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.

SourceResearch connectionFrom yearThrough year

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

At least 1,567 records · Page 87

All sources NASA NTRS DOE OSTI

NASA NTRS1999

Streptomycin ototoxicity and hair cell regeneration in the adult pigeon utricle

OBJECTIVE: The purpose of this study was to develop a technique to investigate the regeneration of utricular hair cells in the adult pigeon (Columba livia) following complete hair cell loss through administration of streptomycin. STUDY DESIGN: Experimental animal study. METHODS: Animals were divided into four groups. Group 1 received 10 to 15 days of systemic streptomycin injections. Animals in Groups 2 and 3 received a single direct placement of a 1-, 2-, 4-, or 8-mg streptomycin dose into the perilymphatic space. Animals in Groups 1 and 2 were analyzed within 1 week from injection to investigate hair cell destruction, whereas Group 3 was investigated at later dates to study hair cell recovery. Group 4 animals received a control injection of saline into the perilymphatic space. Damage and recovery were quantified by counting hair cells in isolated utricles using scanning electron microscopy. RESULTS: Although systemic injections failed to reliably achieve complete utricular hair cell destruction, a single direct placement of a 2-, 4-, or 8-mg streptomycin dose caused complete destruction within the first week. Incomplete hair cell loss was observed with the 1-mg dose. Over the long term, regeneration of the hair cells was seen with the 2-mg dose but not the 8-mg dose. Control injections of saline into the perilymphatic space caused no measurable hair cell loss. CONCLUSIONS: Direct placement of streptomycin into the perilymph is an effective, reliable method for complete destruction of utricular hair cells while preserving the regenerative potential of the neuroepithelium.

Non-NASA Center↗

NASA NTRS2010

CARS Spectral Fitting with Multiple Resonant Species using Sparse Libraries

The dual pump CARS technique is often used in the study of turbulent flames. Fast and accurate algorithms are needed for fitting dual-pump CARS spectra for temperature and multiple chemical species. This paper describes the development of such an algorithm. The algorithm employs sparse libraries, whose size grows much more slowly with number of species than a conventional library. The method was demonstrated by fitting synthetic "experimental" spectra containing 4 resonant species (N2, O2, H2 and CO2), both with noise and without it, and by fitting experimental spectra from a H2-air flame produced by a Hencken burner. In both studies, weighted least squares fitting of signal, as opposed to least squares fitting signal or square-root signal, was shown to produce the least random error and minimize bias error in the fitted parameters.

Cutler, Andrew D.↗

DOE OSTI2020

On Performance Prediction of Big Data Transfer in High-performance Networks

Big data generated by large-scale scientific and industrial applications need to be transferred between different geographical locations for remote storage, processing, and analysis. High-speed dedicated connections provisioned in High-performance Networks (HPNs) are increasingly utilized to carry out such big data transfer. HPN management highly relies on an important capability of performance (mainly throughput) prediction to reserve sufficient bandwidth and meanwhile avoid over-provisioning that may result in unnecessary resource waste. This capability is critical to improving the resource (mainly bandwidth) utilization of dedicated connections and meeting various user requests for data transfer. Conventional methods conduct performance prediction by fitting prior observed transfer history with predefined loss functions, without considering unobservable latent factors such as competing loads on end hosts. Such latent factors also have a significant impact on the application-level data transfer performance, which may result in an inaccurate prediction model. In this paper, we first investigate the impact of latent factors and propose a clustering-based method to eliminate their negative impact on performance prediction. We then develop a robust machine learning-based performance predictor by: i) incorporating the proposed latent factor elimination method into data preprocessing, and ii) adopting a customized domain guided loss function. Extensive experimental results show that our predictor achieves significantly higher prediction accuracy than several other state-of-the-art methods.

