Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “characterization challenges”

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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Advancing the Representation of Human Actions in Large‐Scale Hydrological Models: Challenges and Future Research Directions

Characterizing the impact of human actions on terrestrial water fluxes and storages at multi-basin, continental, and global scales has long been on the agenda of scientists engaged in climate science, hydrology, and water resources systems analysis. This need has resulted in a variety of modeling efforts focused on the representation of water infrastructure operations. Yet, the representation of human-water interactions in large-scale hydrological models is still relatively crude, fragmented across models, and often achieved at coarse resolutions (~10–100 km) that cannot capture local water management decisions. In this commentary, we argue that the concomitance of four drivers and innovations is poised to change the status quo: “hyper-resolution” hydrological models (~0.1–1 km), multi-sector modeling, satellite missions able to monitor the outcome of human actions, and machine learning are creating a fertile environment for human-water research to flourish. We then outline four challenges that chart future research in hydrological modeling: (a) creating hyper-resolution global data sets of water management practices, (b) improving the characterization of anthropogenic interventions on water quantity, stream temperature, and sediment transport, (c) improving model calibration and diagnostic evaluation, and (d) reducing the computational requirements associated with the successful exploration of these challenges. Overcoming them will require addressing modeling, computational, and data development needs that cut across the hydrology community, thereby requiring a major communal effort.

catchment hydrology↗
DOE OSTI2023

MetaboDirect: an analytical pipeline for the processing of FT-ICR MS-based metabolomic data

Background: Microbiomes are now recognized as the main drivers of ecosystem function ranging from the oceans and soils to humans and bioreactors. However, a grand challenge in microbiome science is to characterize and quantify the chemical currencies of organic matter (i.e., metabolites) that microbes respond to and alter. Critical to this has been the development of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), which has drastically increased molecular characterization of complex organic matter samples, but challenges users with hundreds of millions of data points where readily available, user-friendly, and customizable software tools are lacking. Results: Here, we build on years of analytical experience with diverse sample types to develop MetaboDirect, an open-source, command-line-based pipeline for the analysis (e.g., chemodiversity analysis, multivariate statistics), visualization (e.g., Van Krevelen diagrams, elemental and molecular class composition plots), and presentation of direct injection high-resolution FT-ICR MS data sets after molecular formula assignment has been performed. When compared to other available FT-ICR MS software, MetaboDirect is superior in that it requires a single line of code to launch a fully automated framework for the generation and visualization of a wide range of plots, with minimal coding experience required. Among the tools evaluated, MetaboDirect is also uniquely able to automatically generate biochemical transformation networks (ab initio) based on mass differences (mass difference network-based approach) that provide an experimental assessment of metabolite connections within a given sample or a complex metabolic system, thereby providing important information about the nature of the samples and the set of microbial reactions or pathways that gave rise to them. Finally, for more experienced users, MetaboDirect allows users to customize plots, outputs, and analyses. Conclusion: Application of MetaboDirect to FT-ICR MS-based metabolomic data sets from a marine phage-bacterial infection experiment and a Sphagnum leachate microbiome incubation experiment showcase the exploration capabilities of the pipeline that will enable the research community to evaluate and interpret their data in greater depth and in less time. It will further advance our knowledge of how microbial communities influence and are influenced by the chemical makeup of the surrounding system. The source code and User’s guide of MetaboDirect are freely available through (https://github.com/Coayala/MetaboDirect) and (https://metabodirect.readthedocs.io/en/latest/), respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

Computational fluid dynamics↗
NASA NTRS2002

The Design and Use of Calorimeters For Characterization of High-Enthalpy Flows in Arc-Heated Test Facilities

