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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 271 records · Page 15

NREL's Capabilities in Analytical Sciences Supporting Research and Development (R&D)

NREL researchers perform biomass characterization in dedicated laboratories working with over $5 million in state-of-the-art analytical equipment. A dedicated team of highly skilled analytical chemists have over 100 cumulative years of experience in characterization. They have three specialized laboratories with dedicated sample processing and advanced analytical equipment. Core capabilities include biomass and biochemical characterization and quantification, publicly available laboratory analytical procedures (LAPs), and near-infrared rapid analysis.

analysis↗

Uncertainty management by relaxation of conflicting constraints in production process scheduling

Mathematical-analytical methods as used in Operations Research approaches are often insufficient for scheduling problems. This is due to three reasons: the combinatorial complexity of the search space, conflicting objectives for production optimization, and the uncertainty in the production process. Knowledge-based techniques, especially approximate reasoning and constraint relaxation, are promising ways to overcome these problems. A case study from an industrial CIM environment, namely high-grade steel production, is presented to demonstrate how knowledge-based scheduling with the desired capabilities could work. By using fuzzy set theory, the applied knowledge representation technique covers the uncertainty inherent in the problem domain. Based on this knowledge representation, a classification of jobs according to their importance is defined which is then used for the straightforward generation of a schedule. A control strategy which comprises organizational, spatial, temporal, and chemical constraints is introduced. The strategy supports the dynamic relaxation of conflicting constraints in order to improve tentative schedules.

Dorn, Juergen↗

Coolant Pump Predictive Data Analytics from Signatures Generated by the Recursive Short Time Fast Fourier Transform

Although a nuclear reactor is a hostile environment for sensors and signal transmissions, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure installed at the Advanced Test Reactor (ATR) nozzle trench area records acoustic signals that can capture reactor operating states. The distinct states produce unique signatures that can be identified and tracked using data processing and data analytics. The infrastructure relies on acoustic transmission through ATR in-pile structural components, piping, and coolant that transmit acoustically modified signals generated by the coolant pumps. This paper will discuss results from using the Recursive Short Time Fast Fourier Transform (RSTFFT) technique used to process acoustic signals and provide signatures that are identified and monitored by analytics. The RSTFFT is applied to ATR data to understand the vibration levels and signatures for different operating regimes as displayed by the spectrogram. The combination of coolant pumps for normal and high-power operation generate unique signatures. These acoustic signatures are used to develop machine learning approaches to automatically classify operating regimes. Two machine-learning models, Support Vector Machines and Linear Discriminant Analysis, were developed to classify two event classes. Class 1 is a normal steady-state operation, and Class 2 is any event that is due to start up, shut down, or other actions. Both types of machine learning models had over a 96% prediction accuracy for the two classes. These results lay the foundation for predictive analytic frameworks that can be leveraged by ATR to optimize operations and maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Standard Analytical Methods for Pyrolysis Bio-Oils

There has been significant recent interest in the production of renewable fuels and chemicals from biomass and waste feedstocks. Pyrolysis pathways produce a liquid bio-oil product, which must be processed further, or upgraded, to yield fuel or chemical products. Bio-oils are very complex and often unstable samples, and research and development on upgrading processes needs reliable analytical information. In particular, chemical characterization techniques are needed to quantify both functional groups and individual compounds present in bio-oils. Reliable analytics are also needed to enable the bioenergy industry, as industrial facilities often have different analytical needs and capabilities than research facilities. In this presentation, we will discuss the development of a suite of standard analytical methods for pyrolysis bio-oils. Analytical methods to be discussed include: Determination of Carbon, Hydrogen, Nitrogen, and Oxygen in bio-oils; Accelerated Aging of Fast Pyrolysis Bio-oil using Carbonyl Titration; Determination of Water Content in Bio-oils by Volumetric Karl Fischer Titration; Determination of Carbon Functional Groups; Elemental Analysis of Bio-oils by Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) - Na, K, Mg, Ca, S, P, and Fe; Determination of Phenolic Groups in Bio-oils using Revised Folin-Ciocalteu Methods: Single Cuvette and Plate Reader; Corrosivity of Bio-oils: Screening Test using Metal Leaching; Determination of Biogenic Content by 14C Measurement using Liquid Scintillation Counter. These new analytical methods are publicly available as Laboratory Analytical Procedures (https://www.nrel.gov/bioenergy/bio-oil-analysis.html), along with previously developed standard methods: GC-MS, Acid Titration, Carbonyl Titration, and 31P NMR. Additionally, the development of diffusion ordered NMR for characterization of bio-oil molecular weight will be discussed. Collectively, this suite of analytical methods represents the most comprehensive set of standard methods available for pyrolysis bio-oils. These standard methods are commonly used by the bioenergy community, and provide reliable information that enables research, scaleup, and industrial processing of biomass to produce renewable fuels and chemicals.

