Search NASA⌕ Search

SEARCH · Search NASA

Results for “experimental methods development”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26

Application of Jacobian-free Newton–Krylov method in implicitly solving two-fluid six-equation two-phase flow problems: Implementation, validation and benchmark

This work represents a first-of-its-kind successful application to employ advanced numerical methods in solving realistic two-phase flow problems with two-fluid six-equation two-phase flow model. These advanced numerical methods include high-resolution spatial discretization scheme with staggered grids (high-order) fully implicit time integration schemes, and Jacobian-free Newton–Krylov (JFNK) method as the nonlinear solver. The computer code developed in this work has been extensively validated with existing experimental flow boiling data in vertical pipes and rod bundles, which cover wide ranges of experimental conditions, such as pressure, inlet mass flux, wall heat flux and exit void fraction. Additional code-to-code benchmark with the RELAP5-3D code further verifies the correct code implementation. The combined methods employed in this work exhibit strong robustness in solving two-phase flow problems even when phase appearance (boiling) and realistic discrete flow regimes are considered. Transitional flow regimes used in existing system analysis codes, normally introduced to overcome numerical difficulty, were completely removed in this work. As a result, this in turn provides the possibility to utilize more sophisticated flow regime maps in the future to further improve simulation accuracy.

42 ENGINEERING↗

Developing and Demonstrating a Lab Method for Quantifying Hair Exposure to Environmental Tobacco Smoke with a Forensic Perspective

Forensic science and chemistry curricula often lack hands-on experimental designs that effectively simulate the impact of environmental tobacco smoke (ETS) or other common elements found at crime scenes, such as marijuana, on trace forensic evidence. Hair, a critical form of trace evidence, offers unique advantages for assessing long-term exposure to environmental pollutants, including ETS. This study presents a novel, noninvasive forensic laboratory module designed to evaluate ETS exposure on various human hair types (untreated, dyed, and bleached). The experimental procedure involved controlled cigarette smoke exposure, followed by analysis using UV−visible spectroscopy, FTIR spectroscopy, and zeta potential measurements. Thirteen students participated in the three-week lab module (three sessions per week). Pre- and postlab assessments were conducted to evaluate learning outcomes. The prelab assessment focused on baseline knowledge of forensic hair analysis, as well as student expectations and confidence. The postlab assessment evaluated knowledge gained, technical insights, application of techniques, self-reflection, conceptual understanding, and practical skill development. This design helped students comprehend the effects of chemical treatments that significantly influence hair’s capacity to adsorb ETS residues by altering its physical and chemical properties. Integration of this experiment into the forensic chemistry curriculum led to measurable gains in student understanding, technical competency, and appreciation for realworld forensic applications. This method offers a valuable teaching and investigative tool for assessing individual ETS exposure in forensic contexts.

FTIR↗

Experimental Development of a Novel Stress Sensor for in situ Stress Measurement

This paper will describe ongoing work to adapt a previously demonstrated method for measuring stress in ceramics to develop a borehole deployed in situ stress sensor. The method involves the use of a cementitious material which exhibits a strong piezo-spectroscopic stress response as a downhole stress gage. A description of the conceptual approach will be provided along with preliminary analysis and proof-of-concept laboratory results.

Polsky, Yarom↗

Unraveling the Dynamics of Nucleosome Arrays

The organization of genomic DNA into chromatin is a fundamental determinant of genome stability, regulation, and cellular function. Nucleosomes, the basic repeating units of chromatin, assemble into higher-order structures whose organization and heterogeneity remain difficult to characterize using conventional ensemble-averaged techniques. A key need in the field is the development of experimental approaches capable of directly visualizing nucleosome assemblies and their structural variability at the single-molecule level. This LDRD Lab-Wide project focused on establishing and evaluating atomic force microscopy (AFM)–based approaches for the characterization of nucleosome assemblies. The work emphasized experimental workflows for preparing, imaging, and assessing multi-nucleosome systems, rather than isolated single nucleosomes. Through method development and exploratory measurements, the project demonstrated the feasibility of applying scanning probe microscopy to investigate chromatin-relevant assemblies and provided preliminary insight into the strengths and limitations of this approach for future quantitative studies. Results and lessons learned from this effort were disseminated to the broader scientific community through multiple national conference presentations, helping to position LLNL for continued work in chromatin and genome organization research.