High-enthalpy, arc-heated flows used for aerothermal testing present a challenging environment for flow characterization. This paper describes the design and use of cooled dwell probes used for heat-transfer and pressure characterization of the NASA and United States Department of Defense (DoD) arc facilities located at Moffett Field, CA, and Arnold Air Force Base, TN. Dwell calorimeters designed, fabricated, and tested by Thermal Technologies, Inc. (TTI) in the NASA IHF and the USAF H1 and H2 arc test facilities provide heat flux and pressure data with excellent repeatability. These calorimeters use standard Gardon calorimeter gages and pressure ports with unique cooling systems enabling them to withstand the severe arc-heated environments for durations sufficient for acquisition of steady-state data. The TTI probes have proven very robust in the extreme aerothermal environments of these facilities. This paper provides an overview of calorimeter instruments typically used in arc facilities, discusses design features of the TTI dwell probes, presents selected data acquired by the TTI calorimeters, and provides comparisons with data acquired from using measurement techniques.

D Mark Smith↗
DOE OSTI2025

Operando X-ray absorption spectroscopic investigation of electrocatalysts state in anion exchange membrane fuel cells

Capturing the active state of (electro)catalysts under operating conditions, namely operando, is the ultimate objective of (electro)catalyst characterization, enabling the unraveling of reaction mechanisms and advancing (electro)catalyst development. Operando insights advance our understanding of the correlations between electrochemical tests and device-level performances. However, operando characterization of electrocatalysts is challenging due to the complexity of electrochemical devices and instrumental limitations. As a result, the majority of electrocatalyst characterizations have been limited to half-cell in situ studies. Here, we present an operando X-ray absorption spectroscopic study of Mn spinel oxide electrocatalysts in an operating fuel cell employing a custom-designed cell. Our results reveal that in anion exchange membrane fuel cells, the Mn valence state, within spinel Mn 3 O 4 /C, increases to above 3+, adopting an octahedral coordination devoid of Jahn-Teller distortions. This structural change results in an AEMFC performance equivalent to that of Co 1.5 Mn 1.5 O 4 /C, a composition that outperforms Mn 3 O 4 /C in rotating disk electrode tests. Our results underscore the importance of operando characterizations in elucidating the active state of electrocatalysts and understanding the correlation(s) between electrochemical tests and device performance.

Electrocatalysis↗
DOE OSTI2020

Cryo-based Structural Characterization and Growth Model of Salt Film on Metal

Metal salt films play a critical role in high rate dissolution processes such as within an active pit. However, structural and compositional characterization of salt films is challenging owing to the dynamic nature of the dissolving interface. Here, the salt film formed on SS304 one-dimensional artificial pit surface was directly characterized using flash freezing and cryo-based focused ion beam/scanning electron microscopy. The salt film exhibits a porous structure. Ni is co-located with Fe in the salt film, indicating the formation of co-precipitated salt containing Fe2+ and Ni2+. Additionally, a salt film growth model is presented based on ion transport.

Salt film, Pitting corrosion, Cryogenic, Cryo-FIB/↗
DOE OSTI2020

The sensitive surface chemistry of Co-free, Ni-rich layered oxides: identifying experimental conditions that influence characterization results

Recent studies have suggested that Co-free, Ni-rich layered cathodes (e.g., doped LiNiO2) can provide promising battery performance for practical applications. However, these layered cathodes suffer from significant surface instability during various stages of the sample history, which generates inherent challenges for achieving stable battery performance and obtaining statistically representative characterization results. To reliably report the surface chemistry of these materials, delicate controls of stepwise sample preparation are required. In this study, we aim to reveal how the surface chemistry of LiNiO2 based materials changes with various environments, including human exhalation, sample storage, sample preparation, electrochemistry cycling, and surface doping. Our results demonstrate that the surface of these materials is highly reactive and prone to alter at various stages of sample handling and characterization. The sensitive surface could impact the interpretation of the surface chemical and structural information, including surface carbonate formation, transition metal reduction and dissolution, and surface reconstruction. Importantly, the heterogeneity of the surface degradation calls for a consolidation of nanoscale, high-resolution characterization, and ensemble-averaged methods in order to improve statistical representation. Furthermore, the doping chemistry can effectively mitigate the surface degradation and improve overall battery performance due to the enhanced surface oxygen retention. Our study highlights the necessity of strict measurements through complementary characterizations at multiple length scales to eliminate unintentional biased conclusions.

