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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Effects of Roughing on Finish Rolling Simulations in Microalloyed Strip Steels

The effects of a roughing pass in hot rolling simulations were assessed in VN and Nb-Ti steels. Continuous cooling phase transformation temperatures, flow curves, softening mechanisms (dynamic transformation DT and dynamic recrystallization DRX), and deformed microstructure morphologies were analyzed. The application of one or more roughing passes eliminates the effects of prior microstructural history and ensures that all stock material experiences equivalent hot working conditions and state of the microalloying elements. It has been shown that roughing in hot simulation has the following positive influences: (1) provide more reliable flow stress data; (2) give greater consistencies and accuracy in analysis of softening mechanisms giving three distinct regimes (DT regime at temperatures below 800 °C, DT/DRX inter-mode regime between 800 and 950 °C and DRX regime for temperatures above 950 °C for VN steel); (3) promotion of softening mechanisms as evidence by low critical strains (ε{sub c DT} was within the range 0.08-0.12, while for finishing-only pass, the ε{sub c DT} was in the range of 0.11-0.14 at ε-dot =0.1 s{sup −1}); (4) for roughing and finishing schedules, DT was verified to occur at temperatures 117 and 133 °C above Ae{sub 3} for VN steel and Nb-Ti steel, respectively, compared to the F-only schedules which showed that DT can only occur at temperatures below the Ae{sub 3}; (5) RF schedules promoted uniform microstructural morphologies compared to inhomogeneous microstructures realized in F-only schedules.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling of multi-component precipitation and crystallization for zero-liquid-discharge desalination

This study proposes novel ZLD treatment trains that integrate multi-component chemical precipitation and multi-effect evaporative crystallization for efficient brine management. The methodology emphasizes sustainability by integrating CO₂ for chemical precipitation and reducing environmental impact, exemplified with two case studies: produced water that includes industrial waste heat utilization by adopting the emerging vacuum air-gapped membrane distillation (VAGMD) technology, and brackish groundwater that is abundant in sulphate which undergoes treatment by low-salt-rejection reverse osmosis (LSRRO) with interstage chemical precipitation. Here, this study is the first of its kind to simultaneously account for reducing risk of mineral scaling and effective recovery of valuable solids when incorporating VAGMD and LSRRO in ZLD treatment trains. Using Reaktoro and WaterTAP, both Python-based, open-source platforms, we model the recovery of high-purity magnesium, calcium, and sodium salts while optimizing energy consumption and operational efficiency in proposed ZLD pathways for case studies of produced water and brackish desalination brine management. Validation with experimental and reference data confirms the reliability of the models used. In both case studies, the optimized ZLD process achieves recovery rates of 97%, 99%, and 90% for Mg, Ca, and Na, with purities exceeding 99%, and brine volume reduced to less than 4% of the initial feed flow.

3D CT scans↗
DOE OSTI2023

The effect of chemical functional groups on the octane sensitivity of fuel blends for spark-ignited and multimode engines

We report the octane sensitivity of fuel blends containing blendstocks of diverse chemical functionalities blended in concentrations up to 20% by volume into BOBs (Blendstocks for Oxygenate Blending). This study focuses on the blendstocks containing functional groups which lack reliable octane number data. The effects on octane sensitivity of blends of cyclopropanes, alkyl carbonates, oxiranes, alcohols, ketones, esters, nitrogen-containing compounds, cyclic and olefinic hydrocarbons, multifunctional materials containing combinations of these functionalities, and the co-blends of the blendstocks with ethanol in a BOB have been evaluated. Octane sensitivity of the blends containing functional groups that haven’t been evaluated before are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Thermodynamic Modeling and Experimental Study of the Fe-Cr-Zr System

Wide applications of zircaloys, stainless steels and their interactions in nuclear reactors require the knowledge on phase stability and thermodynamic property of the Fe-Cr-Zr system. This knowledge is also important to develop new Zr-contained Fe-Cr ferritic steels. This work aims at developing thermodynamic models for describing phase stability and thermodynamic property of the Fe-Cr-Zr system using the Calphad approach coupled with experimental study. Thermodynamic descriptions of the Fe-Cr and Cr-Zr systems were either directly adopted or slightly modified from literature. The Fe-Zr system has been remodeled to accommodate recent ab-initio calculation of formation enthalpies of various Fe-Zr compounds. Reliable ternary experimental data and thermodynamic models were mainly available in the Zr-rich region. Therefore, selected ternary alloys located in the vicinity of the eutectic valley of (Fe,Cr,Zr) and (Fe,Cr)2Zr laves phase in the Fe-rich region have been experimentally investigated in this study. Microstructure has been examined by using scanning electron microscope, energy-dispersive Xray spectroscopy and X-ray diffraction. These experimental results, along with the literature data were then used to develop thermodynamic models for phases in the Fe-Cr-Zr system. Calculated phase equilibria and thermodynamic properties of the ternary system yield satisfactory agreements with available experimental data, which gives the confidence to use these models as building blocks for developing a Zr, Fe and Cr contained multicomponent thermodynamic database for broader applications in nuclear reactors.