59 BASIC BIOLOGICAL SCIENCES↗

Development and testing of a photometric method to identify non-operating solar hot water systems in field settings

This report presents the results of experimental tests of a concept for using infrared (IR) photos to identify non-operational systems based on their glazing temperatures; operating systems have lower glazing temperatures than those in stagnation. In recent years thousands of new solar hot water (SHW) systems have been installed in some utility districts. As these numbers increase, concern is growing about the systems dependability because installation rebates are often based on the assumption that all of the SHW systems will perform flawlessly for a 20-year period. If SHW systems routinely fail prematurely, then the utilities will have overpaid for grid-energy reduction performance that is unrealized. Moreover, utilities are responsible for replacing energy for loads that failed SHW system were supplying. Thus, utilities are seeking data to quantify the reliability of SHW systems. The work described herein is intended to help meet this need. The details of the experiment are presented, including a description of the SHW collectors that were examined, the testbed that was used to control the system and record data, the IR camera that was employed, and the conditions in which testing was completed. The details of the associated analysis are presented, including direct examination of the video records of operational and stagnant collectors, as well as the development of a model to predict glazing temperatures and an analysis of temporal intermittency of the images, both of which are critical to properly adjusting the IR camera for optimal performance. Many IR images and a video are presented to show the contrast between operating and stagnant collectors. The major conclusion is that the technique has potential to be applied by using an aircraft fitted with an IR camera that can fly over an area with installed SHW systems, thus recording the images. Subsequent analysis of the images can determine the operational condition of the fielded collectors. Specific recommendations are presented relative to the application of the technique, including ways to mitigate and manage potential sources of error.

15 GEOTHERMAL ENERGY↗

Modeling of Powder Bed Manufacturing Defects

Powder bed additive manufacturing offers unmatched capabilities. The deposition resolution achieved is extremely high enabling the production of innovative functional products and materials. Achieving the desired final quality is, however, hampered by many potential defects that have to be managed in due course of the manufacturing process. Defects observed in products manufactured via powder bed fusion have been studied experimentally. In this effort we have relied on experiments reported in the literature and—when experimental data were not sufficient—we have performed additional experiments providing an extended foundation for defect analysis. There is large interest in reducing the effort and cost of additive manufacturing process qualification and certification using integrated computational material engineering. A prerequisite is, however, that numerical methods can indeed capture defects. A multiscale multiphysics platform is developed and applied to predict and explain the origin of several defects that have been observed experimentally during laser-based powder bed fusion processes. The models utilized are briefly introduced. The ability of the models to capture the observed defects is verified. The root cause of the defects is explained by analyzing the numerical results thus confirming the ability of numerical methods to provide a foundation for rapid process qualification.

36 MATERIALS SCIENCE↗

Lignin Utilization

Valorization of lignin has massive potential economic and sustainability benefits for the lignocellulosic biorefinery. However, challenges remain to realize lignin conversion to coproducts, especially related to selective, high yield depolymerization to monomers and quantitative analytics on lignin, the latter of which is critical for accurate process modeling. Towards these goals, the Lignin Utilization project focuses on catalytic lignin deconstruction chemistries for C-O and C-C bond cleavage, development of analytical chemistry techniques to quantitatively characterize lignin, and syntheses of requisite model compounds for understanding lignin transformations. This work is done with and supports multiple BETO projects, including the Biological Lignin Valorization (BLV) project, the Separations Consortium, and others. Outcomes of Lignin Utilization for analytics and synthesis include 1) development of new mass spectrometry (MS) methods to characterize lignin dimers/oligomers in process streams, 2) deployment of a computational-experimental tool (with Biochemical Process Modeling and Simulation) to identify lignin-derived compounds with high fidelity from MS, and 3) delivery of >40 unique compounds. From a catalysis perspective, we have developed new oxidative approaches to cleave C-O and C-C bonds and produce >50% bio-available aromatic monomers for biological funneling for the BLV project and have developed recoverable bases for base-catalyzed deconstruction of lignin.