surface chemistry, Co-free Ni-rich cathodes, Istab↗
DOE OSTI2026

An upgraded frequency-selectable laser source (FLS) calibrator for CMB bandpass characterization

One of the biggest challenges for Cosmic Microwave Background (CMB) experiments comes from the uncertainty in instrument bandpass calibration. Uncertainties in bandpass can limit foreground removal and spectral fitting, which are critical for inflationary and galaxy cluster measurements. CMB experiments currently use Fourier Transform Spectrometers (FTSes) to measure instrument bandpasses. However, FTS systems are currently systematics-limited, so significant improvements in bandpass measurements require novel calibrators. To this end, we developed a Frequency-selectable Laser Source (FLS) calibrator, which uses a laser with adjustable frequency coupled to a system that allows for laser power attenuation. Following initial testing with the first FLS prototype, we developed an upgraded version of the calibrator with improved performance. We present the upgrades to the FLS calibrator, the characterization of the upgraded calibrator and new laser source, and plans for testing with microwave instruments in the field.

Saunders, Lauren J. [Fermilab] (ORCID:000000016367↗
DOE OSTI2025

Vertical Characterization of Flow and Contaminant Concentration in New Hanford Extraction Wells

Effective groundwater remediation should focus on high-concentration, low-permeability zones within the aquifer, as these areas often present significant challenges to contaminant removal. Characterizing the vertical distribution of contamination in an aquifer is therefore critical for optimizing and monitoring pump-and-treat (P&T) systems to meet target cleanup timelines. Flow patterns driven by hydraulic gradients and variations in permeability are described to provide insight into contaminant mass removal from long-screened wells. The objective of this multi-phase work is to provide actionable recommendations for improving remedy performance monitoring and P&T operations, which ongoing evaluations will address. This report summarizes the preliminary results of vertical flow and contaminant distribution monitoring in new extraction wells at the Hanford Site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Frequency-Selectable Laser Source (FLS) Calibrator for CMB Bandpass Characterization

One of the biggest challenges for Cosmic Microwave Background (CMB) experiments comes from our detector bandpass calibration. Uncertainties in bandpass can severely limit our measurements by limiting foreground removal and spectral fitting, which is particularly important for high-$\ell$ observations like cluster science using the Sunyaev-Zeldovich (SZ) effect. Currently, CMB experiments typically use a Fourier Transform Spectrometer (FTS) to measure the detector bandpasses. However, the resolution of the FTS is dependent on the length of the interferometer arms, leading to a need for increasingly large FTS instruments as CMB experiments require tighter constraints on detector bandpasses. Additionally, systematic effects like shifts in bandpass shape from uneven illumination from the FTS further limit the calibration uncertainties. As a complement to the FTS, we have developed a Frequency-selectable Laser Source (FLS) calibrator, which uses a laser with adjustable frequency housed in a calibrator that allows for varying degrees of laser power attenuation. We present several tests used to characterize the first prototype design of the FLS calibrator, as well as the improvements to the calibrator design currently underway.

Saunders, Lauren [Fermilab]↗
DOE OSTI2026

AI-Based Analytics and Energy Modeling Framework for Characterizing Urban Energy Systems