Liu, Wuji↗

DOE OSTI2017

Optical Fier Based System for Multiple Thermophysical Properties for Glove Box, Hot Cell and In-Pile Application

Thermal diffusivity of materials is of interest in nuclear applications at temperatures in excess of 2000°C. Commercial laser flash apparatus (LFA) that heats samples with a furnace typically do not reach these elevated temperatures nor are they easily adapted to a glove-box or hot cell environment. In this research, we performed work on an experimental technique using single laser surface heating, i.e. heating the disk sample only at its front surface with the continuous wave (CW) laser, to allow measurement of thermal diffusivity at very high temperatures within a small chamber. Thermal diffusivity is measured using a separate pulsed laser on the front side and IR detector on the rear side. The new way of heating provides easy operation in comparison to other heating methods. The measurement of sample reference temperature is needed for the measured thermal diffusivity. A theoretical model was developed to describe transient heat transfer across the sample due to the laser pulse, starting from the steady state temperature of the sample heated by the CW laser. The experimental setup was established with a 500W CW laser and maximum 50 Joule pulse laser irradiated at the front surface of the sample. The induced temperature rise at the rear surface, along with the steady-state temperature at the front surface, was recorded for the determination of thermal diffusivity and the sample temperature. Three samples were tested in vacuum over a wide temperature range of 500°C to 2100°C, including graphite, Inconel 600 and tungsten. The latter two samples were coated with sprayed graphite on their front surfaces in order to achieve surface absorption/emission needs, i.e. high absorptivity of the front surface against relatively low emissivity of the rear surface. Thermal diffusivity of graphite determined by our system are within a 5% difference of the commercial LFA data at temperatures below 1300°C and agree well with its trend at higher temperatures. Good agreement would also exist for Inconel 600 and tungsten. Despite large uncertainty of measuringthe sample temperature, the uncertainties of thermal diffusivity are less than 6% for all samples at elevated temperatures. The results indicate that single laser surface heating could be convenient and practical for the application of the LFA measurements without extra uncertainty, as temperature dependence of thermal diffusivity is usually negligible in the sample. Moreover, it is concluded that unequal surface treatment, i.e., high absorption on the front side and low emission on the rear side, greatly improves the measurement in serval aspects: less power requirement of the CW laser, less uncertainty of measured thermal diffusivity, and more uniform temperature distribution in the sample. The result of this research can be used as a general guideline for the design of this type of measurement system for nuclear applications. It can also be used directly to design and build a system similar to the one implemented in this project.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Anisotropy of the Surface Energy and Work Function of IIB Metals

On the basis of electron-statistical method of calculation of the surface energy of metals, a technique for estimating the electron work function of hexagonal and rhombohedral metallic crystals has been developed. This technique relates surface energy to work function and can thus be applied to estimate the surface energy of crystal faces from experimental data for a work function. Computations have been made for cadmium, zinc, and mercury macrocrystals. The temperature and orientation dependences of both quantities have been constructed. Our results are in good agreement with literature experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1984

Mechanics of Composite Materials: Past, Present and Future

Composite mechanics disciplines are presented and described at their various levels of sophistication and attendant scales of application. Correlation with experimental data is used as the prime discriminator between alternative methods and level of sophistication. Major emphasis is placed on: (1) where composite mechanics has been; (2) what it has accomplished; (3) where it is headed, based on present research activities; and (4) at the risk of being presumptuous, where it should be headed. The discussion is developed using selected, but typical examples of each composite mechanics discipline identifying degree of success, with respect to correlation with experimental data, and problems remaining. The discussion is centered about fiber/resin composites drawn mainly from the author's research activities/experience spanning two decades at Lewis.

Chamis, Christos C.↗

NASA NTRS1989

Mechanics of composite materials - Past, present and future

Chamis, Christos C.↗

DOE OSTI2025

Reliable and Efficient Machine Learning (Final Technical Report)

