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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

Review of heat transfer enhancement techniques in two-phase flows for highly efficient and sustainable cooling

We show that two-phase internal flow is ubiquitous to many systems due to its ability to transfer large amounts of heat effectively. Recent advances motivated by sustainability have pushed towards augmenting the heat transfer between the tube and the two-phase working fluid. Augmenting heat transfer in two-phase flows enables process intensification, and compactness leading to reduced cost and material consumption. This review investigates the effect of heat transfer enhancement techniques on different fluids including R134a, R407C, R22, etc … The techniques are categorized into passive and active and focus on durable enhancement methods which do not include surface structuring or coating. Passive techniques utilize geometrical and surface modifications to induce better mixing. Several passive techniques are analyzed including fins, inserts, and more. In analyzing these techniques, the effect of changing geometric parameters is studied, and the limitations are highlighted. Further, active techniques that enable heat transfer enhancement through applying power are also investigated. Electrohydrodynamic approaches are analyzed and compared to passive techniques. Additionally, the implications of heat exchange enhancement in the context of global energy are discussed. An energy analysis discretized by the use sector is conducted, with an emphasis on predicting the future potential for renewable and sustainable development. Moreover, although active approaches provide the highest heat transfer enhancement, due to implementation difficulties, passive techniques are more frequently adopted. The review ends with discussion of next-generation heat exchangers which will rely more on additive manufacturing due to its flexibility and reduced cost per part as the technology matures.

Nusselt number↗
DOE OSTI2025

Development of High-Temperature Bonding Techniques to Enable High-Temperature Static or Dynamic Strain Measurements

Current light-water nuclear reactors rely on a variety of different sensors and sensor applications to meet their structural health monitoring needs throughout the entirety of the reactor primary, secondary, and containment systems. Optical fiber–based sensor technologies could provide solutions to reduce the sensor system footprint while enhancing the measurement fidelity and spatial resolution by leveraging distributed monitoring techniques. Moreover, advanced reactors may require optical fiber–based sensors for structural health monitoring because their operating temperatures will exceed the limits of conventional transducers used to acquire dynamic strain or acoustic data in nuclear power plants. Therefore, this report describes experiments targeting the development of high-temperature bonding techniques that would allow for potentially long lengths of fibers to be bonded to metallic reactor components in advanced reactor systems. The high temperatures experienced within target application, next-generation nuclear reactors, necessitate a high-temperature resistant bond to limit the amount of tension on the fiber at the target application temperature. The primary bonding method investigated in this work is brazing; hot-rolling has also been investigated to a lesser extent. Both techniques are well-suited to bonding optical fibers to large reactor components such as primary coolant piping, pressure vessels, or heat exchangers. Optical frequency domain reflectometry was used to monitor the strain in metal-coated optical fibers before, during, and after the high-temperature bonding process. On select optical fibers that were successfully bonded, additional thermal cycling was performed to assess the extent to which the fiber remained bonded based on the expected thermal expansion of the test specimen material. The results of the various experiments yielded the following general conclusions: (1) brazing is a viable technique for bonding and allows significant compressive strain to be applied to the fiber at room temperature; (2) hot-rolling is a viable technique as well, which has been more optimized than the brazing technique for bonding, but less residual compressive strain has been observed with this technique; and (3) both techniques will need further development and optimization to demonstrate bonding of a long length of fiber that can provably operate at relevant temperatures for an advanced nuclear reactor application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Survey of prospective techniques for molten salt reactor feed monitoring

Safeguards verification measurements of nuclear material content in fresh fuel salt for liquid-fueled molten salt reactors (MSRs) are likely to be required as part of nuclear material accountancy for International Atomic Energy Agency safeguards. Here, this paper presents a comprehensive review and evaluation of 18 potential candidate techniques to quantify total uranium and 235 U for input accountancy measurements for liquid-fueled MSRs. As part of an overall screening and down-selection effort to identify the most promising techniques for further development for an MSR feed monitoring system, this paper defines eight figures of merit (FOMs): reasonably achievable measurement uncertainty, measurement time required, capital cost, burden upon the facility operator, maintenance intensity, technological maturity, human capital requirements for operation, and whether the technique introduces a path for potential material removal. Each candidate technique is then evaluated across these FOMs to identify the techniques with the highest potential for future development for fresh fuel accountancy measurements in MSRs. Our findings indicate that no single technique or combination thereof currently has the requisite technological maturity for immediate implementation in nuclear material accountancy at a liquid-fueled MSR facility. While several promising techniques are identified, there is a critical lack of experimental data for most systems in the context of molten salt applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Proof that Combining the Forced-collision and DXTRAN Monte Carlo Variance-reduction Techniques is Fair