Yang, Ying↗
DOE OSTI2022

Computation of conventional and alternative jet fuel sensitivity to lean blowout

Large Eddy Simulations (LES) are performed to compute the sensitivity of a conventional (A-2) and an alternate bio-jet (C-1) fuel to Lean Blowout (LBO). A realistic aviation gas turbine engine combustor configuration is considered. Reliable experimental LBO data and OH* chemiluminescence data for the conventional and alternate jet fuel in the combustor configuration have recently become available. The present work utilizes a highly automated, on-the-fly meshing strategy, along with adaptive mesh refinement, to demonstrate the feasibility of capturing the realistic combustion processes. A Lagrangian framework, with initial conditions specified using measurements of spray statistics, is used to model the fuel spray. Newly developed compact reaction mechanisms based on fuel surrogates are validated for the A-2 and the C-1 fuels. The compact reaction mechanisms are implemented using a detailed finite rate chemistry solver. Spray statistics computed by the present LES simulations compare well with available measurements at stable flame conditions near the lean blowout limit. The computed shape of the stable flame as represented by line integrated OH concentrations compares well with the experimental OH* chemiluminescence data. Lean blowout is reached by gradually decreasing the fuel flow rate in the computations, similar to that in the experiments. The results of the LES simulations effectively capture the fuel composition effects and estimate the sensitivity of the LBO limits to the fuel type. The computed trends in LBO limits agree within engineering accuracy with the experimental results for conventional and alternative aviation fuels. The methodology for predicting the fuel composition effects on the lean blowout limits in a fully resolved realistic, complex combustor is established for the first time.

Adaptive mesh refinement↗
DOE OSTI2013

Magnetocrystalline interactions and oxidation state determination of Mn{sub (2−x)}V{sub (1+x)}O{sub 4} (x=0, 1/3 and 1) magnetorresistive spinel family

Oxidation states of transition metal cations in spinels-type oxides are sometimes extremely difficult to determine by conventional spectroscopic methods. One of the most complex cases occurs when there are different cations, each one with several possible oxidation states, as in the case of the magnetoresistant Mn{sub (2−x)}V{sub (1+x)}O{sub 4} (x=0, 1/3 and 1) spinel-type family. In this contribution we describe the determination of the oxidation state of manganese and vanadium in Mn{sub (2−x)}V{sub (1+x)}O{sub 4} (x=0, 1/3,1) spinel-type compounds by analyzing XANES and high-resolution Kβ X-ray fluorescence spectra. The ionic models found are Mn{sup 2+}{sub 2}V{sup 4+}O{sub 4}, Mn{sup 2+}{sub 5/3}V{sup 3.5+}{sub 4/3}O{sub 4} and Mn{sup 2+}V{sup 3+}{sub 2}O{sub 4}. Combination of the present results with previous data provided a reliable cation distribution model. For these spinels, single magnetic electron paramagnetic resonance (EPR) lines are observed at 480 K showing the interaction among the different magnetic ions. The analysis of the EPR parameters show that g-values and relative intensities are highly influenced by the concentration and the high-spin state of Mn{sup 2+}. EPR broadening linewidth is explained in terms of the bottleneck effect, which is due to the presence of the fast relaxing V{sup 3+} ion instead of the weak Mn{sup 2+} (S state) coupled to the lattice. The EPR results, at high temperature, are well explained assuming the oxidation states of the magnetic ions obtained by the other spectroscopic techniques. - Graphical abstract: View of the crystallographic structure of a spinel. It shows as an example one of the models of ion distribution determined for the spinels Mn{sub (2−x)}V{sub (1+x)}O{sub 4} (x=0, 1/3,1). Display Omitted - Highlights: • Determination of oxidation state of the metallic ions in Mn{sub (2−x)}V{sub (1+x)}O{sub 4} (x=0,1/3,1) by XAS and XES techniques. • The ionic models found are Mn{sup 2+}{sub 2}V{sup 4+}O{sub 4}, Mn{sup 2+}{sub 5/3}V{sup 3.5+}{sub 4/3}O{sub 4} and Mn{sup 2+}V{sup 3+}O{sub 4}. • EPR spectra correspond almost exclusively to a resonance of Mn{sup 2+}.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine learning based inverse modeling of full-field strain distribution for mechanical characterization of a linear elastic and heterogeneous membrane