analytical↗

Methods for Monte Carlo simulation of the exospheres of the moon and Mercury

A general form of the integral equation of exospheric transport on moon-like bodies is derived in a form that permits arbitrary specification of time varying physical processes affecting atom creation and annihilation, atom-regolith collisions, adsorption and desorption, and nonplanetocentric acceleration. Because these processes usually defy analytic representation, the Monte Carlo method of solution of the transport equation, the only viable alternative, is described in detail, with separate discussions of the methods of specification of physical processes as probabalistic functions. Proof of the validity of the Monte Carlo exosphere simulation method is provided in the form of a comparison of analytic and Monte Carlo solutions to three classical, and analytically tractable, exosphere problems. One of the key phenomena in moonlike exosphere simulations, the distribution of velocities of the atoms leaving a regolith, depends mainly on the nature of collisions of free atoms with rocks. It is shown that on the moon and Mercury, elastic collisions of helium atoms with a Maxwellian distribution of vibrating, bound atoms produce a nearly Maxwellian distribution of helium velocities, despite the absence of speeds in excess of escape in the impinging helium velocity distribution.

Hodges, R. R., Jr.↗

Simulating cosmological evolution by quantum quench of an atomic Bose-Einstein condensate

In cosmological evolution, it is the homogeneous scalar field (inflaton) that drives the universe to expand isotropically and to generate standard model particles. However, to simulate cosmology, atomic gas research has focused on the dynamics of Bose-Einstein condensates (BEC) with continuously applied forces. In this paper we argue that a complementary approach needs also to be pursued; we thus consider the analog BEC experiments in a nondriven and naturally closed atomic system. We implement this using a BEC in an optical lattice which, after a quench, freely transitions from an unstable to a stable state. Furthermore, this dynamical evolution displays the counterpart “preheating,” “reheating,” and “thermalization” phases of cosmology. Importantly, our studies of these analog processes yield tractable analytic models. Additionally, of great utility to the cold atom community, such understanding elucidates the dynamics of nonadiabatic condensate preparation. Indeed, the dynamical processes discussed here are generic and in future cold atom reequilibration experiments it will be important to observe both the preheating stage, corresponding to a fragmented condensate, and the reheating stage, corresponding to a particle cloud.

74 ATOMIC AND MOLECULAR PHYSICS↗

Impact of dilution-induced precipitates on the filtration of Hanford liquid tank wastes

To facilitate its vitrification, a portion of the radioactive wastes currently stored at the Hanford Site will be staged and treated using tank-side operations to render their chemistry compliant with the requirements of Hanford’s low-activity waste vitrification facility. Initial sampling of staged feeds indicates that process-water dilution, used to reduce waste feed sodium content to levels acceptable for vitrification (5–6 M Na), may cause precipitation of fine, difficult to settle solids that could affect downstream tank-side filtration and ion-exchange. However, dilution-induced precipitation has not been demonstrated under controlled, rigorous laboratory conditions. This paper presents a set of qualitative and quantitative assessments of dilution-induced precipitation using a nonradioactive, Hanford Tank AP-105 simulated waste. Further, these studies found that dilution of AP-farm waste simulants induced precipitation of up to 150 ppm solids, regardless of whether dilution was done with process water (which contains, among other analytes, naturally occurring Ca and Mg) or deionized water. Naturally occurring process-water analytes appeared to accelerate the rate (and possibly extent) of precipitation. Filtration of diluted waste simulants also found that the precipitated solids challenged prototypic tank-side filter operations; however, the impact to filtration performance was readily managed through waste staging settle/decant operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Components Refurbishment and Chemical Analysis Facility, SWMU #041 - Per- and Polyfluoroalkyl Substances Site Assessment Report Kennedy Space Center, Florida