This report provides mathematical proof that the MCNP DXTRAN (also known in other codes as forced-flight) and forced-collision variance-reduction techniques do not bias the expected value of Monte Carlo simulation estimates when combined. Proof is also provided that the techniques are unbiased when used independently. To prove that the techniques are unbiased, this report derives the first History Score Moment Equation (HSME) for non-multiplying media employing only forced collisions, only DXTRAN, and then both the variance-reduction techniques combined, as defined next. The HSMEs are found by forming the History Score Probability Density Functions (HSPDFs) and then taking the first score moment. Following its derivation, each HSME with a variance-reduction technique employed is reduced to the HSME for an analog simulation. Because the HSME represents the expected contribution to estimators in the simulation, reducing the HSME with variance reduction to the analog HSME shows that the simulation is unbiased despite the variance-reduction technique considered in the HSME. Analysis regarding higher-score moments of each technique is the subject of prior work and is not addressed herein. Throughout this work, the phase space p is defined to be the particle position x, direction-of-flight unit vector $\hat{Ω}$, energy E, and statistical weight w, $$p ≡ (x; \hat{Ω}; E; w).$$ A reduced phase-space excluding the statistical weight of the particle, $$r ≡ (x; \hat{Ω}; E),$$ is also used.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Ensemble Simulation Techniques and Fast Randomized Algorithms

The major goals of the project were to develop and analyze new ensemble simulation techniques, including trajectory stratification and preconditioned MCMC techniques, as well as develop fast numerical linear algebra techniques closely related to ensemble simulation ideas. The trajectory stratification techniques involve simulating in parallel short trajectory fragments of a Markov process confined to a specific region of space‐time and then patching together the statistics gathered to assemble estimates of very general dynamical properties. We have also developed this approach for rare event simulation and extended the techniques to applications requiring a more general framework (such as electronic structure calculations). The preconditioned MCMC techniques involve simulating multiple Markov chains in parallel and then using information from the ensemble to speed the mixing of each individual chain. The fast randomized linear algebra methods are motivated by the diffusion Monte Carlo technique, but are applicable to finding the dominant eigenvalue of (almost) general matrices. For most non‐negative matrices, the schemes result in an error (compared to the power method) that is constant in the dimension of the problem. For more general matrices, we see a very clear sublinear cost trend in computational tests.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Review of Solid State Consolidation Processing Techniques of ODS Steels (Hot Extrusion, Hot Isostatic Pressing, Spark Plasma Sintering, and Stir Friction Consolidation): Resulting Microstructures and Mechanical Properties

This paper reviews the solid-state consolidation processing techniques for Oxide Dispersion Strengthened steels and compares them in terms of the resulting microstructure and reported mechanical properties. Synthesis techniques include hot extrusion, hot isostatic pressing, spark plasma sintering and friction consolidation. The effects of process parameters on the resulting microstructures and performance are discussed for each technique. Average oxide size, average grain size, and porosity are compared across techniques, as well as mechanical strength and ductility. Across consolidation techniques where temperature can be controlled, a low sintering temperature with a high sintering pressure is favorable for keeping oxide sizes, grain sizes, and porosity low. The use of yttrium and titanium for oxide formation has been evidenced to reduce oxide sizes, and tungsten additions have been shown to improve strength. Current literature suggests that the more mature hot extrusion technique produces stronger steel with consistently fine oxides, while other alternative solid-state consolidation, while promising, offer margin for improvement.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comparison of time-frequency-analysis techniques applied in building energy data noise cancellation for building load forecasting: A real-building case study