Modern scientific experiments generate massive amounts of data at a pace much faster than humans can manually analyze. While machine learning has revolutionized commercial data analysis (such as recommending movies or recognizing faces), applying these tools to complex scientific discovery is challenging because scientific answers must be precise, interpretable, and adhere to physical laws. The research under this project aims to develop new mathematical tools and computer algorithms specifically designed for scientific applications. Major progress has been made in automatically cleaning and deconstructing messy experimental data, analyzing the visual information of physical phenomena, determining the underlying physical variables, and providing rig orous mathematical analysis of interesting algorithms and concepts widely used in machine learning. This project addressed the critical gap between our ability to generate massive scientific data and our ability to extract interpretable information from it. We established mathematical foundations for Scientific Machine Learning (SciML) aimed at effective data analytics and automated discovery. Our work focused on three core objectives: (1) developing reliable feature extraction methods for dynamic high-dimensional data, (2) establishing mathematical foundations for discovering dynamics via neural networks, and (3) creating rigorous optimization techniques for these models. Key outcomes come from two fronts. On the practical side, they include the development of algorithms that significantly enhance the extraction of signals from field data, as well as the capability to handle situations that exhibit smooth variations or physical stretching due to temperature changes. They also include the creation of an automated framework for discovering fundamental state variables from raw experimental data, demonstrating the ability to identify intrinsic physical dimensions without prior knowledge of the governing laws. On the theoretical front, the research results in theoretical advances in Optimal Transport, a widely used notion in SciML, specifically regarding functions with fixed-size nodal sets, provide sharp bounds relevant to uncertainty quantification. Meanwhile, the outcomes also include the establishment of convergence theories for nonlocal gradient descent methods, enabling robust optimization with noisy data in high-dimensional settings commonly encountered in scientific modeling. The project also helps creating opportunities to train the next generation of researchers, equipping them with the necessary technical skills for today’s workplace and preparing them for future advances.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Effects of surface diffusion in electrocatalytic CO 2 reduction on Cu revealed by kinetic Monte Carlo simulations

We report Kinetic Monte Carlo (KMC) methods are frequently used for mechanistic studies of thermally driven heterogeneous catalysis systems but are underused for electrocatalysis. Here, we develop a lattice KMC approach for electrocatalytic CO 2 reduction. The work is motivated by a prior experimental report that performed electroreduction of a mixed feed of 12 CO 2 and 13 CO on Cu; differences in the 13 C content of C2 products ethylene and ethanol (Δ 13 C) were interpreted as evidence of site selectivity. The lattice KMC model considers the effect of surface diffusion on this system. In the limit of infinitely fast diffusion (mean-field approximation), the key intermediates 12 CO* and 13 CO* would be well mixed on the surface and no evidence of site selectivity could have been observed. Using a simple two-site model and adapting a previously reported microkinetic model, we assess the effects of diffusion on the relative isotope fractions in the products using the estimated surface diffusion rate of CO* from literature reports. We find that the size of the active sites and the total surface adsorbate coverage can have a large influence on the values of Δ 13 C that can be observed. Δ 13 C is less sensitive to the CO* diffusion rate as long as it is within the estimated range. We further offer possible methods to estimate surface distribution of intermediates and to predict intrinsic selectivity of active sites based on experimental observations. This work illustrates the importance of considering surface diffusion in the study of electrochemical CO 2 reduction to multi-carbon products. Our approach is entirely based on a freely available open-source code, so will be readily adaptable to other electrocatalytic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2018

NASA ACC High Energy Dynamic Impact Methodology and Outcomes

High fidelity analysis methods known as Progressive Damage Analysis (PDA) methods, capable of reliably predicting the onset and progression of damage in composite materials, are being developed for HEDI event simulation. Four state-of-the-art PDA methods are being investigated: LS-DYNA MAT162, LS-DYNA MAT261, Smooth-Particle Galerkin (SPG), and EMU Peridynamics. Validation of these PDA models aims to follow a building block approach, starting with coupon- and component-level development. As part of the overall effort, material characterization testing was performed to bridge gaps between existing experimental data and the material property inputs required to predict ballistic impact behavior at the component-level. The material models were updated with the results of the coupon-level testing and were then used to predict panel behavior and damage in ballistic impact events. To assess the accuracy of the PDA methods, these pre-test predictions were compared to the results of ballistic impact testing.

Hunziker, Kenneth J.↗

NASA NTRS1982

Development of toughened epoxy polymers for high performance composite and ablative applications

A survey of current procedures for the assessment of state of cure in epoxy polymers and for the evaluation of polymer toughness as related to nature of the crosslinking agent was made to facilitate a cause-effect study of the chemical modification of epoxy polymers. Various conformations of sample morphology were examined to identify testing variables and to establish optimum conditions for the selected physical test methods. Dynamic viscoelasticity testing was examined in conjunction with chemical analyses to allow observation of the extent of the curing reaction with size of the crosslinking agent the primary variable. Specifically the aims of the project were twofold: (1) to consider the experimental variables associated with development of "extent of cure" analysis, and (2) to assess methodology of fracture energy determination and to prescribe a meaningful and reproducible procedure. The following is separated into two categories for ease of presentation.