This PFAS Site Assessment (SA) Report presents the activities and results associated with PFAS investigations at the Components Refurbishment and Chemical Analysis (CRCA) facility located at Kennedy Space Center (KSC), Florida. In 2022, CRCA was identified as an Area of Potential Concern because the facility stores several potential PFAS-containing chemicals. A groundwater sample collected from an onsite monitoring well detected PFOA and PFOS at concentrations greater than State of Florida provisional Groundwater Cleanup Target Levels (pGCTLs). PFAS SA activities were conducted between March 2022 and February 2024. During this timeframe, a total of 16 direct-push technology (DPT) locations and 82 discrete samples were collected from these locations, along with 90 monitoring well samples. The analytical data screening process focused on State of Florida pGCTLs and United States Environmental Protection Agency (USEPA) Regional Screening Level (RSLs) from November 2023 to evaluate the data. Analytical results identified PFOS, PFOA, and PFBA at concentrations exceeding their respective RSLs at each depth interval (shallow, intermediate, and deep). PFOS and PFOA had the largest footprint of RSL exceedances in each depth interval, but pGCTL exceedances were only observed at limited locations in the shallow and intermediate intervals. PFBA had the highest detections of any PFAS compound, with concentrations exceeding 180,000 nanograms per liter (ng/L), which is 100-times the RSL of 1,800 ng/L in the shallow and intermediate intervals and 10-times the RSL in the deep interval. The maximum PFBA detection was 841,000 ng/L at shallow monitoring well, MW0006. The PFAS SA also included samples collected from the onsite hydraulic containment system (HCS) which was installed to control and treat the onsite chlorinated volatile organic compound (CVOC) plume. Influent and effluent aqueous samples were collected monthly from the system. PFAS concentrations were relatively the same for both influent and effluent samples, indicating that while the HCS has been effective for CVOC treatment, it does not provide any additional treatment for PFAS compounds. Since the HCS has achieved its objectives, the system was shut down in December 2024. PFAS data gaps still exist, to include surface water and soil, which were not sampled during this SA. Soil sampling near the Chemical Process Area is recommended. Surface water and soil sampling at select stormwater outfalls is also recommended. Additionally, further groundwater sampling is recommended (DPT and monitoring well) in all depth intervals to delineate the extent of PFAS impacts at CRCA.

K Alex Murphy↗

Disruptive Technology for Carbon Negative Commodity Chemicals

This project was designed to develop an economically attractive process for the carbon negative production of the commodity biochemical succinic acid. To compete against petroleum derived biochemicals, the process must deliver high raw material conversion efficiency and high volumetric productivity to reduce both recurring and capital-related costs, respectively. The proposed process introduces additional electrons sourced from hydrogen into the biosynthetic pathway so that the carbon from two CO2 molecules can be combined with each glucose to significantly increase succinic acid yields. The process also uses ultrafiltration to continuously remove the product from the bioreactor to avoid product inhibition and extend the productive life of the cell extract. Genetic deletions and specific enzyme removal during extract preparation more efficiently direct both atomic and electronic resources toward product formation. A preliminary technoeconomic analysis indicates that these process innovations made possible by cell-free production will enable large scale production with attractive ROI and profitability. This two-year project provided some 29 distinct insights, analytical advances, and process improvements that resulted in a demonstration of process feasibility. However, an estimated two to three years of additional development will be required to achieve convincing pilot scale demonstrations that will motivate large scale investments.