Heterogeneous membranes or films are thin and soft structures with spatial variations in material property and thickness. Mechanical behavior of heterogeneous membranes is not well understood, mainly due to the difficulty in obtaining accurate and reliable material property data. To understand the mechanical behavior of these materials, accurate and efficient characterization methods for heterogeneous membranes are needed. Here, in this paper, an inverse method based on machine learning is developed to efficiently extract mechanical properties from full-field strain distributions. This approach is demonstrated on a flat heterogeneous membrane with uniform thickness formed by up to four linear elastic synthetic materials in a grid arrangement, and deforming in a moderate strain range (true strain ~10%). The results show that the machine learning method achieves accuracy comparable to the traditional inverse finite element method, and is 6 orders of magnitude faster in the demonstrated case studies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Microbial potentiometric sensor: A new approach to longstanding challenges

The underlying hypothesis of this study is that simple potentiometric measurements between sensing electrodes and a shared reference electrode - Microbial Potentiometric Sesnor (MPS) system - can be employed in a long-term, continuous mode of operation to resolve the spatial and temporal changes in environmental systems. To address the hypothesis, (1) a conceptual description of the MPS system and its postulated principle of operation are provided; (2) the MPS system performance is documented under controlled laboratory conditions; and (3) the capabilities of the MPS system are documented under quiescent and dynamic field condition. In a laboratory setting, the variability among different MPS signals was insignificant confirming the postulated high accuracy and reproducibility of the sensor performance. It also demonstrated statistically significant correlations with dissolved oxygen (DO) and oxidation-reduction potential (ORP) sensors, while showing capabilities of operating under anoxic and anaerobic conditions. Regardless of their locations in the model wetland system, three MPS sensors functioned without interruption and cleaning for a period >2 years, and thus demonstrating long-term durability of the MPS technology. In real batch-wastewater treatment facility, the deployed MPS system signals were able to describe the organic carbon trends and correlate with each treatment phase in a cycle. Data reproducibility and reliability exceeded the expectations better describing the carbon treatment levels than the DO and ORP sensors (p < 4.4 × 10 –162 vs phase adjusted p < 3.0 × 10 –58 ). While MPS signals correlate with specific parameters that describe the local process or environments, it is more prudent to employ both the magnitude and pattern of a composite signal like the MPS signal describe the change to reflect any shift in the local environment. Finally, when compared to a baseline pattern, this change in signal magnitude and pattern reveals important information that can be employed to tailor and optimize any condition or process which involves microorganisms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Climate change is intensifying rainfall erosivity and soil erosion in West Africa

Soil erosion is a critical environmental challenge with significant implications for agriculture, water quality, and ecosystem stability. Understanding its dynamics is essential for sustainable environmental management and societal welfare. Here, we analyze rainfall erosivity and erosion patterns across West Africa (WAF) during the historical (1982–2014), near future (2028–2060), and far future (2068–2100) periods under Shared Socioeconomic Pathways (SSPs 370 and 585). Using bias-corrected-downscaled (BCD) climate models validated against reference data, we ensure an accurate representation of rainfall—a key driver of erosivity (R-factor) and soil erosion. We compare Renard's approach and the Modified Fournier Index (MFI) to calculate the R-factor and note a strong correlation. However, Renard's method shows slightly lower accuracy in Sierra Leone, Guinea, and The Gambia, likely due to its inability to capture high-intensity, short-duration rainfall events. In contrast, the MFI, utilizing continuous rain gauge data, proves more reliable for these regions. We also attribute fluctuations in erosivity, such as those seen during the 2003 West Africa floods, to synoptic weather patterns influenced by multiple climate processes. Furthermore, our analysis reveals regions where future soil erosion could exceed 20 t/ha/yr due to climate change. Under the SSP 370 scenario, soil erosion in WAF is projected to rise by 14.84 % in the near future and 18.65 % in the far future, increasing further under SSP 585 to 19.86 % and 23.49 %, respectively. The most severe increases are expected in Benin and Nigeria, with Nigeria potentially facing a 66.41 % rise in erosion by the far future under SSP 585. These findings highlight the region's exposure to intensified climatic conditions and underscore the urgent need for targeted soil management and climate adaptation strategies to mitigate erosion's ecological and socioeconomic impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Bringing Molecular Dynamics Simulation Data into View