Time-frequency analysis that disaggregates a signal in both time and frequency domain is an important supporting technique for building energy analysis such as noise cancellation in data-driven building load forecasting. There is a gap in the literature related to comparing various time–frequency-analysis techniques, especially discrete wavelet transform (DWT) and empirical mode decomposition (EMD), to guide the selection and tuning of time–frequency-analysis techniques in data-driven building load forecasting. This article provides a framework to conduct a comprehensive comparison among thirteen DWT/EMD techniques with various parameters in a load forecasting modeling task. A real campus building is used as a case study for illustration. The DWT and EMD techniques are also compared under various data-driven modeling algorithms for building load forecasting. The results in the case study show that the load forecasting models trained with noise-cancelled energy data have increased their accuracy to 9.6% on average tested under unseen data. This study also shows that the effectiveness of DWT/EMD techniques depends on the data-driven algorithms used for load forecasting modeling and the training data. Hence, DWT/EMD-based noise cancellation needs customized selection and tuning to optimize their performance for data-driven building load forecasting modeling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteins

Here, we outline recent developments in artificial intelligence (AI) and machine learning (ML) techniques for integrative structural biology of intrinsically disordered proteins (IDP) ensembles. IDPs challenge the traditional protein structure-function paradigm by adapting their conformations in response to specific binding partners leading them to mediate diverse, and often complex cellular functions such as biological signaling, self-organization and compartmentalization. Obtaining mechanistic insights into their function can therefore be challenging for traditional structural determination techniques. Often, scientists have to rely on piecemeal evidence drawn from diverse experimental techniques to characterize their functional mechanisms. Multiscale simulations can help bridge critical knowledge gaps about IDP structure-function relationships - however, these techniques also face challenges in resolving emergent phenomena within IDP conformational ensembles. We posit that scalable statistical inference techniques can effectively integrate information gleaned from multiple experimental techniques as well as from simulations, thus providing access to atomistic details of these emergent phenomena.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Timing Calibration and Windowing Technique Comparison for Lightning Mapping Arrays

Abstract Since their introduction 22 years ago, lightning mapping arrays (LMA) have played a central role in the investigation of lightning physics. Even in recent years with the proliferation of digital interferometers and the introduction of the LOw Frequency ARray (LOFAR) radio telescope, LMAs still play an important role in lightning science. LMA networks use a simple windowing technique that records the highest pulse in either 80 μs or 10 μs fixed windows in order to apply a time‐of‐arrival location technique. In this work, we develop an LMA‐emulator that uses lightning data recorded by LOFAR to simulate an LMA, and we use it to test three new styles of pulse windowing. We show that they produce very similar results as the more traditional LMA windowing, implying that LMA lightning mapping results are relatively independent of windowing technique. In addition, each LMA station has its GPS‐conditioned clock. While the timing accuracy of GPS receivers has improved significantly over the years, they still significantly limit the timing measurements of the LMA. Recently, new time‐of‐arrival techniques have been introduced that can be used to self‐calibrate systematic offsets between different receiving stations. Applying this calibration technique to a set of data with 32 ns uncertainty, observed by the Colorado LMA, improves the timing uncertainty to 19 ns. This technique is not limited to LMAs and could be used to help calibrate future multi‐station lightning interferometers.

Hare, Brian M.↗
DOE OSTI2024

A Third Harmonic Voltage Injection Technique to Improve The Power Transmission Capacity

To facilitate the growing deployment of renewable energy sources and increasing load demand, it is imperative to increase the power transmission capacity of the existing transmission corridors. The available power uprating techniques are either costly, or require significant alteration to the existing system. Moreover, most of these techniques are suitable for long transmission lines. In light of these limitations, a third harmonic voltage injection based power uprating technique is proposed in this article. The proposed technique is economic, immune to line impedance unbalance, and is applicable for any length of transmission line. Most importantly, the technique needs very minimal modification in the existing system at the substation level. The efficacy of the proposed technique is validated through simulation and experiments.