BIOMASS FUELS↗

Modern chemical graph theory

Abstract Graph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Structure and Mechanism > Computational Materials Science Structure and Mechanism > Molecular Structures

Leite, Leonardo S. G.↗

Analysis of Uncertainty Impacts on Emissions and Fuel Economy Evaluation for Chassis Dynamometer Testing

This study illustrates a methodology for quantifying the uncertainties encountered in the measurement of tailpipe emissions and in the fuel consumption measurements for light-duty conventional vehicles tested on a four-wheel drive chassis dynamometer. The study leverages high-fidelity experimental data collected over three standard drive cycles, UDDS, HWY and US06, intended to simulate a wide range of operating conditions. Here, a method is developed to estimate the measurement uncertainties in fuel consumption for a test cycle, which occur due to the accumulation of measurement uncertainties propagated through the system. The uncertainty determination model uses statistical analysis and standard propagation techniques to evaluate and combine the uncertainties introduced from various sources (including the vehicle, chassis dynamometer, driver, and instrumentation). The analysis also examines three different experimental methods for determining the fuel consumption: 1) carbon mass balance, 2) volumetric fuel scale and 3) gravimetric fuel scale, and takes into consideration the properties of the instrumentation used. The results show that the most significant influence on the determination of the emissions comes from the concentration measurement, and similarly the biggest impact on the total fuel consumption uncertainty comes from the uncertainty in the determination of the carbon dioxide mass, due to the large presence of this pollutant in the overall emissions. It was found that the fuel consumption uncertainties are in the range of ±1-2% for all three methods analyzed, with the lowest values being obtained for measurements performed using the gravimetric method for all three drive cycles considered.

33 ADVANCED PROPULSION SYSTEMS↗

Gyrokinetic particle simulation of microturbulence for general magnetic geometry and experimental profiles

Developments in gyrokinetic particle simulation enable the gyrokinetic toroidal code (GTC) to simulate turbulent transport in tokamaks with realistic equilibrium profiles and plasma geometry, which is an essential step in the code–experiment validation process. These novel developments include numerical equilibrium representation using B-splines, a new Poisson solver based on finite difference using field-aligned mesh and magnetic flux coordinates, a new zonal flow solver for general geometry, and improvements on the conventional four-point gyroaverage with nonuniform background marker loading. The gyrokinetic Poisson equation is solved in the perpendicular plane instead of the poloidal plane. Exploiting these new features, GTC is able to simulate a typical DIII-D discharge with experimental magnetic geometry and profiles. The simulated turbulent heat diffusivity and its radial profile reflects good agreement with other gyrokinetic codes. The newly developed nonuniform loading method provides a modified radial transport profile to that of the conventional uniform loading method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hardware-In-the-Loop Benchmarking Setup for Phasor Based Control Validation

Phasor Based Control is a novel approach to controlling Distributed Energy Resources that aims at relieving various constraints that arise in the distribution grid. It is a two-layer control system with a supervisory control that coordinates distributed controllers to reach voltage phasor targets. The distributed controllers use local synchrophasor measurements and operate as feedback controllers. This control method is currently under development with several algorithms being under consideration for both the central and distributed components. In this report, we present the experimental setup that was prepared to prototype a hardware implementation and validate the control method in Hardware-In-the-Loop.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hardware-In-the-Loop Benchmarking Setup for Phasor Based Control Validation

Phasor Based Control is a novel approach to controlling Distributed Energy Resources that aims at relieving various constraints that arise in the distribution grid. It is a two-layer control system with a supervisory control that coordinates distributed controllers to reach voltage phasor targets. The distributed controllers use local synchrophasor measurements and operate as feedback controllers. This control method is currently under development with several algorithms being under consideration for both the central and ditributed components. In this paper, we present the experimental setup that was prepared to prototype a hardware implementation and validate the control method in Hardware-In-the-Loop.

Baudette, Maxime↗

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesian inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.