Developing location-specific district energy models is essential for understanding energy patterns and supporting efficient management and planning decisions. However, accurately characterizing these models remains challenging due to gaps in building characteristics and labor-intensive traditional modeling workflows. To address these challenges, we develop an AI-based framework that integrates top-down and bottom-up building energy data to automate urban energy model characterization. The framework trains multimodal deep learning models using heterogeneous ResStockTM datasets to infer missing building characteristics from varying levels of known information and generate simulation-ready inputs for district-scale energy modeling. It also employs a conditioning-based injection approach to generate ”what-if” scenarios, enabling users to explore retrofit, efficiency, and technology-upgrade pathways. Integrated within URBANoptTM, a bottom-up district energy modeling platform for simulating co-located buildings, the framework infers detailed building-level inputs required for bottom-up simulations. Both localized and generalized AI models are developed to learn relationships across categorical, numerical, and time-series data, enabling reconstruction of missing attributes and generation of targeted upgrade scenarios. We demonstrate this methodology on a residential neighborhood in Baltimore, MD, assessing internal consistency against ResStock reference data and URBANopt simulation, and comparing selected attributes against real-world building characteristics. Results show strong overall predictive accuracy in data completion and scenario generation, with localized and generalized models offering complementary trade-offs between precision and scalability. Overall, our automated framework streamlines energy modeling and provides a reliable framework for urban building energy characterization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Nitrene Photochemistry of Manganese N ‐Haloamides**

Abstract Manganese complexes supported by macrocyclic tetrapyrrole ligands represent an important platform for nitrene transfer catalysis and have been applied to both C−H amination and olefin aziridination catalysis. The reactivity of the transient high‐valent Mn nitrenoids that mediate these processes renders characterization of these species challenging. Here we report the synthesis and nitrene transfer photochemistry of a family of Mn III N ‐haloamide complexes. The S= 2 N ‐haloamide complexes are characterized by 1 H NMR, UV‐vis, IR, high‐frequency and ‐field EPR (HFEPR) spectroscopies, and single‐crystal X‐ray diffraction. Photolysis of these complexes results in the formal transfer of a nitrene equivalent to both C−H bonds, such as the α‐C−H bonds of tetrahydrofuran, and olefinic substrates, such as styrene, to afford aminated and aziridinated products, respectively. Low‐temperature spectroscopy and analysis of kinetic isotope effects for C−H amination indicate halogen‐dependent photoreactivity: Photolysis of N ‐chloroamides proceeds via initial cleavage of the Mn−N bond to generate Mn II and amidyl radical intermediates; in contrast, photolysis of N ‐iodoamides proceeds via N−I cleavage to generate a Mn IV nitrenoid (i.e., {MnNR} 7 species). These results establish N ‐haloamide ligands as viable precursors in the photosynthesis of metal nitrenes and highlight the power of ligand design to provide access to reactive intermediates in group‐transfer catalysis.

Van Trieste, III, Gerard P.↗
DOE OSTI2022

Model-based reconstruction for enhanced x-ray CT of dense tri-structural isotropic particles

Tri-structural isotropic (TRISO) fuel particles are a key component of next generation nuclear fuels. Using x-ray computed tomography (CT) to characterize TRISO particles is challenging because of the strong attenuation of the x-ray beam by the uranium core, leading to severe photon starvation in a substantial fraction of the measurements. Furthermore, the overall acquisition time for a high-resolution CT scan can be very long when using conventional laboratory-based x-ray systems and reconstruction algorithms. Specifically, when analytic methods such as the Feldkamp–Davis–Kress (FDK) algorithm are used for reconstruction, it results in severe streak artifacts and noise in the corresponding 3D volume, which makes subsequent analysis of the particles challenging. In this paper, we develop and apply model-based image reconstruction (MBIR) algorithms to improve the quality of CT reconstructions for TRISO particles to facilitate better characterization. We demonstrate that the proposed MBIR algorithms can significantly suppress artifacts with minimal pre-processing compared to conventional approaches. We also demonstrate that the proposed MBIR approach can obtain high-quality reconstruction compared to the FDK approach even when using a fraction of the typically acquired measurements, thereby enabling dramatically faster measurement times for TRISO particles.