Allen, V. R.↗

DOE OSTI2022

Mechanics of the Ring Tension Test (RTT): A Finite Element-based Investigation

The ring tension test (RTT) is an experimental method for determining mechanical behavior in a material’s circumferential or hoop direction. It is a crucial test for testing anisotropic materials with tube geometry, such as nuclear fuel cladding or irradiated pipes. Several RTT configurations exist, each with their own advantages and disadvantages. However, this test is significantly more complex than traditional tensile testing and can be especially sensitive to small differences and inconsistencies in the test setup and geometry, ultimately affecting the derived mechanical properties. Previous research has focused on method development, and little work has been done on understanding the subtle differences between an ideal test and experiments, specifically when the tests are performed on highly irradiated materials in hot cells. In this work, a finite element-based investigation of the RTT is conducted. Two promising test configurations are investigated, comparing their ability to determine accurate material strengths through plastic deformation. Several non-ideal conditions and uncontrollable effects which are likely to occur during experimental testing such as machining tolerances, variations of specimen geometry from nominal dimensions, rotation of specimens and fixturing, and other test setup discrepancies are studied. The sensitivity of measured strengths to these conditions is presented. A mechanics-based approach to describing and correcting raw data to determine actual strengths is also included for one of the configurations, resulting in a robust correction method with highly accurate material strength measurements. Based on these analyses, the hemicylindrical mandrel configuration is recommended with a gauge region oriented at a 45° angle.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

2025 Workshop on Envisioning Frontiers in AI and Computing for Biological Research: Position Papers

This workshop aims to identify key research directions for transforming biology using artificial intelligence (AI), machine learning (ML) and computational methods to facilitate the discovery of new behaviors, mechanisms, and designs of biological processes relevant to DOE missions, underpinning a broader U.S. bioeconomy. By developing novel AI/ML technologies to analyze and interpret complex biological data, researchers can organize and simulate biological processes at various scales as well as advance predictive understanding and manipulation of biological systems. This integration of computation, experimentation, and next-generation experimental technologies can lead to discoveries in new biological behaviors and mechanisms relevant to DOE missions. The focus is on how advanced computational and mathematical methods can impact this mission by exploring digital twins, foundation models, automated laboratory experiments, modeling of complex living systems, and data-driven approaches for the biodesign of plants and microbial systems. While data management is important, it is not the primary focus of this workshop, which will assess the current state, trends, and AI/ML challenges at the interface between biology and computational science to identify opportunities for high-impact research at their intersection. The goal is to define research needs and opportunities that align with biological sciences, computational sciences, and applied mathematics research.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Predicting Char Yield of High-Temperature Resins

A simulation technique has been developed for predicting the char yield of organic resins during high-temperature processing. In silico methods can aid in the screening of new advanced materials for a number of important properties, but no chemistry-sensitive protocol currently exists for predicting the important experimental value of char yield. The proposed method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to pyrolysis temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small by-product molecules to mimic outgassing, and the application of high pressure to encourage the formation of a dense, glassy network. Six different resin chemistries were investigated: an ethynyl, a phenylethynyl, a cyanate ester, a phthalonitrile, acrylonitrile, and adamantane. These candidates represent a diverse group of precursors with respect to initial cyclic content, presence of heteroatoms, and types of reactive groups. The protocol developed accurately predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. Several simulated properties of the carbonized structures are compared with experimental results, including outgassing products, morphology of the final chemical configurations, cyclic content, and mechanical properties.

polymer simulations, molecular dynamics↗

DOE OSTI2023

Modeling Short-Range Order in Disordered Rocksalt Cathodes by Pair Distribution Function Analysis

Pair distribution function (PDF) analysis is a powerful technique for the characterization of short-range order (SRO) in disordered materials. Accurate interpretation of experimental PDF data is critically reliant on the development of structural models that can account for local variations in site occupancies and bond lengths. To this end, we outline an approach to model SRO using first-principles calculations based on the cluster-expansion formalism. These methods are validated on neutron scattering data from two disordered rocksalt oxyfluorides, Li 1.3 Mn 0.4 Ti 0.3 O 1.7 F 0.3 and Li 1.3 Mn 0.4 Nb 0.2 Ti 0.1 O 1.7 F 0.3 . For each composition, we demonstrate that an average structure without any SRO fails to reproduce several key features in the experimental PDF. To pinpoint the origin of the suspected SRO in these materials, configurational and displacive effects were separately investigated using two disparate models. Special quasi-random structures were relaxed using density functional theory to account for local changes in bond lengths while maintaining a near-random ionic configuration. This leads to slightly improved accuracy but still misrepresents asymmetry in the first few peaks of the PDF. Monte Carlo simulations were performed to model configurational SRO on a fixed lattice, which by itself is shown to have a minimal influence on the PDF. Instead, we find that it is the bond length relaxations within environments created by SRO which controls the details of the PDF, thereby highlighting the subtle but important coupling between configurational and displacive SRO in disordered materials.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Residual stress evaluation of components produced via direct metal laser sintering