Das, Anubrata↗
DOE OSTI2023

A Six-Phase Space Vector PWM Technique for Wide Bandgap Device-Based Three-Level Inverters

This article presents a space vector pulsewidth modulation (SVPWM) technique for wide bandgap (WBG) device-based three-level (3L) six-phase inverters. Implementation of the SVPWM techniques for any six-phase inverter is complex for its high number of possible voltage vectors. Different six-phase load configurations are also possible depending on the angle between two consecutive phases and neutral point connections. The implementation techniques change depending on the load configuration. Moreover, a common neutral point for all six phases leads to circulating currents. Capacitor voltage balancing is also needed for 3L inverters. Capacitor voltage balancing and addressing the circulating current problem further increases the implementation complexity. In this article, a generalized SVPWM technique is proposed for the six-phase 3L inverters that is implementable using two three-phase 3L SVPWM blocks. The SVPWM technique also ensures dc bus capacitor voltage balancing and minimizes circulating current. Here, the SVPWM technique is experimentally verified using a GaN-based 3L six-phase active neutral point clamped (ANPC) inverter prototype, and the results are presented in this article.

42 ENGINEERING↗
DOE OSTI2025

Image-Driven Hybrid Structural Analysis Based on Continuum Point Cloud Method with Boundary Capturing Technique

Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure. The captured edge profiles are transformed into essential boundary conditions. This allows the construction of a strongly formulated boundary value problem (BVP), classified as the Dirichlet problem. Capturing boundary conditions from the digital image is novel, although a similar approach was applied to the point cloud data. It was shown that the CPCM is more efficient in this hybrid simulation framework than the weak-form-based numerical schemes. Unlike the finite element method (FEM), it can avoid aligning boundary nodes with regression points. A three-point bending test of a rubber beam was simulated to validate the developed technique. The simulation results were benchmarked against numerical results by ANSYS and various relevant numerical schemes. The technique can effectively solve the Dirichlet-type BVP, yielding accurate deformation, stress, and strain values across the entire problem domain when employing a linear strain model and increasing the number of CPCM nodes. In addition, comparative analysis with conventional displacement tracking techniques verifies the developed technique’s robustness. The proposed technique effectively circumvents the inherent limitations of traditional monitoring methods resulting from the reliance on physical gauges or target markers so that a robust and non-contact solution for remote structural health monitoring in real-scale infrastructures can be provided, even in unfavorable experimental environments.

Chemistry↗
DOE OSTI2022

Evaluation of hydrograph separation techniques with uncertain end-member composition

Hydrograph separation is one of many approaches used to analyse shifts in source water contributions to stream flow resulting from climate change in remote watersheds. Understanding these shifts is vital, as shifts in source water contributions to a stream can shape water management decisions. Because remote watersheds are often inaccessible and have poorly characterized contributing water sources, or end-members, it is critical to understand the implications of using different hydrograph separation techniques in these data-limited environments. To explore the uncertainty associated with different techniques, results from two hydrograph separation techniques, mass balance and principle component analysis, were compared using 3 years of aqueous geochemical data from the East River watershed located in the Elk Mountains of Central Colorado. Solute concentrations of the end-members were characterized by both a limited set of direct chemical measurements of different sources and detailed seasonal instream chemistry to examine the influences of uncertain end-member compositions in a data-limited environment. Annual volumetric end-member contributions to stream flow had relatively good agreement across separation techniques. Large variations in time were observed in the hydrograph separations, depending on the end-member type, and estimated flow contributions varied between the selected solutes. End-member concentrations characterized by stream chemistry showed several limitations including a reduced number of distinguishable end-members and differences in timing of flow contributions. Here the results highlight the benefits of using multiple hydrograph separation techniques by providing a ‘weight-of-evidence’ approach to environments with limited end-member concentration data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A survey on processing-in-memory techniques: Advances and challenges

Processing-in-memory (PIM) techniques have gained much attention from computer architecture researchers, and significant research effort has been invested in exploring and developing such techniques. Increasing the research activity dedicated to improving PIM techniques will hopefully help deliver PIM’s promise to solve or significantly reduce memory access bottleneck problems for memory-intensive applications. We also believe it is imperative to track the advances made in PIM research to identify open challenges and enable the research community to make informed decisions and adjust future research directions. In this survey, we analyze recent studies that explored PIM techniques, summarize the advances made, compare recent PIM architectures, and identify target application domains and suitable memory technologies. We also discuss proposals that address unresolved issues of PIM designs (e.g., address translation/mapping of operands, workload analysis to identify application segments that can be accelerated with PIM, OS/runtime support, and coherency issues that must be resolved to incorporate PIM). We believe this work can serve as a useful reference for researchers exploring PIM techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Survey of Cyber Risk Analysis Techniques for Use in the Nuclear Industry

