. In many problems numerical solution of MHD equations is a challenging task due to the temporal stiffness of this system in the parameter regimes of interest. In this paper we evaluate the performance of exponential integrators on large MHD problems and compare them to a state-of-the-art implicit time integrator. Both the variable and constant time step exponential methods of EPIRK-type are used to simulate magnetic reconnection and the Kevin–Helmholtz instability in plasma. Performance of these methods, which are part of the EPIC software package, is compared to the variable time step variable order BDF scheme included in the CVODE (part of SUNDIALS) library. We study performance of the methods on parallel architectures and with respect to magnitudes of important parameters such as Reynolds, Lundquist, and Prandtl numbers. We find that the exponential integrators provide superior or equal performance in most circumstances and conclude that further development of exponential methods for MHD problems is warranted and can lead to significant computational advantages for large scale stiff systems of differential equations such as MHD.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Searching for primordial non-Gaussianity in Planck CMB maps using a combined estimator

The extensive search for deviations from Gaussianity in cosmic microwave background radiation (CMB) data is very important due to the information about the very early moments of the universe encoded there. Recent analyses from Planck CMB data do not exclude the presence of non-Gaussianity of small amplitude, although they are consistent with the Gaussian hypothesis. The use of different techniques is essential to provide information about types and amplitudes of non-Gaussianities in the CMB data. In particular, we find interesting to construct an estimator based upon the combination of two powerful statistical tools that appears to be sensitive enough to detect tiny deviations from Gaussianity in CMB maps. This estimator combines the Minkowski functionals with a Neural Network, maximizing a tool widely used to study non-Gaussian signals with a reinforcement of another tool designed to identify patterns in a data set. We test our estimator by analyzing simulated CMB maps contaminated with different amounts of local primordial non-Gaussianity quantified by the dimensionless parameter f{sub NL}. We apply it to these sets of CMB maps and find ∼> 98% of chance of positive detection, even for small intensity local non-Gaussianity like f{sub NL} = 38±18, the current limit from Planck data for large angular scales. Additionally, we test the suitability to distinguish between primary and secondary non-Gaussianities: first we train the Neural Network with two sets, one of nearly Gaussian CMB maps (|f{sub NL}| ≤ 10) but contaminated with realistic inhomogeneous Planck noise (i.e., secondary non-Gaussianity) and the other of non-Gaussian CMB maps, that is, maps endowed with weak primordial non-Gaussianity (28 ≤ f{sub NL} ≤ 48); after that we test an ensemble composed of CMB maps either with one of these non-Gaussian contaminations, and find out that our method successfully classifies ∼ 95% of the tested maps as being CMB maps containing primordial or secondary non-Gaussianity. Furthermore, we analyze the foreground-cleaned Planck maps obtaining constraints for non-Gaussianity at large-angles that are in good agreement with recent constraints. Finally, we also test the robustness of our estimator including cut-sky masks and realistic noise maps measured by Planck, obtaining successful results as well.

79 ASTRONOMY AND ASTROPHYSICS↗