Direct metal laser sintering is an additive manufacturing process which is capable of fabricating three-dimensional components using a laser energy source and metal powder particles. Despite the numerous benefits offered by this technology, the process maturity is low with respect to traditional subtractive manufacturing methods. Relationships between key processing parameters and final part properties are generally lacking and require further development. In this study, residual stresses were evaluated as a function of key process variables. The variables evaluated included laser scan strategy and build plate preheat temperature. Residual stresses were measured experimentally via neutron diffraction and computationally via finite element analysis. Good agreement was shown between the experimental and computational results. Results showed variations in the residual stress profile as a function of laser scan strategy. Compressive stresses were dominant along the build height (z) direction, and tensile stresses were dominant in the x and y directions. Build plate preheating was shown to be an effective method for alleviating residual stress due to the reduction in thermal gradient.

36 MATERIALS SCIENCE↗

NASA NTRS1991

Analytical and experimental study of vibrations in a gear transmission

An analytical simulation of the dynamics of a gear transmission system is presented and compared to experimental results from a gear noise test rig at the NASA Lewis Research Center. The analytical procedure developed couples the dynamic behaviors of the rotor-bearing-gear system with the response of the gearbox structure. The modal synthesis method is used in solving the overall dynamics of the system. Locally each rotor-gear stage is modeled as an individual rotor-bearing system using the matrix transfer technique. The dynamics of each individual rotor are coupled with other rotor stages through the nonlinear gear mesh forces and with the gearbox structure through bearing support systems. The modal characteristics of the gearbox structure are evaluated using the finite element procedure. A variable time steping integration routine is used to calculate the overall time transient behavior of the system in modal coordinates. The global dynamic behavior of the system is expressed in a generalized coordinate system. Transient and steady state vibrations of the gearbox system are presented in the time and frequency domains. The vibration characteristics of a simple single mesh gear noise test rig is modeled. The numerical simulations are compared to experimental data measured under typical operating conditions. The comparison of system natural frequencies, peak vibration amplitudes, and gear mesh frequencies are generally in good agreement.

Choy, F. K.↗

DOE OSTI2020

Characterization and Scaling of Forced Convective Swirl in Sinusoidal Wavy-Plate-Fin Cores of Compact Heat Exchangers

The characterization and scaling of the thermal-hydraulic performance in wavy plate-fin compact heat exchanger cores, based on the understanding of the physical phenomena and heat transfer enhancement mechanism is delineated. Experimental data are presented for forced convection in air (Pr = 0.71) with flow rates in the range 50 ≤ Re ≤ 4000. A variety of wavy-fin cores that span viable applications, with geometrical attributes described by the cross section aspect ratio α (ratio of fin spacing to height), fin corrugation aspect ratio γ (ratio of 2× corrugation amplitude to wave pitch), and fin spacing ratio ζ (ratio of fin spacing to wave pitch), are considered. To characterize and correlate the vortex-flow mixing in interfin spaces, a Swirl number Sw is introduced from the balance of viscous, inertial and centrifugal forces. It is shown that the laminar, transitional and turbulent flow regimes can be explicitly identified by this Swirl number. Based on the experimental results and extended analysis, new correlations for Fanning friction factor f and Colburn factor j are developed with Sw, α, γ, and ζ as scaling parameters. Requisite expressions are devised by a superposition of both enhancement components due to the corrugated surface area enlargement and induced swirl flow field, and they are combined to cover the laminar, transitional and turbulent regimes by the method of asymptotic matching. The resulting generalized correlations are further shown to predict all available experimental data for f and j factors to within ±20% and ±15%, respectively.

42 ENGINEERING↗