97 MATHEMATICS AND COMPUTING↗

Investigating Low Temperature Properties of Rubber Seals - 13020

To achieve the required tightness levels of containers for low and intermediate level radioactive wastes rubbers are widely applied as main sealing materials. The save encapsulation of the radioactive container contents has to be guaranteed according to legislation and appropriate guidelines for long storage periods as well as down to temperatures of -40 deg. C during transportation. Therefore the understanding of failure mechanisms that lead to leakage at low temperatures is of high importance. It is known that the material properties of rubbers are strongly influenced by temperature. At low temperatures this is caused by the rubber-glass transition (abbr. glass transition). During continuous cooling the material changes from rubber-like entropy-elastic to stiff energy-elastic behaviour, that allows nearly no strain or retraction. Therefore, rubbers are normally used above their glass transition but the minimum working temperature limit is not defined precisely, what can cause problems during application. The temperature range where full functionality is possible is strongly dependent on the application conditions and the material. For this investigation mainly ethylene propylene diene (EPDM) and fluorocarbon rubbers (FKM) were selected as they are often used for radioactive waste containers. Differential Scanning Calorimetry (DSC) and Dynamic Mechanical Analysis (DMA) are typically used for the determination of the temperature range of the glass transition process. The standardized compression set measurement according to ISO 815 is common for investigation of rubber sealing materials as the test simulates the seal behaviour after release. To reduce the test time of the standard tests a faster technique giving the same information was developed. Additionally, the breakdown temperature of the sealing function of complete O-ring seals is measured in a component test setup to compare it with the results of the other tests. The experimental setup is capable of measuring the leakage rate at low temperatures by the pressure rise method. A model was developed that allows calculating the minimum working temperature limit of a seal by combining the results of the applied methods. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Comparison of Advanced Processing of Irradiated UO{sub 2} Fuels and NpO{sub 2} Targets

Advanced processing methods for UO{sub 2}-based used nuclear fuels have been developed and demonstrated in several experimental programs at the Oak Ridge National Laboratory's Radiochemical Engineering Development Center (REDC). The Consolidated Fuel Recycle Program (1979-1986) and the Advanced Fuel Cycle Initiative (2002- 2008) were sponsored by the U.S. Department of Energy Office of Nuclear Energy (DOE/NE). Currently, DOE/NE is administering a new program for the National Aeronautics and Space Administration to produce {sup 238}Pu by irradiating NpO{sub 2}, and the irradiated targets are to be chemically processed using the same equipment and shielded facilities in the REDC that were used previously to process irradiated UO{sub 2}-based fuels. Flowsheets for processing irradiated NpO{sub 2} targets are now being developed and demonstrated. There are both similarities and differences in the processing of the two types of irradiated fuels/targets, and a comparison of these is useful for application to new types of feed material. A comparison of similarities and differences for processing UO{sub 2}- and NpO{sub 2}-based feed materials has been useful in planning for advanced processing methods and new requirements. Use of existing multistage solvent extraction equipment and shielded processing facilities at the ORNL REDC has enabled development, demonstration, and application of new and improved separations methods. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Characterization of Creep-Fatigue Crack Growth in Alloy 709 and Prediction of Service Lives in Nuclear Reactor Components (Final Report)

This final report summarizes the activities and results that were obtained by the research team working on the project “Characterization of Creep-Fatigue Crack Growth in Alloy 709 and Prediction of Service Lives in Nuclear Reactor Components”, DOE-NEUP Project 15-8623. This project was mainly concerned with the creep-fatigue crack growth characterization of austenitic stainless-steel Fe-20Cr-25Ni (Alloy 709). For this purpose, an array of experimental and computational activities was performed. The main goal of these activities was to describe and predict the crack growth behavior in Alloy 709 under different conditions of applied loading and temperature. Alloy 709 specimens were tested to describe both the uniaxial creep behavior and creep-fatigue crack growth rates at temperatures between 550°C and 700°C. Microstructure and fracture surface analysis was performed using several experimental techniques, and the defining features of crack growth propagation were identified and described. Thermodynamic and diffusion simulations were performed to understand the microstructure evolution of Alloy 709 at elevated temperatures, and to establish an aging schedule relevant for in-service conditions over extended periods. Experimental testing was performed on both as-received and aged Alloy 709 specimens. Two computational methods were developed to predict crack growth rates and remaining lives in specimens loaded under either fatigue of creep-fatigue. The first computational technique was the finite element method, while the second was strip-yield modeling. Both methods relied on the prediction of crack growth rates using the concept of plasticity-induced crack closure. Crack-tip opening loads were computed and used to perform crack growth rate predictions. The computational predictions matched well with the experimental results. The strip-yield model was shown to be an excellent predictive tool not only for crack growth in austenitic SS Alloy 709, but also in 316 SS, martensitic Cr-Mo steels, Ni-based alloys and Al-based alloys. The main conclusion of this study is that Alloy 709 exhibits excellent creep crack growth resistance at temperatures between 550°C and 700°C. In fact, the crack growth resistance of this alloy appears to be higher than that of 316 SS in similar testing conditions. Moreover, when creep loading with hold (dwell) times of 60s or 600s were intercalated every fatigue cycle, the crack growth rates did not change significantly. The conclusion is that the tests performed revealed that the crack growth is insignificant during the creep portion of a loading cycle, as compared with the crack growth during the fatigue portion of the cycle. In general, Alloy 709 shows excellent resistance to creep deformations and creep crack growth up to 700°C.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Nanocatalysis: Size- and Shape-dependent Chemisorption and Catalytic Reactivity