60 APPLIED LIFE SCIENCES↗

Comparing the results of an analytical model of the no-vent fill process with no-vent fill test results for a 4.96 cu m (175 cu ft) tank

NASA-Lewis has been investigating a no-vent fill method for refilling cryogenic storage tanks in low gravity. Analytical modeling based on analyzing the heat transfer of a droplet has successfully represented the process in 0.034 and 0.142 sq m commercial dewars using liquid nitrogen and hydrogen. Recently a large tank (4.96 sq m) was tested with hydrogen. This lightweight tank is representative of spacecraft construction. This paper presents efforts to model the large tank test data. The droplet heat transfer model is found to overpredict the tank pressure level when compared to the large tank data. A new model based on equilibrium thermodynamics has been formulated. This new model is compared to the published large scale tank's test results as well as some additional test runs with the same equipment. The results are shown to match the test results within the measurement uncertainty of the test data except for the initial transient wall cooldown where it is conservative (i.e., overpredicts the initial pressure spike found in this time frame).

Taylor, William J.↗

First-excursion probability in non-stationary random vibration.

The first-excursion probability of a non-stationary Gaussian process with zero mean has been studied. Within the framework of the point process approach, a variety of analytical approximations applicable to stationary random processes is extended herein to non-stationary random processes. The extension is possible owing to a recent definition of non-stationary envelope processes proposed by the author. With the aid of numerical examples, merits of each approximation are examined by comparing with the results of simulation. It is found that under non-stationary excitations with short duration, the Markov approximation is the best among all the approximations discussed in this paper.

Yang, J.-N.↗

Comparing the results of an analytical model of the no-vent fill process with no-vent fill test results for a 4.96 cubic meters (175 cubic feet) tank

The NASA Lewis Research Center (NASA/LeRC) have been investigating a no-vent fill method for refilling cryogenic storage tanks in low gravity. Analytical modeling based on analyzing the heat transfer of a droplet has successfully represented the process in 0.034 m and 0.142 cubic m commercial dewars using liquid nitrogen and hydrogen. Recently a large tank (4.96 cubic m) was tested with hydrogen. This lightweight tank is representative of spacecraft construction. This paper presents efforts to model the large tank test data. The droplet heat transfer model is found to over predict the tank pressure level when compared to the large tank data. A new model based on equilibrium thermodynamics has been formulated. This new model is compared to the published large scale tank's test results as well as some additional test runs with the same equipment. The results are shown to match the test results within the measurement uncertainty of the test data except for the initial transient wall cooldown where it is conservative (i.e., overpredicts the initial pressure spike found in this time frame).

Taylor, William J.↗

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. Here, the predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.

36 MATERIALS SCIENCE↗

Spacelab experiment integration

The capabilities and characteristics of Spacelab are discussed, and a process is described for the integration of a large number of experiments into the vehicle. Spacelab payload services and experiment integration functions are examined. The latter include science management; mission definition, documentation, and control requirements and interfaces; analytical integration; ground processing; flight operations; and postflight activities. It is concluded that the major factors involved in Spacelab experiment integration have been optimized to a great extent with respect to maximum science return for minimum cost.

Lester, R. C.↗

Analytical modeling and sensor monitoring for optimal processing of advanced textile structural composites by resin transfer molding

A two-dimensional model of the resin transfer molding (RTM) process was developed which can be used to simulate the infiltration of resin into an anisotropic fibrous preform. Frequency dependent electromagnetic sensing (FDEMS) has been developed for in situ monitoring of the RTM process. Flow visualization tests were performed to obtain data which can be used to verify the sensor measurements and the model predictions. Results of the tests showed that FDEMS can accurately detect the position of the resin flow-front during mold filling, and that the model predicted flow-front patterns agreed well with the measured flow-front patterns.

Loos, Alfred C.↗

Effect of inhomogeneous radiation fields on free-free scattering processes

The apparent collision cross section of an inverse-bremsstrahlung (free-free) collision process is investigated analytically for the case of laser-field inhomogeneity. Numerical computations are performed for typical experimental conditions involving high-intensity laser fields, and the results are presented in a table: significant effects due to the field inhomogeneity are found, and it is determined that free-free processes are less likely in the TEM(01) mode than in the TEM(00) mode for given values of the parameters p and n.

Curry, P. J.↗