Using traditional probabilistic risk analysis methods for severe accident safety risk management on non-digital systems, structures, and components at nuclear power plants is well-established. In contrast, cyber risk analysis of digital assets is still an immature field with unproven techniques due, in part, to the continuously changing threat environment and the challenge of digital assets failing in unexpected ways. As the nuclear fleet continues to adopt digital instrumentation and control systems, it is increasingly important to have effective and efficient cyber risk analysis techniques to support risk management decisions, such as risk elimination by system redesign or risk mitigation by implementation of prioritized security controls. To understand the state of the art in cyber risk analysis for future research, we surveyed 36 publications across ten application domains. We describe our survey methodology and rate each technique based upon scope, adoptability, and repeatability. In this work, we examine the unique constraints of the nuclear industry and outline the strengths and weaknesses of using the cyber risk analysis techniques in the industry, highlighting gaps with current techniques. We also discuss challenges and potential research directions for advancing the science for both existing and new advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Brownian bridge-based speed imputation technique for truck energy consumption and emissions estimation

The available truck Global Positioning System (GPS) data, typically collected with large time gaps, rely on imputation techniques to obtain second-by-second data that are required in models for estimating truck energy consumption and emissions. However, existing speed imputation techniques either require a large amount of high-resolution data for model training or rely on special movement assumptions. Here, to fill the gap and effectively apply the low-resolution truck GPS datasets, this paper proposes a simple imputation technique that adopts the Brownian bridge structure to impute missing speed data. The proposed technique introduces a feasible imputation region and a combined drift into the imputation procedure to capture vehicle acceleration constraint, travel distance constraint, and speed volatility. The calibrated model is applied to a set of low-resolution truck GPS data. The results demonstrate the robustness of the proposed technique in enhancing estimation accuracy when using low-resolution GPS data to estimate fuel consumption and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Plasma and trap-based techniques for science with antimatter

Positrons (i.e., antielectrons) find use in a wide variety of applications, and antiprotons are required for the formation and study of antihydrogen. Available sources of these antiparticles are relatively weak. To optimize their use, most applications require that the antiparticles be accumulated into carefully prepared plasmas. We present an overview of the techniques that have been developed to efficiently accumulate low energy antiparticles and create, in particular, tailored antiparticle plasmas. Techniques are also described to create tailored antiparticle beams. Many of these techniques are based on methods first developed by the nonneutral plasma community using electron plasmas for increased data rate. They have enabled the creation and trapping of antihydrogen, have been critical to studies of positron and positronium interactions with matter, including advanced techniques to characterize materials and material surfaces, and have led to the creation and study of the positronium molecule. Rather than attempting to be comprehensive, we focus on techniques that have proven most useful, applications where there has been significant, recent progress, and areas that hold promise for future advances. Examples of the latter include the ever more precise comparisons of the properties of antihydrogen and hydrogen, tests of gravity using antihydrogen and positronium atoms, and efforts to create and study phases of the many-electron, many-positron system.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Analysis techniques for blob properties from gas puff imaging data

Filamentary structures, also known as blobs, are a prominent feature of turbulence and transport at the edge of magnetically confined plasmas. They cause cross-field particle and energy transport and are, therefore, of interest in tokamak physics and, more generally, nuclear fusion research. Several experimental techniques have been developed to study their properties. Among these, measurements are routinely performed with stationary probes, passive imaging, and, in more recent years, Gas Puff Imaging (GPI). In this work, we present different analysis techniques developed and used on 2D data from the suite of GPI diagnostics in the Tokamak à Configuration Variable, featuring different temporal and spatial resolutions. Although specifically developed to be used on GPI data, these techniques can be employed to analyze 2D turbulence data presenting intermittent, coherent structures. We focus on size, velocity, and appearance frequency evaluation with, among other methods, conditional averaging sampling, individual structure tracking, and a recently developed machine learning algorithm. We describe in detail the implementation of these techniques, compare them against each other, and comment on the scenarios to which these techniques are best applied and on the requirements that the data must fulfill in order to yield meaningful results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