Molecular Dynamics (MD) simulations monitor time-resolved motions of macromolecules. While visualization of MD trajectories allows an instant and intuitive understanding of dynamics and function, so far mainly static representations are provided in published literature. Recent advances in browser technology may allow for the sharing of trajectories through interactive visualization on the web. We believe that by providing intuitive and interactive visualization along with related protocols and analysis data promotes understanding, reliability, and re-usability of MD simulations. Existing barriers for sharing MD simulations are discussed and emerging solutions are highlighted. We predict that interactive visualization of MD trajectories will quickly be adopted by researchers, research consortiums, journals, and funding agencies to gather and distribute results from MD simulations via the web.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2010

Greenhouse gas emissions from home composting of organic household waste

The emission of greenhouse gases (GHGs) is a potential environmental disadvantage of home composting. Because of a lack of reliable GHG emission data, a comprehensive experimental home composting system was set up. The system consisted of six composting units, and a static flux chamber method was used to measure and quantify the GHG emissions for one year composting of organic household waste (OHW). The average OHW input in the six composting units was 2.6-3.5 kg week{sup -1} and the temperature inside the composting units was in all cases only a few degrees (2-10 {sup o}C) higher than the ambient temperature. The emissions of methane (CH{sub 4}) and nitrous oxide (N{sub 2}O) were quantified as 0.4-4.2 kg CH{sub 4} Mg{sup -1} input wet waste (ww) and 0.30-0.55 kg N{sub 2}O Mg{sup -1} ww, depending on the mixing frequency. This corresponds to emission factors (EFs) (including only CH{sub 4} and N{sub 2}O emissions) of 100-239 kg CO{sub 2}-eq. Mg{sup -1} ww. Composting units exposed to weekly mixing had the highest EFs, whereas the units with no mixing during the entire year had the lowest emissions. In addition to the higher emission from the frequently mixed units, there was also an instant release of CH{sub 4} during mixing which was estimated to 8-12% of the total CH{sub 4} emissions. Experiments with higher loads of OHW (up to 20 kg every fortnight) entailed a higher emission and significantly increased overall EFs (in kg substance per Mg{sup -1} ww). However, the temperature development did not change significantly. The GHG emissions (in kg CO{sub 2}-eq. Mg{sup -1} ww) from home composting of OHW were found to be in the same order of magnitude as for centralised composting plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Analysis of Interpretable Data Representations for 4D-STEM Using Unsupervised Learning

Abstract Understanding the structure of materials is crucial for engineering devices and materials with enhanced performance. Four-dimensional scanning transmission electron microscopy (4D-STEM) is capable of mapping nanometer-scale local crystallographic structure over micron-scale field of views. However, 4D-STEM datasets can contain tens of thousands of images from a wide variety of material structures, making it difficult to automate detection and classification of structures. Traditional automated analysis pipelines for 4D-STEM focus on supervised approaches, which require prior knowledge of the material structure and cannot describe anomalous or deviant structures. In this article, a pipeline for engineering 4D-STEM feature representations for unsupervised clustering using non-negative matrix factorization (NMF) is introduced. Each feature is evaluated using NMF and results are presented for both simulated and experimental data. It is shown that some data representations more reliably identify overlapping grains. Additionally, real space refinement is applied to identify spatially distinct sample regions, allowing for size and shape analysis to be performed. This work lays the foundation for improved analysis of nanoscale structural features in materials that deviate from expected crystallographic arrangement using 4D-STEM.

Bruefach, Alexandra (ORCID:0000000209323477)↗
DOE OSTI2023

Compound Continental Risk of Multiple Extreme Floods in the United States

Abstract Understanding spatially correlated floods and modeling joint hazard associated with threshold exceedances across multiple locations is crucial for accurate estimation of continental‐scale portfolio risk. This work uses a non‐parametric copula‐based spatial simulator to analyze peak floods across the United States to derive the first‐of‐its‐kind continental portfolio risk estimates at the 10‐ and 100‐year return levels. We find significant interdependence in floods across the nation, revealing the recurring pattern of extreme events affecting the Northeast, Central, West, and Northwest United States in the same year. The stochastic simulator effectively manages high‐dimensional data and offers reliable uncertainty estimates for both spatially dependent floods and the aggregated flood losses at the continental level. El Niño‐Southern Oscillation and Atlantic Multidecadal Oscillation are identified as statistically significant tele‐connectors of aggregate loss. This research aims to advance the understanding of compound continental flood hazard and the potential large‐scale climate teleconnections that lead to such compound floods.