Venkatakrishnan, Singanallur↗
DOE OSTI2022

Process design for calcination of nickel-based cathode materials by in situ characterization and multiscale modeling

Developing battery materials towards commercial use, from the early discovery through synthesis, processing, scaling up, and eventually to industrial production, may take decades. A notable example is Ni-based layered oxides, which were discovered as early as 1950s and intensively pursued as cathode active materials (CAMs) since the early 90s but have yet to realize their full commercial potential. Significant efforts have been devoted to materials development aiming at improving performance, far less to process development for large-scale synthesis and processing of CAMs. In this paper, we present a rational design of calcination for scalable production of Ni-based CAMs. We start with an overview of the current understanding and knowledge gaps hindering rational process design and scaling-up of the calcination process. Then with specific examples, we demonstrate how to tackle those fundamental challenges through in situ characterization and multiscale modeling. Finally, we conclude by providing perspectives on the remaining challenges and emerging opportunities in commercial development of Ni-based cathodes, calling for more endeavors in this field.

25 ENERGY STORAGE↗
DOE OSTI2022

Structural Characterization of a Toppling Rock Slab From Array-Based Ambient Vibration Measurements and Numerical Modal Analysis

Accurate assessments of the internal structure and boundary conditions of unstable rock slopes are imperative for evaluating landslide hazard scenarios. However, instability characterization at depth remains challenging and is often limited by costly or invasive subsurface investigations. Here, we develop a new approach coupling array-based ambient vibration modal analysis and numerical modeling to improve structural characterization of rock slope instabilities at depth. We used ambient noise cross-correlation on 4 hr of seismic data recorded by an array of 30 nodal geophones at a 500-m-long toppling rock slab in Utah, USA to identify modal frequencies between 0.8 and 3.5 Hz and derive modal displacements. We show that transverse and longitudinal bending modes span the length of the instability, indicating an interconnected slab. Further, statistical comparison of field results with outputs from >1,000 finite element models with varying boundary conditions showed that the instability depth varies between 40–70 and 10–20 m in the middle and lateral regions, respectively. Our approach yields new information on the structural conditions of rock cliff and column instabilities at depth, which is not easily obtained by other means but is imperative for change detection monitoring and improved hazard assessments.

58 GEOSCIENCES↗
DOE OSTI2025

WigglyRivers: A tool to characterize the multiscale nature of meandering channels

Channel sinuosity is ubiquitous along river networks, producing complex patterns that encapsulate and influence morphodynamic processes and ecosystem services. Accurately characterizing these patterns is challenging with traditional curvature-based algorithms. Here, in this study, we present WigglyRivers, a Python package that builds on existing wavelet-based methods to create an unsupervised meander identification and characterization tool. The package uses planimetric information the user provides or from the USGS’s High-Resolution National Hydrography Dataset to characterize individual reaches or entire river networks. WigglyRivers also includes a supervised river identification tool for manually selecting individual meandering features. Here, we provide examples of idealized river transects and show the capabilities of WigglyRivers. We also use the supervised identification tool to validate the unsupervised identification on river transects across the continental US. WigglyRivers is a tool to understand better the multiscale characteristics of river networks and the link between river geomorphology and river corridor connectivity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Integrated RF/Optical Interplanetary Networking Preliminary Explorations and Empirical Results

Over the last decade interplanetary telecommunication capabilities have been significantly expanded--specifically in support of the Mars exploration rover and lander missions. NASA is continuing to drive advances in new, high payoff optical communications technologies to enhance the network to Gbps performance from Mars, and the transition from technology demonstration to operational system is examined through a hybrid RF/optical approach. Such a system combines the best features of RF and optical communications considering availability and performance to realize a dual band trunk line operating within characteristic constraints. Disconnection due to planetary obscuration and solar conjunction, link delays, timing, ground terminal mission congestion and scheduling policy along with space and atmospheric weather disruptions all imply the need for network protocol solutions to ultimately manage the physical layer in a transparent manner to the end user. Delay Tolerant Networking (DTN) is an approach under evaluation which addresses these challenges. A multi-hop multi-path hybrid RF and optical test bed has been constructed to emulate the integrated deep space network and to support protocol and hardware refinement. Initial experimental results characterize several of these challenges and evaluate the effectiveness of DTN as a solution to mitigate them.

Raible, Daniel E.↗