This review article focuses on correlating the catalytic reactivity of NPs and their geometry. It illustrated that chemisorption and catalytic properties such as the onset reaction temperature, the activity, and selectivity of a nanocatalyst may be tuned through controlled synthesis of NPs with well-defined sizes and shapes. It has become clear that detailed information on the physical/chemical properties of supported NP systems must be available for the rational design of the next generation of nanosized catalysts. Such NP systems must be representative of active catalysts, and must be sufficiently well-defined ( e.g., with respect to size and shape) to serve as a basis for theoretical modeling. In addition, a synergistic combination of in situ and in operando characterization techniques working under realistic reaction conditions ( e.g. elevated temperatures and high pressure) must be available, since the working state of a NP catalyst might not be the state in which the catalyst was prepared, but a structural and/or chemical isomer that adapted to the particular reaction conditions. In order to address the complexity of real-world catalysts, a synergistic approach taking advantage of a variety of state-of-the-art experimental and theoretical methods must be undertaken. In this review, we have described some of the impressive developments that have been made in these areas. Many serious challenges still remain in the areas of catalyst characterization and design. One such challenge is to design highly active metal NP catalysts using abundant, inexpensive metals which can replace precious metal catalysts. Additionally, there is an increasingly pressing need for catalyst development for energy production applications, such as in fuel cells or for the synthesis of chemicals and fuels. Further work is needed to design more active and selective catalysts for these reactions that are viable at an industrial scale. In the coming years, nanocatalysis research must meet these challenges by building on the work described in this report. Further advancements in developing new synthetic methods will allow increased control over NP structure and stability, allowing for new insights into NP structure-reactivity correlations. In addition, the development of higher resolution in situ and in operando measurement techniques capable of probing catalytic reactions at NP surfaces over an extended range of temperatures and pressures and harsh environmental conditions will give unprecedented insight into NP catalysts in their working state. Single-nanoparticle spectroscopic and catalytic characterization must also be further developed. Advancements in computational modeling of more realistic catalysts will also bring us closer to gaining a molecularlevel view of a reaction at a NP surface when used to complement experimental studies. Such progress will bring us closer to realizing the goal of synthesizing highly effective, tailor-made, tunable nanoparticle catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries

Machine learning is rapidly becoming an integral part of experimental physical discovery via automated and high-throughput synthesis, and active experiments in scattering and electron/probe microscopy. This, in turn, necessitates the development of active learning methods capable of exploring relevant parameter spaces with the smallest number of steps. In this work, an active learning approach based on conavigation of the hypothesis and experimental spaces is introduced. This is realized by combining the structured Gaussian processes containing probabilistic models of the possible system's behaviors (hypotheses) with reinforcement learning policy refinement (discovery). This approach closely resembles classical human-driven physical discovery, when several alternative hypotheses realized via models with adjustable parameters are tested during an experiment. This approach is demonstrated for exploring concentration-induced phase transitions in combinatorial libraries of Sm-doped BiFeO 3 using piezoresponse force microscopy, but it is straightforward to extend it to higher-dimensional parameter spaces and more complex physical problems once the experimental workflow and hypothesis generation are available.

36 MATERIALS SCIENCE↗