Geology↗
DOE OSTI2023

Physics-embedded inverse analysis with algorithmic differentiation for the earth’s subsurface

Abstract Inverse analysis has been utilized to understand unknown underground geological properties by matching the observational data with simulators. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented with embedded physics and a technique known as algorithmic differentiation. We use a physics-embedded generative model, which takes statistically simple parameters as input and outputs subsurface properties (e.g., permeability or P-wave velocity), that embeds physical knowledge of the subsurface properties into inverse analysis and improves its performance. We tested the application of this approach on four geologic problems: two heterogeneous hydraulic conductivity fields, a hydraulic fracture network, and a seismic inversion for P-wave velocity. This physics-embedded inverse analysis approach consistently characterizes these geological problems accurately. Furthermore, the excellent performance in matching the observational data demonstrates the reliability of the proposed method. Moreover, the application of algorithmic differentiation makes this an easy and fast approach to inverse analysis when dealing with complicated geological structures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Neutron-capture Cross Sections from Indirect Measurements

Cross sections for compound-nuclear reactions play an important role in models of astrophysical environments and simulations of the nuclear fuel cycle. Providing reliable cross section data remains a formidable task, and direct measurements have to be complemented by theoretical predictions and indirect methods. The surrogate nuclear reactions method provides an indirect approach for determining cross sections for reactions on unstable isotopes, which are difficult or impossible to measure otherwise. Current implementations of the method provide useful cross sections for (n,f) reactions, but need to be improved upon for applications to capture reactions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Simulation of electron-matter interaction during wet-STEM electron tomography

Tomography is an efficient tool to probe the 3 dimensional (3D) structure of materials. In the laboratory, a device has been developed to perform electron tomography in an environmental scanning electron microscopy (ESEM). The configuration of Scanning Transmission Electron Microscopy (STEM) in Environmental Scanning Electron Microscopy (ESEM) provides a novel approach for the characterization of the 3D structure of materials and optimizes a compromise between the resolution level of a few nm and the large tomogram due to the high thickness of transparency. Moreover, STEM allows the observation in 2D of wet samples in an ESEM by finely controlling the sample temperature and the water pressure of the sample environment. It has been recently demonstrated that it was possible to acquire image series of hydrated objects and thus to attain 3D characterization of wet samples. In order to get reliable and quantitative data, the present study deals with the simulation of electron-matter interactions. From such simulation on the MCM-41 material, we determine the minimum quantity of water layer which can be detected on wet materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Designing of smart home automation system based on Raspberry Pi

Locally networked or remotely controlled home automation system becomes a popular paradigm because of the numerous advantages and is suitable for academic research. This paper proposes a method for an implementation of Raspberry Pi based home automation system presented with an android phone access interface. The power consumption profile across the connected load is measured accurately through programming. Users can access the graph of total power consumption with respect to time worldwide using their Dropbox account. An android application has been developed to channelize the monitoring and controlling operation of home appliances remotely. This application facilitates controlling of operating pins of Raspberry Pi by pressing the corresponding key for turning “on” and “off” of any desired appliance. Systems can range from the simple room lighting control to smart microcontroller based hybrid systems incorporating several other additional features. Smart home automation systems are being adopted to achieve flexibility, scalability, security in the sense of data protection through the cloud-based data storage protocol, reliability, energy efficiency, etc.

42 ENGINEERING↗
DOE OSTI2017

Structural evolution and atomic dynamics in Ni–Nb metallic glasses: A molecular dynamics study

In this work, the composition and temperature dependence of static and dynamic structures in Ni x Nb 1– x ( x = 50–70 at. %) were systematically studied using molecular dynamics with a new-released semi-empirical embedded atom method potential by Mendelev. The calculated pair correlation functions and the structure factor match well with the experimental data, demonstrating the reliability of the potential within relatively wide composition and temperature ranges. The local atomic structures were then characterized by bond angle distributions and Voronoi tessellation methods, demonstrating that the icosahedral $\langle$0,0,12,0$\rangle$ is only a small fraction in the liquid state but increases significantly during cooling and becomes dominant at 300 K. The most abundant clusters are identified as $\langle$0,0,12,0$\rangle$ and distorted icosahedron$\langle$0,2,8,2$\rangle$. The large fraction of these two clusters hints that the relatively good glass forming ability is near the eutectic point. Unlike Cu–Zr alloys, both the self-diffusion coefficient and shear viscosity are insensitive to compositions upon cooling in Ni–Nb alloys. The breakdown of the Stokes-Einstein relation happens at around 1.6 T g ( T g : glass transition temperature). In the amorphous state, the solid and liquid-like atoms can be distinguished based on the Debye-Waller factor $\langle$ u 2 $\rangle$. The insensitivity of the dynamic properties of Ni–Nb alloys to compositions may result from the relatively simple solidification process in the phase diagram, in which only one eutectic point exists in the studied composition range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